Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates

Three different enzymes alkaline phosphatase, Urease and Dehydrogenase were measured during this study to monitor the organic matter dynamics during semi-industrial composting of mixture A with 1/3 sludge+2/3 palm waste and mixture B with ½ sludge+1/2 palm waste. The phosphatase activity was higher...

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Main Authors: Loubna El Fels, Ahmed Naylo, Martin Jemo, Nidal Zrikam, Ali Boularbah, Yedir Ouhdouch, Mohamed Hafidi
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-11-01
Series:Frontiers in Microbiology
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Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2024.1423728/full
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author Loubna El Fels
Ahmed Naylo
Martin Jemo
Nidal Zrikam
Ali Boularbah
Ali Boularbah
Yedir Ouhdouch
Mohamed Hafidi
Mohamed Hafidi
author_facet Loubna El Fels
Ahmed Naylo
Martin Jemo
Nidal Zrikam
Ali Boularbah
Ali Boularbah
Yedir Ouhdouch
Mohamed Hafidi
Mohamed Hafidi
author_sort Loubna El Fels
collection DOAJ
description Three different enzymes alkaline phosphatase, Urease and Dehydrogenase were measured during this study to monitor the organic matter dynamics during semi-industrial composting of mixture A with 1/3 sludge+2/3 palm waste and mixture B with ½ sludge+1/2 palm waste. The phosphatase activity was higher for Mix-A (398.7 µg PNP g−1 h−1) than Mix-B (265.3 µg PNP g−1 h−1), while Mix-B (103.3 µg TPF g−1d−1) exhibited greater dehydrogenase content than Mix-A (72.3 µg TPF g−1 d−1). That could contribute to the dynamic change of microbial activity together with high amounts of carbonaceous substrates incorporated with the lignocellulosic. The gradual increase in the dehydrogenase from the compost Mix-A implies that high lignocellulosic substrate requires gradual buildup of dehydrogenase activity to turn the waste into mature compost. A higher pick of urease with a maximum activity of 151.5 and 122.4 µg NH4-N g−1 h−1 were reported, respectively for Mix-A and B. Temperature and pH could also influence the expression of enzyme activity during composting. The machine learning well predicted the compost quality based on NH3/NO3, C/N ratio, decomposition rate and, humification index (HI). The root mean square error (RMSE) values were 1.98, 1.95, 4.61%, and 4.1 for NH+3/NO−3, C/N ratio, decomposition rate, and HI, respectively. The coefficient of determination between observed and predicted values were 0.87, 0.93, 0.89, and 0.94, for the r NH3/NO3, C/N ratio, decomposition rate, and HI. Urease activity significantly predicted the C/N ratio and HI only. The profile of enzymatic activity is tightly linked to the physico-chemical properties, proportion of lignocellulosic-composted substrates. Enzymatic activity assessment provides a simple and rapid measurement of the biological activity adding understunding of organic matter transformation during sludge-lignocellulosic composting.
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spelling doaj-art-d802007b0b3843d1851fe16aadec20752024-11-11T04:38:24ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2024-11-011510.3389/fmicb.2024.14237281423728Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substratesLoubna El Fels0Ahmed Naylo1Martin Jemo2Nidal Zrikam3Ali Boularbah4Ali Boularbah5Yedir Ouhdouch6Mohamed Hafidi7Mohamed Hafidi8Laboratory of Microbial Biotechnologies, Agrosciences and Environment (BioMAgE), Labelled Research Unit-CNRST N°4, Faculty of Sciences Semlalia, University Cadi Ayyad (UCA), Marrakech, MoroccoLaboratoire Bioressources et Sécurité Sanitaire des Aliments, Faculté des Sciences et Techniques, Université Cadi Ayyad, Marrakech, MoroccoAgroBiosciences Program, College for Sustainable Agriculture and Environmental Sciences, University Mohammed VI Polytechnic (UM6P), Ben Guerir, MoroccoLaboratory of Microbial Biotechnologies, Agrosciences and Environment (BioMAgE), Labelled Research Unit-CNRST N°4, Faculty of Sciences Semlalia, University Cadi Ayyad (UCA), Marrakech, MoroccoLaboratoire Bioressources et Sécurité Sanitaire des Aliments, Faculté des Sciences et Techniques, Université Cadi Ayyad, Marrakech, MoroccoCenter of Excellence for Soil and Fertilizer Research in Africa, College of Agriculture and Environmental Sciences, Mohammed VI Polytechnic University, Ben Guerir, MoroccoAfrican Sustainable Agriculture Research Institute (ASARI), College for Sustainable Agriculture and Environmental Sciences, University Mohammed VI Polytechnic (UM6P), Laayoune, MoroccoLaboratory of Microbial Biotechnologies, Agrosciences and Environment (BioMAgE), Labelled Research Unit-CNRST N°4, Faculty of Sciences Semlalia, University Cadi Ayyad (UCA), Marrakech, MoroccoAfrican Sustainable Agriculture Research Institute (ASARI), College for Sustainable Agriculture and Environmental Sciences, University Mohammed VI Polytechnic (UM6P), Laayoune, MoroccoThree different enzymes alkaline phosphatase, Urease and Dehydrogenase were measured during this study to monitor the organic matter dynamics during semi-industrial composting of mixture A with 1/3 sludge+2/3 palm waste and mixture B with ½ sludge+1/2 palm waste. The phosphatase activity was higher for Mix-A (398.7 µg PNP g−1 h−1) than Mix-B (265.3 µg PNP g−1 h−1), while Mix-B (103.3 µg TPF g−1d−1) exhibited greater dehydrogenase content than Mix-A (72.3 µg TPF g−1 d−1). That could contribute to the dynamic change of microbial activity together with high amounts of carbonaceous substrates incorporated with the lignocellulosic. The gradual increase in the dehydrogenase from the compost Mix-A implies that high lignocellulosic substrate requires gradual buildup of dehydrogenase activity to turn the waste into mature compost. A higher pick of urease with a maximum activity of 151.5 and 122.4 µg NH4-N g−1 h−1 were reported, respectively for Mix-A and B. Temperature and pH could also influence the expression of enzyme activity during composting. The machine learning well predicted the compost quality based on NH3/NO3, C/N ratio, decomposition rate and, humification index (HI). The root mean square error (RMSE) values were 1.98, 1.95, 4.61%, and 4.1 for NH+3/NO−3, C/N ratio, decomposition rate, and HI, respectively. The coefficient of determination between observed and predicted values were 0.87, 0.93, 0.89, and 0.94, for the r NH3/NO3, C/N ratio, decomposition rate, and HI. Urease activity significantly predicted the C/N ratio and HI only. The profile of enzymatic activity is tightly linked to the physico-chemical properties, proportion of lignocellulosic-composted substrates. Enzymatic activity assessment provides a simple and rapid measurement of the biological activity adding understunding of organic matter transformation during sludge-lignocellulosic composting.https://www.frontiersin.org/articles/10.3389/fmicb.2024.1423728/fulllignocellulosic-sludge compostingmicrobial enzymes indexmicrobial dynamicmaturity indexalkaline pohosphatase
spellingShingle Loubna El Fels
Ahmed Naylo
Martin Jemo
Nidal Zrikam
Ali Boularbah
Ali Boularbah
Yedir Ouhdouch
Mohamed Hafidi
Mohamed Hafidi
Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates
Frontiers in Microbiology
lignocellulosic-sludge composting
microbial enzymes index
microbial dynamic
maturity index
alkaline pohosphatase
title Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates
title_full Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates
title_fullStr Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates
title_full_unstemmed Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates
title_short Microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates
title_sort microbial enzymatic indices for predicting composting quality of recalcitrant lignocellulosic substrates
topic lignocellulosic-sludge composting
microbial enzymes index
microbial dynamic
maturity index
alkaline pohosphatase
url https://www.frontiersin.org/articles/10.3389/fmicb.2024.1423728/full
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