Conversion of waste animal bones to biofertilizer and adsorbent for wastewater treatment: An innovative approach to develop zero-waste technology

Conversion of waste animal bones to biofertilizer and adsorbent for wastewater treatment: An innovative approach to develop zero-waste technology | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Conversion of waste animal bones to biofertilizer and adsorbent for wastewater treatment: An innovative approach to develop zero-waste technology Abdul Majeed Khan, Muhammad Arsalan Usmani, Kousar Yasmeen, Muhammad Naeem Ahmed, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3134479/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Presently a number of chemical fertilizers are being used which are not only expensive but are also environment threatening. There is a need to replace these fertilizers by biofertilizers. Adsorbent were prepared from waste bones for the waste water treatment. Various bone samples were collected and calcinated to produce biofertilizer and adsorbent. Total carbon (TC) and total nitrogen (TN) were analyzed. The broiler chicken bone-based biofertilizer has the lowest amount of TC and TN (TC = 33 and TN = 5.5 g/Kg) and also the lowest macro-elements; Ca = 55, P = 26, K = 2.5, and Mg = 0.83 g/Kg. All samples were used for the growth of kidney bean plant. After 5 weeks, the highest growth was observed for buffalo bone-based fertilizer and the lowest for broiler bone-based fertilizer. In the present study, the calcinated bones material was also used as nano-adsorbent for the removal of heavy metals from the artificial wastewater. All nano-adsorbent samples showed maximum efficiency at 100 ppm, while maximum removal was at 6 h. The highest removal efficiency was obtained for buffalo bone-based nano-adsorbent (As = 60% and Pb = 75%), and the lowest removal efficiency was obtained for broiler bone-based nano-adsorbent (As = 36% and Pb = 47%). The calcinated animal bones were analyzed using Flame Atomic Absorption Spectrophotometry (FAAS), Fourier Transform Infrared Spectroscopy (FTIR), chemical tests and antimicrobial susceptibility test (AST). This research can play an important role for the promotion of agricultural crops and for wastewater treatment using nano-technology. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction In most parts of the world, people are meat lovers, so animals (bovine, caprine), chicken, and fish are used as a source of meat. Large amounts of animal waste are generated daily (Patel et al. 2015 ; Côrtes et al. 2019 ). Biowaste from animals, poultry, and fish are considered municipal solid waste. The collection and disposal of these wastes has become an alarming problem for both developed and developing countries. In present decade, researchers have focused on converting solid waste into useful by-products such as biofertilizers and biochar, which can help to increase crop production and be used in water treatment (Abdel-Shafy et al. 2018 ; Sharma et al. 2020 ; Ahmed et al. 2021 ; Mozhiarasi and Natarajan 2022 ). Fertile soil is the key to sustainable and high-yield commercial agriculture. The essential ingredients of fertile soil are fertilizers, which ensure a high production rate on agricultural land (Mäder et al. 2002 ; Abbott and Murphy 2007 ; Cunfer and Krausmann 2009 ; Weigand et al. 2013 ). In order to increase soil fertility, chemical fertilizers have been widely used in the last four decades, resulting in the loss of natural habitat and soil health, and causing many hazardous effects such as soil salinization, fertilizer pollution, and dangerous environmental impacts. This has also led to deterioration in food quality and an increase in the cost of cultivation. Due to these drawbacks, alternative farming techniques and strategies are becoming more popular in this decade. Due to their many advantages over chemical fertilizers, organic farming techniques and strategies are attractive to farmers worldwide (Dawson and Hilton 2011 ; Kumar et al. 2013 ; Al-Suhaibani et al. 2020 ; Al-Suhaibani et al. 2021 ). According to the United States Department of Agriculture (USDA), organic farming promotes the cycle process of agricultural resources and maintains the biodiversity in ecosystem. It naturally increases soil fertility and maintains water quality by avoiding synthetic fertilizers, pesticides, growth regulators, feed additives, and genetic engineering. In organic farming, fertilizers should come from natural substances. These types of fertilizers are called biofertilizers (Reganold and Wachter 2016 ; Ahuja et al. 2020 ). Nitrogen (N), phosphorus (P) and potassium (K) in the soil are the most important macronutrients, which are closely related to soil fertility and promote plant growth. A good organic fertilizer should be enriched with N, P and K (Schroder et al. 2010 ; Gao et al. 2019 ). Different types of biowastes contain these elements in larger amounts (Weigand et al. 2013 ; Xu et al. 2007 ; Arvanitoyannis and Kassaveti 2008 ; Soetan et al. 2010 ; Saeid et al. 2012 ; Alotaibi et al. 2013 ; Severin et al. 2014 ; Izydorczyk et al. 2022 ; Samoraj et al. 2022 ). Bones are the only biowaste that contains the highest concentration of macronutrients (Ca, N, P, K, and Mg), and the use of bones as fertilizer is currently the only way to turn this environmentally harmful/polluting waste into a useful product (Schroder et al. 2000 ; Su et al. 2003 ; Mondini et al. 2008 ; Padel et al. 2009 ; Alves et al. 2013 ; Wongrueng et al. 2019 ). Bones form the main skeleton of the animal body and consist of 45% water, 30% protein, 15% bone salts and 10% lipids. The organic matrix is 30–40%, while the inorganic matrix accounts for 60–70% of the bone weight. In bone, calcium (55%) and phosphorus (42%) are present in the largest amount, while only 2% nitrogen is present (Saeid et al. 2012 ; Rauf 2014 ; Ginigaddara 2021 ). Due to the availability of nitrogen and carbon in the bones, they can be used as fertilizer and increase soil fertility. Nitrogen and carbon lead to an increase in microbial biomass, and these microbes also control the decomposition process in the soil by providing more enzymes. Bones are the main source of organic phosphorus. Bones contain the phosphorus in the form of calcium phosphate. The same types of phosphates are also obtained from rocks and sediments, but bone phosphate is preferable. Because phosphates from rocks/sediments may contain cations, they have an affinity for absorbing cations/metals and may naturally contain high concentrations of metals and other contaminants. Therefore, these phosphates can have dangerous effects on the ecosystem. On the other hand, bone phosphate, has the lowest concentration of heavy metals. Therefore, more importance has been given to bone-derived fertilizers (Tütken et al. 2008 ; Enowashu et al. 2009 ; Saeid et al. 2014 ). The high concentration of various heavy metals in the aquatic ecosystems of Pakistan is hazardous. This is because these heavy metals enter the food chain from the aquatic ecosystem and severely affect human health (Perveen et al. 2017 ; Aslam et al. 2020 ; Chan et al. 2021a ; Chan et al. 2021b ; Afzaal et al. 2022 ; Hayder et al. 2022 ). There is an urgent need to take measures to remove these toxic heavy metals from water to make this water safe for the public and agriculture. Various removal methods (e.g., ion exchange, precipitation, electrocoagulation, activated carbon adsorption, and fixed bed filtration) have been used to remove these toxic metals from water. However, most of these techniques are expensive, and there is a need to develop more cost-effective technologies using inexpensive adsorbents. The development of biochar technology offers a way to meet the need for low-cost adsorbents for aqueous heavy metals. In the last decade, biochar has received considerable attention in water treatment (Inyang et al. 2016 ; Gwenzi et al. 2017 ; da Silva Veiga et al. 2020 ; Castiglioni et al. 2021 ). The present study was designed to produce low-cost nano-biofertilizer and biochar as nan-adsorbent from the biowaste of animals. For this purpose, the waste products of different animals were used, such as bones of marine piscine (fish), galline (country and broiler chicken), and bones and horns of caprine (goat) and bovine (cows and buffaloes). Total carbon (TC) and total nitrogen (TN) of these wastes were determined at different temperatures to observe the loss of carbon and nitrogen. Other macronutrients (Ca, P, K, and Mg) required for plant growth were also analyzed in these bone/horn samples. The effectiveness of these macronutrients as biofertilizers was determined using a weekly-based plant growth experiment. In addition, this study determined the filtration capacity of different biochar samples to remove six heavy metals (As, Cd, Cr, Cu, Ni, and Pb) from the artificial wastewater samples. This comparative evaluation provides useful information on the adsorption capacity of the different biochar samples. This study is based on the hypothesis that the efficiency of biofertilizers and biochar produced from different animal waste products depends on the animal species and body parts. In the future, this study will provide helpful information for the production of effective biofertilizer and biochar from animal bones/horns. Materials and Methods Sample collection In this study, the biowastes of different animals were used: marine piscine (fish), galline (chicken), caprine (goat) and bovine (buffalo and cow). Both bones and horns were used for buffalo, cow and goat, while bones were used for fish and chicken (both country and broiler). The piscine biowastes were collected from Karachi fish harbor, while bovine, caprine and galline biowastes were collected from different slaughterhouses and poultry markets in Karachi. Analysis and instrumentation To conduct different experiments, we used different instrumental techniques including Atomic Absorption Spectrophotometry (AAS), Fourier Transform Infrared Spectroscopy (FTIR), Thin Layer Chromatography (TLC), furnace for calcination and microscope for microbial analysis. Atomic Absorption Spectrophotometry (AAS) PE-A Analyst 700 was used in order to find out the metal composition of animal bones. Fourier Transform Infrared Spectroscopy (FTIR) model IR Prestige-21, Shimadzu, Japan is used to detect the functional group region in calcinated animal bones. Muffle furnace SX-2-5-12 box type resistance furnace is used to calcinate the animal bones. Total carbon (TC) and nitrogen (TN) were measured using a CHN analyzer (Perkin Elmer, 2400 Series II). Phosphorus content was determined spectrophotometrically using a Marcel Media UV-VIS spectrophotometer. Pretreatment and calcination of bones Different bones including fish bones (A), country hen bones (B), broiler hen bones (C), goat trotters (D), goat horns (E), cow bones (F) and buffalo horns (G) were collected from different meat shops of Karachi. The bones were washed with water and boiled in NaOH solution (10%) for three hours, then rinsed with water (approx. 1000 ml) for the removal of base and other impurities. The bones were dried at 100°C for 2 hours and then converted into the powdered form. After then, the bones powder was calcinated at 200°C, 400°C, 600°C, 800°C and 1000°C in a muffle furnace for 4 hours gradually (Fig. 1 ). Basicity test 1 ml of 20% w/v of bones and (0.5 ml; 1.5mg/ml) of phenolphthalein in toluene were taken in a conical flask and titrated it with standard 0.01 M solution of benzoic acid which was prepared in toluene. The basicity of the waste bones were measured by using the burette reading of consumed benzoic acid against samples solutions of bones. The basicity results were reported in mmoles per 100 g of bones. Analysis of elements The saturated solutions of bones were prepared and few drops of ammonium hydroxide (NH 4 OH) and ammonium oxalate solution were added, and the test tube was shaken well that resulted in the appearance of white precipitates. Calcinated animal bones (0.2 g) which are the source of CaO were used for the analysis of calcium content. Distilled water (12.5 ml) and conc. HCl (4.0 ml) were added and placed the flask on the hotplate stirrer then the beaker was covered with watch glass. The solution was boiled till the maximum CO 2 was evolved. Now, distilled water (120.0 ml) was added to make up the solution up to 125.0 ml and 2 drops of methyl red was added then the solution was boiled and covered with the watch glass. The solution of ammonium oxalate (8%) was prepared and boiled then added in the sample solution. NH 4 OH (1:1) solution was added drop wise till orange precipitates were appeared. The solution was subjected to filtration and the residue was collected. The residue was charred in the muffle furnace to form CaO. For the detection of Mg, the saturated solutions of bones were prepared then ammonium hydroxide (NH 4 OH) and NaHPO 4 were added and then the test tube was shaken well that resulted in the appearance of gelatinous white precipitates. Analysis of bones by atomic absorption spectrophotometry To find the heavy metals quantitatively in waste bones samples, we used atomic absorption spectrophotometer (AAS). For sample preparation 5.0 g of waste bone was digested in 10 ml of concentrated HNO 3 by using wet digestion method. Analysis of waste bones samples on AAS PE-A Analyst 700 were performed on Air-Acetylene flame with fuel flow rate of 10 L/min at a specific wavelength of metal to be analyzed. Carbon and nitrogen analysis The bone samples were boiled in water for 1 hour to remove the residual meat, while the horn samples were washed with water to remove dust and debris. Now both samples were washed with distilled water before carbon and nitrogen analysis. The bones were dried in oven at 70°C for 72 h, crushed, and passed through a 2 mm sieve. For ash recovery, the bones and horns were placed in open crucibles to ensure the supply of oxygen during combustion. Bone ash and horn ash were produced at temperatures of 200°C, 400°C, 600°C, 800°C, and 1000°C with a residence time of 3 h. The products were stored at room temperature until the experiments. Total carbon (TC) and nitrogen (TN) were measured using a CHN analyzer (Perkin Elmer, 2400 Series II). Briefly, 2 mg of the oven-dried bone ash sample was sieved through 150 µm, placed in a tin capsule, and analysed (Patel et al. 2015 ; Ahmed et al. 2021b ). Determination of calcium, phosphorus, potassium and magnesium Prior to the determination of Ca, P, K, and Mg, the bone powder was gradually calcined at 1000°C in a muffle furnace for 4 h (Ahmed et al., 2021b ; Sealy et al., 2014 ). Phosphorus content was determined spectrophotometrically using a Marcel Media UV-VIS spectrophotometer after the sample was previously mineralized in a mixture of concentrated hydrochloric and nitric acids. This method consists of the formation of a yellow colored phosphorus-vanadium-molybdenum complex and photometric measurement of the absorbance at a wavelength of 430 nm (Sobczak et al., 2009 ). Ca, K, and Mg were determined by atomic absorption spectrophotometry. For this purpose, the bone and horn samples were digested according to USEPA standard method #3051. Samples were digested in a microwave oven, diluted with the appropriate amount of deionized water, and filtered through a 42 µm Whatman filter paper (Chan et al., 2021b ). All samples were analyzed for calcium, potassium, and magnesium using an atomic absorption spectrometer (Perkin Elmer (USA), Model AAnalyst 700). Efficacy of biofertilizers To determine the effectiveness of the biofertilizer, eight pots were placed and filled with 1 kg of sand. Each pot was inoculated with powder from calcined animal bones/horns. Two seeds of kidney beans were sown in each pot and the pots were watered regularly for 5 weeks. Plant growth was measured weekly by measuring the size of the stem and the leaves (Fig. 2 ). Antimicrobial potential of calcinated bones Animal bones (0.1 g) including fish bones (A), country hen bones (B), broiler hen bones (C), goat trotters (D), goat horns (E), cow bones (F) and buffalo horns (G) were separately subjected for the determination of their antimicrobial potential against different bacterial and fungal pathogens. The saturated solutions of bones were prepared in water (5 ml) and the test was performed by agar well diffusion method using 100 µl (0.1 M) of test solution in each well made in Nutrient agar plate for bacteria and Sabouraud`s Dextrose agar for fungal strains. The zone of inhibition was measured in millimetre (Buksh et al. 2020 ). Determination of heavy metals removal efficiency of biochar The dried bone/horn samples were calcined at 500°C to 900°C with different durations (1, 2, and 3 h) in a muffle furnace with limited oxygen supply. The resulting biochar adsorbents were ground, sieved to particle size (< 63 µm), and stabilized for further experiments. Synthetic solutions of metals (arsenic, cadmium, chromium, copper, nickel, and lead) were prepared by their salts in deionized water at various concentrations (100–500 ppm). Experiments on the removal of heavy metals were carried out in a laboratory incubator shaker under different conditions. The effects of time (in hours) for the removal of heavy metals from solutions by biochar samples were studied at 25°C. The effects of heavy metal concentrations in solution and the effects of biochar concentrations were also studied. Optimization of time to determine effective removal of heavy metals was evaluated from 1 to 7 h, while heavy metal concentrations were maintained at 100–500 ppm and biochar concentrations at 1 to 4 mg/mL. The experiment was performed batchwise and the flasks were shaken at 110 rpm using an orbital shaker and the observations were recorded. 1 mL of the solution was removed and the biochar was immediately separated from the solution by centrifugation at 10000 rpm for 10 minutes. Each sample was repeated six times, and controls without the biosorbent material were used to distinguish between possible metal precipitation and actual metal adsorption. Samples were filtered through a #42 µm Whatman filter paper, and metal concentration was determined by atomic absorption spectrophotometry (AAS). Arsenic (As) was determined using the cold vapor technique, and Cd, Cr, Cu, Ni, and Pb were determined using the FAAS technique. The MHS-15 chemical vapor generation system (Perkin-Elmer) was coupled to the AA spectrometer for the determination of As. The instrument was calibrated before performing the experiment to ensure the accuracy of the results with an RSD of less than 5% (Chan et al. 2021b ; Roy and Bharadvaja 2021 ; Xing et al. 2021 ). The removal efficiency (E) of heavy metals was calculated as follows: $$\text{%} \text{R}\text{e}\text{m}\text{o}\text{v}\text{a}\text{l}=\frac{\text{C}\text{i}-\text{C}\text{f}}{\text{C}\text{i}} \times 100$$ Where Ci is the initial concentration of metal of metal and Cf is the final concentration of metal in ppm. Results Different types of animal bones including fish bones (A), country hen bones (B), broiler hen bones (C), goat trotters (D), goat horns (E), cow bones (F) and buffalo horns (G) were subjected for the chemical tests and instrumental techniques such as basicity test, qualitative analysis of element and quantitative analysis of Ca + 2 . The instrumental techniques which are used are furnace for calcination, atomic absorption spectrophotometry (AAS) and Fourier transform infrared spectroscopy (FTIR). All the samples were also analyzed for microbial activities. In addition, the samples were also tested as nano-biofertilizers. All bones were calcinated at 1000°C. By calcination all bones were converted into the oxide particularly CaO and other oxides. After calcination, the animal bones surface was very smooth, and they contained tiny pore size (nanosized) particles. At low temperature like 600 o C only organic components are removed and carbonates are not converted into CaO. At high temperatures like 1000 o C or 1200 o C, carbonates are converted into CaO. FTIR spectra of all samples were determined by Fourier transform infrared spectroscopy. Their FTIR spectra showed only one peak at 1050 cm − 1 which is the characteristic peak for CaO (Fig. 3 ). It was further supported by the reported literature (Engin et al. 2006 ; Figueiredo et al. 2010 ). Buffalo horns showed the highest basicity among the above mentioned bones which means it contains high percentages of Ca, P and N. Goat trotters and goat horns also showed the high basicity but lower than buffalo horns (Table 1 ). Cow bones and chicken bones (country) showed the lowest basicity while fish bones and chicken bone (broiler) showed the moderate basicity (Table 1 ). White precipitates were appeared as a result of calcium test which confirmed the presence of calcium in bones and gelatin like white precipitates were appeared as a result of magnesium test which confirmed the presence of magnesium in bones. Buffalo horns showed the highest percentage of Ca + 2 than all the other bones (Table 2 ). Cow bones also showed the high percentage of Ca + 2 but buffalo bones dominated all bones. Similarly, fish bones and chicken bones (country) showed the moderate percentages while chicken bones (broiler), goat trotters and goat horns showed the lowest percentages of calcium. Chicken bones (broiler) contained the lowest percentage of calcium (Table 2 ). The animal bones were analyzed by flame atomic absorption spectrophotometry which showed the presence of different metals like Ca, Cd, Cu, Fe, K, Mg, Ni, As, Pb etc. The highest percentage of Ca (106.80 mg/l), Mg (2.038 mg/l) and As (9,690 mg/l) were observed in chicken bones (broiler) and the lowest percentage of Ca (89.44 mg/l), Mg (1.656 mg/l) and As (10.30 mg/l) were observed in buffalo horns (Table 3 ). Table 1 Determination of basicity of different calcinated bones by chemical method Name of bones Basicity (m. moles of benzoic acid/g of bones) Fish bones (A) 0.025 Chicken bones (country) (B) 0.015 Chicken bones (broiler) (C) 0.02 Goat trotters (D) 0.035 Goat horns (E) 0.03 Cow bones (F) 0.015 Buffalo horns (G) 0.13 In the present study, fish bones, chicken bones (both country and broiler), and bones and horns of goats, cows, and buffaloes were collected from fish harbor, poultry markets, and slaughterhouses at different locations in Karachi. To determine their importance as biofertilizers, their macronutrients (C, N, Ca, P, K, and Mg) were evaluated and fertility was assessed by growing kidney bean plants. Plant growth with each fertilizer was checked after 1–5 weeks. Biochar was prepared from different bones/horns, and the filtration capacity of each type of biochar was tested with different heavy metal solutions at different concentrations. Table 2 Determination of percentage of calcium in different calcinated bones by chemical method Name of bones and code Ca + 2 (%) Fish bones (A) 53.57 Chicken bones (country) (B) 52.50 Chicken bones (broiler) (C) 40.0 Goat trotters (D) 47.12 Goat horns (E) 43.19 Cow bones (F) 57.12 Buffalo horns (G) 63.90 Table 3 Determination of metals content (ppm) in samples by flame Atomic Absorption Spectrophotometer (FAAS). Sample ID Ca Mean ± SD Cd Mean ± SD Cu Mean ± SD Fe Mean ± SD K Mean ± SD Mg Mean ± SD Ni Mean ± SD As Mean ± SD Pb Mean ± SD 1 92.73 ± 1.041 0.012 ± 0.0001 0.406 ± 0.0034 3.636 ± 0.0313 18.23 ± 0.004 5.668 ± 0.0181 0.323 ± 0.0012 7.786 ± 0.3837 0.804 ± 0.0188 2 98.78 ± 6.187 0.013 ± 0.0001 0.159 ± 0.0027 1.464 ± 0.0135 18.28 ± 0.016 5.544 ± 0.0199 0.301 ± 0.0015 8.775 ± 0.5173 0.776 ± 0.0102 3 106.80 ± 8.28 0.013 ± 0.0002 0.137 ± 0.0964 0.396 ± 0.0039 18.30 ± 0.000 2.038 ± 0.0093 0.287 ± 0.0056 9.690 ± 0.8197 0.724 ± 0.0135 4 92.95 ± 0.576 0.012 ± 0.0002 0.159 ± 0.0015 5.089 ± 0.0119 18.36 ± 0.001 1.936 ± 0.0058 0.328 ± 0.0027 10.88 ± 0.623 0.861 ± 0.0242 5 94.23 ± 1.703 0.012 ± 0.0002 0.172 ± 0.0034 1.682 ± 0.0185 18.36 ± 0.001 1.960 ± 0.0057 0.286 ± 0.0041 12.11 ± 0.258 0.836 ± 0.0313 6 96.67 ± 1.908 0.012 ± 0.0003 0.120 ± 0.0028 0.843 ± 0.0060 18.37 ± 0.002 1.950 ± 0.0066 0.305 ± 0.0025 13.22 ± 0.346 0.930 ± 0.0017 7 89.44 ± 0.146 0.004 ± 0.0002 0.924 ± 0.0039 2.185 ± 0.0056 5.816 ± 0.0191 1.656 ± 0.0031 0.116 ± 0.0083 10.30 ± 0.293 0.422 ± 0.0102 Total carbon (TC) and total nitrogen (TN) were determined at different temperatures (200°C, 400°C, 600°C, 800°C, and 1000°C) from different samples; fish bones, chicken bones (both country and broiler), goat bones, goat horns, cow bones, cow horns, buffalo bones, and buffalo horns (Table 4 ). TC and TN tended to decrease with increasing temperature. At a given temperature (200–1000°C), among the different bones and horns samples, broiler chicken bones generally had the lowest TC and TN values (TC = 33 − 1.1 g/Kg; TN = 5.5 − 0.24 g/Kg), while the highest TC and TN values were found in buffalo bone samples (TC = 329 − 14.3 g/Kg; TN = 44-1.21 g/Kg). When comparing bones and horns, higher TC and TN values were found in the bone samples than in the horn samples. During combustion, the concentration of TC and TN was highest at 200°C, while the lowest concentration was measured at 1000°C. At 1000°C, the maximum loss of TC and TN was found to be between 95.5 and 97.5%. Table 4 Determination of carbon and nitrogen by CHN analyzer Total Carbon (g/Kg) at different temp. Total Nitrogen (g/Kg) at different temp. Samples 200°C 400°C 600°C 800°C 1000°C 200°C 400°C 600°C 800°C 1000°C Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Fish bone 125 ± 5.28 42.5 ± 2.33 7.3 ± 0.75 5.5 ± 0.63 3.7 ± 0.70 19 ± 0.71 6.9 ± 0.34 2.6 ± 0.26 0.8 ± 0.07 0.68 ± 0.03 Chicken bone (country) 112 ± 5.32 37.2 ± 1.10 6.1 ± 0.50 4.7 ± 0.25 3.1 ± 0.36 15 ± 0.51 4.8 ± 0.28 1.9 ± 0.22 0.6 ± 0.07 0.52 ± 0.03 Chicken bone (broiler) 33 ± 1.47 14 ± 0.80 3 ± 0.34 2.1 ± 0.27 1.1 ± 0.18 5.5 ± 0.27 2 ± 0.23 1.1 ± 0.14 0.39 ± 0.04 0.24 ± 0.02 Goat bone 317 ± 10.20 103.6 ± 4.15 21.4 ± 1.06 17.4 ± 0.48 13.1 ± 0.41 41 ± 1.33 17.9 ± 0.57 3.9 ± 0.31 1.3 ± 0.17 1.09 ± 0.08 Goat horns 288 ± 8.62 96.1 ± 4.01 19.3 ± 0.63 15.7 ± 0.42 11.4 ± 0.50 33 ± 1.36 16.1 ± 0.56 3.3 ± 0.42 1.09 ± 0.08 0.99 ± 0.06 Cow bone 155 ± 7.07 52.3 ± 1.88 10.5 ± 0.55 8.1 ± 0.37 6.9 ± 0.38 22 ± 0.88 10.9 ± 0.51 2.7 ± 0.24 0.98 ± 0.04 0.81 ± 0.04 Cow horns 122 ± 2.20 41.9 ± 0.67 8.5 ± 0.43 7.7 ± 0.35 6 ± 0.34 17 ± 0.79 8.3 ± 0.31 2.1 ± 0.24 0.88 ± 0.05 0.72 ± 0.03 Buffalo bone 329 ± 4.86 110.2 ± 2.65 22.8 ± 1.11 18.1 ± 0.35 14.3 ± 0.40 44 ± 1.08 18.1 ± 0.48 4.1 ± 0.36 1.42 ± 0.14 1.21 ± 0.03 Buffalo horns 299 ± 5.24 98.1 ± 2.49 19.4 ± 0.86 17.2 ± 0.44 13.2 ± 0.48 37 ± 1.41 17.5 ± 0.46 3.5 ± 0.45 1.22 ± 0.07 1.1 ± 0.03 The total content of calcium (Ca), phosphorus (P), potassium (K) and magnesium (Mg) in the calcified bone samples was determined. Overall, among the different samples, the lowest concentration of these four elements was recorded in the bones of broiler chickens (Ca; 55 g/Kg, P; 26 g/Kg, K; 2.5 g/Kg and Mg; 0.83 g/Kg), while the highest concentrations were recorded in the bones of buffaloes (Ca; 112 g/Kg, P; 54 g/Kg, K; 5.5 g/Kg and Mg; 1.9 g/Kg). When comparing bone and horn samples, the concentration of these elements was higher in the bones than in the horn samples from the same animal. The concentration in the bone country chickens was higher than in those of broiler chickens (Table 5 ). Table 5 Determination of Ca, K and Mg by atomic absorption spectroscopy and P by UV-VIS spectroscopy Samples Ca Mean ± SD P Mean ± SD K Mean ± SD Mg Mean ± SD Fish bone 95 ± 3.62 46 ± 1.21 5 ± 0.45 1.8 ± 0.09 Chicken bone (country) 81 ± 1.83 40 ± 0.89 4.2 ± 0.34 1.4 ± 0.18 Chicken bone (broiler) 55 ± 1.05 26 ± 0.75 2.5 ± 0.12 0.83 ± 0.01 Goat bone 107 ± 2.88 52 ± 1.33 5.3 ± 0.44 1.8 ± 0.21 Goat horns 99 ± 2.59 47 ± 1.51 4.5 ± 0.39 1.5 ± 0.14 Cow bone 101 ± 2.32 48 ± 1.69 5 ± 0.52 1.8 ± 0.40 Cow horns 96 ± 2.64 47 ± 1.38 4.8 ± 0.36 1.7 ± 0.21 Buffalo bone 112 ± 3.39 54 ± 1.76 5.5 ± 0.38 1.9 ± 0.23 Buffalo horns 105 ± 3.16 51 ± 1.97 5.2 ± 0.51 1.7 ± 0.27 To determine the fertility effect of the biofertilizers prepared from the bone/horn samples, kidney bean plants were grown in pots containing the biofertilizers prepared from the bone samples. Seeds were sown in each pot and their growth was observed for up to 5 weeks. Each week, the size of the stems and leaves of each plant was determined (cm). The plant grown in buffalo bone biofertilizer showed maximum growth after 5 weeks (leaves 7.5 cm and stems 27.2 cm), while the plant grown in the broiler chicken bone biofertilizer showed minimum growth (stems 15.2 cm, leaves 4 cm). In comparison, the plants fertilized with the horns grew less than the plants fertilized with the bones of the same animal (Table 6 ). Table 6: Determination of biofertilizer efficacy of different samples S. No. Name of Samples After 1 st week After 2 nd week After 3 rd week After 4th week After 5 th week Average Size (cm) Stem Leaves Stem Leaves Stem Leaves Stem Leaves Stem Leaves 1 Fish bones 5.2 2 10.8 4 12 4.6 19 5.2 21.5 5.5 2 Chicken bones (country) 4.4 2.5 8.2 3.7 15.2 3.8 17 4 17.5 4.7 3 Chicken bones (broiler) 3.2 1.7 4.5 1.8 8.3 3.2 14.8 3.5 15.2 4 4 Goat bones 11.5 3.9 16.2 4.35 20 5.8 21.5 6.5 25 7.1 5 Goat horns 11 3.1 15.9 4.34 21.5 5.6 25 6 20 6.9 6 Cow bones 6.5 2.4 11.9 4.85 17 5.2 19.5 5.9 23.7 6.7 7 Cow horns 5.5 1.8 10.5 3.9 14.9 4.4 18.9 5 21.3 5.4 8 Buffalo bones 12 3.5 18.2 5 22.4 6.1 23.7 7.4 27.2 7.6 9 Buffalo horns 11.8 3.2 18 4.98 22.2 6 23.5 7.2 27 7.5 10 Reference 3 1.4 4 1.6 8 3 14.5 3.5 15 3.8 In Tables 7 – 16 , the heavy metals adsorption capability of biochar from each sample (bones/horns) was determined. This adsorption capability was checked by the effect of time and concentration on removal of six heavy metals; arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni) and lead (Pb). Comparison of the adsorption capability of the biochar made by the different animals, the comparison of bones biochar and horns biochar was done by comparing their adsorption ability by filtration of water solutions containing different heavy metals. In this study concentration of biochar (made from fish and chicken bones and bones and horns of goat, cow and buffalo) was 1 mg/mL and heavy metal concentration of 100 ppm was used. As time of adsorption was changed from 1 to 6 h, efficiency increases and after 6 h, the efficiency began to decrease. The lowest concentration of heavy metals removal (at 6 h) was recorded by broiler chicken bone biochar while the highest concentration was recorded from the biochar of buffalo bone. In the comparison of biochar made by bones and horns, it was observed that the biochar made by the bones have higher ability of removal of heavy metals than those of horns of same animal. Overall, at 6 h, the lowest removal efficiency of broiler chicken bone biochar was recorded for arsenic (36%) while highest removal efficiency was recorded by the biochar of buffalo bone (75%). Among the metals, the lowest filtration was observed for the arsenic while highest filtration was recorded for lead (for each biochar sample). Efficiency of biochar was studied at different concentration of six heavy metals (As, Cd, Cr, Cu, Ni and Pb) removed from the artificial wastewater (100 to 500 mg/Kg). All the biochar samples showed highest ability of heavy metals removal at the concentration of 100 mg/Kg while the lowest capability at 500 mg/Kg of artificial wastewater. Among the comparison of all the biochar samples, biochar made from buffalo bone showed the highest filtration for all of the heavy metals from wastewater at 100 mg/Kg (As = 61%, Cd = 71%, Cr = 68%, Cu = 66%, Ni = 63%, Pb = 76%). While the lowest percentage of filtration was recorded by the broiler chicken bone biochar sample (As = 38%, Cd = 46%, Cr = 43%, Cu = 42%, Ni = 39%, Pb = 50%). The removal order of all heavy metals during both time and concentration was same i.e. Pb > Cd > Cr > Cu > Ni > As. While the efficiency order of biochar samples was; buffalo bone biochar > buffalo horn biochar > goat bone biochar > goat horn biochar > cow bone biochar > fish bone biochar > cow horn biochar > country chicken biochar > broiler chicken bone biochar. Table 7 Removal of heavy metals from wastewater at different time (hour) in fish bone Time (h) As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 1 2 ± 0.29 4 ± 0.52 3 ± 0.33 3 ± 0.34 2 ± 0.34 5 ± 0.69 2 10 ± 0.93 18 ± 0.88 15 ± 0.87 13 ± 0.69 12 ± 0.68 20 ± 1.33 3 25 ± 1.33 35 ± 1.94 30 ± 1.41 28 ± 1.30 26 ± 1.03 40 ± 1.63 4 37 ± 1.51 43 ± 1.63 41 ± 1.38 39 ± 1.63 38 ± 1.47 49 ± 1.67 5 42 ± 1.67 50 ± 1.76 48 ± 1.63 45 ± 1.64 43 ± 1.30 55 ± 1.43 6 47 ± 1.51 57 ± 1.83 55 ± 1.30 52 ± 1.30 50 ± 1.03 62 ± 2.09 7 46 ± 1.17 56 ± 1.26 54 ± 1.90 51 ± 1.63 49 ± 1.02 61 ± 1.30 Table 8 Removal of heavy metals from wastewater by biochar Conc. mg/Kg As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 100 48 ± 1.60 58 ± 2.56 56 ± 1.72 54 ± 2.06 52 ± 1.90 64 ± 2.35 200 43 ± 1.79 50 ± 2.60 42 ± 1.57 45 ± 1.91 45 ± 1.60 56 ± 1.90 300 35 ± 1.30 38 ± 1.02 33 ± 1.14 41 ± 1.26 39 ± 0.97 50 ± 1.72 400 25 ± 1.46 26 ± 0.88 25 ± 1.10 28 ± 1.02 27 ± 0.95 42 ± 1.29 500 15 ± 0.88 19 ± 0.79 19 ± 0.63 18 ± 0.82 16 ± 0.68 21 ± 0.93 Table 9 Removal of heavy metals from wastewater by the biochar of chicken bones at different time (hour) Chicken bone (country) Chicken bone (broiler) Time (h) As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 1 2 ± 0.36 4 ± 0.54 3 ± 0.38 3 ± 0.36 3 ± 0.32 4 ± 0.45 2 ± 0.25 3 ± 0.29 3 ± 0.33 3 ± 0.35 3 ± 0.37 4 ± 0.40 2 10 ± 0.88 16 ± 0.79 13 ± 0.71 12 ± 0.74 12 ± 0.89 18 ± 0.71 8 ± 0.71 13 ± 0.88 11 ± 0.67 10 ± 0.54 9 ± 0.55 15 ± 0.98 3 20 ± 1.11 31 ± 0.92 29 ± 1.03 25 ± 1.28 24 ± 1.11 35 ± 1.33 18 ± 0.92 25 ± 1.24 24 ± 0.84 22 ± 0.93 19 ± 0.88 30 ± 1.33 4 33 ± 1.36 41 ± 1.41 38 ± 1.26 35 ± 1.33 30 ± 1.33 45 ± 1.08 28 ± 1.37 33 ± 1.41 30 ± 1.03 29 ± 1.03 25 ± 1.17 39 ± 1.63 5 40 ± 1.38 48 ± 1.33 43 ± 1.13 40 ± 1.08 35 ± 1.08 52 ± 1.26 35 ± 1.33 42 ± 1.60 40 ± 1.63 37 ± 1.67 33 ± 1.21 45 ± 1.94 6 42 ± 1.51 52 ± 1.67 50 ± 1.25 45 ± 1.47 43 ± 1.67 56 ± 1.76 36 ± 1.36 44 ± 1.69 41 ± 1.74 40 ± 1.69 37 ± 1.40 47 ± 1.67 7 41 ± 1.21 51 ± 1.17 49 ± 1.28 43 ± 1.41 42 ± 1.69 54 ± 1.28 35 ± 1.41 42 ± 1.33 40 ± 1.26 39 ± 1.17 36 ± 1.03 45 ± 1.72 Table 10 Removal of heavy metals from wastewater by the biochar of chicken bones Chicken bone (country) Chicken bone (broiler) Conc. mg/Kg As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 100 46 ± 1.41 54 ± 1.72 52 ± 1.74 47 ± 1.46 45 ± 1.50 57 ± 1.99 38 ± 1.30 46 ± 1.50 43 ± 1.47 42 ± 1.08 39 ± 1.20 50 ± 1.78 200 41 ± 1.33 49 ± 1.63 45 ± 1.33 41 ± 1.07 36 ± 0.89 53 ± 1.76 35 ± 1.08 43 ± 1.11 40 ± 1.03 39 ± 1.11 35 ± 1.01 46 ± 1.36 300 35 ± 1.03 42 ± 1.21 39 ± 1.44 37 ± 1.07 30 ± 1.03 45 ± 1.41 28 ± 0.89 34 ± 1.03 32 ± 0.93 31 ± 0.94 27 ± 0.86 40 ± 1.08 400 22 ± 0.86 33 ± 1.11 30 ± 0.97 27 ± 0.98 25 ± 0.82 36 ± 1.03 18 ± 0.74 27 ± 0.88 25 ± 0.92 24 ± 0.86 20 ± 0.92 32 ± 1.03 500 12 ± 0.69 18 ± 0.97 14 ± 0.74 14 ± 0.72 13 ± 0.83 19 ± 0.85 10 ± 0.46 14 ± 0.63 12 ± 0.61 12 ± 0.60 11 ± 0.69 17 ± 0.74 Table 11 Removal of heavy metals from wastewater by the biochar of goat bones and horns at different time (hour) Goat bone Goat horns Time (h) As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 1 4 ± 0.47 5 ± 0.46 5 ± 0.35 5 ± 0.35 5 ± 0.34 6 ± 0.34 4 ± 0.59 5 ± 0.88 5 ± 0.52 5 ± 0.69 5 ± 0.63 6 ± 0.71 2 15 ± 0.66 20 ± 1.33 18 ± 0.84 18 ± 0.66 16 ± 0.66 22 ± 0.98 11 ± 0.88 16 ± 1.03 14 ± 0.84 14 ± 0.92 14 ± 0.98 20 ± 0.98 3 28 ± 0.71 39 ± 0.93 35 ± 1.56 34 ± 0.92 30 ± 1.37 40 ± 1.37 24 ± 1.11 35 ± 1.37 31 ± 1.11 30 ± 1.37 29 ± 1.17 38 ± 0.82 4 45 ± 0.94 52 ± 1.28 50 ± 2.04 48 ± 1.26 48 ± 1.60 54 ± 1.76 40 ± 1.60 48 ± 1.63 43 ± 1.99 42 ± 1.67 40 ± 1.43 50 ± 1.36 5 53 ± 1.23 61 ± 1.03 58 ± 1.43 56 ± 1.67 56 ± 1.28 65 ± 2.16 48 ± 1.78 59 ± 1.79 54 ± 2.04 53 ± 1.90 49 ± 1.90 61 ± 1.97 6 58 ± 1.42 69 ± 2.04 65 ± 2.16 63 ± 1.76 60 ± 2.09 73 ± 2.23 53 ± 2.23 63 ± 2.06 60 ± 2.50 58 ± 2.07 57 ± 1.60 68 ± 2.51 7 57 ± 1.28 68 ± 1.33 64 ± 1.41 62 ± 1.60 59 ± 1.94 72 ± 1.86 52 ± 1.63 62 ± 2.00 59 ± 2.19 57 ± 1.90 56 ± 1.76 67 ± 2.75 Table 12 Removal of heavy metals from wastewater by biochar of goat bones and horns at concentration of heavy metals Goat bone Goat horns Conc. mg/Kg As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 100 59 ± 1.90 70 ± 2.95 67 ± 1.63 65 ± 1.51 61 ± 2.04 75 ± 2.14 55 ± 1.63 65 ± 2.53 62 ± 2.28 60 ± 1.84 58 ± 1.96 69 ± 2.25 200 54 ± 1.60 63 ± 1.80 60 ± 1.60 58 ± 1.69 57 ± 1.90 67 ± 1.86 49 ± 1.33 60 ± 1.72 56 ± 1.90 55 ± 1.41 50 ± 1.41 63 ± 1.78 300 46 ± 1.76 54 ± 1.67 52 ± 1.87 50 ± 1.33 50 ± 1.41 55 ± 1.90 42 ± 1.41 50 ± 1.30 45 ± 1.60 44 ± 1.33 42 ± 1.28 52 ± 1.74 400 30 ± 1.03 41 ± 1.26 37 ± 0.99 36 ± 1.02 32 ± 1.14 42 ± 1.63 26 ± 0.93 37 ± 1.08 33 ± 0.98 32 ± 0.97 31 ± 1.03 40 ± 1.10 500 17 ± 0.89 21 ± 0.88 20 ± 0.71 20 ± 0.98 17 ± 0.88 24 ± 1.02 13 ± 0.56 17 ± 0.66 16 ± 0.75 16 ± 0.56 16 ± 0.83 22 ± 1.02 Table 13 Removal of heavy metals from wastewater by the biochar of cow bones and horns at different time (hour) Cow bones Cow horns Time (h) As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 1 2 ± 0.37 5 ± 0.66 4 ± 0.63 4 ± 0.52 4 ± 0.38 6 ± 0.82 2 ± 0.28 4 ± 0.71 4 ± 0.46 4 ± 0.38 4 ± 0.36 5 ± 0.48 2 14 ± 0.71 18 ± 0.88 16 ± 0.99 16 ± 0.80 15 ± 0.71 20 ± 0.88 12 ± 0.52 17 ± 0.80 16 ± 0.88 16 ± 1.02 15 ± 0.66 0.82 ± 0.81 3 28 ± 1.03 32 ± 1.37 31 ± 1.11 30.5 ± 1.13 29 ± 1.03 36 ± 1.03 25 ± 1.21 33 ± 1.02 32 ± 1.03 31 ± 1.11 29 ± 1.02 35 ± 1.03 4 1.02 45 ± 1.60 44 ± 1.33 42 ± 1.17 41 ± 1.33 50 ± 1.37 34 ± 1.30 45 ± 1.36 44 ± 1.38 43 ± 1.03 41 ± 1.21 48 ± 1.22 5 45 ± 1.37 54 ± 1.69 52 ± 1.39 51 ± 1.43 49 ± 1.17 56 ± 1.26 42 ± 1.41 52 ± 1.33 51 ± 1.67 49 ± 1.11 47 ± 1.38 56 ± 1.60 6 49 ± 1.68 60 ± 2.11 58 ± 1.60 55 ± 1.10 52 ± 1.60 65 ± 2.23 47 ± 2.07 58 ± 1.86 56 ± 2.07 53 ± 1.33 50 ± 1.33 63 ± 1.86 7 48 ± 1.50 59 ± 1.75 56 ± 1.26 54 ± 1.33 51 ± 1.05 64 ± 1.36 46 ± 1.84 57 ± 1.72 55 ± 1.47 52 ± 1.37 49 ± 1.90 62 ± 1.72 Table 14 Removal of heavy metals from wastewater by biochar of cow bones and horns at concentration of heavy metals Cow bones Cow horns Conc. mg/Kg As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 100 51 ± 1.30 62 ± 1.91 59 ± 2.23 57 ± 1.75 53 ± 1.86 67 ± 2.28 49 ± 1.87 60 ± 3.16 57 ± 2.46 55 ± 2.28 51 ± 2.61 65 ± 2.83 200 46 ± 1.24 53 ± 1.60 50 ± 1.86 50 ± 1.33 47 ± 1.86 58 ± 2.64 41 ± 1.76 54 ± 2.66 52 ± 2.14 50 ± 1.74 45 ± 2.38 57 ± 2.73 300 37 ± 1.16 45 ± 1.33 42 ± 1.28 41 ± 1.37 37 ± 1.41 51 ± 1.75 35 ± 1.36 46 ± 1.96 44 ± 1.76 42 ± 1.80 40 ± 1.36 49 ± 2.32 400 27 ± 0.97 30 ± 1.11 30 ± 1.11 29 ± 1.28 27 ± 1.33 38 ± 1.41 26 ± 1.28 35 ± 1.67 34 ± 1.36 31 ± 1.25 30 ± 1.03 36 ± 1.44 500 16 ± 0.72 19 ± 0.86 17 ± 0.60 16 ± 0.95 16 ± 0.98 22 ± 0.98 14 ± 0.76 17 ± 0.92 15 ± 0.97 15 ± 0.83 15 ± 0.91 20 ± 1.033 Table 15 Removal of heavy metals from wastewaterby biochar of buffalo bones and horns at different time (hour) Buffalo bones Buffalo horns Time (h) As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 1 4 ± 0.46 6 ± 0.55 5 ± 0.06 5 ± 0.46 4 ± 0.37 7 ± 0.47 4 ± 0.46 5 ± 0.41 5 ± 0.41 5 ± 0.46 4 ± 0.47 6 ± 0.55 2 16 ± 0.93 22 ± 0.66 20 ± 0.99 18 ± 0.98 17 ± 0.71 23 ± 0.99 15 ± 0.92 18 ± 0.88 17 ± 0.71 17 ± 0.94 16 ± 0.71 20 ± 1.08 3 32 ± 1.02 40 ± 1.26 38 ± 1.26 36 ± 1.03 35 ± 1.02 42 ± 1.33 30 ± 1.17 37 ± 1.33 36 ± 0.88 34 ± 0.95 33 ± 0.99 39 ± 1.40 4 44 ± 1.41 54 ± 1.33 52 ± 1.38 50 ± 1.33 48 ± 1.63 56 ± 1.38 42 ± 1.33 51 ± 1.30 49 ± 1.60 47 ± 1.33 45 ± 1.30 52 ± 1.14 5 55 ± 1.97 65 ± 1.33 63 ± 1.72 61 ± 1.94 59 ± 1.94 68 ± 1.75 52 ± 1.40 62 ± 1.76 60 ± 1.67 57 ± 1.28 54 ± 1.60 66 ± 1.90 6 60 ± 2.23 70 ± 1.63 67 ± 1.86 65 ± 2.42 62 ± 1.86 75 ± 2.32 56 ± 1.75 66 ± 1.80 64 ± 1.63 62 ± 1.41 59 ± 2.04 71 ± 1.63 7 59 ± 2.11 69 ± 2.06 66 ± 2.25 64 ± 1.63 61 ± 2.23 74 ± 1.90 55 ± 1.36 65 ± 1.43 63 ± 1.72 61 ± 1.41 60 ± 1.70 70 ± 1.96 Table 16 Removal of heavy metals by biochar of buffalo bones and horns at concentration of HM Buffalo bones Buffalo horns Conc. mg/Kg As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD As Mean ± SD Cd Mean ± SD Cr Mean ± SD Cu Mean ± SD Ni Mean ± SD Pb Mean ± SD 100 61 ± 2.94 71 ± 3.72 68 ± 2.14 66 ± 2.64 63 ± 2.50 76 ± 3.31 57 ± 2.73 67 ± 3.33 65 ± 3.09 63 ± 2.29 60 ± 3.46 72 ± 3.37 200 56 ± 1.75 64 ± 2.64 63 ± 2.07 62 ± 2.48 60 ± 2.71 70 ± 2.61 53 ± 2.07 63 ± 3.08 61 ± 3.31 55 ± 2.43 53 ± 2.34 65 ± 2.42 300 45 ± 1.86 55 ± 1.86 53 ± 2.16 51 ± 2.17 50 ± 2.59 57 ± 2.53 42 ± 1.75 52 ± 2.48 50 ± 2.88 45 ± 1.67 44 ± 2.14 53 ± 2.06 400 33 ± 1.41 42 ± 1.33 40 ± 1.75 38 ± 1.75 36 ± 1.43 43 ± 1.69 31 ± 1.41 38 ± 1.41 37 ± 1.41 33 ± 1.41 32 ± 1.60 40 ± 2.42 500 18 ± 0.94 24 ± 1.11 21 ± 1.03 19 ± 1.03 18 ± 0.86 25 ± 1.33 18 ± 1.03 20 ± 1.02 19 ± 0.88 19 ± 1.08 18 ± 0.88 23 ± 1.02 According to results, fish bones, chicken bones (country), chicken bones (broiler) and goat trotters showed antibacterial activities against Enterococcus faecalis while fish bones were found to be active against Staphylococcus aureus and Bacillus subtilis . Chicken bones (country) and goat trotters showed antibacterial activities against Salmonella typhi while goat trotters were found to be active against Pseudomonas aeruginosa . However, none of the bones had any bioactivity against E. coli . Fish bones showed antifungal activities against Candida albicans while none of the bones were found to be active against plant pathogenic fungi (Table 17 – 20 ; Fig. 4 – 6 ). Table 17 Antibacterial activity of different calcinated bones against Gram positive bacteria. Sample names Zone of inhibition (mm) Staphylococcus aureus Bacillus subtilis Enterococcus faecalis Fish bones 19 mm 20 mm 10 mm Chicken bones (country) -ve -ve 20 mm Chicken bones (broiler) -ve -ve 15 mm Goat trotters -ve -ve 20 mm Goat horns -ve -ve -ve Cow bones -ve -ve -ve Buffaloes horns -ve -ve -ve -ve = no zone of growth inhibition. Table 18 Antibacterial activity of different calcinated bones against Gram negative bacteria Sample names Zone of inhibition (mm) Escherichia coli Pseudomonas aeruginosa Salmonella typhi Fish bones -ve -ve -ve Chicken bones (country) -ve -ve 10mm Chicken bones (broiler) -ve -ve -ve Goat trotters -ve 15 mm 12 mm Goat horns -ve -ve -ve Cow bones -ve -ve -ve Buffaloes horns -ve -ve -ve -ve = no zone of growth inhibition. Table 19 Antifungal activity of different calcinated bones against fungi Name of samples Zone of inhibition (mm) Candida albicans Candida glabrata Mucor sp. Aspergillus niger Aspergillus flavus Fish bones 10 mm -ve -ve -ve -ve Chicken bones (country) -ve -ve -ve -ve -ve Chicken bones (broiler) -ve -ve -ve -ve -ve Goat trotters -ve -ve -ve -ve -ve Goat horns -ve -ve -ve -ve -ve Cow bones -ve -ve -ve -ve -ve Buffaloes horns -ve -ve -ve -ve -ve Table 20 Antifungal activity of different calcinated bones against plant pathogenic fungi Sample names Zone of inhibition (mm) Alternaria sp. Drechslera sp. Humicola sp. Fish bones -ve -ve -ve Hen bones (country) -ve -ve -ve Hen bones (broiler) -ve -ve -ve Goat trotters -ve -ve -ve Goat horns -ve -ve -ve Cow bones -ve -ve -ve Buffaloes horns -ve -ve -ve Discussion The rapid increase in the population causes the decline in food and pure water resources as a result; the use of inorganic fertilizers and use of different technologies for the treatment of polluted water are being increased in present decade. While there is another big alarming problem caused by burgeoning population. It is the consumption of meat, which has also been increased in large scale, as a result the biowastes of fish, poultry and animals indirectly posing challenge to the final disposal. The use of inorganic/chemical fertilizers is not only cost intensive but also creates the problem of environmental pollution. Chemical fertilizers cause water pollution by eutrophication of water bodies. It has been recorded that in majority of the cases, the efficiency of the inorganic fertilizers is lower. Almost, half of the inorganic fertilizer in most cases and more often almost 80–90%, of these fertilizers remain unutilized by the plants, so the excessive amount has been flown from agricultural land to the water bodies, and become a source of contamination. This become the cause of decrease in crops production and also increase the aquatic pollution (Arao et al. 2010 ; Qiutong and Mingkui 2017 ; Rashmi et al. 2020 ). The inorganic fertilizers often contain heavy metals, while the fertilizer industry is also considered to be source of natural radionuclides and heavy metals as a potential source, these heavy metals once entered into the aquatic ecosystem, they become the part of food chain and, thus, can affect animal and human health (Rashmi et al. 2020 ; Savci 2012 ). In Pakistan, due to excessive use of inorganic fertilizers, the cost of crops production and water contamination issues have been increased. So there is need of introduction of new low cost and ecofriendly method in agriculture in Pakistan. Moreover, in Pakistan, the animal waste has been a common problem like other countries of the world. Waste from the meat industry is hazardous and causing pollution in the environment. The wastes can become valuable biofertilizer because the animal wastes are the reservoirs of organic matter (50-80%), containing the macronutrients e.g. total carbon, total nitrogen, phosphorus, calcium, potassium and magnesium all of which are important components to increase the fertility of soil and used to increase the crops/plants production. Therefore, in present decade the animal waste is being used for the manufacturing of biofertilizers (Staroń et al. 2017 ; Chojnacka et al. 2019 ; Stępień et al. 2021 ). Researchers also use nitrogen-rich waste as carbon and nitrogen source to produce biochar. The animal waste e.g. bones and horns are rich source of nitrogen and carbon so can be used to produce biochar. Porous carbon material refers to an excellent adsorbent, including biochar contains, activated carbon, and have excellent adsorbent capacity for environmental pollutants especially heavy metals (Smith 2019 ; Jin et al. 2022 ). In the present study, the fish, poultry and animal wastes have been used to make two valuable products i.e. biofertilizer and biochar which were further applied to increase the soil fertility (through biofertilizer) and purifying the water from heavy metals. The biofertilizers were made from the waste bones of fish and poultry and also from the bones and horns of different animals (goat, cow and buffalo). In order to observe the loss of total carbon and nitrogen, during pyrolysis process, different temperatures were applied (200 °C, 400 °C, 600 °C, 800 °C and 1000 °C), and it was recorded that total carbon and nitrogen productivity were decreased with increasing the temperature, both were maximum at minimum temperature (200°C) while became minimized at maximum temperature (1000 °C). It means, total carbon and nitrogen productivity rate in the biofertilizer during pyrolysis, is temperature dependent (Sharma et al. 2020 ; Ahmed et al. 2021a ; Ahmed et al. 2021b ; Khoshnevisan et al. 2021 ). The decrease of TC and TN content of samples, with increasing pyrolysis temperature is attributed to the decomposition of the oxygenated bonds and release of low molecular weight byproducts at high pyrolysis temperature (Suliman et al. 2016 ; Zhang et al. 2017 ; Shafiq and Capareda 2021 ). Because at the lowest temperature (200 °C), the highest productivity (g/Kg) of total carbon (TC) and total nitrogen (TN) was obtained so concentration (g/Kg) of calcium, phosphorus, potassium and magnesium was also determined at the same temperature. During this study, the productivity (g/Kg) of TC, TN, Ca, P, K and Mg was higher in the bone as compared to horn samples of the same animal. The higher productivity of above elements in bone than those of horn samples is probably relates to the differential metabolic processes (found in bones) that occur during different tissue formation, as well as to physiological and dietary parameters. As the horns are derived from bones so higher amount of TC, TN, Ca, P, K and Mg was found in bones as compared to horns (Landete-Castillejos et al. 2007 ; Landete-Castillejos et al. 2012 ; Stevens and O'Connell 2016 ). The usability of animal bone/horns (use in this study) as nano-biofertilizers depends on their composition and a concentration of valuable elements (macronutrients). These macronutrients, found in the byproducts of various animals, affect the plants growth (Samoraj et al. 2022 ) so the present study was designed to focus to observe the effect of nano-biofertilizers on the growth of the plants. The nano-biofertilizers made from the byproducts (bones/horns) of different animals i.e. bones waste of fish and chickens and bones and horns of goat, cow and buffalo. In order to observe the effect of different nano-biofertilizers on the plant growth, the kidney plants were selected. The growth rate was observed in the 5 weeks. The highest growth rate was recorded from the nano-biofertilizers made by the bones of buffalo. It is due to highest concentration of TC and TN and other macroelements e.g. Ca, P, K and Mg. This could be correlated with the nature of the bone, as compared to other bovines, the buffalo growth pattern is slow but it stores more mineral and nutrients in its bones (Spanghero et al. 2004 ). Plants growing under the influence of nano-biofertilizers made by goat and cow bones, showed difference in their growth pattern. Plants growth by the nano-biofertilizers prepared from the bone of goat, showed higher growth pattern as compared to those which grew in the pot containing cow bone biofertilizer. From the previous literature, it was shown that as compared to cow bone, higher concentration of TC, TN and other macro/micronutrients were recorded in the goat bone (Samoraj et al. 2022 ; Ahmed et al. 2021b ; Ramesh et al. 2018 ). It was also found that higher quantity of gelatin could be recorded in the bones of goat (Matulessy et al. 2021 ). Therefore in the present study, the biofertilizer made from goat bone showed more plant growth as compared to that of biofertilizer made from cow. The efficiency of nano-biofertilizer of fish is associated with the high protein and lipid contents found in the fish waste/bone (Maktoof et al., 2020). Therefore, the fish biofertilizer showed more growth in the kidney plant as compared to the biofertilizer made from chicken bones. The biofertilizer produced from the broiler chicken bone showed lowest growth pattern in the kidney bean plant as compared to all of the biofertilizers used in this study. The comparison of biofertilizer of broiler chicken bone with that of the country chicken bone showed that more growth was recorded by the biofertilizer of country chicken bone. Due to unhealthy breeding conditions, many broiler chickens develop weak bone structures and a high risk for avian diseases due to inbreeding, as a result the broiler chickens have less amount of TC, TN, Ca, P, K, Mg and other elements as compared to the country chicken bones. These elements are enriched in bones of country chicken because of their slow growth rate, enables the bones stronger by the enrichment of TC, TN, Ca, P, K, Mg and other elements (Jeon et al. 2010 ; Sokołowicz et al. 2016 ; Ullengala et al. 2020 ). In this study, the artificial wastewater was made by adding different concentration of heavy metals (100 to 500 ppm), the absorption of metals was higher in case of biochar derived from bone samples as compared to biochar derived from horn samples. As compared to horn, the bone has more porosity, so the bone is an excellent adsorbent for heavy metals and dyes, the animal bone char has porous structure, due to porosity, it has been traditionally used as adsorbent for the removal of toxic heavy elements from wastewater (McKittrick et al. 2010 ; Park et al. 2015 ; Park et al. 2016 ; Azeem et al. 2022 ). As compared to chicken-based biochar, the fish-based biochar were more effective to remove the heavy metals. The collagen-rich biomasses are the excellent precursors for the production of biochar. It was recorded from the previous literature that as compared to chicken, the marine fish is best source of collagen; about 30% of fish wastes (especially bone) are very rich in collagen. The formation of biochar from fish bone could be a promising means to gain value-added product, and to lower environmental pollution (Jeong et al. 2013 ; Niu et al. 2019 ; Zhang et al. 2021 ). The biochar made by the country chicken bones showed more efficiency than that of broiler chicken based biochar. This efficiency can be measured by bone structure and the amount of collagen in both types of the chicken. It was recorded that the country chicken bones are more stronger with more minerals (e.g. Ca, P, K, Mg etc.) than those of broiler chicken bones. Moreover, the bones of country chicken contain more collagen than those of broiler chicken (Cchicken et al. 2016 ; Mabelebele et al. 2017 ; Buss et al. 2022 ). Buffalo bone based biochar showed the highest heavy metals removal efficiency. This efficiency is based on the mineral contents (Ca, P, K etc.), which are higher in the bones of buffalo than those of other animals bones, used in this study. The highest minerals are related to the higher growth recorded in the buffalo skeleton. The efficiency may also be increased due to highest TC and TN in the bone which is directly linked with the collagen which is found in the higher amount in the buffalo bones (Mitchell et al. 2005 ; Vidu et al. 2013 ; Samatra et al. 2020 ). The heavy metals adsorption capacity of goat bone biochar was higher than that of cow bone biochar. This efficiency may be related with gelatin and minerals which are higher in goat as compared to cow. The TC, TN, Ca, P, K, Mg etc increase the efficiency of biochar in removal of heavy metals (Wang et al. 2019 ; Ambaye et al. 2021 ; Piash et al. 2021 ; Wang et al. 2021 ). In present study, the removal of heavy metals was maximum at 100 ppm and percentage of removal capacity decreased by increasing the concentration. The adsorption capacity of biochar is highest at low concentration of heavy metals in the solution (Roy and Bharadvaja 2021 ; Ambaye et al. 2021 ; Qiu et al. 2021 ). All the biochar samples, removed the heavy metals from the artificial wastewater samples, with the following order; Pb > Cd > Cr > Cu > Ni > As. High adsorption capacities of Pb by biochars involves multiple mechanisms, including ion exchange, complexation with oxygen-containing functional groups, precipitation with inorganic components and interactions with π electrons (C=C) (Cao et al. 2009 ; Inyang et al. 2012 ; Lu et al. 2012 ; Han et al. 2017 ). Cd is the second metal, which was removed by biochar samples, with higher concentration after Pb because Pb is often accompanied by Cd from a range of anthropogenic sources such as batteries, mining and smelting operations (Han et al. 2017 ; He et al. 2013 ; Li et al. 2014 ). This study suggests that the animal bones (waste product) might be used to produce the commercial fertilizers in terms of crop-enhancing efficiency. These waste bones can also be used to produce biochar which can be used as an effective, low-cost and environmentally friendly nano-adsorbent for the removal of heavy metals from the household, agricultural and industrial wastewaters. Conclusion Pakistan has low resources while its population is increasing rapidly. To meet the demand of rapid growing population, the food and water resources are declining to be lowest level. While the pollution from the animal waste materials is big issue especially in the urban areas. After observing these two burning issues (food water/shortage and animal waste) of the present decade, this study was designed. In the present study, two valuable products are produced from the animal waste products: 1) biofertilizer formulations, which can be used to enhance the efficiency of crops production. By applying these nano-biofertilizers to the commercial scale, the inexpensive green revolution can be obtained in the society, which can fulfil the food to the hunger population. 2) biochar formation; It is recorded from the present study that the biochar prepared from the animals waste could be effective and easy formulated nano-bioadsorbent which is low cost and efficacious resource which can be used for abstraction of heavy metals from aqueous solution. Thus, this adsorbent can be best utilized for adsorption of heavy metals for wastewater treatment. Declarations Author Contributions A. M. Khan: Principal investigator for this research article. He designed main concept and theme of this article. M. A. Usmani: Performed experimental work and written the research article. K. Yasmeen: Performed Atomic Absorption Spectroscopy (AAS) technique for determination of heavy metals. M. N. Ahmed: Improved the drafting of manuscript with valuable suggestions. M. 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Rapid Commun Mass Spectrom, 30(17), 1969–1984. https://doi.org/10.1002/rcm.7670 Su X, Sun K, Cui FZ, Landis WJ (2003) Organization of apatite crystals in human woven bone. Bone 32(2): 150–162. https://doi.org/10.1016/S8756-3282(02)00945-6 Suliman W, Harsh JB, Abu-Lail NI, Fortuna AM, Dallmeyer I, Garcia-Perez M (2016) Influence of feedstock source and pyrolysis temperature on biochar bulk and surface properties. Biomass Bioenerg 84: 37–48. https://doi.org/10.1016/j.biombioe.2015.11.010 Tütken T, Vennemann T W, Pfretzschner HU (2008) Early diagenesis of bone and tooth apatite in fluvial and marine settings: constraints from combined oxygen isotope, nitrogen and REE analysis. Palaeogeography, Palaeoclimatol Palaeoecol 266(3–4): 254–268. https://doi.org/10.1016/j.palaeo.2008.03.037 Ullengala R, Paswan C, Prince LLL, Muthukumar M, Haunshi S, Reddy BL, Chatterjee R (2020) Studies on growth, carcass and meat quality traits in Aseel crosses suitable for small scale intensive broiler farming. J Appl Anim Res 48(1): 507–514. https://doi.org/10.1080/09712119.2020.1837137 Vidu L, Diaconescu C, Călin I, Băcilă V, Bran M (2013) Researches regarding the carcass structure and chemical composition of meat at young buffalo. Paper proceedings of Agri Animal Sci 519. Wang Y, Wang HS, Tang CS, Gu K, Shi B (2019) Remediation of heavy-metal-contaminated soils by biochar: a review. Environ Geotech 9(3): 135–148. https://doi.org/10.1680/jenge.18.00091 Wang Z, Miao R, Ning P, He L, Guan Q (2021) From wastes to functions: a paper mill sludge-based calcium-containing porous biochar adsorbent for phosphorus removal. J Colloid Interface Sci 593: 434–446. https://doi.org/10.1016/j.jcis.2021.02.118 Weigand H, Bertau M, Hübner W, Bohndick F, Bruckert A (2013) RecoPhos: Full-scale fertilizer production from sewage sludge ash. Waste Manag 33(3): 540–544. https://doi.org/10.1016/j.wasman.2012.07.009 Wongrueng A, Rakruam P, Siri A, Siyasukh A (2019) Synthesis of porous pig bone char as adsorbent for removal of DBP precursors from surface water. Water Sci Technol 79(5): 857–865. https://doi.org/10.2166/wst.2018.486 Xing Y, Luo X, Liu S, Wan W, Huang Q, Cchicken W (2021) A novel eco-friendly recycling of food waste for preparing biofilm-attached biochar to remove Cd and Pb in wastewater. J Clean Prod 311: 127514. https://doi.org/10.1016/j.jclepro.2021.127514 Xu Z, Lin X, Lin Q, Yang Y, Wang Y (2007) Nitrogen, phosphorus and energy waste outputs of four marine cage-cultured fish fed with trash fish. Aquac 263(1–4): 130–141. https://doi.org/10.1016/j.aquaculture.2006.10.020 Zhang D, He Q, Hu X, Zhang K, Cchicken C, Xue Y (2021) Enhanced adsorption for the removal of tetracycline hydrochloride (TC) using ball-milled biochar derived from crayfish shell. Colloids Surf A: Physicochem Eng Asp 615: 126254. https://doi.org/10.1016/j.colsurfa.2021.126254 Zhang H, Cchicken C, Gray EM, Boyd SE (2017) Effect of feedstock and pyrolysis temperature on properties of biochar governing end use efficacy. Biomass Bioenerg 105: 136–146. https://doi.org/10.1016/j.biombioe.2017.06.024 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3134479","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":215998322,"identity":"0de6de1e-5db6-4cc4-b063-f4768fcb68a5","order_by":0,"name":"Abdul Majeed Khan","email":"","orcid":"","institution":"Federal Urdu University of Arts, Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Abdul","middleName":"Majeed","lastName":"Khan","suffix":""},{"id":215998325,"identity":"56308fc5-11b7-44d8-8ec7-054f1ce56d1c","order_by":1,"name":"Muhammad Arsalan Usmani","email":"","orcid":"","institution":"Federal Urdu University of Arts, Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Arsalan","lastName":"Usmani","suffix":""},{"id":215998327,"identity":"be2bf817-1f26-4508-b1a0-ed974591013c","order_by":2,"name":"Kousar Yasmeen","email":"data:image/png;base64,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","orcid":"","institution":"Federal Urdu University of Arts, Science and Technology","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Kousar","middleName":"","lastName":"Yasmeen","suffix":""},{"id":215998331,"identity":"4b4cba7e-226b-46af-b739-8348407a9c11","order_by":3,"name":"Muhammad Naeem Ahmed","email":"","orcid":"","institution":"The University of Azad Jammu and Kashmir","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Naeem","lastName":"Ahmed","suffix":""},{"id":215998333,"identity":"aad26937-f1fd-4b59-9f1e-4b257d2acc06","order_by":4,"name":"Muhammad Obaid","email":"","orcid":"","institution":"Federal Urdu University of Arts, Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Obaid","suffix":""},{"id":215998334,"identity":"75267056-441a-4604-af0e-54a73ca08be4","order_by":5,"name":"Sehar Afshan Naz","email":"","orcid":"","institution":"Federal Urdu University of Arts, Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sehar","middleName":"Afshan","lastName":"Naz","suffix":""},{"id":215998335,"identity":"52936b12-110d-493b-a871-612fa7d4d24f","order_by":6,"name":"Sobia Pervaiz","email":"","orcid":"","institution":"Federal Urdu University of Arts, Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sobia","middleName":"","lastName":"Pervaiz","suffix":""},{"id":215998336,"identity":"779fded9-0c0a-4150-9aa3-ae287695efe1","order_by":7,"name":"Malik Wajid Hussain Chan","email":"","orcid":"","institution":"Federal Urdu University of Arts, Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Malik","middleName":"Wajid Hussain","lastName":"Chan","suffix":""},{"id":215998337,"identity":"8f6140cd-dadf-4ac8-83ee-6826b52f01db","order_by":8,"name":"Ali Khan","email":"","orcid":"","institution":"Federal Urdu University of Arts, Sciences and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Khan","suffix":""},{"id":215998338,"identity":"e2c99e33-a0de-4547-be45-e800f5d195d8","order_by":9,"name":"Sardar Aslam","email":"","orcid":"","institution":"University of Karachi","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sardar","middleName":"","lastName":"Aslam","suffix":""}],"badges":[],"createdAt":"2023-07-03 07:14:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3134479/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3134479/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":39856050,"identity":"85e7ab8e-bc24-4b08-9f9d-0ca10895f951","added_by":"auto","created_at":"2023-07-11 14:12:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":259052,"visible":true,"origin":"","legend":"\u003cp\u003eWaste animal bones after calcination: fish bones (A), chicken bones country (B), chicken bones broiler (C), goat trotters (D), goat horns (E), cow bones (F) and buffalo horns (G).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3134479/v1/4c6c0614fc8c68d2d275712e.png"},{"id":39856049,"identity":"c109cd9f-2c07-4cf8-b5b8-37b94abd8338","added_by":"auto","created_at":"2023-07-11 14:12:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":819267,"visible":true,"origin":"","legend":"\u003cp\u003eWeekly measurement of plant’s growth of kidney beans in the presence of different animals calcinated bones.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3134479/v1/4dfa44e8cf8288e5df7d8f5e.png"},{"id":39856053,"identity":"f3b87848-9e3b-46e2-98ed-b8a5f7520556","added_by":"auto","created_at":"2023-07-11 14:12:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":507058,"visible":true,"origin":"","legend":"\u003cp\u003eFTIR spectra of bones including fish bones (A), chicken bones (country) (B), chicken bones (broiler) (C), goat trotters (D), goat horn (E), cow bones (F) and buffalo horns (G).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3134479/v1/a26f03bb09bd4a7d28e8bf67.png"},{"id":39856051,"identity":"88d64221-5092-4934-a441-84307838c212","added_by":"auto","created_at":"2023-07-11 14:12:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":101007,"visible":true,"origin":"","legend":"\u003cp\u003eAntibacterial activity of different calcinated bones against Enterococcus faecalis.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3134479/v1/5a0fd7e7564c4468fbc7734f.png"},{"id":39857579,"identity":"80fa6721-71c6-45af-b7c4-67a34bc90bd4","added_by":"auto","created_at":"2023-07-11 14:20:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":196122,"visible":true,"origin":"","legend":"\u003cp\u003eAntibacterial activity of different calcinated bones against: Pseudomonas aeruginosa (a) and Salmonella typhi (b).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3134479/v1/2605e0124c0d728b0ecb66e0.png"},{"id":39856054,"identity":"b76487d2-f802-4ac7-8185-a561e4a8ccb8","added_by":"auto","created_at":"2023-07-11 14:12:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":104620,"visible":true,"origin":"","legend":"\u003cp\u003eAntifungal activity of different calcinated bones against \u003cem\u003eCandida albicans\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3134479/v1/56f901b1ed4cde5df109be6a.png"},{"id":39857597,"identity":"09a2a6fa-235b-405c-ba15-707ccf84a68f","added_by":"auto","created_at":"2023-07-11 14:20:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2702299,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3134479/v1/d5822b53-a1e7-4f19-b7fc-39139599c9c6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Conversion of waste animal bones to biofertilizer and adsorbent for wastewater treatment: An innovative approach to develop zero-waste technology","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn most parts of the world, people are meat lovers, so animals (bovine, caprine), chicken, and fish are used as a source of meat. Large amounts of animal waste are generated daily (Patel et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; C\u0026ocirc;rtes et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Biowaste from animals, poultry, and fish are considered municipal solid waste. The collection and disposal of these wastes has become an alarming problem for both developed and developing countries. In present decade, researchers have focused on converting solid waste into useful by-products such as biofertilizers and biochar, which can help to increase crop production and be used in water treatment (Abdel-Shafy et al. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e2018\u003c/span\u003e; Sharma et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ahmed et al. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e2021\u003c/span\u003e; Mozhiarasi and Natarajan \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Fertile soil is the key to sustainable and high-yield commercial agriculture. The essential ingredients of fertile soil are fertilizers, which ensure a high production rate on agricultural land (M\u0026auml;der et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Abbott and Murphy \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Cunfer and Krausmann \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Weigand et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In order to increase soil fertility, chemical fertilizers have been widely used in the last four decades, resulting in the loss of natural habitat and soil health, and causing many hazardous effects such as soil salinization, fertilizer pollution, and dangerous environmental impacts. This has also led to deterioration in food quality and an increase in the cost of cultivation. Due to these drawbacks, alternative farming techniques and strategies are becoming more popular in this decade. Due to their many advantages over chemical fertilizers, organic farming techniques and strategies are attractive to farmers worldwide (Dawson and Hilton \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kumar et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Al-Suhaibani et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Al-Suhaibani et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). According to the United States Department of Agriculture (USDA), organic farming promotes the cycle process of agricultural resources and maintains the biodiversity in ecosystem. It naturally increases soil fertility and maintains water quality by avoiding synthetic fertilizers, pesticides, growth regulators, feed additives, and genetic engineering. In organic farming, fertilizers should come from natural substances. These types of fertilizers are called biofertilizers (Reganold and Wachter \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Ahuja et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Nitrogen (N), phosphorus (P) and potassium (K) in the soil are the most important macronutrients, which are closely related to soil fertility and promote plant growth. A good organic fertilizer should be enriched with N, P and K (Schroder et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Gao et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Different types of biowastes contain these elements in larger amounts (Weigand et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Arvanitoyannis and Kassaveti \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Soetan et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Saeid et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Alotaibi et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Severin et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Izydorczyk et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Samoraj et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Bones are the only biowaste that contains the highest concentration of macronutrients (Ca, N, P, K, and Mg), and the use of bones as fertilizer is currently the only way to turn this environmentally harmful/polluting waste into a useful product (Schroder et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Su et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Mondini et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Padel et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Alves et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wongrueng et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBones form the main skeleton of the animal body and consist of 45% water, 30% protein, 15% bone salts and 10% lipids. The organic matrix is 30\u0026ndash;40%, while the inorganic matrix accounts for 60\u0026ndash;70% of the bone weight. In bone, calcium (55%) and phosphorus (42%) are present in the largest amount, while only 2% nitrogen is present (Saeid et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rauf \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ginigaddara \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Due to the availability of nitrogen and carbon in the bones, they can be used as fertilizer and increase soil fertility. Nitrogen and carbon lead to an increase in microbial biomass, and these microbes also control the decomposition process in the soil by providing more enzymes. Bones are the main source of organic phosphorus. Bones contain the phosphorus in the form of calcium phosphate. The same types of phosphates are also obtained from rocks and sediments, but bone phosphate is preferable. Because phosphates from rocks/sediments may contain cations, they have an affinity for absorbing cations/metals and may naturally contain high concentrations of metals and other contaminants. Therefore, these phosphates can have dangerous effects on the ecosystem. On the other hand, bone phosphate, has the lowest concentration of heavy metals. Therefore, more importance has been given to bone-derived fertilizers (T\u0026uuml;tken et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Enowashu et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Saeid et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe high concentration of various heavy metals in the aquatic ecosystems of Pakistan is hazardous. This is because these heavy metals enter the food chain from the aquatic ecosystem and severely affect human health (Perveen et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Aslam et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chan et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Chan et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e; Afzaal et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hayder et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). There is an urgent need to take measures to remove these toxic heavy metals from water to make this water safe for the public and agriculture. Various removal methods (e.g., ion exchange, precipitation, electrocoagulation, activated carbon adsorption, and fixed bed filtration) have been used to remove these toxic metals from water. However, most of these techniques are expensive, and there is a need to develop more cost-effective technologies using inexpensive adsorbents. The development of biochar technology offers a way to meet the need for low-cost adsorbents for aqueous heavy metals. In the last decade, biochar has received considerable attention in water treatment (Inyang et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Gwenzi et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; da Silva Veiga et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Castiglioni et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present study was designed to produce low-cost nano-biofertilizer and biochar as nan-adsorbent from the biowaste of animals. For this purpose, the waste products of different animals were used, such as bones of marine piscine (fish), galline (country and broiler chicken), and bones and horns of caprine (goat) and bovine (cows and buffaloes). Total carbon (TC) and total nitrogen (TN) of these wastes were determined at different temperatures to observe the loss of carbon and nitrogen. Other macronutrients (Ca, P, K, and Mg) required for plant growth were also analyzed in these bone/horn samples. The effectiveness of these macronutrients as biofertilizers was determined using a weekly-based plant growth experiment. In addition, this study determined the filtration capacity of different biochar samples to remove six heavy metals (As, Cd, Cr, Cu, Ni, and Pb) from the artificial wastewater samples. This comparative evaluation provides useful information on the adsorption capacity of the different biochar samples. This study is based on the hypothesis that the efficiency of biofertilizers and biochar produced from different animal waste products depends on the animal species and body parts. In the future, this study will provide helpful information for the production of effective biofertilizer and biochar from animal bones/horns.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eSample collection\u003c/h2\u003e\n \u003cp\u003eIn this study, the biowastes of different animals were used: marine piscine (fish), galline (chicken), caprine (goat) and bovine (buffalo and cow). Both bones and horns were used for buffalo, cow and goat, while bones were used for fish and chicken (both country and broiler). The piscine biowastes were collected from Karachi fish harbor, while bovine, caprine and galline biowastes were collected from different slaughterhouses and poultry markets in Karachi.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis and instrumentation\u003c/h2\u003e\n \u003cp\u003eTo conduct different experiments, we used different instrumental techniques including Atomic Absorption Spectrophotometry (AAS), Fourier Transform Infrared Spectroscopy (FTIR), Thin Layer Chromatography (TLC), furnace for calcination and microscope for microbial analysis. Atomic Absorption Spectrophotometry (AAS) PE-A Analyst 700 was used in order to find out the metal composition of animal bones. Fourier Transform Infrared Spectroscopy (FTIR) model IR Prestige-21, Shimadzu, Japan is used to detect the functional group region in calcinated animal bones. Muffle furnace SX-2-5-12 box type resistance furnace is used to calcinate the animal bones. Total carbon (TC) and nitrogen (TN) were measured using a CHN analyzer (Perkin Elmer, 2400 Series II). Phosphorus content was determined spectrophotometrically using a Marcel Media UV-VIS spectrophotometer.\u003c/p\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003ePretreatment and calcination of bones\u003c/h2\u003e\n \u003cp\u003eDifferent bones including fish bones (A), country hen bones (B), broiler hen bones (C), goat trotters (D), goat horns (E), cow bones (F) and buffalo horns (G) were collected from different meat shops of Karachi. The bones were washed with water and boiled in NaOH solution (10%) for three hours, then rinsed with water (approx. 1000 ml) for the removal of base and other impurities. The bones were dried at 100\u0026deg;C for 2 hours and then converted into the powdered form. After then, the bones powder was calcinated at 200\u0026deg;C, 400\u0026deg;C, 600\u0026deg;C, 800\u0026deg;C and 1000\u0026deg;C in a muffle furnace for 4 hours gradually (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eBasicity test\u003c/h2\u003e\n \u003cp\u003e1 ml of 20% w/v of bones and (0.5 ml; 1.5mg/ml) of phenolphthalein in toluene were taken in a conical flask and titrated it with standard 0.01 M solution of benzoic acid which was prepared in toluene. The basicity of the waste bones were measured by using the burette reading of consumed benzoic acid against samples solutions of bones. The basicity results were reported in mmoles per 100 g of bones.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis of elements\u003c/h2\u003e\n \u003cp\u003eThe saturated solutions of bones were prepared and few drops of ammonium hydroxide (NH\u003csub\u003e4\u003c/sub\u003eOH) and ammonium oxalate solution were added, and the test tube was shaken well that resulted in the appearance of white precipitates. Calcinated animal bones (0.2 g) which are the source of CaO were used for the analysis of calcium content. Distilled water (12.5 ml) and conc. HCl (4.0 ml) were added and placed the flask on the hotplate stirrer then the beaker was covered with watch glass. The solution was boiled till the maximum CO\u003csub\u003e2\u003c/sub\u003e was evolved. Now, distilled water (120.0 ml) was added to make up the solution up to 125.0 ml and 2 drops of methyl red was added then the solution was boiled and covered with the watch glass. The solution of ammonium oxalate (8%) was prepared and boiled then added in the sample solution. NH\u003csub\u003e4\u003c/sub\u003eOH (1:1) solution was added drop wise till orange precipitates were appeared. The solution was subjected to filtration and the residue was collected. The residue was charred in the muffle furnace to form CaO. For the detection of Mg, the saturated solutions of bones were prepared then ammonium hydroxide (NH\u003csub\u003e4\u003c/sub\u003eOH) and NaHPO\u003csub\u003e4\u003c/sub\u003e were added and then the test tube was shaken well that resulted in the appearance of gelatinous white precipitates.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis of bones by atomic absorption spectrophotometry\u003c/h2\u003e\n \u003cp\u003eTo find the heavy metals quantitatively in waste bones samples, we used atomic absorption spectrophotometer (AAS). For sample preparation 5.0 g of waste bone was digested in 10 ml of concentrated HNO\u003csub\u003e3\u003c/sub\u003e by using wet digestion method. Analysis of waste bones samples on AAS PE-A Analyst 700 were performed on Air-Acetylene flame with fuel flow rate of 10 L/min at a specific wavelength of metal to be analyzed.\u003c/p\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003eCarbon and nitrogen analysis\u003c/h2\u003e\n \u003cp\u003eThe bone samples were boiled in water for 1 hour to remove the residual meat, while the horn samples were washed with water to remove dust and debris. Now both samples were washed with distilled water before carbon and nitrogen analysis. The bones were dried in oven at 70\u0026deg;C for 72 h, crushed, and passed through a 2 mm sieve. For ash recovery, the bones and horns were placed in open crucibles to ensure the supply of oxygen during combustion. Bone ash and horn ash were produced at temperatures of 200\u0026deg;C, 400\u0026deg;C, 600\u0026deg;C, 800\u0026deg;C, and 1000\u0026deg;C with a residence time of 3 h. The products were stored at room temperature until the experiments. Total carbon (TC) and nitrogen (TN) were measured using a CHN analyzer (Perkin Elmer, 2400 Series II). Briefly, 2 mg of the oven-dried bone ash sample was sieved through 150 \u0026micro;m, placed in a tin capsule, and analysed (Patel et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ahmed et al. \u003cspan class=\"CitationRef\"\u003e2021b\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eDetermination of calcium, phosphorus, potassium and magnesium\u003c/h2\u003e\n \u003cp\u003ePrior to the determination of Ca, P, K, and Mg, the bone powder was gradually calcined at 1000\u0026deg;C in a muffle furnace for 4 h (Ahmed et al., \u003cspan class=\"CitationRef\"\u003e2021b\u003c/span\u003e; Sealy et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Phosphorus content was determined spectrophotometrically using a Marcel Media UV-VIS spectrophotometer after the sample was previously mineralized in a mixture of concentrated hydrochloric and nitric acids. This method consists of the formation of a yellow colored phosphorus-vanadium-molybdenum complex and photometric measurement of the absorbance at a wavelength of 430 nm (Sobczak et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). Ca, K, and Mg were determined by atomic absorption spectrophotometry. For this purpose, the bone and horn samples were digested according to USEPA standard method #3051. Samples were digested in a microwave oven, diluted with the appropriate amount of deionized water, and filtered through a 42 \u0026micro;m Whatman filter paper (Chan et al., \u003cspan class=\"CitationRef\"\u003e2021b\u003c/span\u003e). All samples were analyzed for calcium, potassium, and magnesium using an atomic absorption spectrometer (Perkin Elmer (USA), Model AAnalyst 700).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eEfficacy of biofertilizers\u003c/h2\u003e\n \u003cp\u003eTo determine the effectiveness of the biofertilizer, eight pots were placed and filled with 1 kg of sand. Each pot was inoculated with powder from calcined animal bones/horns. Two seeds of kidney beans were sown in each pot and the pots were watered regularly for 5 weeks. Plant growth was measured weekly by measuring the size of the stem and the leaves (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eAntimicrobial potential of calcinated bones\u003c/h2\u003e\n \u003cp\u003eAnimal bones (0.1 g) including fish bones (A), country hen bones (B), broiler hen bones (C), goat trotters (D), goat horns (E), cow bones (F) and buffalo horns (G) were separately subjected for the determination of their antimicrobial potential against different bacterial and fungal pathogens. The saturated solutions of bones were prepared in water (5 ml) and the test was performed by agar well diffusion method using 100 \u0026micro;l (0.1 M) of test solution in each well made in Nutrient agar plate for bacteria and Sabouraud`s Dextrose agar for fungal strains. The zone of inhibition was measured in millimetre (Buksh et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eDetermination of heavy metals removal efficiency of biochar\u003c/h2\u003e\n \u003cp\u003eThe dried bone/horn samples were calcined at 500\u0026deg;C to 900\u0026deg;C with different durations (1, 2, and 3 h) in a muffle furnace with limited oxygen supply. The resulting biochar adsorbents were ground, sieved to particle size (\u0026lt;\u0026thinsp;63 \u0026micro;m), and stabilized for further experiments. Synthetic solutions of metals (arsenic, cadmium, chromium, copper, nickel, and lead) were prepared by their salts in deionized water at various concentrations (100\u0026ndash;500 ppm). Experiments on the removal of heavy metals were carried out in a laboratory incubator shaker under different conditions. The effects of time (in hours) for the removal of heavy metals from solutions by biochar samples were studied at 25\u0026deg;C. The effects of heavy metal concentrations in solution and the effects of biochar concentrations were also studied. Optimization of time to determine effective removal of heavy metals was evaluated from 1 to 7 h, while heavy metal concentrations were maintained at 100\u0026ndash;500 ppm and biochar concentrations at 1 to 4 mg/mL. The experiment was performed batchwise and the flasks were shaken at 110 rpm using an orbital shaker and the observations were recorded. 1 mL of the solution was removed and the biochar was immediately separated from the solution by centrifugation at 10000 rpm for 10 minutes. Each sample was repeated six times, and controls without the biosorbent material were used to distinguish between possible metal precipitation and actual metal adsorption. Samples were filtered through a #42 \u0026micro;m Whatman filter paper, and metal concentration was determined by atomic absorption spectrophotometry (AAS). Arsenic (As) was determined using the cold vapor technique, and Cd, Cr, Cu, Ni, and Pb were determined using the FAAS technique. The MHS-15 chemical vapor generation system (Perkin-Elmer) was coupled to the AA spectrometer for the determination of As. The instrument was calibrated before performing the experiment to ensure the accuracy of the results with an RSD of less than 5% (Chan et al. \u003cspan class=\"CitationRef\"\u003e2021b\u003c/span\u003e; Roy and Bharadvaja \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xing et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe removal efficiency (E) of heavy metals was calculated as follows:\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\text{%} \\text{R}\\text{e}\\text{m}\\text{o}\\text{v}\\text{a}\\text{l}=\\frac{\\text{C}\\text{i}-\\text{C}\\text{f}}{\\text{C}\\text{i}} \\times 100$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003eWhere Ci is the initial concentration of metal of metal and Cf is the final concentration of metal in ppm.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDifferent types of animal bones including fish bones (A), country hen bones (B), broiler hen bones (C), goat trotters (D), goat horns (E), cow bones (F) and buffalo horns (G) were subjected for the chemical tests and instrumental techniques such as basicity test, qualitative analysis of element and quantitative analysis of Ca\u003csup\u003e+\u0026thinsp;2\u003c/sup\u003e. The instrumental techniques which are used are furnace for calcination, atomic absorption spectrophotometry (AAS) and Fourier transform infrared spectroscopy (FTIR). All the samples were also analyzed for microbial activities. In addition, the samples were also tested as nano-biofertilizers. All bones were calcinated at 1000\u0026deg;C. By calcination all bones were converted into the oxide particularly CaO and other oxides. After calcination, the animal bones surface was very smooth, and they contained tiny pore size (nanosized) particles.\u003c/p\u003e\n\u003cp\u003eAt low temperature like 600 \u003csup\u003eo\u003c/sup\u003eC only organic components are removed and carbonates are not converted into CaO. At high temperatures like 1000 \u003csup\u003eo\u003c/sup\u003eC or 1200 \u003csup\u003eo\u003c/sup\u003eC, carbonates are converted into CaO. FTIR spectra of all samples were determined by Fourier transform infrared spectroscopy. Their FTIR spectra showed only one peak at 1050 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e which is the characteristic peak for CaO (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). It was further supported by the reported literature (Engin et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Figueiredo et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eBuffalo horns showed the highest basicity among the above mentioned bones which means it contains high percentages of Ca, P and N. Goat trotters and goat horns also showed the high basicity but lower than buffalo horns (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Cow bones and chicken bones (country) showed the lowest basicity while fish bones and chicken bone (broiler) showed the moderate basicity (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). White precipitates were appeared as a result of calcium test which confirmed the presence of calcium in bones and gelatin like white precipitates were appeared as a result of magnesium test which confirmed the presence of magnesium in bones. Buffalo horns showed the highest percentage of Ca\u003csup\u003e+\u0026thinsp;2\u003c/sup\u003e than all the other bones (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Cow bones also showed the high percentage of Ca\u003csup\u003e+\u0026thinsp;2\u003c/sup\u003e but buffalo bones dominated all bones. Similarly, fish bones and chicken bones (country) showed the moderate percentages while chicken bones (broiler), goat trotters and goat horns showed the lowest percentages of calcium. Chicken bones (broiler) contained the lowest percentage of calcium (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The animal bones were analyzed by flame atomic absorption spectrophotometry which showed the presence of different metals like Ca, Cd, Cu, Fe, K, Mg, Ni, As, Pb etc. The highest percentage of Ca (106.80 mg/l), Mg (2.038 mg/l) and As (9,690 mg/l) were observed in chicken bones (broiler) and the lowest percentage of Ca (89.44 mg/l), Mg (1.656 mg/l) and As (10.30 mg/l) were observed in buffalo horns (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetermination of basicity of different calcinated bones by chemical method\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eName of bones\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBasicity (m. moles of benzoic acid/g of bones)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bones (A)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (country) (B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (broiler) (C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat trotters (D)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns (E)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bones (F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffalo horns (G)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn the present study, fish bones, chicken bones (both country and broiler), and bones and horns of goats, cows, and buffaloes were collected from fish harbor, poultry markets, and slaughterhouses at different locations in Karachi. To determine their importance as biofertilizers, their macronutrients (C, N, Ca, P, K, and Mg) were evaluated and fertility was assessed by growing kidney bean plants. Plant growth with each fertilizer was checked after 1\u0026ndash;5 weeks. Biochar was prepared from different bones/horns, and the filtration capacity of each type of biochar was tested with different heavy metal solutions at different concentrations.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetermination of percentage of calcium in different calcinated bones by chemical method\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eName of bones and code\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCa\u003csup\u003e+\u0026thinsp;2\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bones (A)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (country) (B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (broiler) (C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat trotters (D)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns (E)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bones (F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffalo horns (G)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetermination of metals content (ppm) in samples by flame Atomic Absorption Spectrophotometer (FAAS).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSample ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCa\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFe\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.012\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.406\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.636\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.668\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.323\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.786\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.804\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.78\u0026thinsp;\u0026plusmn;\u0026thinsp;6.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.013\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.159\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.464\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.544\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.301\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.775\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.776\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e106.80\u0026thinsp;\u0026plusmn;\u0026thinsp;8.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.013\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.137\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.396\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.038\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.287\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.690\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.724\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.012\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.159\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.089\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.936\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.328\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.861\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.012\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.172\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.682\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.960\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.286\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.836\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0313\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.012\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.120\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.843\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.950\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.305\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.930\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.924\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.185\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.816\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.656\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.116\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.422\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTotal carbon (TC) and total nitrogen (TN) were determined at different temperatures (200\u0026deg;C, 400\u0026deg;C, 600\u0026deg;C, 800\u0026deg;C, and 1000\u0026deg;C) from different samples; fish bones, chicken bones (both country and broiler), goat bones, goat horns, cow bones, cow horns, buffalo bones, and buffalo horns (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). TC and TN tended to decrease with increasing temperature. At a given temperature (200\u0026ndash;1000\u0026deg;C), among the different bones and horns samples, broiler chicken bones generally had the lowest TC and TN values (TC\u0026thinsp;=\u0026thinsp;33\u0026thinsp;\u0026minus;\u0026thinsp;1.1 g/Kg; TN\u0026thinsp;=\u0026thinsp;5.5\u0026thinsp;\u0026minus;\u0026thinsp;0.24 g/Kg), while the highest TC and TN values were found in buffalo bone samples (TC\u0026thinsp;=\u0026thinsp;329\u0026thinsp;\u0026minus;\u0026thinsp;14.3 g/Kg; TN\u0026thinsp;=\u0026thinsp;44-1.21 g/Kg). When comparing bones and horns, higher TC and TN values were found in the bone samples than in the horn samples. During combustion, the concentration of TC and TN was highest at 200\u0026deg;C, while the lowest concentration was measured at 1000\u0026deg;C. At 1000\u0026deg;C, the maximum loss of TC and TN was found to be between 95.5 and 97.5%.\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eDetermination of carbon and nitrogen by CHN analyzer\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTotal Carbon (g/Kg) at different temp.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eTotal Nitrogen (g/Kg) at different temp.\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSamples\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e200\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e400\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e600\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e800\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1000\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e200\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e400\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e600\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e800\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1000\u0026deg;C\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;5.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bone (country)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112\u0026thinsp;\u0026plusmn;\u0026thinsp;5.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bone (broiler)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e317\u0026thinsp;\u0026plusmn;\u0026thinsp;10.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e288\u0026thinsp;\u0026plusmn;\u0026thinsp;8.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e155\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffalo bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e329\u0026thinsp;\u0026plusmn;\u0026thinsp;4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffalo horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e299\u0026thinsp;\u0026plusmn;\u0026thinsp;5.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe total content of calcium (Ca), phosphorus (P), potassium (K) and magnesium (Mg) in the calcified bone samples was determined. Overall, among the different samples, the lowest concentration of these four elements was recorded in the bones of broiler chickens (Ca; 55 g/Kg, P; 26 g/Kg, K; 2.5 g/Kg and Mg; 0.83 g/Kg), while the highest concentrations were recorded in the bones of buffaloes (Ca; 112 g/Kg, P; 54 g/Kg, K; 5.5 g/Kg and Mg; 1.9 g/Kg). When comparing bone and horn samples, the concentration of these elements was higher in the bones than in the horn samples from the same animal. The concentration in the bone country chickens was higher than in those of broiler chickens (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetermination of Ca, K and Mg by atomic absorption spectroscopy and P by UV-VIS spectroscopy\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSamples\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCa\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bone (country)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bone (broiler)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e107\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99\u0026thinsp;\u0026plusmn;\u0026thinsp;2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e101\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffalo bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e112\u0026thinsp;\u0026plusmn;\u0026thinsp;3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffalo horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105\u0026thinsp;\u0026plusmn;\u0026thinsp;3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTo determine the fertility effect of the biofertilizers prepared from the bone/horn samples, kidney bean plants were grown in pots containing the biofertilizers prepared from the bone samples. Seeds were sown in each pot and their growth was observed for up to 5 weeks. Each week, the size of the stems and leaves of each plant was determined (cm). The plant grown in buffalo bone biofertilizer showed maximum growth after 5 weeks (leaves 7.5 cm and stems 27.2 cm), while the plant grown in the broiler chicken bone biofertilizer showed minimum growth (stems 15.2 cm, leaves 4 cm). In comparison, the plants fertilized with the horns grew less than the plants fertilized with the bones of the same animal (Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6: \u0026nbsp;Determination of biofertilizer efficacy of different samples\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.208333333333333%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eS. No.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eName of Samples\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter 1\u003csup\u003est\u003c/sup\u003e week\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter 2\u003csup\u003end\u003c/sup\u003e week\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.708333333333332%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter 3\u003csup\u003erd\u003c/sup\u003e week\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter 4th week\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter 5\u003csup\u003eth\u003c/sup\u003e week\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage Size (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStem\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeaves\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStem\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeaves\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStem\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeaves\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStem\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeaves\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStem\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.722222222222221%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeaves\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eFish bones\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eChicken bones (country)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eChicken bones (broiler)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eGoat bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eCow bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eCow horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eBuffalo bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e27.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eBuffalo horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e22.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.4945054945054945%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89010989010989%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eIn Tables \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e16\u003c/span\u003e, the heavy metals adsorption capability of biochar from each sample (bones/horns) was determined. This adsorption capability was checked by the effect of time and concentration on removal of six heavy metals; arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni) and lead (Pb). Comparison of the adsorption capability of the biochar made by the different animals, the comparison of bones biochar and horns biochar was done by comparing their adsorption ability by filtration of water solutions containing different heavy metals.\u003c/p\u003e\n\u003cp\u003eIn this study concentration of biochar (made from fish and chicken bones and bones and horns of goat, cow and buffalo) was 1 mg/mL and heavy metal concentration of 100 ppm was used. As time of adsorption was changed from 1 to 6 h, efficiency increases and after 6 h, the efficiency began to decrease. The lowest concentration of heavy metals removal (at 6 h) was recorded by broiler chicken bone biochar while the highest concentration was recorded from the biochar of buffalo bone. In the comparison of biochar made by bones and horns, it was observed that the biochar made by the bones have higher ability of removal of heavy metals than those of horns of same animal. Overall, at 6 h, the lowest removal efficiency of broiler chicken bone biochar was recorded for arsenic (36%) while highest removal efficiency was recorded by the biochar of buffalo bone (75%). Among the metals, the lowest filtration was observed for the arsenic while highest filtration was recorded for lead (for each biochar sample).\u003c/p\u003e\n\u003cp\u003eEfficiency of biochar was studied at different concentration of six heavy metals (As, Cd, Cr, Cu, Ni and Pb) removed from the artificial wastewater (100 to 500 mg/Kg). All the biochar samples showed highest ability of heavy metals removal at the concentration of 100 mg/Kg while the lowest capability at 500 mg/Kg of artificial wastewater. Among the comparison of all the biochar samples, biochar made from buffalo bone showed the highest filtration for all of the heavy metals from wastewater at 100 mg/Kg (As =\u0026thinsp;61%, Cd\u0026thinsp;=\u0026thinsp;71%, Cr\u0026thinsp;=\u0026thinsp;68%, Cu\u0026thinsp;=\u0026thinsp;66%, Ni\u0026thinsp;=\u0026thinsp;63%, Pb\u0026thinsp;=\u0026thinsp;76%). While the lowest percentage of filtration was recorded by the broiler chicken bone biochar sample (As =\u0026thinsp;38%, Cd\u0026thinsp;=\u0026thinsp;46%, Cr\u0026thinsp;=\u0026thinsp;43%, Cu\u0026thinsp;=\u0026thinsp;42%, Ni\u0026thinsp;=\u0026thinsp;39%, Pb\u0026thinsp;=\u0026thinsp;50%). The removal order of all heavy metals during both time and concentration was same i.e. Pb\u0026thinsp;\u0026gt;\u0026thinsp;Cd\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;As. While the efficiency order of biochar samples was; buffalo bone biochar\u0026thinsp;\u0026gt;\u0026thinsp;buffalo horn biochar\u0026thinsp;\u0026gt;\u0026thinsp;goat bone biochar\u0026thinsp;\u0026gt;\u0026thinsp;goat horn biochar\u0026thinsp;\u0026gt;\u0026thinsp;cow bone biochar\u0026thinsp;\u0026gt;\u0026thinsp;fish bone biochar\u0026thinsp;\u0026gt;\u0026thinsp;cow horn biochar\u0026thinsp;\u0026gt;\u0026thinsp;country chicken biochar\u0026thinsp;\u0026gt;\u0026thinsp;broiler chicken bone biochar.\u003c/p\u003e\n\u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater at different time (hour) in fish bone\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (h)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 \u0026plusmn; 1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater by biochar\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConc. mg/Kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater by the biochar of chicken bones at different time (hour)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eChicken bone (country)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eChicken bone (broiler)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (h)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab10\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater by the biochar of chicken bones\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eChicken bone (country)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eChicken bone (broiler)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConc. mg/Kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab11\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater by the biochar of goat bones and horns at different time (hour)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eGoat bone\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (h)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u0026thinsp;\u0026plusmn;\u0026thinsp;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab12\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater by biochar of goat bones and horns at concentration of heavy metals\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eGoat bone\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConc. mg/Kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab13\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater by the biochar of cow bones and horns at different time (hour)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eCow bones\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eCow horns\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (h)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab14\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 14\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewater by biochar of cow bones and horns at concentration of heavy metals\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eCow bones\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eCow horns\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConc. mg/Kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab15\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 15\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals from wastewaterby biochar of buffalo bones and horns at different time (hour)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eBuffalo bones\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eBuffalo horns\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (h)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab16\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 16\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRemoval of heavy metals by biochar of buffalo bones and horns at concentration of HM\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eBuffalo bones\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eBuffalo horns\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConc. mg/Kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u0026thinsp;\u0026plusmn;\u0026thinsp;3.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u0026thinsp;\u0026plusmn;\u0026thinsp;3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;3.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAccording to results, fish bones, chicken bones (country), chicken bones (broiler) and goat trotters showed antibacterial activities against \u003cem\u003eEnterococcus faecalis\u003c/em\u003e while fish bones were found to be active against \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and \u003cem\u003eBacillus subtilis\u003c/em\u003e. Chicken bones (country) and goat trotters showed antibacterial activities against \u003cem\u003eSalmonella typhi\u003c/em\u003e while goat trotters were found to be active against \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e. However, none of the bones had any bioactivity against \u003cem\u003eE. coli\u003c/em\u003e. Fish bones showed antifungal activities against \u003cem\u003eCandida albicans\u003c/em\u003e while none of the bones were found to be active against plant pathogenic fungi (Table \u003cspan class=\"InternalRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e20\u003c/span\u003e; Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab17\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 17\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAntibacterial activity of different calcinated bones against Gram positive bacteria.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSample names\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eZone of inhibition (mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBacillus subtilis\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEnterococcus faecalis\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (country)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (broiler)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat trotters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffaloes horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e-ve\u0026thinsp;=\u0026thinsp;no zone of growth inhibition.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab18\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 18\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAntibacterial activity of different calcinated bones against Gram negative bacteria\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSample names\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eZone of inhibition (mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSalmonella typhi\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (country)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (broiler)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat trotters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffaloes horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e-ve\u0026thinsp;=\u0026thinsp;no zone of growth inhibition.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab19\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 19\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAntifungal activity of different calcinated bones against fungi\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eName of samples\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eZone of inhibition (mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCandida glabrata\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMucor sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAspergillus niger\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAspergillus flavus\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (country)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChicken bones (broiler)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat trotters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffaloes horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab20\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 20\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAntifungal activity of different calcinated bones against plant pathogenic fungi\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSample names\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eZone of inhibition (mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAlternaria sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDrechslera sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHumicola sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFish bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHen bones (country)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHen bones (broiler)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat trotters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGoat horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCow bones\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuffaloes horns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-ve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe rapid increase in the population causes the decline in food and pure water resources as a result; the use of inorganic fertilizers and use of different technologies for the treatment of polluted water are being increased in present decade. While there is another big alarming problem caused by burgeoning population. It is the consumption of meat, which has also been increased in large scale, as a result the biowastes of fish, poultry and animals indirectly posing challenge to the final disposal. The use of inorganic/chemical fertilizers is not only cost intensive but also creates the problem of environmental pollution. Chemical fertilizers cause water pollution by eutrophication of water bodies. It has been recorded that in majority of the cases, the efficiency of the inorganic fertilizers is lower. Almost, half of the inorganic fertilizer in most cases and more often almost 80\u0026ndash;90%, of these fertilizers remain unutilized by the plants, so the excessive amount has been flown from agricultural land to the water bodies, and become a source of contamination. This become the cause of decrease in crops production and also increase the aquatic pollution (Arao et al. \u003cu\u003e2010\u003c/u\u003e; Qiutong and Mingkui \u003cu\u003e2017\u003c/u\u003e; Rashmi et al. \u003cu\u003e2020\u003c/u\u003e). \u0026nbsp;The inorganic fertilizers often contain heavy metals, while the fertilizer industry is also considered to be source of natural radionuclides and heavy metals as a potential source, these heavy metals once entered into the aquatic ecosystem, they become the part of food chain and, thus, can affect animal and human health (Rashmi et al. \u003cu\u003e2020\u003c/u\u003e; Savci \u003cu\u003e2012\u003c/u\u003e). In Pakistan, due to excessive use of inorganic fertilizers, the cost of crops production and water contamination issues have been increased. So there is need of introduction of new low cost and ecofriendly method in agriculture in Pakistan.\u003c/p\u003e\n\u003cp\u003eMoreover, in Pakistan, the animal waste has been a common problem like other countries of the world. Waste from the meat industry is hazardous and causing pollution in the environment. The wastes can become valuable biofertilizer because the animal wastes are the reservoirs of organic matter (50-80%), containing the macronutrients e.g. total carbon, total nitrogen, phosphorus, calcium, potassium and magnesium all of which are important components to increase the fertility of soil and used to increase the crops/plants production. Therefore, in present decade the animal waste is being used for the manufacturing of biofertilizers (Staroń et al. \u003cu\u003e2017\u003c/u\u003e; Chojnacka et al. \u003cu\u003e2019\u003c/u\u003e; Stępień et al. \u003cu\u003e2021\u003c/u\u003e). Researchers also use nitrogen-rich waste as carbon and nitrogen source to produce biochar. The animal waste e.g. bones and horns are rich source of nitrogen and carbon so can be used to produce biochar. Porous carbon material refers to an excellent adsorbent, including biochar contains, activated carbon, and have excellent adsorbent capacity for environmental pollutants especially heavy metals (Smith \u003cu\u003e2019\u003c/u\u003e; Jin et al. \u003cu\u003e2022\u003c/u\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the present study, the fish, poultry and animal wastes have been used to make two valuable products i.e. biofertilizer and biochar which were further applied to increase the soil fertility (through biofertilizer) and purifying the water from heavy metals. The biofertilizers were made from the waste bones of fish and poultry and also from the bones and horns of different animals (goat, cow and buffalo). In order to observe the loss of total carbon and nitrogen, during pyrolysis process, different temperatures were applied (200 \u0026deg;C, 400 \u0026deg;C, 600 \u0026deg;C, 800 \u0026deg;C and 1000 \u0026deg;C), and it was recorded that total carbon and nitrogen productivity were decreased with increasing the temperature, both were maximum at minimum temperature (200\u0026deg;C) while became minimized at maximum temperature (1000 \u0026deg;C). It means, total carbon and nitrogen productivity rate in the biofertilizer during pyrolysis, is temperature dependent (Sharma et al. \u003cu\u003e2020\u003c/u\u003e; Ahmed et al. \u003cu\u003e2021a\u003c/u\u003e; Ahmed et al. \u003cu\u003e2021b\u003c/u\u003e; Khoshnevisan et al. \u003cu\u003e2021\u003c/u\u003e). The decrease of TC and TN content of samples, with increasing pyrolysis temperature is attributed to the decomposition of the oxygenated bonds and release of low molecular weight byproducts at high pyrolysis temperature (Suliman et al. \u003cu\u003e2016\u003c/u\u003e; Zhang et al. \u003cu\u003e2017\u003c/u\u003e; Shafiq and Capareda \u003cu\u003e2021\u003c/u\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBecause at the lowest temperature (200 \u0026deg;C), the highest productivity (g/Kg) of total carbon (TC) and total nitrogen (TN) was obtained so concentration (g/Kg) of calcium, phosphorus, potassium and magnesium was also determined at the same temperature. During this study, the productivity (g/Kg) of TC, TN, Ca, P, K and Mg was higher in the bone as compared to horn samples of the same animal. The higher productivity of above elements in bone than those of horn samples is probably relates to the differential metabolic processes (found in bones) that occur during different tissue formation, as well as to physiological and dietary parameters. As the horns are derived from bones so higher amount of TC, TN, Ca, P, K and Mg was found in bones as compared to horns (Landete-Castillejos et al. \u003cu\u003e2007\u003c/u\u003e; Landete-Castillejos et al. \u003cu\u003e2012\u003c/u\u003e; Stevens and O\u0026apos;Connell \u003cu\u003e2016\u003c/u\u003e).\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe usability of animal bone/horns (use in this study) as nano-biofertilizers depends on their composition and a concentration of valuable elements (macronutrients). These macronutrients, found in the byproducts of various animals, affect the plants growth (Samoraj et al. \u003cu\u003e2022\u003c/u\u003e) so the present study was designed to focus to observe the effect of nano-biofertilizers on the growth of the plants. The nano-biofertilizers made from the byproducts (bones/horns) of different animals i.e. bones waste of fish and chickens and bones and horns of goat, cow and buffalo. In order to observe the effect of different nano-biofertilizers on the plant growth, the kidney plants were selected. The growth rate was observed in the 5 weeks. The highest growth rate was recorded from the nano-biofertilizers made by the bones of buffalo. It is due to highest concentration of TC and TN and other macroelements e.g. Ca, P, K and Mg. This could be correlated with the nature of the bone, as compared to other bovines, the buffalo growth pattern is slow but it stores more mineral and nutrients in its bones (Spanghero et al. \u003cu\u003e2004\u003c/u\u003e).\u003csup\u003e\u0026nbsp;\u003c/sup\u003e Plants growing under the influence of nano-biofertilizers made by goat and cow bones, showed difference in their growth pattern. Plants growth by the nano-biofertilizers prepared from the bone of goat, showed higher growth pattern as compared to those which grew in the pot containing cow bone biofertilizer. From the previous literature, it was shown that as compared to cow bone, higher concentration of TC, TN and other macro/micronutrients were recorded in the goat bone (Samoraj et al. \u003cu\u003e2022\u003c/u\u003e; Ahmed et al. \u003cu\u003e2021b\u003c/u\u003e; Ramesh et al. \u003cu\u003e2018\u003c/u\u003e). It was also found that higher quantity of gelatin could be recorded in the bones of goat (Matulessy et al. \u003cu\u003e2021\u003c/u\u003e). Therefore in the present study, the biofertilizer made from goat bone showed more plant growth as compared to that of biofertilizer made from cow. The efficiency of nano-biofertilizer of fish is associated with the high protein and lipid contents found in the fish waste/bone (Maktoof et al., 2020). Therefore, the fish biofertilizer showed more growth in the kidney plant as compared to the biofertilizer made from chicken bones. The biofertilizer produced from the broiler chicken bone showed lowest growth pattern in the kidney bean plant as compared to all of the biofertilizers used in this study. The comparison of biofertilizer of broiler chicken bone with that of the country chicken bone showed that more growth was recorded by the biofertilizer of country chicken bone. Due to unhealthy breeding conditions, many broiler chickens develop weak bone structures and a high risk for avian diseases due to inbreeding, as a result the broiler chickens have less amount of TC, TN, Ca, P, K, Mg and other elements as compared to the country chicken bones. These elements are enriched in bones of country chicken because of their slow growth rate, enables the bones stronger by the enrichment of TC, TN, Ca, P, K, Mg and other elements (Jeon et al. \u003cu\u003e2010\u003c/u\u003e; Sokołowicz et al. \u003cu\u003e2016\u003c/u\u003e; Ullengala et al. \u003cu\u003e2020\u003c/u\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, the artificial wastewater was made by adding different concentration of heavy metals (100 to 500 ppm), the absorption of metals was higher in case of biochar derived from bone samples as compared to biochar derived from horn samples. As compared to horn, the bone has more porosity, so the bone is an excellent adsorbent for heavy metals and dyes, the animal bone char has porous structure, due to porosity, it has been traditionally used as adsorbent for the removal of toxic heavy elements from wastewater (McKittrick et al. \u003cu\u003e2010\u003c/u\u003e; Park et al. \u003cu\u003e2015\u003c/u\u003e; Park et al. \u003cu\u003e2016\u003c/u\u003e; Azeem et al. \u003cu\u003e2022\u003c/u\u003e). As compared to chicken-based biochar, the fish-based biochar were more effective to remove the heavy metals. The collagen-rich biomasses are the excellent precursors for the production of biochar. It was recorded from the previous literature that as compared to chicken, the marine fish is best source of collagen; about 30% of fish wastes (especially bone) are very rich in collagen. The formation of biochar from fish bone could be a promising means to gain value-added product, and to lower environmental pollution (Jeong et al. \u003cu\u003e2013\u003c/u\u003e; Niu et al. \u003cu\u003e2019\u003c/u\u003e; Zhang et al. \u003cu\u003e2021\u003c/u\u003e). The biochar made by the country chicken bones showed more efficiency than that of broiler chicken based biochar. This efficiency can be measured by bone structure and the amount of collagen in both types of the chicken. It was recorded that the country chicken bones are more stronger with more minerals (e.g. Ca, P, K, Mg etc.) than those of broiler chicken bones. Moreover, the bones of country chicken contain more collagen than those of broiler chicken (Cchicken et al. \u003cu\u003e2016\u003c/u\u003e; Mabelebele et al. \u003cu\u003e2017\u003c/u\u003e; Buss et al. \u003cu\u003e2022\u003c/u\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBuffalo bone based biochar showed the highest heavy metals removal efficiency. This efficiency is based on the mineral contents (Ca, P, K etc.), which are higher in the bones of buffalo than those of other animals bones, used in this study. The highest minerals are related to the higher growth recorded in the buffalo skeleton. The efficiency may also be increased due to highest TC and TN in the bone which is directly linked with the collagen which is found in the higher amount in the buffalo bones (Mitchell et al. \u003cu\u003e2005\u003c/u\u003e; Vidu et al. \u003cu\u003e2013\u003c/u\u003e; Samatra et al. \u003cu\u003e2020\u003c/u\u003e). The heavy metals adsorption capacity of goat bone biochar was higher than that of cow bone biochar. This efficiency may be related with gelatin and minerals which are higher in goat as compared to cow. The TC, TN, Ca, P, K, Mg etc increase the efficiency of biochar in removal of heavy metals (Wang et al. \u003cu\u003e2019\u003c/u\u003e; Ambaye et al. \u003cu\u003e2021\u003c/u\u003e; Piash et al. \u003cu\u003e2021\u003c/u\u003e; Wang et al. \u003cu\u003e2021\u003c/u\u003e).\u003c/p\u003e\n\u003cp\u003eIn present study, the removal of heavy metals was maximum at 100 ppm and percentage of removal capacity decreased by increasing the concentration. The adsorption capacity of biochar is highest at low concentration of heavy metals in the solution (Roy and Bharadvaja \u003cu\u003e2021\u003c/u\u003e; Ambaye et al. \u003cu\u003e2021\u003c/u\u003e; Qiu et al. \u003cu\u003e2021\u003c/u\u003e).\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAll the biochar samples, removed the heavy metals from the artificial wastewater samples, with the following order; Pb \u0026gt; Cd \u0026gt; Cr \u0026gt; Cu \u0026gt; Ni \u0026gt; As. High adsorption capacities of Pb by biochars involves multiple mechanisms, including ion exchange, complexation with oxygen-containing functional groups, precipitation with inorganic components and interactions with \u0026pi; electrons (C=C) (Cao et al. \u003cu\u003e2009\u003c/u\u003e; Inyang et al. \u003cu\u003e2012\u003c/u\u003e; Lu et al. \u003cu\u003e2012\u003c/u\u003e; Han et al. \u003cu\u003e2017\u003c/u\u003e). Cd is the second metal, which was removed by biochar samples, with higher concentration after Pb because Pb is often accompanied by Cd from a range of anthropogenic sources such as batteries, mining and smelting operations (Han et al. \u003cu\u003e2017\u003c/u\u003e; He et al. \u003cu\u003e2013\u003c/u\u003e; Li et al. \u003cu\u003e2014\u003c/u\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study suggests that the animal bones (waste product) might be used to produce the commercial fertilizers in terms of crop-enhancing efficiency. These waste bones can also be used to produce biochar which can be used as an effective, low-cost and environmentally friendly nano-adsorbent for the removal of heavy metals from the household, agricultural and industrial wastewaters. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePakistan has low resources while its population is increasing rapidly. To meet the demand of rapid growing population, the food and water resources are declining to be lowest level. While the pollution from the animal waste materials is big issue especially in the urban areas. After observing these two burning issues (food water/shortage and animal waste) of the present decade, this study was designed. In the present study, two valuable products are produced from the animal waste products: 1) biofertilizer formulations, which can be used to enhance the efficiency of crops production. By applying these nano-biofertilizers to the commercial scale, the inexpensive green revolution can be obtained in the society, which can fulfil the food to the hunger population. 2) biochar formation; It is recorded from the present study that the biochar prepared from the animals waste could be effective and easy formulated nano-bioadsorbent which is low cost and efficacious resource which can be used for abstraction of heavy metals from aqueous solution. Thus, this adsorbent can be best utilized for adsorption of heavy metals for wastewater treatment.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eA. M. Khan: Principal investigator for this research article. He designed main concept and theme of this article. M. A. Usmani: Performed experimental work and written the research article. K. Yasmeen: Performed Atomic Absorption Spectroscopy (AAS) technique for determination of heavy metals. M. N. Ahmed: Improved the drafting of manuscript with valuable suggestions. M. Obaid: Performed FTIR Spectroscopy. \u0026nbsp;S. A. Naz: Conducted the microbial examination of the samples. S. Pervaiz: Conducted the literature regarding this article. M. W. H. Chan: Performed the analytical data. A. Khan: Conducted statistical evaluation of the data. S. Aslam: Water treatment of the samples.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors are greatly thankful to those researchers whose articles have been used as a reference to support this article.\u003c/p\u003e\n\u003cp\u003eConflicts of interest\u003c/p\u003e\n\u003cp\u003eThe Authors declare that there is no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eAbbott LK, Murphy DV (2007) What is soil biological fertility?. 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Biomass Bioenerg 105: 136\u0026ndash;146. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biombioe.2017.06.024\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3134479/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3134479/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePresently a number of chemical fertilizers are being used which are not only expensive but are also environment threatening. There is a need to replace these fertilizers by biofertilizers. Adsorbent were prepared from waste bones for the waste water treatment. \u0026nbsp;Various bone samples were collected and calcinated to produce biofertilizer and adsorbent. Total carbon (TC) and total nitrogen (TN) were analyzed. The broiler chicken bone-based biofertilizer has the lowest amount of TC and TN (TC = 33 and TN = 5.5 g/Kg) and also the lowest macro-elements; Ca = 55, P = 26, K = 2.5, and Mg = 0.83 g/Kg. All samples were used for the growth of kidney bean plant. After 5 weeks, the highest growth was observed for buffalo bone-based fertilizer and the lowest for broiler bone-based fertilizer. In the present study, the calcinated bones material was also used as nano-adsorbent for the removal of heavy metals from the artificial wastewater. All nano-adsorbent samples showed maximum efficiency at 100 ppm, while maximum removal was at 6 h. The highest removal efficiency was obtained for buffalo bone-based nano-adsorbent (As = 60% and Pb = 75%), and the lowest removal efficiency was obtained for broiler bone-based nano-adsorbent (As = 36% and Pb = 47%). The calcinated animal bones were analyzed using Flame Atomic Absorption Spectrophotometry (FAAS), Fourier Transform Infrared Spectroscopy (FTIR), chemical tests and antimicrobial susceptibility test (AST). This research can play an important role for the promotion of agricultural crops and for wastewater treatment using nano-technology.\u003c/p\u003e","manuscriptTitle":"Conversion of waste animal bones to biofertilizer and adsorbent for wastewater treatment: An innovative approach to develop zero-waste technology","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-11 14:12:46","doi":"10.21203/rs.3.rs-3134479/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"287c64a5-b2b8-4405-993f-5df9d37efb80","owner":[],"postedDate":"July 11th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-07-11T14:12:49+00:00","versionOfRecord":[],"versionCreatedAt":"2023-07-11 14:12:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3134479","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3134479","identity":"rs-3134479","version":["v1"]},"buildId":"wLkW0s4AflPzk-lpfg-fK","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}