Biochar production suitability in Borno State based on predicted agricultural waste mapping

Biochar production suitability in Borno State based on predicted agricultural waste mapping | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Biochar production suitability in Borno State based on predicted agricultural waste mapping Abdulrahman Maina Zubairu, Sherwan Yassin Hammad, Mohammed Zubairu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7087185/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 It was considered necessary to perform a preliminary data gathering before decision making regarding production of biochar, an important carbonaceous soil amendment which enhances soil fertility. The Normalized Difference Vegetation Index (NDVI) data was instrumental in achieving this goal due to its possibility in classifying vegetation according to density in Borno state as suitability classes for biochar production. The aims of this research were to assess and predict seasonal biomass availability for biochar production and promote the sustainable use of agricultural waste to enhance the production of biochar in Borno State, Nigeria. This method aimed to seize the chance to generate biochar from agricultural waste, thereby simplifying the planning and raising farmers' profitability by means of better soil fertility. Normalized Difference Vegetation Index (NDVI) data implemented provides a significant insight into the agricultural waste variations in Borno state, particularly during its most vegetative period (October to November) and its driest phase (March to April). Following the period of vegetative growth, the agricultural waste could be efficiently dried and recommended for local biochar production, ideally in the month of November. Several Local Government Areas were predicted to have abundant waste after the cultivation period which are classified to have higher suitability for biochar production. However, socio-economic factors pertaining to these areas, including the utilization of agricultural waste for purposes such as animal feed, fuel, and construction of thatched/mud houses, were some influential factors that can compete with the use of agricultural waste for biochar production in the study area even though no data record were available for reference purposes. Moreover, certain policies including but not limited to subsidizing biochar production and promoting carbon credits to make biochar production economically viable compared to alternative uses can serve as a possible solution. NDVI Soil Soil Quality Borno State Agricultural Waste Biochar Figures Figure 1 Figure 2 Figure 3 Figure 4 1.0 Introduction Borno state is the second largest state in Nigeria in terms of land area, and the eleventh most populous state with a population of about 5,860,300 people in 2016 (National Bureau of Statistics, 2016 ). From a geographical point of view, it is located in the northeastern region of Nigeria and comprises of 26 Local Government Areas (Fig. 1 ; A and B). Borno has complex terrains and might be divided into three zones: Sahelian savanna in the north, Sudanian savanna in Central and southern parts. The southeast region contains a part of the Mandara mountain. In the extreme North eastern part the state shares her boundaries with the Nigerian part of Lake Chad and the Lake Chad flooded savanna ecoregion. Economically, most of the remote areas in Borno depend on the rearing of cattle and growing of crops. Besides, Maiduguri, the state capital provide best opportunity as a major trade and service hub for the region. But the Boko Haram insurgency has severely constrained the state’s growth for example farmers from the rural areas have been forced to flee their homes. Consequently, Borno State is faced with the problems of how to utilize the opportunities within the agricultural resource potential. However, attempts have been made to revive development in the state after the improvement of the long-standing violence insurgency. The demographic factors such as population size and educational needs and development in the region affect the biochar production and other facets of development in region. The proper disposal of animal and agricultural crop by-products is an essential factor to observe in sustainable farming and the use of biochar production is deemed an answer to this. Analyzing NDVI is therefore very effective in evaluating the status of vegetation cover, which can give useful information concerning the state of environment in a given area. In this study, the NDVI measure will be used to determine areas with high biomass, which is critical for biochar production. This will aid in identifying the locations where agricultural waste is available to support biochar production with highest efficiency in the use of resources. According to Sandabe et al. ( 2019 ), the soils in Borno state exhibit variations in color, texture, structure, physico-chemical properties, and other essential features as one moves from the elevated southern regions to the northern dune landscape. In the flat plains near Lake Chad and within depressions, Vertisols predominate. These are dense, dark clay soils (Firki) that form extensive cracks during the dry season. The dunes, on the other hand, are characterized by regosols, which are shallow and have poorly developed profiles. In areas with volcanic and Basement Complex formations, the valley bottoms contain fertile clayey loamy soils, while skeletal soils and rock outcrops are present on the gentle and steep slopes. Improper agricultural waste disposal causes greenhouse gas emissions such as carbon dioxide (CO 2 ), nitrous oxide (N 2 O), and methane (CH 4 ), which affect both humans and the natural environment (Kaab et al., 2019 ). Various forms of agricultural waste, particularly crop wastes, have become serious challenges, affecting the long-term viability of agricultural operations (Duque-Acevedo et al., 2020 ; Koul et al., 2022 ). For example, inappropriate disposal of tons of rice straw left over after harvest, as well as the practice of burning, result in the loss of vital organic matter, leading to soil degradation and lower fertility. This, in turn, impacts crop yields and overall agricultural production. Significant biomass is produced by agriculture and this biomass might be a useful input for the bioeconomy (Koul et al., 2022 ). Nigeria's rich tropical rainforests have produced a wealth of biomass resources. The production of biochar, which has uses in environmental management and agriculture, has been investigated using these resources (Olorunfemi et al., 2019 ). Whether unprocessed or supplemented mixed with synthetic ingredients, crop residue and certain grasses are widely used as animal feed in Borno state. Large-scale and semi-intensive methods for fattening cattle and sheep use the grasses that are easily accessible following the wet season. Nomads who raise sheep and cattle also scavenge in the forests for appropriate grasses to feed their animals. The sustainability of agriculture is threatened by some farmers' choice to burn crop residue in order to convert biomass into fuel for heating, boiling water, and cooking (Kumar and Singh, 2021 ). In this process, biomass and oxygen undergo a rapid chemical reaction that produces carbon dioxide, water, organic matter oxidation products, and release energy (Klass, 2004 ). To produce biochar, agricultural wastes are subjected to high temperatures (400 and 600°C) without or partial presence of oxygen during the pyrolysis process, which causes thermal degradation. Adeniyi et al. ( 2019 ) emphasize that the final product, biochar, is a carbon-rich substance (65–90% carbon) with a porous structure of charred particles. According to Adekiya et al. ( 2019 ), biochar is preferred for enhancing soil fertility as well as restoring nutrients in the soil thus preventing leaching. The two main byproducts of thermal degradation of lignocellulosic biomass are biochar and bio-oil. Koul and Taak ( 2018 ) have defined biochar as a high-carbon, fine-grained form of charcoal. According to Koul et al. ( 2022 ), the use of biochar together with agricultural residues has drawn interest recently as a means of maintaining soil quality and having a major impact on soil carbon sequestration. According to Lemann and Joseph ( 2009 ), biochar produced from plant biomass is a recalcitrant source of carbon that, when added to soil, resists microbial degradation, making it appropriate for carbon sequestration. Applying biochar to soil offers a practical way to reduce soil fertility and organic carbon loss while also reducing global carbon emissions. Numerous studies have demonstrated how adding biochar to soils may improve their ability to retain water, which in turn directly increases plant health and productivity (Githinji, 2014 ). According to published research, adding biochar promotes root growth, which in turn strengthens soil water retention (Bruun, 2014). In dry and semi-arid regions, which have low carbon stocks, the capacity of the soil to retain water and nutrients is reduced. Application of biochar is a viable approach to this problem. The availability of feedstock and agricultural waste for biochar production is a problem in arid regions. The development of remote sensing technology, which allows data collection without presence at the site while also minimizing costs, gives hope for locating prime sources of agricultural waste or feedstock for effective biochar production. When it comes to identifying living green plant canopies, the Normalized Difference Vegetation Index (NDVI) continues to be the most popular option for quickly and easily identifying vegetated zones. The NDVI, well-known for evaluating vegetative state and measuring vegetation properties (Huang et al., 2021 ), appears as a critical instrument. The major goal of this study, which makes use of NDVI data and maps, is to identify and assess suitable biochar production locations in Borno state, Nigeria. 2.0 Objective The goal of these studies was to produce information about Borno State on possible hotspots rich in agricultural waste as they are becoming a burden to dispose of after agricultural harvest period and to interpret its suitability on a classification scale and potential for biochar production for subsequent use during dry season irrigation using NDVI data. 3.0 Material and Method 3.1 Study area The study was carried out in Borno, which is located in northeastern Nigeria (see Fig. 1 above). It has an arid and semi-arid climate, a limited rainy season with erratic rainfall patterns, and the predominance of sandy loam soils low in nutrients. Prominent geographical elements of significance were the Lake Chad Basin. 3.2 Normalized Difference Vegetation Index ( NDVI) Data Acquisition and Selection Normalized Difference Vegetation Index (NDVI) data were downloaded and achieved from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor aboard the Terra satellite (Didan, 2021 ). The NDVI images were taken for two different seasons for Borno State (dry and wet season). For the vegetative season, three NDVI images were provided for October 2022, and three images were provided for dry season for March 2022 from the MODIS dataset, which provides 500-meter resolution NDVI values at 16-day intervals. After comparing the NDVI values from the three datasets in QGIS software (QGIS Development Team, 2024 ), The image with the highest greenness was selected for vegetative period, which corresponded to 16th October 2022 and selected the image that best reflected the driest of vegetation for dry season which was on March 6, 2022. 3.2 NDVI Classification of Agricultural Waste for Biochar Production The NDVI values were classified based on Local Government Areas (LGAs) for Borno State for both dry and vegetative seasons. This classification assisted in identifying areas with the highest vegetation areas to create the agricultural waste prediction map, which was further used to make biochar production suitability map of Borno State. 4.0 Result and Discussion 4.1 Vegetative analyses in dry and wet seasons The NDVI maps for Borno State showed seasonal variations in vegetation. During the dry season, the result shows that NDVI values ranged from 0.012 to 0.441. In contrast, the vegetative season in October 2022 showed a higher NDVI value (0.072–0.767), reflecting increased vegetation growth following rainfall period (Fig. 2). Figure 3 have shown that NDVI values across Borno State's Local Government Areas (LGAs) are varied significantly between the dry and vegetative seasons. The highest NDVI values in vegetative season were recorded in Gwoza (0.443), Lake Chad (0.431), Damboa (0.422), and Chibok (0.418), indicating high dense vegetation which can be predicted to have higher availability of agricultural waste. These LGAs are expected to have the greatest potential for biochar production due to their higher biomass residues. In contrast, areas like Kala/Balge (0.304) and Mobbar (0.314) had relatively lower NDVI values, suggesting lower vegetation cover. Higher NDVI values, which indicate more vegetation, are shown by dark green patches. Light green, on the other hand, denotes regions with less vegetation and lower NDVI values. More agricultural waste that may be used to produce biochar is likely to be found in areas with darker greens (higher NDVI). More agricultural residue, pruning scraps, and other organic materials left over after harvest operations are frequently associated with denser vegetation. The main source of feedstock to produce biochar are these organic resources. It is expected that immediately after wet season more agricultural waste are produced which farmers can utilize to produce biochar for subsequent use in dry season as biochar`s potential for production depends on agricultural waste availability. Based on the prediction, agricultural waste will usually be available late October to early September as harvest usually occurs in mid of September to late September. This denotes that the month of November will be good for biochar production as the agricultural waste needs to be dried before biochar are produced locally. The results as suitability classification were presented in a map (Fig. 4 ). 4.2 Predicted Agricultural Waste for Biochar Production in Borno State The distribution of predicted agricultural waste across Borno State as shown in Fig. 4 , were classified across five suitability classes based on the NDVI values in vegetative period as very low(S1), low (S2), moderate (S3), high (S4) and very high (S5). It shows higher or lower potential for biochar production in each of these LGAs. Local Government areas (LGAs) classified with S5 were Konduga, Damboa, Chibok, Askira/Uba, Gwoza as well as the Lake Chad area. These S5 LGAs and the Lake Chad area indicate the densest vegetation cover during the vegetative season, indicating to have higher biomass availability, thus could be predicted as good locations for biochar production. High class (S4) values of agricultural waste are shown in LGAs Bama, Biu, Bayo, Marte and Mafa which also displayed significant vegetation cover and biomass accumulation. LGAs categorized as moderate suitability included LGAs as Monguno, Nganzai, Magumeri, Hawul, Kwaya Kusar and Jere. While LGAs classified as low suitability include Gubio, Guzamala, Kaga, Ngala and Shani and very low Mobbar, Abadam, Kukawa, Kalabalge, Dikwa and Maiduguri. By prioritizing areas with high biomass availability for effective resource utilization, these regional variations highlight the significance of suited biochar production processes. It is expected that areas with very high and high suitability can be economical to produce biochar which can be utilized as soil amendment on the soil during dry season farming. This will improve the irrigation regime of the area as less moisture will be lost during the dry period farming signaling possible reduction in production cost and more profit margin to farmers as expected. Based on the vegetation observed, areas classified as S5 and S4 are more suitable to farming as presence of vegetation shows that plants can thrive. The demographic properties of Borno state also affect the use of available agricultural waste. Notable amount of agricultural waste is also utilised for feeding animals, burning as fuel for cooking food in the rural areas. an estimated population of about 5.86 million as of 2016 (National Bureau of Statistics, n.d. ). There are few industries in the capital with concrete houses spread all over the cities and appreciable road networks that link the local governments and the city. Thatch/mud houses were dominant in the far and remote villages of all local governments of Borno state. Most of these demographic characteristics had few or no effect on local biochar production except for use of some agricultural waste for thatch houses, animal feeding and burning as fuel for cooking food. It is important to note that NDVI alone cannot definitively determine biochar production feasibility as NDVI alone doesn't equate biochar feedstock . Although greater vegetation may indicate more agricultural waste, the kind of vegetation is not shown by NDVI. Certain plants, such as trees, might not produce a lot of waste that can be used to make biochar. Agricultural practices are also important. The quantity and kind of waste available are significantly determined by the crops grown and their management practices for example, regions abundant in trees may lack sufficient agricultural waste to generate biochar. 4.3 Discussion The recognition of biochar has been steadily increasing, primarily owing to its numerous advantages. In the context of the obtained Normalized Difference Vegetation Index (NDVI) results, it is evident that most delineated areas exhibited poor vegetation during the dry season, except for the Lake Chad region (as depicted in Fig. 2). Upon closer examination of areas classified as S1 and S2 (as shown in Fig. 3 ), it becomes apparent that producing biochar in these regions might incur higher costs. This is due to the necessity of collecting agricultural waste, which may be in distant places from the farms, thereby escalating the production expenses. Conversely, in areas categorized as S4 and S5, it can be anticipated that agricultural waste is readily available, making it feasible to produce biochar with relative ease and efficiency. As for areas classified as S3, where vegetation is moderate, there lies a promising opportunity. Through the strategic utilization of the existing agricultural waste to generate recalcitrant biochar and reintroducing it into the soil, there is potential for substantial improvement in the soil quality in the coming years. Prudent utilization of accessible agricultural waste materials can substantially improve soil fertility. The suitability class may increase from this beneficial intervention to S4, due to a definite improvement to an upward trend in the quality of soil of the area. Aside from being beneficial for identification, NDVI data is critical for farmers to successfully plan their activities. Farmers may use the many categories provided by the NDVI investigation to plan how to produce biochar and other related activities, such as dry season farming. With such data, they may maximize the use of agricultural waste and assure its conversion into biochar, a method that not only eliminates solid waste but also improves soil quality. However, despite the potential benefits, certain challenges seems to be substantial. Alternative uses for agricultural waste, as well as regional demographics, may impede the smoothintegration of agricultural waste into biochar production. The management of agricultural waste may be affected by the social, economic and cultural factors of the certain community. Furthermore, the procedure may become much more complicated due to practical concerns with agricultural waste collection and transportation. To address these challenges, it is suggested to apply the complex approach that encompass the cooperation of farmers with regional authorities and agricultural experts. These challenges can be overcome by increasing people awareness about the benefits of biochar production, recognizing the benefits of private sustainable agriculture, and offering assistance in management of wastes and transportation. Decisions can be made with the help of smart technologies supported by the analysis of the NDVI data in order to bring a better condition to the Borno soil and thus increase agricultural production and promote the effective farming in the area. 5.0 Conclusion NDVI, as a technique, efficiently identifies areas with denser vegetation (darker green) during and immediate after the rainy season, indicating that there is more potential agricultural waste ideal for biochar production. The analysis identifies November, after the harvest season (mid-September to late September), as a suitable time for biochar production, allowing for waste drying before processing. Biochar use could improve soil moisture retention during the dry season and potentially reduce irrigation cost and increasing farmer's profit margin. The classification map (Fig. 4 ) provides a valuable tool for identifying areas with the highest potential for biochar production (S5 class). Whereas population density and infrastructure may not directly control the production of biochar, they may perhaps have an effect on the logistic and collection of the biochar. In fact, the current researchers and policymakers must consider these constraints in an effort to identify a more targeted and viable investment strategy to address Borno State’s biochar production. However, NDVI doesn't reveal crop types, areas with dense forests may not have suitable waste for biochar production because of crop types and management practices which may significantly affect waste availability. Understanding these practices is important for accurate assessment of biochar production suitability. Declarations Acknowledgement We thank the Hungarian University of Agriculture and Life Sciences, MATE for providing the necessary services for the successful completion of this work. Conflicts of Interest The authors declare no conflicts of interest. Ethics, Consent to Participate, and Consent to Publish declarations Not applicable. Clinical Trial Number Not applicable Funding The work was supported by the project ‘The feasibility of the circular economy during national defense activities’ of 2021 Thematic Excellence Programme of the National Research, Development and Innovation Office under grant no.: TKP2021-NVA-22, led by the Centre for Circular Economy Analysis. Data Availability Statement Not applicable. Author Contribution Author Contributions Conceptualization: Abdulrahman Maina Zubairu and Sherwan Yassin Hammad. Methodology: Sherwan Yassin Hammad and Abdulrahman Maina Zubairu. Writing—original draft preparation: Abdulrahman Maina Zubairu and Mohammed Zubairu. Writing—review and editing: Sinazo Ajibade, Boglárka Anna Dálnoki, Caleb Melenya Ocansey, Abdulrahman Maina Zubairu and Miklos Gulyás References Adekiya AO, Agbede TM, Aboyeji CM, Dunsin O, Simeon VT (2019) Biochar and poultry manure effects on soil properties and radish ( Raphanus sativus L.) yield. Biol Agric Hortic 35(1):33–45 Adeniyi AG, Ighalo JO, Onifade DV (2019) Production of biochar from elephant grass ( Pernisetum purpureum ) using an updraft biomass gasifier with retort heating. Biofuels . http://dx.doi.org/10.1080/17597269.2018.1554949 Bruun EW, Petersen CT, Hansen E, Holm JK, Hauggaard-Nielsen H (2014) Biochar amendment to coarse sandy subsoil improves root growth and increases water retention. Soil Use Manag. 2014, 30 , 109–118 Didan K (2021) MOD13A1 MODIS/Terra Vegetation Indices 16-Day L3 Global 500m SIN Grid V061. https://doi.org/10.5067/MODIS/MOD13A1.061 . 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-7087185","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486535449,"identity":"9ac966e6-5a82-4516-acc7-12f5d7dfbbf4","order_by":0,"name":"Abdulrahman Maina Zubairu","email":"data:image/png;base64,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","orcid":"","institution":"Hungarian University of Agriculture and Life Sciences","correspondingAuthor":true,"prefix":"","firstName":"Abdulrahman","middleName":"Maina","lastName":"Zubairu","suffix":""},{"id":486535450,"identity":"57fc42fa-7827-4fb5-8156-754fb65f28e8","order_by":1,"name":"Sherwan Yassin Hammad","email":"","orcid":"","institution":"Hungarian University of Agriculture and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sherwan","middleName":"Yassin","lastName":"Hammad","suffix":""},{"id":486535451,"identity":"25af9f32-dd4e-4a6f-b54e-ae3ec61c0a5c","order_by":2,"name":"Mohammed Zubairu","email":"","orcid":"","institution":"Mohamet Lawan College of Agriculture, Maiduguri","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Zubairu","suffix":""},{"id":486535452,"identity":"c2296191-3252-4db2-9518-1d6f03554359","order_by":3,"name":"Sinazo Ajibade","email":"","orcid":"","institution":"Hungarian University of Agriculture and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sinazo","middleName":"","lastName":"Ajibade","suffix":""},{"id":486535453,"identity":"4dd09067-cfb9-4bbc-9e37-f5783c4f71a7","order_by":4,"name":"Caleb Melenya Ocansey","email":"","orcid":"","institution":"Crops Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Caleb","middleName":"Melenya","lastName":"Ocansey","suffix":""},{"id":486535454,"identity":"806033f0-457a-40ae-9c60-386ef115ba1a","order_by":5,"name":"Boglárka Anna Dálnoki","email":"","orcid":"","institution":"Hungarian University of Agriculture and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Boglárka","middleName":"Anna","lastName":"Dálnoki","suffix":""},{"id":486535455,"identity":"09bca409-769d-4070-8f65-6bf52f297266","order_by":6,"name":"Miklos Gulyás","email":"","orcid":"","institution":"Hungarian University of Agriculture and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Miklos","middleName":"","lastName":"Gulyás","suffix":""}],"badges":[],"createdAt":"2025-07-09 20:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7087185/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7087185/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87187748,"identity":"0a140d71-d77b-45dd-9fa3-c901f6ddf8de","added_by":"auto","created_at":"2025-07-21 10:46:27","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":284003,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing Borno State location in Nigeria (A) and Borno State Local Government Areas (B). Source: GADM (2025).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7087185/v1/4ab857e1678b3e33ac2aa86a.jpeg"},{"id":87187753,"identity":"43a16bc0-0f2b-4cba-966e-e7c7de5d9ea1","added_by":"auto","created_at":"2025-07-21 10:46:27","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":621538,"visible":true,"origin":"","legend":"\u003cp\u003eNDVI map for Borno State for the dry season in March 2022 (A) and vegetative period in October 2022 (B).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7087185/v1/d93d22b2247d852801452956.jpeg"},{"id":87187747,"identity":"c3d32589-ced6-4d18-889e-89c23071297a","added_by":"auto","created_at":"2025-07-21 10:46:27","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":400410,"visible":true,"origin":"","legend":"\u003cp\u003eNDVI values based on Local Government Areas LGAs in Borno State for dry season (A) and vegetative period (B).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7087185/v1/4b12c695f9498f8bb958f403.jpeg"},{"id":87189315,"identity":"72e5e095-ee50-446d-b415-b0efd2282062","added_by":"auto","created_at":"2025-07-21 11:02:27","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":417454,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing the predicted agricultural waste areas, classified based on LGAs suitability for biochar production.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7087185/v1/f09a8422c5bff2b1d9afb97c.jpeg"},{"id":96191675,"identity":"46e14edf-27c5-4566-a6e2-2ba842e2c9d6","added_by":"auto","created_at":"2025-11-18 14:39:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2300130,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7087185/v1/1ccc0fe6-6fb7-4b65-9c83-5fc404d178e7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eBiochar production suitability in Borno State based on predicted agricultural waste mapping\u003c/p\u003e","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eBorno state is the second largest state in Nigeria in terms of land area, and the eleventh most populous state with a population of about 5,860,300 people in 2016 (National Bureau of Statistics, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). From a geographical point of view, it is located in the northeastern region of Nigeria and comprises of 26 Local Government Areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; A and B). Borno has complex terrains and might be divided into three zones: Sahelian savanna in the north, Sudanian savanna in Central and southern parts. The southeast region contains a part of the Mandara mountain. In the extreme North eastern part the state shares her boundaries with the Nigerian part of Lake Chad and the Lake Chad flooded savanna ecoregion.\u003c/p\u003e\u003cp\u003eEconomically, most of the remote areas in Borno depend on the rearing of cattle and growing of crops. Besides, Maiduguri, the state capital provide best opportunity as a major trade and service hub for the region. But the Boko Haram insurgency has severely constrained the state\u0026rsquo;s growth for example farmers from the rural areas have been forced to flee their homes. Consequently, Borno State is faced with the problems of how to utilize the opportunities within the agricultural resource potential. However, attempts have been made to revive development in the state after the improvement of the long-standing violence insurgency. The demographic factors such as population size and educational needs and development in the region affect the biochar production and other facets of development in region.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe proper disposal of animal and agricultural crop by-products is an essential factor to observe in sustainable farming and the use of biochar production is deemed an answer to this. Analyzing NDVI is therefore very effective in evaluating the status of vegetation cover, which can give useful information concerning the state of environment in a given area. In this study, the NDVI measure will be used to determine areas with high biomass, which is critical for biochar production. This will aid in identifying the locations where agricultural waste is available to support biochar production with highest efficiency in the use of resources.\u003c/p\u003e\u003cp\u003eAccording to Sandabe et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the soils in Borno state exhibit variations in color, texture, structure, physico-chemical properties, and other essential features as one moves from the elevated southern regions to the northern dune landscape. In the flat plains near Lake Chad and within depressions, Vertisols predominate. These are dense, dark clay soils (Firki) that form extensive cracks during the dry season. The dunes, on the other hand, are characterized by regosols, which are shallow and have poorly developed profiles. In areas with volcanic and Basement Complex formations, the valley bottoms contain fertile clayey loamy soils, while skeletal soils and rock outcrops are present on the gentle and steep slopes.\u003c/p\u003e\u003cp\u003eImproper agricultural waste disposal causes greenhouse gas emissions such as carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e), nitrous oxide (N\u003csub\u003e2\u003c/sub\u003eO), and methane (CH\u003csub\u003e4\u003c/sub\u003e), which affect both humans and the natural environment (Kaab et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Various forms of agricultural waste, particularly crop wastes, have become serious challenges, affecting the long-term viability of agricultural operations (Duque-Acevedo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Koul et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For example, inappropriate disposal of tons of rice straw left over after harvest, as well as the practice of burning, result in the loss of vital organic matter, leading to soil degradation and lower fertility. This, in turn, impacts crop yields and overall agricultural production. Significant biomass is produced by agriculture and this biomass might be a useful input for the bioeconomy (Koul et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nigeria's rich tropical rainforests have produced a wealth of biomass resources. The production of biochar, which has uses in environmental management and agriculture, has been investigated using these resources (Olorunfemi et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Whether unprocessed or supplemented mixed with synthetic ingredients, crop residue and certain grasses are widely used as animal feed in Borno state. Large-scale and semi-intensive methods for fattening cattle and sheep use the grasses that are easily accessible following the wet season. Nomads who raise sheep and cattle also scavenge in the forests for appropriate grasses to feed their animals. The sustainability of agriculture is threatened by some farmers' choice to burn crop residue in order to convert biomass into fuel for heating, boiling water, and cooking (Kumar and Singh, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this process, biomass and oxygen undergo a rapid chemical reaction that produces carbon dioxide, water, organic matter oxidation products, and release energy (Klass, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo produce biochar, agricultural wastes are subjected to high temperatures (400 and 600\u0026deg;C) without or partial presence of oxygen during the pyrolysis process, which causes thermal degradation. Adeniyi et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) emphasize that the final product, biochar, is a carbon-rich substance (65\u0026ndash;90% carbon) with a porous structure of charred particles. According to Adekiya et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), biochar is preferred for enhancing soil fertility as well as restoring nutrients in the soil thus preventing leaching. The two main byproducts of thermal degradation of lignocellulosic biomass are biochar and bio-oil. Koul and Taak (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) have defined biochar as a high-carbon, fine-grained form of charcoal.\u003c/p\u003e\u003cp\u003eAccording to Koul et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the use of biochar together with agricultural residues has drawn interest recently as a means of maintaining soil quality and having a major impact on soil carbon sequestration. According to Lemann and Joseph (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), biochar produced from plant biomass is a recalcitrant source of carbon that, when added to soil, resists microbial degradation, making it appropriate for carbon sequestration. Applying biochar to soil offers a practical way to reduce soil fertility and organic carbon loss while also reducing global carbon emissions.\u003c/p\u003e\u003cp\u003eNumerous studies have demonstrated how adding biochar to soils may improve their ability to retain water, which in turn directly increases plant health and productivity (Githinji, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). According to published research, adding biochar promotes root growth, which in turn strengthens soil water retention (Bruun, 2014). In dry and semi-arid regions, which have low carbon stocks, the capacity of the soil to retain water and nutrients is reduced. Application of biochar is a viable approach to this problem. The availability of feedstock and agricultural waste for biochar production is a problem in arid regions. The development of remote sensing technology, which allows data collection without presence at the site while also minimizing costs, gives hope for locating prime sources of agricultural waste or feedstock for effective biochar production. When it comes to identifying living green plant canopies, the Normalized Difference Vegetation Index (NDVI) continues to be the most popular option for quickly and easily identifying vegetated zones.\u003c/p\u003e\u003cp\u003eThe NDVI, well-known for evaluating vegetative state and measuring vegetation properties (Huang et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), appears as a critical instrument. The major goal of this study, which makes use of NDVI data and maps, is to identify and assess suitable biochar production locations in Borno state, Nigeria.\u003c/p\u003e"},{"header":"2.0 Objective","content":"\u003cp\u003eThe goal of these studies was to produce information about Borno State on possible hotspots rich in agricultural waste as they are becoming a burden to dispose of after agricultural harvest period and to interpret its suitability on a classification scale and potential for biochar production for subsequent use during dry season irrigation using NDVI data.\u003c/p\u003e"},{"header":"3.0 Material and Method","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Study area\u003c/h2\u003e\u003cp\u003eThe study was carried out in Borno, which is located in northeastern Nigeria (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e above). It has an arid and semi-arid climate, a limited rainy season with erratic rainfall patterns, and the predominance of sandy loam soils low in nutrients. Prominent geographical elements of significance were the Lake Chad Basin.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.2 Normalized Difference Vegetation Index\u003c/b\u003e (\u003cb\u003eNDVI) Data Acquisition and Selection\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eNormalized Difference Vegetation Index (NDVI) data were downloaded and achieved from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor aboard the Terra satellite (Didan, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The NDVI images were taken for two different seasons for Borno State (dry and wet season). For the vegetative season, three NDVI images were provided for October 2022, and three images were provided for dry season for March 2022 from the MODIS dataset, which provides 500-meter resolution NDVI values at 16-day intervals. After comparing the NDVI values\u003c/p\u003e\u003cp\u003efrom the three datasets in QGIS software (QGIS Development Team, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), The image with the highest greenness was selected for vegetative period, which corresponded to 16th October 2022 and selected the image that best reflected the driest of vegetation for dry season which was on March 6, 2022.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.2 NDVI Classification of Agricultural Waste for Biochar Production\u003c/h2\u003e\u003cp\u003eThe NDVI values were classified based on Local Government Areas (LGAs) for Borno State for both dry and vegetative seasons. This classification assisted in identifying areas with the highest vegetation areas to create the agricultural waste prediction map, which was further used to make biochar production suitability map of Borno State.\u003c/p\u003e\u003c/div\u003e"},{"header":"4.0 Result and Discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Vegetative analyses in dry and wet seasons\u003c/h2\u003e\u003cp\u003eThe NDVI maps for Borno State showed seasonal variations in vegetation. During the dry season, the result shows that NDVI values ranged from 0.012 to 0.441. In contrast, the vegetative season in October 2022 showed a higher NDVI value (0.072\u0026ndash;0.767), reflecting increased vegetation growth following rainfall period (Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e have shown that NDVI values across Borno State's Local Government Areas (LGAs) are varied significantly between the dry and vegetative seasons. The highest NDVI values in vegetative season were recorded in Gwoza (0.443), Lake Chad (0.431), Damboa (0.422), and Chibok (0.418), indicating high dense vegetation which can be predicted to have higher availability of agricultural waste. These LGAs are expected to have the greatest potential for biochar production due to their higher biomass residues. In contrast, areas like Kala/Balge (0.304) and Mobbar (0.314) had relatively lower NDVI values, suggesting lower vegetation cover.\u003c/p\u003e\u003cp\u003eHigher NDVI values, which indicate more vegetation, are shown by dark green patches. Light green, on the other hand, denotes regions with less vegetation and lower NDVI values. More agricultural waste that may be used to produce biochar is likely to be found in areas with darker greens (higher NDVI). More agricultural residue, pruning scraps, and other organic materials left over after harvest operations are frequently associated with denser vegetation. The main source of feedstock to produce biochar are these organic resources. It is expected that immediately after wet season more agricultural waste are produced which farmers can utilize to produce biochar for subsequent use in dry season as biochar`s potential for production depends on agricultural waste availability. Based on the prediction, agricultural waste will usually be available late October to early September as harvest usually occurs in mid of September to late September. This denotes that the month of November will be good for biochar production as the agricultural waste needs to be dried before biochar are produced locally. The results as suitability classification were presented in a map (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Predicted Agricultural Waste for Biochar Production in Borno State\u003c/h2\u003e\u003cp\u003eThe distribution of predicted agricultural waste across Borno State as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, were classified across five suitability classes based on the NDVI values in vegetative period as very low(S1), low (S2), moderate (S3), high (S4) and very high (S5). It shows higher or lower potential for biochar production in each of these LGAs. Local Government areas (LGAs) classified with S5 were Konduga, Damboa, Chibok, Askira/Uba, Gwoza as well as the Lake Chad area. These S5 LGAs and the Lake Chad area indicate the densest vegetation cover during the vegetative season, indicating to have higher biomass availability, thus could be predicted as good locations for biochar production. High class (S4) values of agricultural waste are shown in LGAs Bama, Biu, Bayo, Marte and Mafa which also displayed significant vegetation cover and biomass accumulation. LGAs categorized as moderate suitability included LGAs as Monguno, Nganzai, Magumeri, Hawul, Kwaya Kusar and Jere. While LGAs classified as low suitability include Gubio, Guzamala, Kaga, Ngala and Shani and very low Mobbar, Abadam, Kukawa, Kalabalge, Dikwa and Maiduguri. By prioritizing areas with high biomass availability for effective resource utilization, these regional variations highlight the significance of suited biochar production processes.\u003c/p\u003e\u003cp\u003eIt is expected that areas with very high and high suitability can be economical to produce biochar which can be utilized as soil amendment on the soil during dry season farming. This will improve the irrigation regime of the area as less moisture will be lost during the dry period farming signaling possible reduction in production cost and more profit margin to farmers as expected. Based on the vegetation observed, areas classified as S5 and S4 are more suitable to farming as presence of vegetation shows that plants can thrive. The demographic properties of Borno state also affect the use of available agricultural waste. Notable amount of agricultural waste is also utilised for feeding animals, burning as fuel for cooking food in the rural areas. an estimated population of about 5.86\u0026nbsp;million as of 2016 (National Bureau of Statistics, \u003cem\u003en.d.\u003c/em\u003e). There are few industries in the capital with concrete houses spread all over the cities and appreciable road networks that link the local governments and the city. Thatch/mud houses were dominant in the far and remote villages of all local governments of Borno state. Most of these demographic characteristics had few or no effect on local biochar production except for use of some agricultural waste for thatch houses, animal feeding and burning as fuel for cooking food. It is important to note that NDVI alone cannot definitively determine biochar production feasibility as \u003cem\u003eNDVI alone doesn't equate biochar feedstock\u003c/em\u003e. Although greater vegetation may indicate more agricultural waste, the kind of vegetation is not shown by NDVI. Certain plants, such as trees, might not produce a lot of waste that can be used to make biochar. Agricultural practices are also important. The quantity and kind of waste available are significantly determined by the crops grown and their management practices for example, regions abundant in trees may lack sufficient agricultural waste to generate biochar.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Discussion\u003c/h2\u003e\u003cp\u003eThe recognition of biochar has been steadily increasing, primarily owing to its numerous advantages. In the context of the obtained Normalized Difference Vegetation Index (NDVI) results, it is evident that most delineated areas exhibited poor vegetation during the dry season, except for the Lake Chad region (as depicted in Fig.\u0026nbsp;2). Upon closer examination of areas classified as S1 and S2 (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e), it becomes apparent that producing biochar in these regions might incur higher costs. This is due to the necessity of collecting agricultural waste, which may be in distant places from the farms, thereby escalating the production expenses. Conversely, in areas categorized as S4 and S5, it can be anticipated that agricultural waste is readily available, making it feasible to produce biochar with relative ease and efficiency. As for areas classified as S3, where vegetation is moderate, there lies a promising opportunity. Through the strategic utilization of the existing agricultural waste to generate recalcitrant biochar and reintroducing it into the soil, there is potential for substantial improvement in the soil quality in the coming years. Prudent utilization of accessible agricultural waste materials can substantially improve soil fertility. The suitability class may increase from this beneficial intervention to S4, due to a definite improvement to an upward trend in the quality of soil of the area.\u003c/p\u003e\u003cp\u003eAside from being beneficial for identification, NDVI data is critical for farmers to successfully plan their activities. Farmers may use the many categories provided by the NDVI investigation to plan how to produce biochar and other related activities, such as dry season farming. With such data, they may maximize the use of agricultural waste and assure its conversion into biochar, a method that not only eliminates solid waste but also improves soil quality. However, despite the potential benefits, certain challenges seems to be substantial. Alternative uses for agricultural waste, as well as regional demographics, may impede the smoothintegration of agricultural waste into biochar production. The management of agricultural waste may be affected by the social, economic and cultural factors of the certain community. Furthermore, the procedure may become much more complicated due to practical concerns with agricultural waste collection and transportation.\u003c/p\u003e\u003cp\u003eTo address these challenges, it is suggested to apply the complex approach that encompass the cooperation of farmers with regional authorities and agricultural experts. These challenges can be overcome by increasing people awareness about the benefits of biochar production, recognizing the benefits of private sustainable agriculture, and offering assistance in management of wastes and transportation. Decisions can be made with the help of smart technologies supported by the analysis of the NDVI data in order to bring a better condition to the Borno soil and thus increase agricultural production and promote the effective farming in the area.\u003c/p\u003e\u003c/div\u003e"},{"header":"5.0 Conclusion","content":"\u003cp\u003eNDVI, as a technique, efficiently identifies areas with denser vegetation (darker green) during and immediate after the rainy season, indicating that there is more potential agricultural waste ideal for biochar production. The analysis identifies November, after the harvest season (mid-September to late September), as a suitable time for biochar production, allowing for waste drying before processing. Biochar use could improve soil moisture retention during the dry season and potentially reduce irrigation cost and increasing farmer's profit margin. The classification map (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e) provides a valuable tool for identifying areas with the highest potential for biochar production (S5 class). Whereas population density and infrastructure may not directly control the production of biochar, they may perhaps have an effect on the logistic and collection of the biochar. In fact, the current researchers and policymakers must consider these constraints in an effort to identify a more targeted and viable investment strategy to address Borno State\u0026rsquo;s biochar production. However, NDVI doesn't reveal crop types, areas with dense forests may not have suitable waste for biochar production because of crop types and management practices which may significantly affect waste availability. Understanding these practices is important for accurate assessment of biochar production suitability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Hungarian University of Agriculture and Life Sciences, MATE for providing the necessary services for the successful completion of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was supported by the project \u0026lsquo;The feasibility of the circular economy during national defense activities\u0026rsquo; of 2021 Thematic Excellence Programme of the National Research, Development and Innovation Office under grant no.: TKP2021-NVA-22, led by the Centre for Circular Economy Analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003cstrong\u003e\u003c/strong\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions Conceptualization: Abdulrahman Maina Zubairu and Sherwan Yassin Hammad. Methodology: Sherwan Yassin Hammad and Abdulrahman Maina Zubairu. Writing\u0026mdash;original draft preparation: Abdulrahman Maina Zubairu and Mohammed Zubairu. Writing\u0026mdash;review and editing: Sinazo Ajibade, Bogl\u0026aacute;rka Anna D\u0026aacute;lnoki, Caleb Melenya Ocansey, Abdulrahman Maina Zubairu and Miklos Guly\u0026aacute;s\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdekiya AO, Agbede TM, Aboyeji CM, Dunsin O, Simeon VT (2019) Biochar and poultry manure effects on soil properties and radish (\u003cem\u003eRaphanus sativus\u003c/em\u003e L.) yield. 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Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.usgs.gov/landsat-missions\u003c/span\u003e\u003cspan address=\"https://www.usgs.gov/landsat-missions\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\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":"NDVI, Soil, Soil Quality, Borno State, Agricultural Waste, Biochar","lastPublishedDoi":"10.21203/rs.3.rs-7087185/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7087185/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIt was considered necessary to perform a preliminary data gathering before decision making regarding production of biochar, an important carbonaceous soil amendment which enhances soil fertility. The Normalized Difference Vegetation Index (NDVI) data was instrumental in achieving this goal due to its possibility in classifying vegetation according to density in Borno state as suitability classes for biochar production. The aims of this research were to assess and predict seasonal biomass availability for biochar production and promote the sustainable use of agricultural waste to enhance the production of biochar in Borno State, Nigeria. This method aimed to seize the chance to generate biochar from agricultural waste, thereby simplifying the planning and raising farmers' profitability by means of better soil fertility. Normalized Difference Vegetation Index (NDVI) data implemented provides a significant insight into the agricultural waste variations in Borno state, particularly during its most vegetative period (October to November) and its driest phase (March to April). Following the period of vegetative growth, the agricultural waste could be efficiently dried and recommended for local biochar production, ideally in the month of November. Several Local Government Areas were predicted to have abundant waste after the cultivation period which are classified to have higher suitability for biochar production. However, socio-economic factors pertaining to these areas, including the utilization of agricultural waste for purposes such as animal feed, fuel, and construction of thatched/mud houses, were some influential factors that can compete with the use of agricultural waste for biochar production in the study area even though no data record were available for reference purposes. Moreover, certain policies including but not limited to subsidizing biochar production and promoting carbon credits to make biochar production economically viable compared to alternative uses can serve as a possible solution.\u003c/p\u003e","manuscriptTitle":"Biochar production suitability in Borno State based on predicted agricultural waste mapping","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-21 10:46:23","doi":"10.21203/rs.3.rs-7087185/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":"d2a87f43-f341-4e11-8f2e-e6f20c2094c2","owner":[],"postedDate":"July 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-18T14:39:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-21 10:46:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7087185","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7087185","identity":"rs-7087185","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}