Organic Matter And Anaerobic Cellulolytic Activity In Sediments of Ashtamudi Estuary, Kerala, India

Organic Matter And Anaerobic Cellulolytic Activity In Sediments of Ashtamudi Estuary, Kerala, India | 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 Organic Matter And Anaerobic Cellulolytic Activity In Sediments of Ashtamudi Estuary, Kerala, India Dennison Bindhulekha Arya, Salom Gnana Thanga Vincent, J.K Reshma, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-757184/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Estuarine sediments are best suited for bioprospecting cellulose degrading microorganisms because of continuous input of cellulosic carbon from rivers and terrestrial runoff, and such sediments act as a substrate for decomposition by microbes. Sediment samples were collected from thirteen stations of Ashtamudi estuary, a tropical Ramsar site during April 2016 and January 2017 and analysed for environmental variables such as temperature, pH, electrical conductivity, oxidation- reduction potential, sulphate, total organic carbon (C org ), carbohydrate, protein, lipid and labile organic matter. Microcosm experiments were conducted in the sediment samples to compare native and substrate-induced cellulase enzyme activities in mesophilic and thermophilic conditions added with crystalline cellulose and cellobiose as substrates. Abundance of cellulolytic anaerobes in the roll tubes was higher with cellobiose than crystalline cellulose. Substrate induced enzyme activity was more than native enzyme activity [0.0012±0.0001- 0.004±0.002 (April 2016) and 0.004±0.001- 0.161±0.002 mg glucose h -1 (January 2017)] in the sediment samples and cellulolytic activity was more pronounced in thermophilic conditions during April 2016. Redundancy analysis indicated that salinity was the highest determining factor for explaining variations among bacterial abundance and activity during April 2016 and sediment lipid content during January 2017. The study reveals that estuarine sediments can act as a potential source of thermophilic cellulase enzyme producing bacteria, which needs to be further explored owing to their vast industrial applications. Environmental Chemistry Estuaries Anaerobic Cellulolytic bacteria Enzyme activity Redundancy analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Estuaries are considered to be an important link between land and the sea and function as natural sinks of organic matter that comes from marine, terrestrial and anthropogenic sources. Most of the organic matter in sediments is dominated by cellulose due to the plant derived sources (Cowie and Hedges 1984 ; Bacic et al 2012 ).The organic carbon rich sediments of estuaries harbour abundant cellulolytic bacteria which have considerable influence on the carbon cycle in both aerobic and anaerobic environments. The structure and function of microbial communities in the estuarine sediment depend upon the human input of soluble and insoluble particulate form of organic matter (Babu et al 2010 ). The soluble form of organic matter is contributed by carbohydrate, protein, lipid and other biological compounds which can be easily metabolized (He et al 2010 ). Studies indicate that carbohydrate accounts for ~ 3–10% of total sedimentary organic matter (Skoog and Benner 1997 ; Bergamaschi et al 1999 ; Burdige et al 2000 ; Kerhervé et al 2002 ) whereas, protein is an important biochemical compound which can be easily utilized by bacteria than other biochemical compounds (Newell and Field 1983 ). Deposition of labile and refractory organic matter from the water column provides energy and nutrients for microbes inhabiting coastal sediments (Middelburg and Levin 2009 ). A major part of the organic matter consists of plant structural polymers referred as lignocelluloses and these polymers need to be hydrolyzed by extracellular enzymes before it is taken by microbes (Billen 1982 ; King 1986 ). These enzymes play an important role in organic matter degradation in natural ecosystems (Boschker and Cappenberg 2006 ). In anaerobic environment, cellulolytic bacteria hydrolyze organic polymers to monomers through fermentation; the monomers are further degraded by secondary fermenters such as methanogens (Zinder 1993 ). In the global carbon cycle, enzymatic degradation of cellulose by microorganism is a key process (Malhi 2002 ; Wilson 2011 ). Especially, extracellular enzymes such as cellulase have an important role in organic matter decomposition in the sediments, which depends upon the quantity and quality of organic matter (Meyer-Reil 1987 ; Boetius and Lochte 1996 ). Enzymatic conversion of lignocellulosic material is important because of their insolubility in water (Behera et al 2017 ). The cellulose degradation occurs by the hydrolysis of β 1–4 glycosidic bonds, which needs the concerted action of three enzymes such as endoglucanase, exoglucanase and β- glucosidase (Jørgensen et al 2007 ). These enzymes acts synergistically: endoglucanases hydrolyze the exposed cellulose chains of the cellulose polymer; exoglucanases (cellobiohydrolases) act to release cellobiose from the reducing and nonreducing ends, and β -glucosidases help to cleave the cellobiose and short-chain cello-oligosaccharide into glucose (Chandra and Madakka 2018 ). However, in anaerobic cellulolytic bacteria a “cellulosome” consisting of cellulose binding proteins and hydrolytic enzymes are responsible for cellulolysis (Doi et al 1994 ). A high molecular weight protein (> 2 MDa) was reported in cellobiose grown anaerobic cellulolytic bacteria such as Clostridium sp., Acetivibrio sp. and Bacteroides sp. that could bind to filter paper cellulose (Vincent and Ramasamy 2001). Ultimately, cellulolytic microorganisms degrade cellulose into simple sugar derivatives (Tengerdy and Szakacs 2003 ). Because of the complexity and high molecular weight of cellulose, it needs the action of various enzymes for degradation which is associated with various environmental conditions such as temperature, pressure and salinity (Taketani et al 2010 ). The cellulolytic microbes and their enzymes receive much attention due to their diverse applications in several industries such as textile, food, paper and pulp, beer and wine brewing, fuel and chemical industries (Gao et al 2008 ; Behera et al 2016 ). A study conducted by Odisi et al. (Odisi et al 2012 ) on five different strains of bacteria revealed the potential of cellulase enzyme activity in both mesophilic and thermophilic conditions. Isolation of cellulose degrading bacterial strains were well documented from various coastal habitats such as salt marshes on Sapelo island, Ga (Benner et al 1984 ), Sundarbans mangrove of West Bengal, India (Ramanathan et al 2008 ), mangrove soil of Bhitarkanka, Odisha, India (Thatoi et al 2012 ), Philippine’s mangrove (Tabao and Monsalud 2010 ), Uppanar estuary, India (Kalaiselvi et al 2013 ) and mangrove soil of Mahanadi river delta, Odisha, India (Behera et al 2014 ). Tropical estuaries receives multiple input of organic matter from allochthonous and autochthonous source. The increased microbial activities on organic matter mineralization leads to the depletion of oxygen and cause the prevalence of anoxic conditions and further leads to anaerobic metabolic activities. In Ashtamudi Estuary, the predominant anaerobic microbial activity was previously related to sulphate reduction, although denitrification and methanogenesis also occurred in the sediments (Vincent et al 2017 ). Hence, this study was done to explore the hydrolytic activity of Ashtamudi estuarine sediment by analysing the abundance and activity of anaerobic cellulolytic bacteria and also to investigate the environmental factors influencing the spatio-temporal variations in native and substrate-induced cellulolytic activity. Materials And Methods Study area and Relevance Ashtamudi estuary, located between 76 ◦ 32’ and 76 ◦ 41’E Longitude and 8 ◦ 52’ and 9 ◦ 2’ N latitude (Fig. 1) is the second-largest estuarine system having a surface area of 32 km 2 and gains international importance as a Ramsar site. It is a palm shaped estuarine system and opens into Neendakara, which is one of the most important fishing harbours of India. Kollam city is located in the southern side of the estuary, and it receives freshwater input from Kallada river (on the eastern side) with a length of 120 km with basin area of 1,699 km 2 and an annual average discharge of 3,375 Mm 3 . Ashtamudi estuary receives organic matter from non-point and point sources such as urban and agricultural runoff, tourism, waste and sewage disposal, discharge from coconut husk industries, clay factory and fish processing industries(Babu et al 2010 ) and also a huge amount of organic matter is transported by Kallada river (Jennerjahn et al 2008 ). Based on the geography, the entire Ashtamudi estuary can be subdivided into three categories- the northeast Kallada River joining portion and finger like portion as Kallada section(S1-S5), the middle portion as open estuary having marine influence(S6-S10) and southern tip as Kollam section (S11- S13) (Jennerjahn et al 2008 ). The anthropogenic pressure on the sampling stations were: S1- influence of clay factory, S4- confluence of Kallada River and also owing pressure of direct sewage disposal from the population inhabiting in the river catchments, S8- The sediments dredged for widening or national waterways were dumped, S10- Fishing harbour and hydrocarbon discharges from the fishing boats, S11- Solid waste plant of Kollam city, S12 – Presence of coir retting industries (Reshmi et al 2015 ). Sample collection and preparation Sediment samples were collected from thirteen stations of Ashtamudi estuary using Van Veen’s grab sampler during April 2016 and January 2017. The samples for microbial analysis were transferred to sterile airtight bottles and brought to lab and kept under 4°C. The remaining sediment samples were collected in polythene bags for physicochemical analysis. Environmental variables of sediment The environmental variables of estuarine sediments [temperature, pH, electrical conductivity (EC), oxidation- reduction potential (ORP), sulphate, total organic carbon (C org ), carbohydrate, protein, lipid and labile organic matter (LOM)] were analysed using standard procedures (Lowry et al 1951 ; Dubois et al 1956 ; Parsons et al 1984 ; Trivedy et al 1998 ; Grasshoff et al 1999 ). Lipid, carbohydrate and protein were converted into carbon equivalents using 0.75, 0.40 and 0.49 µgCµg − 1 conversion factors, respectively (Fabiano and Pusceddu 1998 ). The biopolymeric carbon fraction (BPC) was calculated by taking the sum of lipid, carbohydrate and protein (Fabiano et al 1995 ). The protein: carbohydrate and lipid: carbohydrate ratios were calculated to determine the quality of sedimentary organic matter (Pusceddu et al 2003 ). Abundance of cellulolytic anaerobes The sediment samples were enriched in pre-reduced Hungate’s mineral broth containing (gL − 1 ) Potassium dihydrogen phosphate (0.2); Di-potassium hydrogen phosphate (0.3); Magnesium sulphate (0.1); Calcium chloride (0.1); Sodium chloride (1.0); Ammonium sulphate (1.0); Cysteine HCl (0.2); Sodium bicarbonate (0.2); Resazurin (0.001). Vitamin solution (Wolin et al 1963 ) and trace element solution (Ferguson and Mah 1983 ) were added to final concentration of 1%(V/V). Crystalline cellulose (0.2%) and cellobiose (0.2%) were the two substrates used in this study as insoluble and soluble substrate respectively. Cellulolytic anaerobes were enumerated by the roll tube method (modified method of Hungate (Ramasamy et al 1992 ). Growth of cellulolytic anaerobes observed as cleared zones or colonies in the roll tube, were counted and expressed as colony forming units per gram of sediments (CFUg − 1 ). Assay of native and substrate induced enzyme activities For native enzyme assay, 2.0 g sediment was incubated with 0.7% carboxy methyl cellulose in acetate buffer (pH-5.5) at 50 o c for 24 hours. For substrate induced enzyme assay, 10 mL of pre-reduced Hungate’s mineral broth was dispensed to screw capped vials (40 mL) sealed with butyl rubber stopper and aluminium cap assembly. Crystalline cellulose (1.0%) was added as the substrate and to maintain anaerobic conditions, the vials were flushed with high purity nitrogen gas. 2.0 g sediment samples were transferred to the vials and incubated for 10 days. Two sets of the vials for the sediment samples were prepared and each set were maintained in mesophilic and thermophilic conditions separately. After the incubation period, 1.0 mL of supernatant was incubated with 0.7% carboxy methyl cellulose in acetate buffer (pH-5.5) at 50 o c for 24 hours. The amount of reducing sugar was analyzed by the dinitrosalicyclic acid method (Miller 1959 ). Enzyme activity was expressed in terms of milligram of glucose released per hour (Schinner and Von Mersi 1990 ). Statistical analysis Two-way analysis of variance (two-way ANOVA) and principal component analysis (PCA) were conducted to test for significant spatial and temporal differences in the variables and also study the influence of environmental parameters on the activity of cellulolytic anaerobes. Redundancy Analysis (RDA) analysis is a method to extract and summarize the variation in a set of response variables that can be explained by a set of explanatory variables. RDA reveals the relationship between environmental parameters and activity of enzyme and bacterial abundance. All statistical analyses were performed using SPSS 20.0 and R studio. Results And Discussion Spatio- temporal variation of environmental variables The changes in environmental variables of Ashtamudi estuarine sediments is summarized in Table 1.0. The overall sediment temperature was higher during April 2016 than January 2017. The spatial variation of sediment temperature was statistically insignificant along the estuary whereas the temporal variation was significant (p=0.001) (Table 2). Previous study by Reshmi et al. (Reshmi et al 2015) in Ashtamudi estuarine sediment also points out similar results. During both sampling periods, Ashtamudi estuary exhibited brackish to marine conditions with regard to pH and salinity values (Jennerjahn et al 2008). Alkaline pH was observed all over the estuary during the sampling seasons with an average value of 7.97 and 8.26. However, the spatial variation of salinity was statistically significant (p<0.001) and temporal variation was insignificant. Ashtamudi estuary opens to the Arabian sea through a wide opening which obviously shows a marine influence all over the estuary (Vincent et al 2017). Maximum electrical conductivity was observed in the Kollam city part of the estuary during April 2016 and Kallada River part of the estuary during January 2017, which indicates the influence of dissolved nutrient load from the Kallada River (Jennerjahn et al 2008) during the post-monsoon season. Spatio- temporal variation and source of organic matter The quality and quantity of organic matter can regulate the composition and activity of microbial communities in aquatic sediments (Torres et al 2011; Cawley et al 2012). Particularly, the lignocellulosic biomass forms the substrate for cellulolytic anaerobes in the anaerobic sediment. Hence, it is important to analyze the quality and quantity of organic matter in the sediment. Significant spatial variations (p < 0.001) in the C org values were observed, whereas the temporal variations were statistically insignificant in the Ashtamudi estuary. In both seasons, average C org values was higher in Kollam city part as compared to the marine and river influenced part of the estuary. The sampling station S12 in the Kollam city region showed higher values during both seasons. Previous studies (Jennerjahn et al 2008; Vincent et al 2017) also showed the dominance of C org in the Kollam city region. Lowest C org values were observed in the open estuary portion particularly S9 and S10. That is related to the flushing of sea water to the open estuary during the tidal cycles and high rate of microbial degradative activities (Jonathan et al 2004; Hussain et al 2020). Stable isotopic δ13 C org study by Jennerjahn et al. (Jennerjahn et al 2008) points out the different source and diagenesis of organic matter, in which open estuary had highest value of δ13 C org indicating the presence of marine derived organic matter (Thimdee et al 2003) and lowest value of δ13 C org in the upper part, which is attributed to the presence of river derived organic matter. LOM and BPC values showed significant spatio- temporal variations (p<0.001). The higher LOM and BPC values were observed in Kallada River region during April 2016 and in Kollam city region of the estuary during January 2017. The LOM to TOM value can be used as an index of organic matter lability (Gonsalves et al 2011). In Ashtamudi estuarine sediments, higher LOM of TOM values were observed during January 2017 (21.82%) than during April 2016 (13.22%), which indicates that the organic matter was more labile during January 2017. LOM was dominated by protein followed by lipid and carbohydrate for both seasons. Similar result was observed in Kerala coast (Nair and Sujatha 2012), Galician coast (Cividanes et al 2002) and Ross sea, Antarctica (Fabiano et al 1995). Low carbohydrate values were also observed in cochin estuary (Joseph et al 2008) of Kerala. High protein concentration in the sediment is due to allochthonous inputs (Danovaro 1996) of organic matter. Usually, proteins can be readily utilized by the bacteria than carbohydrate (Newell and Field 1983) and the dominance of protein concentration indicates the presence of fresh organic matter. Contrastingly, high values of lipid were reported from decayed organism (Danovaro et al 1993). Nevertheless, carbohydrates are important fraction of C org contributed by living organisms (Børsheim et al 1999; Burdige et al 2000; Bacic et al 2012) and low carbohydrate values show the refractory nature of organic matter (Danovaro et al 1993). Protein: carbohydrate ratio was observed to be higher in Kallada River region during April 2016 and in Kollam region during January 2017. The high protein to carbohydrate ratio also indicates that the organic matter is fresh and recently generated (Danovaro et al 1993; Fabiano and Pusceddu 1998; Joseph et al 2008; Joy et al 2019), whereas higher lipid carbohydrate ratio was observed in the open estuary during both seasons. Abundance and distribution of cellulolytic anaerobes The abundance of cellulolytic anaerobes was comparatively higher during January 2017 than April 2016 (Table 3). During both seasons, maximum cellulolytic population was observed with cellobiose and limited or slow growth with crystalline cellulose as substrate, which is attributed to the insolubility nature of crystalline cellulose (Leschine 1995). In S7 (open estuary) maximum growth was observed in April 2016 and S8 (open estuary) in January 2017 for cellobiose substrate. In case of crystalline cellulose substrate, S12 (Kollam city region) showed maximum growth in April 2016 and S9 in January 2017. The cellulolytic population of cellulolytic anaerobes were very low in Ashtamudi estuary as compared to the populations of other group of obligate anaerobes like methanogens and sulphate reducing bacteria (Reshmi et al 2015). Cellulolytic enzyme activity In natural lake sediments, most of the cellulose degradation occurs aerobically and only 5-10 % is available for anaerobic degradation (Leschine 1995). During April 2016, native enzyme activity (NEA) was predominant in the open estuary (Fig. 2). Whereas, during January 2017, NEA was more pronounced in the Kallada River region, that might be due the confluence of Kallada river and the availability of fresh organic load from the river as native substrate. In this study, the cumulative substrate induced enzyme activity (SIEA) (Fig. 3 & 4) was more than NEA. This reveals the potential of added substrates to induce cellulosic activity. Previous studies in Lake Gooimeer also showed increased activity of β –glucosidase by addition of cellulose (Boschker and Cappenberg 2006). During April 2016, thermophilic activity was predominant in the Kallada River region, whereas mesophilic enzyme activity was higher in the Kallada River and Kollam city region of the estuary. During January 2017, thermophilic cellulase activity predominated in the open estuary and mesophilic enzyme activity in the Kollam city and Kallada River regions. Overall cellulolytic activity was higher towards Kallada River region of the estuary. Biogeochemical analysis of Ashtamudi estuarine sediment by Jennerjahn et al. (Jennerjahn et al 2008) revealed that, most of the Kallada River load is deposited in the upper part of the estuary and middle and lower parts are subjected to strong marine influence. So, it is evident that the riverine dissolved organic load contains sufficient amount of labile fraction, that can be easily consumed by the microbial communities (Abril et al 2002). Environmental controls on abundance and activity of cellulolytic anaerobe The relationship between environmental variables and cellulolytic activity were analysed using principal component analysis (PCA) and redundancy analysis (RDA). The PCA generated three principal components (Table 3, Fig.5). During April 2016, the first PC accounted for 32.02% of total variance. Whereas PC2 and PC3 explained 22.03 and 17.68 of total variance respectively and also explained a cumulative variance of 71.74%. In the first PC, EC, sulphate C org and TOM showed strong positive loadings and the factors were collectively referred as conductivity- nutrient factor. In PC 2 lipid:carbohydrate ratio showed strong positive loading and in PC3 carbohydrate showed strong negative loadings. During January 2017, the first PC accounted for 31.62% of total variance. Whereas PC2 and PC3 explained 22.59 and 17.89 of total variance respectively and also showed a cumulative variance of 71.74%. In the first PC, C org , TOM, protein, LOM and BPC showed strong positive loadings and was referred as nutrient factor. The composition of organic matter can influence extra cellular enzyme activities in lake sediments (Boschker and Cappenberg 2006). The second PC exhibited strong positive loading on protein:carbohydrate ratio and had a negative loading on carbohydrate. The third PC showed high positive loading on temperature and salinity. Hence, the factor was named as temperature- salinity factor. During April 2016, RDA output showed that lipid followed by salinity, protein and C org (explanatory variables) were the highest determining factors for explaining most of the variation in the abundance and activity of cellulolytic anaerobes (response variables) (Fig. 6). During January 2017, salinity followed by sulphate and organic matter were the highest determining factors. Energetic requirements of bacteria are associated with higher salinity and that can affect the abundance and activity of microbial groups (Gu et al 2012). Conclusions Estuarine ecosystems are an untapped resource for cellulosic biomass which provide opportunity for identifying novel microbial species that carry cellulase enzyme with novel biotechnological potential. Microbial cellulases are now commercially produced by several industries globally and are being widely used in food, animal feed, fuel, paper industry, textile industry and also various chemical industries. In the present work, even though, cellulolytic anaerobic abundance was found to be very low in Ashtamudi estuarine sediments, higher enzyme activity was observed in thermophilic conditions than mesophilic conditions. This clearly updates the evidence of tapping the enormous potential of thermophilic anaerobic cellulolytic bacteria for commercial and industrial applications. The substrate induced enzyme activity was more than native activity, which shows that addition of substrates induced the growth of cellulolytic anaerobe and enhanced their enzyme activities in the sediments. RDA revealed the importance of salinity and lipid with enzyme activity. To meet the growing demand for cellulases and to realize their full potential in biotechnology and research, continued research on bioprospecting cellulolytic microbes from potential sources such as estuarine sediments are vital. The development of rapid and reliable methods for the screening of cellulases from microorganisms within inhospitable environments like estuaries will allow a greater number of novel bacterial cellulases to be isolated with purpose for various applications in future. Declarations Acknowledgements We would like to thank the University of Kerala for providing the facilities for conducting laboratory analysis. Funding Not Applicable Conflict of interest The authors declare that they have no conflict of interest Ethics approval Not Applicable for this study Consent to participate Not Applicable Consent for publication Not Applicable Availability of data and material Most of the data produced from this study are provided in this manuscript and the remaining datasets used or analysed during the current study are available from the corresponding author on reasonable request. Code availability Not Applicable Authors' contributions SGTV led the conceptualisation of this study and edited the MS; DBA conducted the laboratory analysis and wrote the first draft of the MS; JKR edited the MS; JHS added valuable comments to the MS and created GIS maps; Field sampling was done by SGTV; DBA and JHS; All the mentioned authors also read the final MS and approved. References Abril G, Nogueira M, Etcheber H et al (2002) Behaviour of organic carbon in nine contrasting European estuaries. Estuarine, Coastal and Shelf Science 54:241–262. doi: 10.1006/ecss.2001.0844 Babu KN, Omana PK, Mohan M (2010) Water and sediment quality of Ashtamudi estuary, a Ramsar site, southwest coast of India-a statistical appraisal. Environ Monit Assess 165:307–319. doi: 10.1007/s10661-009-0947-0 Bacic A, Harris PJ, Stone BA (2012) Structure and function of plant cell walls. In: The Biochemistry of Plants: A Comprehensive Treatise. Elsevier Inc., pp 297–371 Behera BC, Mishra RR, Singh SK et al (2016) Cellulase from Bacillus licheniformis and Brucella sp. isolated from mangrove soils of Mahanadi river delta, Odisha, India. Biocatal Biotransform 34:44–53. doi: 10.1080/10242422.2016.1212846 Behera BC, Parida S, Dutta SK, Thatoi HN (2014) Isolation and Identification of Cellulose Degrading Bacteria from Mangrove Soil of Mahanadi River Delta and Their Cellulase Production Ability. American Journal of Microbiological Research 2:41–46. doi: 10.12691/ajmr-2-1-6 Behera BC, Sethi BK, Mishra RR et al (2017) Microbial cellulases – Diversity & biotechnology with reference to mangrove environment: A review. Journal of Genetic Engineering Biotechnology 15:197–210. doi: 10.1016/j.jgeb.2016.12.001 Benner R, Newell SY, Maccubbin AE, Hodson RE (1984) Relative contributions of bacteria and fungi to rates of degradation of lignocellulosic detritus in salt-marsh sediments. Appl Environ Microbiol 48:36–40. doi: 10.1128/aem.48.1.36-40.1984 Bergamaschi BA, Fram MS, Kendall C et al (1999) Carbon isotopic constraints on the contribution of plant material to the natural precursors of trihalomethanes. Org Geochem 30:835–842. doi: 10.1016/S0146-6380(99)00066-2 Billen G (1982) Modelling the processes of organic matter degradation and nutrients recycling in sedimentary systems. Sediment Microbiol Boetius A, Lochte K (1996) Effect of organic enrichments on hydrolytic potentials and growth of bacteria in deep-sea sediments. Mar Ecol Prog Ser 140:239–250. doi: 10.3354/meps140239 Børsheim KY, Myklestad SM, Sneli JA (1999) Monthly profiles of DOC, mono- and polysaccharides at two locations in the Trondheimsfjord (Norway) during two years. Mar Chem 63:255–272. doi: 10.1016/S0304-4203(98)00066-8 Boschker HT, Cappenberg T (2006) Patterns of extracellular enzyme activities in littoral sediments of Lake Gooimeer, The Netherlands. FEMS Microbiol Ecol 25:79–86. doi: 10.1111/j.1574-6941.1998.tb00461.x Burdige DJ, Skoog A, Gardner K (2000) Dissolved and particulate carbohydrates in contrasting marine sediments. Geochim Cosmochim Acta 64:1029–1041. doi: 10.1016/S0016-7037(99)00361-0 Cawley K, Wolski P, Mladenov N, Jaffe R (2012) Dissolved organic matter biogeochemistry along a transect of the Okavango Delta. Botswana Wetlands 32:475–486. doi: 10.1007/s13157-012-0281-0 Chandra MRGS, Madakka M (2018) Comparative biochemistry and kinetics of microbial lignocellulolytic enzymes. Recent Developments in Applied Microbiology and Biochemistry. Elsevier, pp 147–159 Cividanes S, Incera M, López J (2002) Temporal variability in the biochemical composition of sedimentary organic matter in an intertidal flat of the Galician coast (NW Spain). Oceanol Acta 25:1–12. doi: 10.1016/S0399-1784(01)01178-1 Cowie GL, Hedges JI (1984) Carbohydrate sources in a coastal marine environment. Geochim Cosmochim Acta 48:2075–2087. doi: 10.1016/0016-7037(84)90388-0 Danovaro R (1996) Detritus-bacteria-meiofauna interactions in a seagrass bed (Posidonia oceanica) of the NW mediterranean. Mar Biol 127:1–13. doi: 10.1007/BF00993638 Danovaro R, Fabiano M, Della Croce N (1993) Labile organic matter and microbial biomasses in deep-sea sediments (Eastern Mediterranean Sea). Deep-Sea Research Part I 40:953–965. doi: 10.1016/0967-0637(93)90083-F Doi RH, Goldstein M, Hashida S et al (1994) The clostridium cellulovorans cellulosome. Crit Rev Microbiol 20:87–93. doi: 10.3109/10408419409113548 Dubois M, Gilles KA, Hamilton JK et al (1956) Colorimetric Method for Determination of Sugars and Related Substances. Anal Chem 28:350–356 Fabiano M, Danovaro R, Fraschetti S (1995) Temporal trend analysis of the elemental composition of the sediment organic matter in subtidal sandy sediments of the Ligurian Sea (NW Mediterranean): A three years study. Cont Shelf Res 15:1453–1469 Fabiano M, Pusceddu A (1998) Total and hydrolizable particulate organic matter (carbohydrates, proteins and lipids) at a coastal station in Terra Nova Bay (Ross Sea, Antarctica). Polar Biol 19:125–132. doi: 10.1007/s003000050223 Ferguson TJ, Mah RA (1983) Isolation and characterization of an H2-oxidizing thermophilic methanogen. Appl Environ Microbiol 45:265–274. doi: 10.1128/aem.45.1.265-274.1983 Gao J, Weng H, Zhu D et al (2008) Production and characterization of cellulolytic enzymes from the thermoacidophilic fungal Aspergillus terreus M11 under solid-state cultivation of corn stover. Biores Technol 99:7623–7629. doi: 10.1016/j.biortech.2008.02.005 Gonsalves M-J, Fernandes CEG, Sheryl · et al (2011) Effects of composition of labile organic matter on biogenic production of methane in the coastal sediments of the Arabian Sea. Environ Monit Assess 182:385–395. doi: 10.1007/s10661-011-1883-3 Grasshoff K, Kremling K, Ehrhardt M (1999) Methods of Seawater Analysis, 3rd edn. Methods of Seawater Analysis: Third, Completely Revised and Extended Edition. doi: 10.1002/9783527613984 Gu C, Laverman AM, Pallud CE (2012) Environmental controls on nitrogen and sulfur cycles in surficial aquatic sediments. Front Microbiol 3:45. doi: 10.3389/fmicb.2012.00045 He B, Dai M, Huang W et al (2010) Sources and accumulation of organic carbon in the Pearl River Estuary surface sediment as indicated by elemental, stable carbon isotopic, and carbohydrate compositions. Biogeosciences 7:3343–3362. doi: 10.5194/bg-7-3343-2010 Hungate RE (1969) Chapter IV A Roll Tube Method for Cultivation of Strict Anaerobes. Methods in Microbiology 3:117–132. doi: 10.1016/S0580-9517(08)70503-8 Hussain SM, Anbalagan S, Kumar KS et al (2020) A baseline study on elemental concentration and potential ecological risk status of the surface sediments of Ashtamudi Lake, south west coast of India. Mar Pollut Bull 158:111410. doi: 10.1016/j.marpolbul.2020.111410 Jennerjahn TC, Soman K, Ittekkot V et al (2008) Effect of land use on the biogeochemistry of dissolved nutrients and suspended and sedimentary organic matter in the tropical Kallada River and Ashtamudi estuary, Kerala, India. Biogeochemistry 90:29–47. doi: 10.1007/s10533-008-9228-1 Jonathan MP, Ram-Mohan V, Srinivasalu S (2004) Geochemical variations of major and trace elements in recent sediments, off the Gulf of Mannar, the southeast coast of India. Environ Geol 45:466–480. doi: 10.1007/s00254-003-0898-7 Jørgensen H, Bach Kristensen J, Felby C (2007) Enzymatic conversion of lignocellulose into fermentable sugars: Challenges and opportunities. Biofuels Bioprod Biorefin 1:119–134. doi: 10.1002/bbb.4 Joseph MM, Kumar CSR, Gireesh Kumar TR et al (2008) Biogeochemistry of surficial sediments in the intertidal systems of a tropical environment Biogeochemistry of surficial sediments in the intertidal systems of a tropical environment. Chem Ecol 24:247–258. doi: 10.1080/02757540802119871 Joy A, Anoop P, Rajesh R et al (2019) Biochemical composition of sedimentary organic matter in the coral reefs of Lakshadweep Archipelago. Indian Ocean Chemistry Ecology 35:805–824. doi: 10.1080/02757540.2019.1665031 Kalaiselvi V, Jayalakshmi S, Narayanan RL (2013) Biofuel production using marine microbes. Internationalnternational Journal of Current Microbiology Applied Sciences 2:67–74 Kerhervé P, Buscail R, Gadel F, Serve L (2002) Neutral monosaccharides in surface sediments of the Northwestern Mediterranean sea. Org Geochem 33:421–435. doi: 10.1016/S0146-6380(02)00003-7 King GM (1986) Characterization of β-Glucosidase Activity in Intertidal Marine Sediments. Appl Environ Microbiol 51:373–380. doi: 10.1128/aem.51.2.373-380.1986 Leschine SB (1995) Cellulose degradation in anaerobic environments. Annu Rev Microbiol 49:399–426. doi: 10.1146/annurev.mi.49.100195.002151 Lowry OH, Rosebrough NJ, Farr AL, Randall RJ (1951) Protein measurement with the Folin phenol reagent. J Biol Chem 193:265–275 Malhi Y (2002) Carbon in the atmosphere and terrestrial biosphere in the 21st century. Philosophical Transactions of the Royal Society A: Mathematical Physical Engineering Sciences 360:2925–2945. doi: 10.1098/rsta.2002.1098 Meyer-Reil L-A (1987) Seasonal and Spatial Distribution of Extracellular Enzymatic Activities and Microbial Incorporation of Dissolved Organic Substrates in Marine Sediments. Appl Environ Microbiol 53:1748–1755. doi: 10.1128/aem.53.8.1748-1755.1987 Middelburg JJ, Levin LA (2009) Coastal hypoxia and sediment biogeochemistry. Biogeosciences 6:1273–1293 Miller GL (1959) Use of Dinitrosalicylic Acid Reagent for Determination of Reducing Sugar. Anal Chem 31:426–428. doi: 10.1021/ac60147a030 Nair MP, Sujatha CH (2012) Biogeochemical quality assessment of the sediments in Kerala coast. International Journal of Environmental Sciences 3:707–719. doi: 10.6088/ijes.20120301310699 Newell R, Field JG (1983) Relative flux of carbon and nitrogen in a kelp-dominated system. Marine Biology Letters 4:249–257 Odisi E, Silverstrin M, Takahashi R et al (2012) Bioprospection of cellulolytic and lipolytic South Atlantic deep-sea bacteria. Electron J Biotechnol 5:18–18 Parsons TR, Takahashi M, Hargrave B (1984) Biological Oceanographic Processes, 3rd edn. Pergamon Press Pusceddu A, Dell’Anno A, Danovaro R et al (2003) Enzymatically hydrolyzable protein and carbohydrate sedimentary pools as indicators of the trophic state of detritus sink systems: A case study in a mediterranean coastal lagoon. Estuaries 26:641–650. doi: 10.1007/BF02711976 Ramanathan AL, Singh G, Majumdar J et al (2008) A study of microbial diversity and its interaction with nutrients in the sediments of Sundarban mangroves Ramasamy K, Kalaichelvan G, Nagamani B (1992) Working with Anaerobes-Laboratory Manual. Fermentation Laboratory, Tamil Nadu Agrcultural University, Coimbatore Reshmi RR, Nair KD, Zachariah EJ, Vincent SGT (2015) Methanogenesis: Seasonal changes in human impacted regions of Ashtamudi estuary (Kerala, South India. Estuar Coast Shelf Sci 156:144–154 Schinner F, Von Mersi W (1990) Xylanase-, CM-cellulase-and invertase activity in soil: an improved method. soil Biology Biochemistry 22:511–515 Skoog A, Benner R (1997) Aldoses in various size fractions of marine organic matter: Implications for carbon cycling. Limnol Oceanogr 42:1803–1813. doi: 10.4319/lo.1997.42.8.1803 Tabao NSC, Monsalud RG (2010) Characterization and identification of high cellulose producing bacterial strains from philippine mangroves. Philippine Journal of Systematic Biology 4:13–20 Taketani RG, Yoshiura CA, Dias ACF et al (2010) Diversity and identification of methanogenic archaea and sulphate-reducing bacteria in sediments from a pristine tropical mangrove. Antonie van Leeuwenhoek. International Journal of General Molecular Microbiology 97:401–411. doi: 10.1007/s10482-010-9422-8 Tengerdy RP, Szakacs G (2003) Bioconversion of lignocellulose in solid substrate fermentation. Biochem Eng J 13:169–179. doi: 10.1016/S1369-703X(02)00129-8 Thatoi H, Behera B, Dangar T, Mishra R (2012) Microbial biodiversity in mangrove soils of Bhitarkanika, Odisha, India. International Journal of Environmental Biology 2:50–58 Thimdee W, Deein G, Sangrungruang C et al (2003) Sources and fate of organic matter in Khung Krabaen Bay (Thailand) as traced by δ 13 C and C/N atomic ratiosand C/N atomic ratios. Wetlands 23:729–738 Torres IC, Inglett KS, Reddy KR (2011) Heterotrophic microbial activity in lake sediments: Effects of organic electron donors. Biogeochemistry 104:165–181. doi: 10.1007/s10533-010-9494-6 Trivedy RK, Goel PK, Trisal CL (1998) Practical Methods in Ecology and Environmental Science. Environmental Publications Vincent SGT, Ramaswamy K (2001) Cellulose binding proteins of anaerobic bacteria: role in cellulolysis. Asian Journal of Microbiology Biotechnology Environmental Science 3:263–268 Vincent SGT, Reshmi RR, Hassan SJ et al. Estuarine (2017) Predominant terminal electron accepting processes during organic matter degradation: Spatio-temporal changes in Ashtamudi estuary, Kerala, India. Coastal Shelf Science 198:508–517. doi: 10.1016/J.ECSS.2017.05.013 Wilson DB (2011) Microbial diversity of cellulose hydrolysis. Curr Opin Microbiol 14:259–263. doi: 10.1016/J.MIB.2011.04.004 Wolin EA, Wolin MJ, Wolfe R (1963) Formation of Methane by Bacterial Extracts*. The Journal of Biological Chemistry 238 8:2882–2886. doi: 10.1016/S0021-9258(18)67912-8 Zinder SH (1993) Physiological Ecology of Methanogens. Methanogenesis. Springer US, pp 128–206 Tables Table 1. Environmental variables of Ashtamudi estuary (April 2016 and January 2017) April 2016 Environmental variables S 1 S 2 S 3 S 4 S 5 S 6 S 7 S 8 S 9 S 10 S 11 S 12 S 13 Temperature (°C) 29±0.53 29±0.58 29±0.40 29±0.74 29±0.61 28±0.79 28±0.36 28±0.36 29±0.25 28±0.31 28±0.36 29±0.40 29±0.31 pH 8.00±0.31 8.15±0.03 7.95±0.10 8.11±0.07 7.91±0.03 7.95±0.04 7.97±0.03 7.8±0.20 7.85±0.02 7.99±0.31 7.88±0.08 8.13±0.01 7.96±0.03 EC (µs/cm) 2.32±0.02 2.23±0.03 1.75±0.01 2.00±0.11 1.03±0.04 2.47±0.04 1.93±0.03 2.33±0.03 1.34±0.03 1.50±0.46 1.93±0.04 1.93±0.13 2.24±0.02 Salinity (ppt) 24.2±0.30 27.00±0.44 25.70±0.25 21±0.35 22.5±0.40 25.8±0.26 26.4±0.10 25.9±0.47 26.3±0.15 25.6±0.32 27.3±0.08 29.6±0.36 27.1±0.38 Redox potential (mv) -128±2.31 -188±4.16 -269±3.51 -251±4.93 -313±5.03 -223±2.52 -298±3.51 -303±3.06 -204±4.04 -288±8.33 -300±8.54 -415±3.06 -277±5.29 Sulphate (mg/g) 63.61±0.05 63.05±0.02 40.89±0.04 22.77±0.03 23.44±0.03 27.38±0.04 28.05±0.04 37.94±0.04 23.33±0.01 16.27±0.032 44.05±0.03 70.11±0.14 63±2.64 C org (%) 6.21±0.02 5.08±0.05 4.26±0.03 4.5±0.15 0.92±0.03 3.88±0.03 3.12±0.02 1.89±0.03 0.89±0.03 0.89±0.03 5.55±0.01 7.54±0.02 4.17±0.03 TOM (%) 10.7±0.04 8.76±0.09 7.35±0.05 7.75±0.26 1.6±0.06 6.7±0.06 5.39±0.04 3.26±0.05 1.54±0.06 1.54±0.06 9.57±0.02 13.01±0.04 7.2±0.07 Carbohydrate (mg/g) 0.23±0.02 0.19±0.03 0.84±0.02 0.68±0.02 0.24±0.03 0.57±0.02 0.43±0.02 0.24±0.02 0.6±0.25 0.03±0.03 0.79±0.04 0.25±0.02 0.36±0.02 Protein (mg/g) 7.36±0.03 8.4±0.34 3.2±0.20 3.97±0.02 4.43±0.03 4.19±0.04 2.57±o.02 3.91±0.01 2.37±0.01 3.66±0.01 5.83±0.01 3.15±0.02 6.01±0.09 Lipid (mg/g) 1.02±0.02 0.33±0.01 0.6±0.15 1.22±0.01 1.37±0.02 0.03±0.02 0.12±0.04 0.51±0.01 0.03±0.02 0.02±0.02 0.56±0.02 0.78±0.02 0.92±0.02 LOM (%) 0.86±0.42 0.89±0.44 0.4±0.2 0.54±0.26 0.6±0.28 0.44±0.23 0.29±0.15 0.46±0.22 0.26±0.13 0.39±0.19 0.66±0.34 0.41±0.20 0.72±0.35 LOM of TOM (%) 8.05±0.56 10.24±0.55 5.49±0.20 6.99±0.38 37.76±4.90 6.65±0.23 5.43±0.05 14.29±0.88 17.08±0.99 25.38±1.10 6.92±0.01 3.2±0.32 9.99±0.66 BPC (mgCg 1 ) 4.46±0.04 4.44±0.04 2.35±0.03 3.13±0.02 3.29±0.06 2.3±0.06 1.52±0.04 2.39±0.02 1.42±0.05 1.82±0.04 3.59±0.02 2.23±0.02 3.78±0.03 Protein:Carbohydrate 32±2.67 44.21±5.23 3.81±0.15 5.84±0.14 18.46±2.19 7.35±0.25 5.98±0.29 16.29±1.30 3.95±1.63 122±163 7.38±0.44 12.6±1.57 16.69±0.66 Lipid:Carbohydrate 4.43±0.44 1.74±0.19 0.71±0.16 1.79±0.03 5.71±0.61 0.05±0.04 0.28±0.07 2.13±0.11 0.05±0.02 0.67±0.69 0.71±0.02 3.12±0.31 2.56±0.07 January 2017 Environmental variables S 1 S 2 S 3 S 4 S 5 S 6 S 7 S 8 S 9 S 10 S 11 S 12 S 13 Temperature (°C) 28±0.30 29±0.30 29±0.20 26±0.51 27±0.41 28±0.55 30±0.52 29±0.40 28±0.30 28±0.43 28±0.17 29±0.34 28±0.37 pH 8.62±0.03 8.37±0.03 8.2±0.12 8.13±0.04 7.77±0.02 8.39±0.04 8.37±0.02 8.18±0.03 8.49±0.03 8.07±0.04 8.21±0.01 8.41±0.03 8.42±0.01 EC (µs/cm) 6.25±0.03 6.3±0.29 8.04±0.02 7.8±0.32 6.48±0.01 6.38±0.02 6.27±0.01 6.21±0.04 6.34±0.02 6.25±0.02 6.34±0.01 6.27±0.03 6.14±0.03 Salinity (ppt) 25.8±0.2 26.3±0.15 26±0.25 19.1±0.32 24±0.35 26.3±0.30 27±0.25 28.3±0.20 27±0.37 26.7±0.25 28.6±0.26 29.1±0.39 26.4±0.1 Redox potential (mv) -393±3.05 -291±5.00 -234±3.51 -301±2.00 -262±2.51 -209±2.08 -277±3.60 -302±2.51 -229±4.16 -234±1.52 -289±2.51 -175±2.51 -391±2.51 Sulphate (mg/g) 58.27±0.02 37.72±0.02 14±0.20 15.66±0.02 19.27±0.04 33.72±0.02 20.05±0.03 25.55±0.03 8.55±0.03 17.77±0.02 34.16±0.03 4.44±0.02 38.05±0.02 C org (%) 3.37±0.02 0.9±0.05 0.52±0.03 1.35±0.03 0.37±0.01 0.3±0.17 0.07±0.02 0.6±0.15 0.3±0.11 0.97±0.02 2.17±0.03 5.02±0.03 2.85±0.02 TOM (%) 5.82±0.03 1.55±0.09 0.9±0.06 2.33±0.06 0.64±0.02 0.52±0.29 0.12±0.03 1.03±0.36 0.52±0.20 1.67±0.03 3.75±0.05 8.66±0.05 4.91±0.04 Carbohydrate (mg/g) 0.18±0.01 0.15±0.03 0.94±0.01 0.05±0.01 0.71±0.03 0.73±0.03 0.57±0.02 0.92±0.03 0.23±0.02 0.01±0.01 0.37±0.02 0.17±0.02 0.35±0.02 Protein (mg/g) 3.07±0.02 1.47±0.03 1.24±0.02 1.38±0.01 0.77±0.01 1.44±0.02 0.88±0.02 1.05±0.02 1.32±0.03 0.31±0.02 2.44±0.02 4.51±0.02 3.64±0.03 Lipid (mg/g) 0.96±0.02 1.31±0.02 0.74±0.02 1.08±0.02 1.23±0.02 0.45±0.02 0.27±0.02 0.56±0.03 0.51±0.01 0.71±0.02 0.15±0.02 0.91±0.03 1.43±0.02 LOM (%) 0.42±0.05 0.29±0.07 0.29±0.04 0.25±0.06 0.27±0.07 0.26±0.02 0.17±0.01 0.25±0.03 0.2±0.03 0.1±0.04 0.29±0.01 0.55±0.05 0.54±0.08 LOM of TOM (%) 7.24±0.94 18.97±4.4 32.46±3.61 10.87±2.56 42.03±10.42 50.49±12.48 13.42±76.25 24.51±2.98 39.4±7.46 6.02±2.43 7.92±0.16 6.45±0.60 11.05±1.67 BPC (mgCg 1 ) 2.3±0.3 1.76±0.03 1.54±0.02 1.51±0.01 1.58±0.03 1.34±0.02 0.86±0.02 1.3±0.25 1.12±0.01 0.69±0.01 1.46±0.02 2.96±0.02 3±0.01 Protein:Carbohydrate 17.06±1.44 9.8±2.20 1.32±0.001 27.6±7.08 1.08±0.03 1.97±0.04 1.54±0.02 1.14±0.01 5.74±0.44 31±10.78 6.59±0.30 26.53±4.17 10.4±0.67 Lipid:Carbohydrate 5.33±0.35 8.73±2.04 0.79±0.01 21.6±5.35 1.73±0.05 0.62±0.01 0.47±0.01 0.61±0.01 2.22±0.16 71±26.46 0.41±0.04 5.35±0.70 4.09±0.23 Table 2. Two-way ANOVA on environmental variables of Ashtamudi estuary Season Station Season * Station Variables F ratio P value F ratio P value F ratio P value Carbohydrate .013 .910 12.953** .000 7.545** .000 Protein 1307.239** .000 83.884** .000 48.461** .000 Lipid 14.492** .000 15.233** .000 3.638* .001 LOM 310.832** .000 29.960** .000 12.722** .000 C org 90.779** .000 15.958** .000 2.679* .007 TOM 90.779** .000 15.958** .000 2.679* .007 LOM of TOM 200.676** .000 69.189** .000 71.196** .000 Sulphate 1333.328** .000 697.103** .000 84.337** .000 pH 9.769* .003 .499 .906 .413 .952 Temperature 4.318* .043 2.268* .021 3.733** .000 Conductivity 1245.138** .000 3.085 .002 5.463** .000 ORP 4.832* .032 9.204** .000 30.056** .000 salinity 15.091** .000 .050 1.000 .045 1.000 Substrate induced enzyme activity (Mesophilic) 1.836 .181 1.966* .047 2.178* .027 Substrate induced enzyme activity (Thermophilic) .762 .387 2.165* .028 1.034 .434 Native enzyme activity 165.349** .000 31.944** .000 32.167** .000 BPC 67764.499** .000 8799.901** .000 3014.457** .000 Protein: carbohydrate 27.555** .000 16.801** .000 9.381** .000 Lipid: Carbohydrate 8.232* .006 3.759** .000 4.064** .000 ** P<0.001; *P<0.05 Table 3. Factor loadings for various environmental variables Rotated Component Matrix a Components PC1 PC2 PC3 April 2016 Temperature .181 .739 -.069 pH .511 .203 .182 EC .754 -.241 .172 Salinity .462 -.546 -.031 Redoxpotential .111 .072 .408 Sulphate .828 .230 .213 Corg .938 .178 -.097 TOM .938 .177 -.098 Carbohydrate .161 -.005 -.757 Protein .520 .325 .708 Lipid .091 .941 -.056 LOM .493 .514 .633 BPC .501 .600 .525 Protein:carbohydrate -.292 -.273 .743 Lipid:carbohydrate -.025 .829 .299 Eigen value 5.125 3.525 2.829 % of Variance 32.029 22.034 17.682 Cumulative % 32.029 54.063 71.744 January 2017 Temperature -.050 -.217 .811 pH .458 .070 .500 EC -.144 -.098 -.591 Salinity .056 -.071 .938 Redoxpotential -.544 .057 .278 Sulphate .490 -.149 -.016 Corg .750 .554 .239 TOM .750 .554 .239 Carbohydrate -.121 -.859 .102 Protein .870 .283 .301 Lipid .534 .167 -.569 LOM .948 .099 .123 BPC .946 .156 .034 Protein:Carbohydrate .068 .962 -.183 Lipid:Carbohydrate -.478 .740 -.190 Eigen value 5.060 3.615 2.862 % of Variance 31.627 22.592 17.890 Cumulative % 31.627 54.219 72.109 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 29 Nov, 2021 Reviewers invited by journal 25 Nov, 2021 Editor invited by journal 30 Jul, 2021 Editor assigned by journal 30 Jul, 2021 First submitted to journal 27 Jul, 2021 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-757184","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":59456030,"identity":"68842046-5fb3-42ce-9006-8d814c70d938","order_by":0,"name":"Dennison Bindhulekha Arya","email":"","orcid":"","institution":"University of Kerala","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dennison","middleName":"Bindhulekha","lastName":"Arya","suffix":""},{"id":59456031,"identity":"b91828b6-b82f-4bec-8626-9c55cb458f2e","order_by":1,"name":"Salom Gnana Thanga Vincent","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-1816-3532","institution":"University of Kerala","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Salom","middleName":"Gnana Thanga","lastName":"Vincent","suffix":""},{"id":59456032,"identity":"8061f1f2-4959-4f54-b934-5703c9502a3d","order_by":2,"name":"J.K Reshma","email":"","orcid":"","institution":"All Saints' College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"J.K","middleName":"","lastName":"Reshma","suffix":""},{"id":59456033,"identity":"109886d4-7619-4df3-9868-b9ddabdb4dbf","order_by":3,"name":"Junaid Hassan Salahudeen","email":"","orcid":"","institution":"University of Kerala","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junaid","middleName":"Hassan","lastName":"Salahudeen","suffix":""}],"badges":[],"createdAt":"2021-07-28 01:44:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-757184/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-757184/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":15109713,"identity":"1b9f4443-e4c6-4e3b-b6cb-2f55f3c84b56","added_by":"auto","created_at":"2021-11-01 19:24:25","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":199060,"visible":true,"origin":"","legend":"Ashtamudi estuary, located between 76◦32’ and 76◦41’E Longitude and 8◦52’ and 9◦2’ N latitude (Fig. 1) is the second-largest estuarine system having a surface area of 32 km2 and gains international importance as a Ramsar site.","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-757184/v1/084e710cdd40095bfd913288.jpg"},{"id":15109710,"identity":"193a465c-8d86-4a54-9ea8-409f19c6de0f","added_by":"auto","created_at":"2021-11-01 19:24:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1050518,"visible":true,"origin":"","legend":"During April 2016, native enzyme activity (NEA) was predominant in the open estuary (Fig. 2).","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-757184/v1/50711130081cd9eaca45a8d0.jpg"},{"id":15109814,"identity":"fb9bdc29-f8c8-4807-8ad0-1b031aebb651","added_by":"auto","created_at":"2021-11-01 19:27:25","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1238925,"visible":true,"origin":"","legend":"In this study, the cumulative substrate induced enzyme activity (SIEA) (Fig. 3) was more than NEA","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-757184/v1/9b2983711c79ce04fcbc01e7.jpg"},{"id":15109711,"identity":"30dd1621-19f3-4710-b98a-21733340a836","added_by":"auto","created_at":"2021-11-01 19:24:25","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1213589,"visible":true,"origin":"","legend":"In this study, the cumulative substrate induced enzyme activity (SIEA) (Fig. 4) was more than NEA","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-757184/v1/36be9c615c5b1fcec5950633.jpg"},{"id":15109815,"identity":"615175e5-e65e-4d93-9e31-826c2bc48bc0","added_by":"auto","created_at":"2021-11-01 19:27:25","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":53426,"visible":true,"origin":"","legend":"The relationship between environmental variables and cellulolytic activity were analysed using principal component analysis (PCA) and redundancy analysis (RDA). The PCA generated three principal components (Table 3, Fig.5).","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-757184/v1/36e985e73023226630609374.jpg"},{"id":15109708,"identity":"5ebf3563-1368-460e-b653-f2af67be6361","added_by":"auto","created_at":"2021-11-01 19:24:25","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":59843,"visible":true,"origin":"","legend":"During April 2016, RDA output showed that lipid followed by salinity, protein and Corg (explanatory variables) were the highest determining factors for explaining most of the variation in the abundance and activity of cellulolytic anaerobes (response variables) (Fig. 6). ","description":"","filename":"fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-757184/v1/a85498c072c0410eca0c01ab.jpg"},{"id":15109816,"identity":"970b4d22-3921-4a7a-b7f2-b86480aa2c0f","added_by":"auto","created_at":"2021-11-01 19:27:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":794847,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-757184/v1/0acdf56a-1830-4472-b6ff-4229623833f1.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eOrganic Matter And Anaerobic Cellulolytic Activity In Sediments of Ashtamudi Estuary, Kerala, India\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEstuaries are considered to be an important link between land and the sea and function as natural sinks of organic matter that comes from marine, terrestrial and anthropogenic sources. Most of the organic matter in sediments is dominated by cellulose due to the plant derived sources (Cowie and Hedges \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Bacic et al \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).The organic carbon rich sediments of estuaries harbour abundant cellulolytic bacteria which have considerable influence on the carbon cycle in both aerobic and anaerobic environments. The structure and function of microbial communities in the estuarine sediment depend upon the human input of soluble and insoluble particulate form of organic matter (Babu et al \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The soluble form of organic matter is contributed by carbohydrate, protein, lipid and other biological compounds which can be easily metabolized (He et al \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Studies indicate that carbohydrate accounts for ~\u0026thinsp;3\u0026ndash;10% of total sedimentary organic matter (Skoog and Benner \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Bergamaschi et al \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Burdige et al \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Kerherv\u0026eacute; et al \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) whereas, protein is an important biochemical compound which can be easily utilized by bacteria than other biochemical compounds (Newell and Field \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1983\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDeposition of labile and refractory organic matter from the water column provides energy and nutrients for microbes inhabiting coastal sediments (Middelburg and Levin \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). A major part of the organic matter consists of plant structural polymers referred as lignocelluloses and these polymers need to be hydrolyzed by extracellular enzymes before it is taken by microbes (Billen \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; King \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). These enzymes play an important role in organic matter degradation in natural ecosystems (Boschker and Cappenberg \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In anaerobic environment, cellulolytic bacteria hydrolyze organic polymers to monomers through fermentation; the monomers are further degraded by secondary fermenters such as methanogens (Zinder \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1993\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the global carbon cycle, enzymatic degradation of cellulose by microorganism is a key process (Malhi \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Wilson \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Especially, extracellular enzymes such as cellulase have an important role in organic matter decomposition in the sediments, which depends upon the quantity and quality of organic matter (Meyer-Reil \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Boetius and Lochte \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Enzymatic conversion of lignocellulosic material is important because of their insolubility in water (Behera et al \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The cellulose degradation occurs by the hydrolysis of β 1\u0026ndash;4 glycosidic bonds, which needs the concerted action of three enzymes such as endoglucanase, exoglucanase and β- glucosidase (J\u0026oslash;rgensen et al \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These enzymes acts synergistically: endoglucanases hydrolyze the exposed cellulose chains of the cellulose polymer; exoglucanases (cellobiohydrolases) act to release cellobiose from the reducing and nonreducing ends, and \u003cem\u003eβ\u003c/em\u003e-glucosidases help to cleave the cellobiose and short-chain cello-oligosaccharide into glucose (Chandra and Madakka \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, in anaerobic cellulolytic bacteria a \u0026ldquo;cellulosome\u0026rdquo; consisting of cellulose binding proteins and hydrolytic enzymes are responsible for cellulolysis (Doi et al \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). A high molecular weight protein (\u0026gt;\u0026thinsp;2 MDa) was reported in cellobiose grown anaerobic cellulolytic bacteria such as \u003cem\u003eClostridium\u003c/em\u003e sp., \u003cem\u003eAcetivibrio\u003c/em\u003e sp. and \u003cem\u003eBacteroides\u003c/em\u003e sp. that could bind to filter paper cellulose (Vincent and Ramasamy 2001). Ultimately, cellulolytic microorganisms degrade cellulose into simple sugar derivatives (Tengerdy and Szakacs \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Because of the complexity and high molecular weight of cellulose, it needs the action of various enzymes for degradation which is associated with various environmental conditions such as temperature, pressure and salinity (Taketani et al \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe cellulolytic microbes and their enzymes receive much attention due to their diverse applications in several industries such as textile, food, paper and pulp, beer and wine brewing, fuel and chemical industries (Gao et al \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Behera et al \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). A study conducted by Odisi et al. (Odisi et al \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) on five different strains of bacteria revealed the potential of cellulase enzyme activity in both mesophilic and thermophilic conditions. Isolation of cellulose degrading bacterial strains were well documented from various coastal habitats such as salt marshes on Sapelo island, Ga (Benner et al \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1984\u003c/span\u003e), Sundarbans mangrove of West Bengal, India (Ramanathan et al \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), mangrove soil of Bhitarkanka, Odisha, India (Thatoi et al \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), Philippine\u0026rsquo;s mangrove (Tabao and Monsalud \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), Uppanar estuary, India (Kalaiselvi et al \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and mangrove soil of Mahanadi river delta, Odisha, India (Behera et al \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Tropical estuaries receives multiple input of organic matter from allochthonous and autochthonous source. The increased microbial activities on organic matter mineralization leads to the depletion of oxygen and cause the prevalence of anoxic conditions and further leads to anaerobic metabolic activities. In Ashtamudi Estuary, the predominant anaerobic microbial activity was previously related to sulphate reduction, although denitrification and methanogenesis also occurred in the sediments (Vincent et al \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Hence, this study was done to explore the hydrolytic activity of Ashtamudi estuarine sediment by analysing the abundance and activity of anaerobic cellulolytic bacteria and also to investigate the environmental factors influencing the spatio-temporal variations in native and substrate-induced cellulolytic activity.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003eStudy area and Relevance\u003c/p\u003e \u003cp\u003eAshtamudi estuary, located between 76\u003csup\u003e◦\u003c/sup\u003e32\u0026rsquo; and 76\u003csup\u003e◦\u003c/sup\u003e41\u0026rsquo;E Longitude and 8\u003csup\u003e◦\u003c/sup\u003e52\u0026rsquo; and 9\u003csup\u003e◦\u003c/sup\u003e2\u0026rsquo; N latitude (Fig.\u0026nbsp;1) is the second-largest estuarine system having a surface area of 32 km\u003csup\u003e2\u003c/sup\u003e and gains international importance as a Ramsar site. It is a palm shaped estuarine system and opens into Neendakara, which is one of the most important fishing harbours of India. Kollam city is located in the southern side of the estuary, and it receives freshwater input from Kallada river (on the eastern side) with a length of 120 km with basin area of 1,699 km\u003csup\u003e2\u003c/sup\u003e and an annual average discharge of 3,375 Mm\u003csup\u003e3\u003c/sup\u003e. Ashtamudi estuary receives organic matter from non-point and point sources such as urban and agricultural runoff, tourism, waste and sewage disposal, discharge from coconut husk industries, clay factory and fish processing industries(Babu et al \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and also a huge amount of organic matter is transported by Kallada river (Jennerjahn et al \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Based on the geography, the entire Ashtamudi estuary can be subdivided into three categories- the northeast Kallada River joining portion and finger like portion as Kallada section(S1-S5), the middle portion as open estuary having marine influence(S6-S10) and southern tip as Kollam section (S11- S13) (Jennerjahn et al \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The anthropogenic pressure on the sampling stations were: S1- influence of clay factory, S4- confluence of Kallada River and also owing pressure of direct sewage disposal from the population inhabiting in the river catchments, S8- The sediments dredged for widening or national waterways were dumped, S10- Fishing harbour and hydrocarbon discharges from the fishing boats, S11- Solid waste plant of Kollam city, S12 \u0026ndash; Presence of coir retting industries (Reshmi et al \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSample collection and preparation\u003c/p\u003e \u003cp\u003eSediment samples were collected from thirteen stations of Ashtamudi estuary using Van Veen\u0026rsquo;s grab sampler during April 2016 and January 2017. The samples for microbial analysis were transferred to sterile airtight bottles and brought to lab and kept under 4\u0026deg;C. The remaining sediment samples were collected in polythene bags for physicochemical analysis.\u003c/p\u003e \u003cp\u003eEnvironmental variables of sediment\u003c/p\u003e \u003cp\u003eThe environmental variables of estuarine sediments [temperature, pH, electrical conductivity (EC), oxidation- reduction potential (ORP), sulphate, total organic carbon (C\u003csub\u003eorg\u003c/sub\u003e), carbohydrate, protein, lipid and labile organic matter (LOM)] were analysed using standard procedures (Lowry et al \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1951\u003c/span\u003e; Dubois et al \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1956\u003c/span\u003e; Parsons et al \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Trivedy et al \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Grasshoff et al \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Lipid, carbohydrate and protein were converted into carbon equivalents using 0.75, 0.40 and 0.49 \u0026micro;gC\u0026micro;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e conversion factors, respectively (Fabiano and Pusceddu \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The biopolymeric carbon fraction (BPC) was calculated by taking the sum of lipid, carbohydrate and protein (Fabiano et al \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The protein: carbohydrate and lipid: carbohydrate ratios were calculated to determine the quality of sedimentary organic matter (Pusceddu et al \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAbundance of cellulolytic anaerobes\u003c/p\u003e \u003cp\u003eThe sediment samples were enriched in pre-reduced Hungate\u0026rsquo;s mineral broth containing (gL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) Potassium dihydrogen phosphate (0.2); Di-potassium hydrogen phosphate (0.3); Magnesium sulphate (0.1); Calcium chloride (0.1); Sodium chloride (1.0); Ammonium sulphate (1.0); Cysteine HCl (0.2); Sodium bicarbonate (0.2); Resazurin (0.001). Vitamin solution (Wolin et al \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1963\u003c/span\u003e) and trace element solution (Ferguson and Mah \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) were added to final concentration of 1%(V/V). Crystalline cellulose (0.2%) and cellobiose (0.2%) were the two substrates used in this study as insoluble and soluble substrate respectively. Cellulolytic anaerobes were enumerated by the roll tube method (modified method of Hungate (Ramasamy et al \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). Growth of cellulolytic anaerobes observed as cleared zones or colonies in the roll tube, were counted and expressed as colony forming units per gram of sediments (CFUg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eAssay of native and substrate induced enzyme activities\u003c/p\u003e \u003cp\u003eFor native enzyme assay, 2.0 g sediment was incubated with 0.7% carboxy methyl cellulose in acetate buffer (pH-5.5) at 50\u003csup\u003eo\u003c/sup\u003ec for 24 hours. For substrate induced enzyme assay, 10 mL of pre-reduced Hungate\u0026rsquo;s mineral broth was dispensed to screw capped vials (40 mL) sealed with butyl rubber stopper and aluminium cap assembly. Crystalline cellulose (1.0%) was added as the substrate and to maintain anaerobic conditions, the vials were flushed with high purity nitrogen gas. 2.0 g sediment samples were transferred to the vials and incubated for 10 days. Two sets of the vials for the sediment samples were prepared and each set were maintained in mesophilic and thermophilic conditions separately. After the incubation period, 1.0 mL of supernatant was incubated with 0.7% carboxy methyl cellulose in acetate buffer (pH-5.5) at 50\u003csup\u003eo\u003c/sup\u003ec for 24 hours. The amount of reducing sugar was analyzed by the dinitrosalicyclic acid method (Miller \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1959\u003c/span\u003e). Enzyme activity was expressed in terms of milligram of glucose released per hour (Schinner and Von Mersi \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1990\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTwo-way analysis of variance (two-way ANOVA) and principal component analysis (PCA) were conducted to test for significant spatial and temporal differences in the variables and also study the influence of environmental parameters on the activity of cellulolytic anaerobes. Redundancy Analysis (RDA) analysis is a method to extract and summarize the variation in a set of response variables that can be explained by a set of explanatory variables. RDA reveals the relationship between environmental parameters and activity of enzyme and bacterial abundance. All statistical analyses were performed using SPSS 20.0 and R studio.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results And Discussion","content":"\u003cp\u003eSpatio- temporal variation of environmental variables\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe changes in environmental variables of Ashtamudi estuarine sediments is summarized in Table 1.0. The overall sediment temperature was higher during April 2016 than January 2017. The spatial variation of sediment temperature was statistically insignificant along the estuary whereas the temporal variation was significant (p=0.001) (Table 2). Previous study by Reshmi et al. (Reshmi et al 2015) in Ashtamudi estuarine sediment also points out similar results. During both sampling periods, Ashtamudi estuary exhibited brackish to marine conditions with regard to pH and salinity values (Jennerjahn et al 2008). \u0026nbsp; Alkaline pH was observed all over the estuary during the sampling seasons with an average value of 7.97 and 8.26. However, the spatial variation of salinity was statistically significant (p\u0026lt;0.001) and temporal variation was insignificant. Ashtamudi estuary opens to the Arabian sea through a wide opening which obviously shows a marine influence all over the estuary (Vincent et al 2017). Maximum electrical conductivity was observed in the Kollam city part of the estuary during April 2016 and Kallada River part of the estuary during January 2017, which indicates the influence of dissolved nutrient load from the Kallada River (Jennerjahn et al 2008) during the post-monsoon season.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"isPasted\"\u003eSpatio- temporal variation and source of organic matter\u003c/p\u003e\n\u003cp\u003eThe quality and quantity of organic matter can regulate the composition and activity of microbial communities in aquatic sediments\u0026nbsp;(Torres et al 2011; Cawley et al 2012). Particularly, the lignocellulosic biomass forms the substrate for cellulolytic anaerobes in the anaerobic sediment. Hence, it is important to analyze the quality and quantity of organic matter in the sediment. Significant spatial variations (p \u0026lt; 0.001) in the C\u003csub\u003eorg\u003c/sub\u003e values were observed, whereas the temporal variations were statistically insignificant in the Ashtamudi estuary. In both seasons, average C\u003csub\u003eorg\u0026nbsp;\u003c/sub\u003evalues was higher in Kollam city part as compared to the marine and river influenced part of the estuary. The sampling station S12 in the Kollam city region showed higher values during both seasons. Previous studies\u0026nbsp;(Jennerjahn et al 2008; Vincent et al 2017)\u0026nbsp;also showed the dominance of C\u003csub\u003eorg\u003c/sub\u003e in the Kollam city region. Lowest C\u003csub\u003eorg\u0026nbsp;\u003c/sub\u003evalues were observed in the open estuary portion particularly S9 and S10. That is related to the flushing of sea water to the open estuary during the tidal cycles and high rate of microbial degradative activities\u0026nbsp;(Jonathan et al 2004; Hussain et al 2020). Stable isotopic\u0026nbsp;\u0026delta;13 C\u003csub\u003eorg\u0026nbsp;\u003c/sub\u003estudy by Jennerjahn et al.\u0026nbsp;(Jennerjahn et al 2008)\u0026nbsp;points out the different source and diagenesis of organic matter, in which open estuary had highest value of\u0026nbsp;\u0026delta;13 C\u003csub\u003eorg\u0026nbsp;\u003c/sub\u003eindicating the presence of marine derived organic matter\u0026nbsp;(Thimdee et al 2003)\u0026nbsp;and lowest value of \u0026delta;13 C\u003csub\u003eorg\u0026nbsp;\u003c/sub\u003ein the upper part, which\u003csub\u003e\u0026nbsp;\u003c/sub\u003eis attributed to the presence of river derived organic matter. LOM and BPC values showed significant spatio- temporal variations (p\u0026lt;0.001). The higher LOM and BPC values were observed in Kallada River region during April 2016 and in Kollam city region of the estuary during January 2017.\u0026nbsp;The LOM to TOM value can be used as an index of organic matter lability\u0026nbsp;(Gonsalves et al 2011). In Ashtamudi estuarine sediments, higher LOM of TOM values were observed during January 2017 (21.82%) than during April 2016 (13.22%), which indicates that the organic matter was more labile during January 2017. LOM was dominated by protein followed by lipid and carbohydrate for both seasons. Similar result was observed in Kerala coast\u0026nbsp;(Nair and Sujatha 2012), Galician coast\u0026nbsp;(Cividanes et al 2002)\u0026nbsp;and Ross sea, Antarctica\u0026nbsp;(Fabiano et al 1995). Low carbohydrate values were also observed in cochin estuary\u0026nbsp;(Joseph et al 2008)\u0026nbsp;of Kerala. High protein concentration in the sediment is due to allochthonous inputs\u0026nbsp;(Danovaro 1996)\u0026nbsp;of organic matter. Usually, proteins can be readily utilized by the bacteria than carbohydrate\u0026nbsp;(Newell and Field 1983)\u0026nbsp;and the dominance of protein concentration indicates the presence of fresh organic matter. Contrastingly, high values of lipid were reported from decayed organism\u0026nbsp;(Danovaro et al 1993). Nevertheless, carbohydrates are important fraction of C\u003csub\u003eorg\u003c/sub\u003e contributed by living organisms\u0026nbsp;(B\u0026oslash;rsheim et al 1999; Burdige et al 2000; Bacic et al 2012)\u0026nbsp;and low carbohydrate values show the refractory nature of organic matter\u0026nbsp;(Danovaro et al 1993). Protein: carbohydrate ratio was observed to be higher in Kallada River region during April 2016 and in Kollam region during January 2017. The high protein to carbohydrate ratio also indicates that the organic matter is fresh and recently generated\u0026nbsp;(Danovaro et al 1993; Fabiano and Pusceddu 1998; Joseph et al 2008; Joy et al 2019), whereas higher lipid carbohydrate ratio was observed in the open estuary during both seasons.\u003c/p\u003e\n\u003cp\u003eAbundance and distribution of cellulolytic anaerobes\u003c/p\u003e\n\u003cp\u003eThe abundance of cellulolytic anaerobes was comparatively higher during January 2017 than April 2016 (Table 3). During both seasons, maximum cellulolytic population was observed with cellobiose and limited or slow growth with crystalline cellulose as substrate, \u0026nbsp;which is attributed to the insolubility nature of crystalline cellulose\u0026nbsp;(Leschine 1995). In S7 (open estuary) maximum growth was observed in April 2016 and S8 (open estuary) in January 2017 for cellobiose substrate. In case of crystalline cellulose substrate, S12 (Kollam city region) showed maximum growth in April 2016 and S9 in January 2017. The cellulolytic population of cellulolytic anaerobes were very low in Ashtamudi estuary as compared to the populations of other group of obligate anaerobes like methanogens and sulphate reducing bacteria\u0026nbsp;(Reshmi et al 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCellulolytic enzyme activity\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;In natural lake sediments, most of the cellulose degradation occurs aerobically and only 5-10 % is available for anaerobic degradation\u0026nbsp;(Leschine 1995). During April 2016, native enzyme activity (NEA) was predominant in the open estuary (Fig. 2). Whereas, during January 2017, NEA was more pronounced in the Kallada River region, that might be due the confluence of Kallada river and the availability of fresh organic load from the river as native substrate. In this study, the cumulative substrate induced enzyme activity (SIEA) (Fig. 3 \u0026amp; 4) was more than NEA. This reveals the potential of added substrates to induce cellulosic activity. Previous studies in Lake Gooimeer also showed increased activity of \u0026beta; \u0026ndash;glucosidase by addition of cellulose\u0026nbsp;(Boschker and Cappenberg 2006). During April 2016, thermophilic activity was predominant in the Kallada River region, whereas mesophilic enzyme activity was higher in the Kallada River and Kollam city region of the estuary. During January 2017, thermophilic cellulase activity predominated in the open estuary and mesophilic enzyme activity in the Kollam city and Kallada River regions. Overall cellulolytic activity was higher towards Kallada River region of the estuary.\u0026nbsp;Biogeochemical analysis of Ashtamudi estuarine sediment by Jennerjahn et al.\u0026nbsp;(Jennerjahn et al 2008)\u0026nbsp;revealed that, most of the Kallada River load is deposited in the upper part of the estuary and middle and lower parts are subjected to strong marine influence.\u0026nbsp;\u0026nbsp;So, it is evident that the riverine dissolved organic load contains sufficient amount of labile fraction, that can be easily consumed by the microbial communities\u0026nbsp;(Abril et al 2002).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEnvironmental controls on abundance and activity of cellulolytic anaerobe\u003c/p\u003e\n\u003cp\u003eThe relationship between environmental variables and cellulolytic activity were analysed using principal component analysis (PCA) and redundancy analysis (RDA). The PCA generated three principal components (Table 3, Fig.5). During April 2016, the first PC accounted for 32.02% of total variance. Whereas PC2 and PC3 explained 22.03 and 17.68 of total variance respectively and also explained a cumulative variance of 71.74%. In the first PC, EC, sulphate C\u003csub\u003eorg\u003c/sub\u003e and TOM showed strong positive loadings and the factors were collectively referred as conductivity- nutrient factor. In PC 2 lipid:carbohydrate ratio showed strong positive loading and in PC3 carbohydrate showed strong negative loadings.\u003c/p\u003e\n\u003cp\u003eDuring January 2017, the first PC accounted for 31.62% of total variance. Whereas PC2 and PC3 explained 22.59 and 17.89 of total variance respectively and also showed a cumulative variance of 71.74%. In the first PC, C\u003csub\u003eorg\u003c/sub\u003e, TOM, protein, LOM and BPC showed strong positive loadings and was referred as nutrient factor. The composition of organic matter can influence extra cellular enzyme activities in lake sediments (Boschker and Cappenberg 2006). The second PC exhibited strong positive loading on protein:carbohydrate ratio and had a negative loading on carbohydrate. The third PC showed high positive loading on temperature and salinity. Hence, the factor was named as temperature- salinity factor.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring April 2016, RDA output showed that lipid followed by salinity, protein and C\u003csub\u003eorg\u0026nbsp;\u003c/sub\u003e(explanatory variables)\u003csub\u003e\u0026nbsp;\u003c/sub\u003ewere the highest determining factors for explaining most of the variation in the abundance and activity of cellulolytic anaerobes (response variables) (Fig. 6). \u0026nbsp;During January 2017, salinity followed by sulphate and organic matter were the highest determining factors. Energetic requirements of bacteria are associated with higher salinity and that can affect the abundance and activity of microbial groups (Gu et al 2012).\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eEstuarine ecosystems are an untapped resource for cellulosic biomass which provide opportunity for identifying novel microbial species that carry cellulase enzyme with novel biotechnological potential. Microbial cellulases are now commercially produced by several industries globally and are being widely used in food, animal feed, fuel, paper industry, textile industry and also various chemical industries. In the present work, even though, cellulolytic anaerobic abundance was found to be very low in Ashtamudi estuarine sediments, higher enzyme activity was observed in thermophilic conditions than mesophilic conditions. This clearly updates the evidence of tapping the enormous potential of thermophilic anaerobic cellulolytic bacteria for commercial and industrial applications. The substrate induced enzyme activity was more than native activity, which shows that addition of substrates induced the growth of cellulolytic anaerobe and enhanced their enzyme activities in the sediments. RDA revealed the importance of salinity and lipid with enzyme activity. To meet the growing demand for cellulases and to realize their full potential in biotechnology and research, continued research on bioprospecting cellulolytic microbes from potential sources such as estuarine sediments are vital. The development of rapid and reliable methods for the screening of cellulases from microorganisms within inhospitable environments like estuaries will allow a greater number of novel bacterial cellulases to be isolated with purpose for various applications in future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the University of Kerala for providing the facilities for conducting laboratory analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003eNot Applicable for this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u0026nbsp;\u003c/strong\u003eMost of the data produced from this study are provided in this manuscript and the remaining datasets used or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003eSGTV led the conceptualisation of this study and edited the MS; DBA conducted the laboratory analysis and wrote the first draft of the MS; \u0026nbsp;JKR edited the MS; JHS added valuable comments to the MS and created GIS maps; Field sampling was done by SGTV; DBA and JHS; All the mentioned authors also read the final MS and approved.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbril G, Nogueira M, Etcheber H et al (2002) Behaviour of organic carbon in nine contrasting European estuaries. Estuarine, Coastal and Shelf Science 54:241\u0026ndash;262. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1006/ecss.2001.0844\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBabu KN, Omana PK, Mohan M (2010) Water and sediment quality of Ashtamudi estuary, a Ramsar site, southwest coast of India-a statistical appraisal. Environ Monit Assess 165:307\u0026ndash;319. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10661-009-0947-0\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBacic A, Harris PJ, Stone BA (2012) Structure and function of plant cell walls. In: The Biochemistry of Plants: A Comprehensive Treatise. Elsevier Inc., pp\u0026nbsp;297\u0026ndash;371\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBehera BC, Mishra RR, Singh SK et al (2016) Cellulase from Bacillus licheniformis and Brucella sp. isolated from mangrove soils of Mahanadi river delta, Odisha, India. Biocatal Biotransform 34:44\u0026ndash;53. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10242422.2016.1212846\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBehera BC, Parida S, Dutta SK, Thatoi HN (2014) Isolation and Identification of Cellulose Degrading Bacteria from Mangrove Soil of Mahanadi River Delta and Their Cellulase Production Ability. American Journal of Microbiological Research 2:41\u0026ndash;46. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.12691/ajmr-2-1-6\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBehera BC, Sethi BK, Mishra RR et al (2017) Microbial cellulases \u0026ndash; Diversity \u0026amp; biotechnology with reference to mangrove environment: A review. Journal of Genetic Engineering Biotechnology 15:197\u0026ndash;210. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jgeb.2016.12.001\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenner R, Newell SY, Maccubbin AE, Hodson RE (1984) Relative contributions of bacteria and fungi to rates of degradation of lignocellulosic detritus in salt-marsh sediments. Appl Environ Microbiol 48:36\u0026ndash;40. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/aem.48.1.36-40.1984\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBergamaschi BA, Fram MS, Kendall C et al (1999) Carbon isotopic constraints on the contribution of plant material to the natural precursors of trihalomethanes. Org Geochem 30:835\u0026ndash;842. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0146-6380(99)00066-2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBillen G (1982) Modelling the processes of organic matter degradation and nutrients recycling in sedimentary systems. Sediment Microbiol\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoetius A, Lochte K (1996) Effect of organic enrichments on hydrolytic potentials and growth of bacteria in deep-sea sediments. Mar Ecol Prog Ser 140:239\u0026ndash;250. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3354/meps140239\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB\u0026oslash;rsheim KY, Myklestad SM, Sneli JA (1999) Monthly profiles of DOC, mono- and polysaccharides at two locations in the Trondheimsfjord (Norway) during two years. Mar Chem 63:255\u0026ndash;272. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0304-4203(98)00066-8\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoschker HT, Cappenberg T (2006) Patterns of extracellular enzyme activities in littoral sediments of Lake Gooimeer, The Netherlands. FEMS Microbiol Ecol 25:79\u0026ndash;86. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1574-6941.1998.tb00461.x\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurdige DJ, Skoog A, Gardner K (2000) Dissolved and particulate carbohydrates in contrasting marine sediments. Geochim Cosmochim Acta 64:1029\u0026ndash;1041. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0016-7037(99)00361-0\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCawley K, Wolski P, Mladenov N, Jaffe R (2012) Dissolved organic matter biogeochemistry along a transect of the Okavango Delta. Botswana Wetlands 32:475\u0026ndash;486. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s13157-012-0281-0\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChandra MRGS, Madakka M (2018) Comparative biochemistry and kinetics of microbial lignocellulolytic enzymes. Recent Developments in Applied Microbiology and Biochemistry. Elsevier, pp\u0026nbsp;147\u0026ndash;159\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCividanes S, Incera M, L\u0026oacute;pez J (2002) Temporal variability in the biochemical composition of sedimentary organic matter in an intertidal flat of the Galician coast (NW Spain). Oceanol Acta 25:1\u0026ndash;12. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0399-1784(01)01178-1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCowie GL, Hedges JI (1984) Carbohydrate sources in a coastal marine environment. Geochim Cosmochim Acta 48:2075\u0026ndash;2087. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0016-7037(84)90388-0\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDanovaro R (1996) Detritus-bacteria-meiofauna interactions in a seagrass bed (Posidonia oceanica) of the NW mediterranean. Mar Biol 127:1\u0026ndash;13. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/BF00993638\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDanovaro R, Fabiano M, Della Croce N (1993) Labile organic matter and microbial biomasses in deep-sea sediments (Eastern Mediterranean Sea). Deep-Sea Research Part I 40:953\u0026ndash;965. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0967-0637(93)90083-F\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoi RH, Goldstein M, Hashida S et al (1994) The clostridium cellulovorans cellulosome. Crit Rev Microbiol 20:87\u0026ndash;93. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/10408419409113548\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDubois M, Gilles KA, Hamilton JK et al (1956) Colorimetric Method for Determination of Sugars and Related Substances. Anal Chem 28:350\u0026ndash;356\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFabiano M, Danovaro R, Fraschetti S (1995) Temporal trend analysis of the elemental composition of the sediment organic matter in subtidal sandy sediments of the Ligurian Sea (NW Mediterranean): A three years study. Cont Shelf Res 15:1453\u0026ndash;1469\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFabiano M, Pusceddu A (1998) Total and hydrolizable particulate organic matter (carbohydrates, proteins and lipids) at a coastal station in Terra Nova Bay (Ross Sea, Antarctica). Polar Biol 19:125\u0026ndash;132. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s003000050223\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerguson TJ, Mah RA (1983) Isolation and characterization of an H2-oxidizing thermophilic methanogen. Appl Environ Microbiol 45:265\u0026ndash;274. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/aem.45.1.265-274.1983\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao J, Weng H, Zhu D et al (2008) Production and characterization of cellulolytic enzymes from the thermoacidophilic fungal Aspergillus terreus M11 under solid-state cultivation of corn stover. Biores Technol 99:7623\u0026ndash;7629. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.biortech.2008.02.005\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonsalves M-J, Fernandes CEG, Sheryl \u0026middot; et al (2011) Effects of composition of labile organic matter on biogenic production of methane in the coastal sediments of the Arabian Sea. Environ Monit Assess 182:385\u0026ndash;395. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10661-011-1883-3\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrasshoff K, Kremling K, Ehrhardt M (1999) Methods of Seawater Analysis, 3rd edn. Methods of Seawater Analysis: Third, Completely Revised and Extended Edition. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/9783527613984\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu C, Laverman AM, Pallud CE (2012) Environmental controls on nitrogen and sulfur cycles in surficial aquatic sediments. Front Microbiol 3:45. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmicb.2012.00045\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe B, Dai M, Huang W et al (2010) Sources and accumulation of organic carbon in the Pearl River Estuary surface sediment as indicated by elemental, stable carbon isotopic, and carbohydrate compositions. Biogeosciences 7:3343\u0026ndash;3362. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5194/bg-7-3343-2010\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHungate RE (1969) Chapter IV A Roll Tube Method for Cultivation of Strict Anaerobes. Methods in Microbiology 3:117\u0026ndash;132. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0580-9517(08)70503-8\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHussain SM, Anbalagan S, Kumar KS et al (2020) A baseline study on elemental concentration and potential ecological risk status of the surface sediments of Ashtamudi Lake, south west coast of India. Mar Pollut Bull 158:111410. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.marpolbul.2020.111410\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJennerjahn TC, Soman K, Ittekkot V et al (2008) Effect of land use on the biogeochemistry of dissolved nutrients and suspended and sedimentary organic matter in the tropical Kallada River and Ashtamudi estuary, Kerala, India. Biogeochemistry 90:29\u0026ndash;47. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10533-008-9228-1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJonathan MP, Ram-Mohan V, Srinivasalu S (2004) Geochemical variations of major and trace elements in recent sediments, off the Gulf of Mannar, the southeast coast of India. Environ Geol 45:466\u0026ndash;480. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00254-003-0898-7\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ\u0026oslash;rgensen H, Bach Kristensen J, Felby C (2007) Enzymatic conversion of lignocellulose into fermentable sugars: Challenges and opportunities. Biofuels Bioprod Biorefin 1:119\u0026ndash;134. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/bbb.4\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoseph MM, Kumar CSR, Gireesh Kumar TR et al (2008) Biogeochemistry of surficial sediments in the intertidal systems of a tropical environment Biogeochemistry of surficial sediments in the intertidal systems of a tropical environment. Chem Ecol 24:247\u0026ndash;258. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/02757540802119871\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoy A, Anoop P, Rajesh R et al (2019) Biochemical composition of sedimentary organic matter in the coral reefs of Lakshadweep Archipelago. Indian Ocean Chemistry Ecology 35:805\u0026ndash;824. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/02757540.2019.1665031\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalaiselvi V, Jayalakshmi S, Narayanan RL (2013) Biofuel production using marine microbes. Internationalnternational Journal of Current Microbiology Applied Sciences 2:67\u0026ndash;74\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKerherv\u0026eacute; P, Buscail R, Gadel F, Serve L (2002) Neutral monosaccharides in surface sediments of the Northwestern Mediterranean sea. Org Geochem 33:421\u0026ndash;435. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0146-6380(02)00003-7\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKing GM (1986) Characterization of β-Glucosidase Activity in Intertidal Marine Sediments. Appl Environ Microbiol 51:373\u0026ndash;380. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/aem.51.2.373-380.1986\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeschine SB (1995) Cellulose degradation in anaerobic environments. Annu Rev Microbiol 49:399\u0026ndash;426. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1146/annurev.mi.49.100195.002151\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLowry OH, Rosebrough NJ, Farr AL, Randall RJ (1951) Protein measurement with the Folin phenol reagent. J Biol Chem 193:265\u0026ndash;275\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalhi Y (2002) Carbon in the atmosphere and terrestrial biosphere in the 21st century. Philosophical Transactions of the Royal Society A: Mathematical Physical Engineering Sciences 360:2925\u0026ndash;2945. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1098/rsta.2002.1098\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeyer-Reil L-A (1987) Seasonal and Spatial Distribution of Extracellular Enzymatic Activities and Microbial Incorporation of Dissolved Organic Substrates in Marine Sediments. Appl Environ Microbiol 53:1748\u0026ndash;1755. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/aem.53.8.1748-1755.1987\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiddelburg JJ, Levin LA (2009) Coastal hypoxia and sediment biogeochemistry. Biogeosciences 6:1273\u0026ndash;1293\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller GL (1959) Use of Dinitrosalicylic Acid Reagent for Determination of Reducing Sugar. Anal Chem 31:426\u0026ndash;428. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1021/ac60147a030\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNair MP, Sujatha CH (2012) Biogeochemical quality assessment of the sediments in Kerala coast. International Journal of Environmental Sciences 3:707\u0026ndash;719. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.6088/ijes.20120301310699\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewell R, Field JG (1983) Relative flux of carbon and nitrogen in a kelp-dominated system. Marine Biology Letters 4:249\u0026ndash;257\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOdisi E, Silverstrin M, Takahashi R et al (2012) Bioprospection of cellulolytic and lipolytic South Atlantic deep-sea bacteria. Electron J Biotechnol 5:18\u0026ndash;18\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParsons TR, Takahashi M, Hargrave B (1984) Biological Oceanographic Processes, 3rd\u0026nbsp;edn. Pergamon Press\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePusceddu A, Dell\u0026rsquo;Anno A, Danovaro R et al (2003) Enzymatically hydrolyzable protein and carbohydrate sedimentary pools as indicators of the trophic state of detritus sink systems: A case study in a mediterranean coastal lagoon. Estuaries 26:641\u0026ndash;650. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/BF02711976\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamanathan AL, Singh G, Majumdar J et al (2008) A study of microbial diversity and its interaction with nutrients in the sediments of Sundarban mangroves\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamasamy K, Kalaichelvan G, Nagamani B (1992) Working with Anaerobes-Laboratory Manual. Fermentation Laboratory, Tamil Nadu Agrcultural University, Coimbatore\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReshmi RR, Nair KD, Zachariah EJ, Vincent SGT (2015) Methanogenesis: Seasonal changes in human impacted regions of Ashtamudi estuary (Kerala, South India. Estuar Coast Shelf Sci 156:144\u0026ndash;154\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchinner F, Von Mersi W (1990) Xylanase-, CM-cellulase-and invertase activity in soil: an improved method. soil Biology Biochemistry 22:511\u0026ndash;515\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkoog A, Benner R (1997) Aldoses in various size fractions of marine organic matter: Implications for carbon cycling. Limnol Oceanogr 42:1803\u0026ndash;1813. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4319/lo.1997.42.8.1803\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTabao NSC, Monsalud RG (2010) Characterization and identification of high cellulose producing bacterial strains from philippine mangroves. Philippine Journal of Systematic Biology 4:13\u0026ndash;20\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaketani RG, Yoshiura CA, Dias ACF et al (2010) Diversity and identification of methanogenic archaea and sulphate-reducing bacteria in sediments from a pristine tropical mangrove. Antonie van Leeuwenhoek. International Journal of General Molecular Microbiology 97:401\u0026ndash;411. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10482-010-9422-8\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTengerdy RP, Szakacs G (2003) Bioconversion of lignocellulose in solid substrate fermentation. Biochem Eng J 13:169\u0026ndash;179. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S1369-703X(02)00129-8\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThatoi H, Behera B, Dangar T, Mishra R (2012) Microbial biodiversity in mangrove soils of Bhitarkanika, Odisha, India. International Journal of Environmental Biology 2:50\u0026ndash;58\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThimdee W, Deein G, Sangrungruang C et al (2003) Sources and fate of organic matter in Khung Krabaen Bay (Thailand) as traced by δ 13 C and C/N atomic ratiosand C/N atomic ratios. Wetlands 23:729\u0026ndash;738\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorres IC, Inglett KS, Reddy KR (2011) Heterotrophic microbial activity in lake sediments: Effects of organic electron donors. Biogeochemistry 104:165\u0026ndash;181. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10533-010-9494-6\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrivedy RK, Goel PK, Trisal CL (1998) Practical Methods in Ecology and Environmental Science. Environmental Publications\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVincent SGT, Ramaswamy K (2001) Cellulose binding proteins of anaerobic bacteria: role in cellulolysis. Asian Journal of Microbiology Biotechnology Environmental Science 3:263\u0026ndash;268\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVincent SGT, Reshmi RR, Hassan SJ et al. Estuarine (2017) Predominant terminal electron accepting processes during organic matter degradation: Spatio-temporal changes in Ashtamudi estuary, Kerala, India. Coastal Shelf Science 198:508\u0026ndash;517. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/J.ECSS.2017.05.013\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilson DB (2011) Microbial diversity of cellulose hydrolysis. Curr Opin Microbiol 14:259\u0026ndash;263. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/J.MIB.2011.04.004\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolin EA, Wolin MJ, Wolfe R (1963) Formation of Methane by Bacterial Extracts*. The Journal of Biological Chemistry 238 8:2882\u0026ndash;2886. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0021-9258(18)67912-8\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZinder SH (1993) Physiological Ecology of Methanogens. Methanogenesis. Springer US, pp\u0026nbsp;128\u0026ndash;206\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Environmental variables of Ashtamudi estuary (April 2016 and January 2017)\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eApril 2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnvironmental variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemperature (\u0026deg;C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.00\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.15\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.95\u0026plusmn;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.11\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.91\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.95\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.97\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.8\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.85\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.99\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.88\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e8.13\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.96\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEC (\u0026micro;s/cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.32\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.23\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.75\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.00\u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.03\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.47\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.93\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.33\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.34\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.50\u0026plusmn;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.93\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.93\u0026plusmn;0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.24\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSalinity (ppt)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e24.2\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e27.00\u0026plusmn;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e25.70\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e21\u0026plusmn;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e22.5\u0026plusmn;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e25.8\u0026plusmn;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e26.4\u0026plusmn;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e25.9\u0026plusmn;0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e26.3\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e25.6\u0026plusmn;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e27.3\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e29.6\u0026plusmn;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e27.1\u0026plusmn;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRedox potential (mv)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-128\u0026plusmn;2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-188\u0026plusmn;4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-269\u0026plusmn;3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-251\u0026plusmn;4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-313\u0026plusmn;5.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-223\u0026plusmn;2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-298\u0026plusmn;3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-303\u0026plusmn;3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-204\u0026plusmn;4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-288\u0026plusmn;8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-300\u0026plusmn;8.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-415\u0026plusmn;3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-277\u0026plusmn;5.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSulphate (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e63.61\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e63.05\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e40.89\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e22.77\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e23.44\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e27.38\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e28.05\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e37.94\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e23.33\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e16.27\u0026plusmn;0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e44.05\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e70.11\u0026plusmn;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e63\u0026plusmn;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003csub\u003eorg\u003c/sub\u003e (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.21\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.08\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e4.26\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e4.5\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.92\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.88\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.12\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.89\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.89\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.89\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.55\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.54\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e4.17\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e10.7\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.76\u0026plusmn;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.35\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.75\u0026plusmn;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.7\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e5.39\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.26\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.54\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.54\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e9.57\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e13.01\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.2\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarbohydrate (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.23\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.19\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.84\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.68\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.24\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.57\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.43\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.24\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.6\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.03\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.79\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.25\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.36\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.36\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.4\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.2\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.97\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e4.43\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e4.19\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.57\u0026plusmn;o.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.91\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.37\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.66\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.83\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.15\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.01\u0026plusmn;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLipid (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.02\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.33\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.6\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.22\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.37\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.03\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.12\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.51\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.03\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.02\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.56\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.78\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.92\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.86\u0026plusmn;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.89\u0026plusmn;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.4\u0026plusmn;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.54\u0026plusmn;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.6\u0026plusmn;0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.44\u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.29\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.46\u0026plusmn;0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.26\u0026plusmn;0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.39\u0026plusmn;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.66\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.41\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.72\u0026plusmn;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOM of TOM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.05\u0026plusmn;0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e10.24\u0026plusmn;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.49\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.99\u0026plusmn;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e37.76\u0026plusmn;4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.65\u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e5.43\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e14.29\u0026plusmn;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e17.08\u0026plusmn;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e25.38\u0026plusmn;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.92\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.2\u0026plusmn;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e9.99\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBPC (mgCg\u003csup\u003e1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e4.46\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e4.44\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.35\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.13\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.29\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.3\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.52\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.39\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.42\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.82\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.59\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.23\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.78\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein:Carbohydrate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e32\u0026plusmn;2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e44.21\u0026plusmn;5.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.81\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.84\u0026plusmn;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e18.46\u0026plusmn;2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.35\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e5.98\u0026plusmn;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e16.29\u0026plusmn;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.95\u0026plusmn;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e122\u0026plusmn;163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.38\u0026plusmn;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e12.6\u0026plusmn;1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e16.69\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLipid:Carbohydrate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e4.43\u0026plusmn;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.74\u0026plusmn;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.71\u0026plusmn;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.79\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e5.71\u0026plusmn;0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.05\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.28\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.13\u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.05\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.67\u0026plusmn;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.71\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.12\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.56\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eJanuary 2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnvironmental variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemperature (\u0026deg;C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e26\u0026plusmn;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e27\u0026plusmn;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e30\u0026plusmn;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e29\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e28\u0026plusmn;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.62\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.37\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.2\u0026plusmn;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.13\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e7.77\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e8.39\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e8.37\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.18\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.49\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e8.07\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.21\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e8.41\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e8.42\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEC (\u0026micro;s/cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.25\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.3\u0026plusmn;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.04\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.8\u0026plusmn;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.48\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.38\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.27\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.21\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.34\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.25\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.34\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.27\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.14\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSalinity (ppt)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e25.8\u0026plusmn;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e26.3\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e26\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e19.1\u0026plusmn;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e24\u0026plusmn;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e26.3\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e27\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e28.3\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e27\u0026plusmn;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e26.7\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e28.6\u0026plusmn;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e29.1\u0026plusmn;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e26.4\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRedox potential (mv)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-393\u0026plusmn;3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-291\u0026plusmn;5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-234\u0026plusmn;3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-301\u0026plusmn;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-262\u0026plusmn;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-209\u0026plusmn;2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-277\u0026plusmn;3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-302\u0026plusmn;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-229\u0026plusmn;4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-234\u0026plusmn;1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e-289\u0026plusmn;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-175\u0026plusmn;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e-391\u0026plusmn;2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSulphate (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e58.27\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e37.72\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e14\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e15.66\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e19.27\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e33.72\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e20.05\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e25.55\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.55\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e17.77\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e34.16\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e4.44\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e38.05\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003csub\u003eorg\u003c/sub\u003e (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.37\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.9\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.52\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.35\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.37\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.3\u0026plusmn;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.07\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.6\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.3\u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.97\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.17\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e5.02\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.85\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.82\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.55\u0026plusmn;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.9\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.33\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.64\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.52\u0026plusmn;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.12\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.03\u0026plusmn;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.52\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.67\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.75\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e8.66\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e4.91\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarbohydrate (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.18\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.15\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.94\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.05\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.71\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.73\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.57\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.92\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.23\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.01\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.37\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.17\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.35\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e3.07\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.47\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.24\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.38\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.77\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.44\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.88\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.05\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.32\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.31\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.44\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e4.51\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3.64\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLipid (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.96\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.31\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.74\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.08\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.23\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.45\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.27\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.56\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.51\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.71\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.15\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.91\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.43\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.42\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.29\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.29\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.25\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.27\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.26\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.17\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.25\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.2\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.1\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.29\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.55\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.54\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOM of TOM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.24\u0026plusmn;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e18.97\u0026plusmn;4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e32.46\u0026plusmn;3.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e10.87\u0026plusmn;2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e42.03\u0026plusmn;10.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e50.49\u0026plusmn;12.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e13.42\u0026plusmn;76.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e24.51\u0026plusmn;2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e39.4\u0026plusmn;7.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.02\u0026plusmn;2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e7.92\u0026plusmn;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e6.45\u0026plusmn;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e11.05\u0026plusmn;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBPC (mgCg\u003csup\u003e1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.3\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.76\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.54\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.51\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.58\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.34\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.86\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.3\u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.12\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.69\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.46\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e2.96\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e3\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein:Carbohydrate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e17.06\u0026plusmn;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e9.8\u0026plusmn;2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.32\u0026plusmn;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e27.6\u0026plusmn;7.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.08\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.97\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.54\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e1.14\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.74\u0026plusmn;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e31\u0026plusmn;10.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e6.59\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e26.53\u0026plusmn;4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e10.4\u0026plusmn;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.209302325581396%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLipid:Carbohydrate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e5.33\u0026plusmn;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e8.73\u0026plusmn;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.79\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e21.6\u0026plusmn;5.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e1.73\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.62\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e0.47\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.61\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e2.22\u0026plusmn;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e71\u0026plusmn;26.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.4186046511627906%\"\u003e\n \u003cp\u003e0.41\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e5.35\u0026plusmn;0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.976744186046512%\"\u003e\n \u003cp\u003e4.09\u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003eTable 2. Two-way ANOVA on environmental variables of Ashtamudi estuary\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason * Station\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCarbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.953**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.545**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1307.239**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83.884**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48.461**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLipid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.492**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.233**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.638*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e310.832**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.960**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.722**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eC\u003csub\u003eorg\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.779**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.958**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.679*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.779**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.958**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.679*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLOM of TOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e200.676**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69.189**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71.196**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSulphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1333.328**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e697.103**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.337**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.769*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.952\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTemperature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.318*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.268*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.733**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConductivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1245.138**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.463**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eORP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.832*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.204**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.056**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003esalinity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.091**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSubstrate induced enzyme activity (Mesophilic)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.966*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.178*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSubstrate induced enzyme activity (Thermophilic)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.165*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.434\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNative enzyme activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e165.349**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.944**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.167**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBPC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67764.499**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8799.901**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3014.457**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProtein: carbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.555**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.801**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.381**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLipid: Carbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.232*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.759**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.064**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;** P\u0026lt;0.001; *P\u0026lt;0.05\u003c/p\u003e\n\u003cp\u003eTable 3. Factor loadings for various environmental variables\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.10169491525424%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"83.89830508474576%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRotated Component Matrix\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.10169491525424%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"32.76836158192091%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"51.12994350282486%\"\u003e\n \u003cp\u003eComponents\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.89937106918239%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.366876310272538%\"\u003e\n \u003cp\u003ePC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.366876310272538%\"\u003e\n \u003cp\u003ePC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.366876310272538%\"\u003e\n \u003cp\u003ePC3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"18\" valign=\"top\" width=\"16.07898448519041%\"\u003e\n \u003cp\u003e\u003cstrong\u003eApril 2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"32.722143864598024%\"\u003e\n \u003cp\u003eTemperature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.066290550070523%\"\u003e\n \u003cp\u003e.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.066290550070523%\"\u003e\n \u003cp\u003e.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.066290550070523%\"\u003e\n \u003cp\u003e-.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eSalinity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eRedoxpotential\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eSulphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.213\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eCorg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eTOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eCarbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eLipid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eLOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.633\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eBPC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.525\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eProtein:carbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.743\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eLipid:carbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.299\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eEigen value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e5.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e3.525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e2.829\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003e% of Variance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e32.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e22.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e17.682\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eCumulative %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e32.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e54.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e71.744\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"18\" valign=\"top\" width=\"16.07898448519041%\"\u003e\n \u003cp\u003e\u003cstrong\u003eJanuary 2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"32.722143864598024%\"\u003e\n \u003cp\u003eTemperature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.066290550070523%\"\u003e\n \u003cp\u003e-.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.066290550070523%\"\u003e\n \u003cp\u003e-.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.066290550070523%\"\u003e\n \u003cp\u003e.811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.591\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eSalinity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.938\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eRedoxpotential\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.278\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eSulphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eCorg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eTOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eCarbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.301\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eLipid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.569\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eLOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eBPC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eProtein:Carbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eLipid:Carbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e-.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eEigen value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e5.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e3.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e2.862\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003e% of Variance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e31.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e22.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e17.890\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"38.99159663865546%\"\u003e\n \u003cp\u003eCumulative %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e31.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e54.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.33613445378151%\"\u003e\n \u003cp\u003e72.109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eExtraction Method: Principal Component Analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRotation Method: Varimax with Kaiser Normalization.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"wetlands","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wela","sideBox":"Learn more about [Wetlands](https://www.springer.com/journal/13157)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/wela/default.aspx","title":"Wetlands","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Estuaries, Anaerobic, Cellulolytic bacteria, Enzyme activity, Redundancy analysis","lastPublishedDoi":"10.21203/rs.3.rs-757184/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-757184/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEstuarine sediments are best suited for bioprospecting cellulose degrading microorganisms because of continuous input of cellulosic carbon from rivers and terrestrial runoff, and such sediments act as a substrate for decomposition by microbes. Sediment samples were collected from thirteen stations of Ashtamudi estuary, a tropical Ramsar site during April 2016 and January 2017 and analysed for environmental variables such as temperature, pH, electrical conductivity, oxidation- reduction potential, sulphate, total organic carbon (C\u003csub\u003eorg\u003c/sub\u003e), carbohydrate, protein, lipid and labile organic matter. Microcosm experiments were conducted in the sediment samples to compare native and substrate-induced cellulase enzyme activities in mesophilic and thermophilic conditions added with crystalline cellulose and cellobiose as substrates. Abundance of cellulolytic anaerobes in the roll tubes was higher with cellobiose than crystalline cellulose. Substrate induced enzyme activity was more than native enzyme activity [0.0012±0.0001- 0.004±0.002 (April 2016) and 0.004±0.001- 0.161±0.002 mg glucose h\u003csup\u003e-1\u003c/sup\u003e (January 2017)] in the sediment samples and cellulolytic activity was more pronounced in thermophilic conditions during April 2016. Redundancy analysis indicated that salinity was the highest determining factor for explaining variations among bacterial abundance and activity during April 2016 and sediment lipid content during January 2017. The study reveals that estuarine sediments can act as a potential source of thermophilic cellulase enzyme producing bacteria, which needs to be further explored owing to their vast industrial applications.\u003c/p\u003e","manuscriptTitle":"Organic Matter And Anaerobic Cellulolytic Activity In Sediments of Ashtamudi Estuary, Kerala, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-01 19:24:23","doi":"10.21203/rs.3.rs-757184/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-11-29T11:54:54+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-11-25T12:37:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Wetlands","date":"2021-07-30T16:27:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-07-30T10:05:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Wetlands","date":"2021-07-27T06:20:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"wetlands","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wela","sideBox":"Learn more about [Wetlands](https://www.springer.com/journal/13157)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/wela/default.aspx","title":"Wetlands","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2c91dacc-cab7-4681-85b7-66c122df4d68","owner":[],"postedDate":"November 1st, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":8181854,"name":"Environmental Chemistry"}],"tags":[],"updatedAt":"2022-08-22T15:40:38+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-01 19:24:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-757184","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-757184","identity":"rs-757184","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}