Abstract
It is important to discover the connections undergoing between data in order to asses complete and robust mathematical relations (Quinn et al. in Bioinformatics 34(16):2870–2878, 2018).
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References
Quinn TP, Erb I, Richardson MF, Crowley TM (2018) Understanding sequencing data as compositions: an outlook and review. Bioinformatics 34(16):2870–2878. https://doi.org/10.1093/bioinformatics/bty175
Ross SM (2021) Chapter 6: distributions of sampling statistics. In: Ross SM (ed) Introduction to probability and statistics for engineers and scientists (6th edn). Academic Press, New York, 221–244. https://doi.org/10.1016/B978-0-12-824346-6.00015-6.
Yvonnet J, Monteiro E, He Q-C (2013) Computational homogenization method and reduced database model for hyperelastic heterogeneous structures. Int J Multiscale Comput Eng 11:3. https://doi.org/10.1615/IntJMultCompEng.2013005374
Kiernan D (2023) Chapter 7: correlation and simple linear regression. https://milnepublishing.geneseo.edu/natural-resources-biometrics/chapter/chapter-7-correlation-and-simple-linear-regression/
Benesty J, Chen J, Huang Y, Cohen I (2009) Pearson correlation coefficient. In: Noise reduction in speech processing, in Springer topics in signal processing, vol 2. Springer, Berlin, pp 1–4. https://doi.org/10.1007/978-3-642-00296-0_5
Farebrother RW (2017) Linear least squares computations. Routledge, New York. https://doi.org/10.1201/9780203748923
Agawin NSR, Duarte CM, Agustí S (2000) Nutrient and temperature control of the contribution of picoplankton to phytoplankton biomass and production. Limnol Oceanogr 45(3):591–600. https://doi.org/10.4319/lo.2000.45.3.0591
Tokuşoglu O, Unal MK (2003) Biomass nutrient profiles of three microalgae: spirulina platensis, chlorella vulgaris, and isochrisis galbana. J Food Sci 68(4):1144–1148. https://doi.org/10.1111/j.1365-2621.2003.tb09615.x
Michalik M, Wilczyńska-Michalik W (2012) Mineral and chemical composition of biomass ash. https://doi.org/10.13140/2.1.4298.5603
Gil A, Toledo M, Siles JA, Martín MA (2018) Multivariate analysis and biodegradability test to evaluate different organic wastes for biological treatments: anaerobic co-digestion and co-composting. Waste Manag 78:819–828. https://doi.org/10.1016/j.wasman.2018.06.052
Myers L, Sirois MJ (2006) Spearman correlation coefficients, differences between. In: Encyclopedia of statistical sciences. Wiley, Amsterdam. https://doi.org/10.1002/0471667196.ess5050.pub2
de Winter JCF, Gosling SD, Potter J (2016) Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: a tutorial using simulations and empirical data. Psychol Methods 21(3):273–290. https://doi.org/10.1037/met0000079
Atkinson CF, Jones DD, Gauthier JJ (1996) Biodegradability and microbial activities during composting of poultry litter. Poult Sci 75(5):608–617. https://doi.org/10.3382/ps.0750608
Ahmadi-Pirlou M, Ebrahimi-Nik M, Khojastehpour M, Ebrahimi SH (2017) Mesophilic co-digestion of municipal solid waste and sewage sludge: effect of mixing ratio, total solids, and alkaline pretreatment. Int Biodeterior Biodegrad 125:97–104. https://doi.org/10.1016/j.ibiod.2017.09.004
Jain S, Jain S, Wolf IT, Lee J, Tong YW (2015) A comprehensive review on operating parameters and different pretreatment methodologies for anaerobic digestion of municipal solid waste. Renew Sustain Energy Rev 52:142–154. https://doi.org/10.1016/j.rser.2015.07.091
Batstone DJ et al (2002) The IWA anaerobic digestion model No 1 (ADM1). Water Sci Technol 45(10):65–73. https://doi.org/10.2166/wst.2002.0292
Liu J, Smith SR (2022) The link between organic matter composition and the biogas yield of full-scale sewage sludge anaerobic digestion. Water Sci Technol 85(5):1658–1672. https://doi.org/10.2166/wst.2022.058
Siddique MNI, Wahid ZA (2018) Achievements and perspectives of anaerobic co-digestion: a review. J Clean Prod 194(1):359–371. https://doi.org/10.1016/j.jclepro.2018.05.155
Wang X, Yang G, Feng Y, Ren G, Han X (2012) Optimizing feeding composition and carbon-nitrogen ratios for improved methane yield during anaerobic co-digestion of dairy, chicken manure and wheat straw. Bioresour Technol 120:78–83. https://doi.org/10.1016/j.biortech.2012.06.058
Benner R, Maccubbin AE, Hodson RE (1984) Anaerobic biodegradation of the lignin and polysaccharide components of lignocellulose and synthetic lignin by sediment microflora. Appl Environ Microbiol 47(5):998–1004
Wang M, Li W, Li P, Yan S, Zhang Y (2017) An alternative parameter to characterize biogas materials: available carbon-nitrogen ratio. Waste Manag 62:76–83. https://doi.org/10.1016/j.wasman.2017.02.025
Turner BL (2010) Variation in pH optima of hydrolytic enzyme activities in tropical rain forest soils. Appl Environ Microbiol 76(19):6485–6493. https://doi.org/10.1128/AEM.00560-10
Sutton A et al (2006) Manipulation of animal diets to affect manure production, composition and odors: state of the science. In: Animal agriculture and the environment, national center for manure and animal waste management white papers. ASABE, St. Joseph. https://doi.org/10.13031/2013.20259
Tang J, Wang XC, Hu Y, Zhang Y, Li Y (2017) Effect of pH on lactic acid production from acidogenic fermentation of food waste with different types of inocula. Bioresour Technol 224:544–552. https://doi.org/10.1016/j.biortech.2016.11.111
Cheah Y-K, Vidal-Antich C, Dosta J, Mata-Álvarez J (2019) Volatile fatty acid production from mesophilic acidogenic fermentation of organic fraction of municipal solid waste and food waste under acidic and alkaline pH. Environ Sci Pollut Res 26(35):35509–35522. https://doi.org/10.1007/s11356-019-05394-6
Li Y, Jin Y, Borrion A, Li H, Li J (2017) Effects of organic composition on the anaerobic biodegradability of food waste. Bioresour Technol 243:836–845. https://doi.org/10.1016/j.biortech.2017.07.028
Hanum F et al (2023) Treatment of sewage sludge using anaerobic digestion in Malaysia: current state and challenges. Front Energy Res 7:7. https://doi.org/10.3389/fenrg.2019.00019
Labatut RA, Pronto JL (2018) Chapter 4—sustainable waste-to-energy technologies: anaerobic digestion. In: Trabold TA, Babbitt CW (eds) Sustainable food waste-to-energy systems. Academic Press, New York, pp 47–67. https://doi.org/10.1016/B978-0-12-811157-4.00004-8
Li D et al (2015) Effects of feedstock ratio and organic loading rate on the anaerobic mesophilic co-digestion of rice straw and cow manure. Bioresour Technol 189:319–326. https://doi.org/10.1016/j.biortech.2015.04.033
Jabeen M, Zeshan S, Yousaf S, Haider MR, Malik RN (2015) High-solids anaerobic co-digestion of food waste and rice husk at different organic loading rates. Int Biodeterior Biodegrad 102:149–153. https://doi.org/10.1016/j.ibiod.2015.03.023
Dewil R, Baeyens J, Roels J, Steene BVD (2008) Distribution of Sulphur Compounds in Sewage Sludge Treatment. Environ Eng Sci 25(6):879–886. https://doi.org/10.1089/ees.2007.0143
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Moretta, F., Bozzano, G. (2024). Statistical Analysis. In: Mathematical and Statistical Approaches for Anaerobic Digestion Feedstock Optimization. SpringerBriefs in Energy. Springer, Cham. https://doi.org/10.1007/978-3-031-56460-4_3
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