Literature DB >> 19256089

Calibration of chemical and biological changes in cocomposting of biowastes using near-infrared spectroscopy.

Remy Albrecht1, Richard Joffre, Jean Le Petit, Gerard Terrom, Claude Périssol.   

Abstract

Cocomposting of green wastes and sewage sludges is a complex process involving rapid biological and chemical changes. The objective of the study was to assess the usefulness of near-infrared reflectance spectroscopy (NIRS) to characterize these changes, as an alternative to standard procedures which are often time-consuming and laborious. Samples obtained during 146 days of composting were analyzed by 14 conventional methods and NIRS. Results from conventional methods demonstrated a noticeable separation into two distinct phases. An initial phase from 4 to 50-60 days was characterized by intensive degradation. A second phase up to 146 days was characterized by a decrease in all biological activities. NIRS calibrations allowed accurate predictions of nitrogen (N), carbon (C), C/N, humic acid (HA), pH, respiration, cellulase, phenoloxidase, and composting time successfully. Results were less accurate for organic matter (OM), protease, acid, and alkaline phosphatases and unsatisfactory for fulvic acid. NIRS calibration allows composting time/state of progress of maturation to be predicted accurately to within 10 days. A global index of composting evolution (GICE), resulting from the 14 parameters studied, is proposed. It is precisely predicted and shows that since NIRS is able to predict essential parameters of compost maturity, it could prove invaluable for monitoring biowastes cocomposting.

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Year:  2009        PMID: 19256089     DOI: 10.1021/es802064u

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  4 in total

1.  Concentration estimation of heavy metal in soils from typical sewage irrigation area of Shandong Province, China using reflectance spectroscopy.

Authors:  Fei Wang; Chunfang Li; Jining Wang; Wentao Cao; Quanyuan Wu
Journal:  Environ Sci Pollut Res Int       Date:  2017-06-01       Impact factor: 4.223

2.  High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

Authors:  Gerald Forkuor; Ozias K L Hounkpatin; Gerhard Welp; Michael Thiel
Journal:  PLoS One       Date:  2017-01-23       Impact factor: 3.240

3.  Evaluation of Leymus chinensis quality using near-infrared reflectance spectroscopy with three different statistical analyses.

Authors:  Jishan Chen; Ruifen Zhu; Ruixuan Xu; Wenjun Zhang; Yue Shen; Yingjun Zhang
Journal:  PeerJ       Date:  2015-12-03       Impact factor: 2.984

4.  Rapid and accurate evaluation of the quality of commercial organic fertilizers using near infrared spectroscopy.

Authors:  Chang Wang; Chichao Huang; Jian Qian; Jian Xiao; Huan Li; Yongli Wen; Xinhua He; Wei Ran; Qirong Shen; Guanghui Yu
Journal:  PLoS One       Date:  2014-02-25       Impact factor: 3.240

  4 in total

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