Predicting the biochemical methane potential of wide range of organic substrates by near infrared spectroscopy
► The use of near infrared spectroscopy (NIRS) to predict the biochemical methane potential (BMP) was investigated. ► The NIRS appears as a suitable method for the fast prediction of BMP. ► The integration of the entire diversity of waste remains nevertheless difficult. ► The NIR model for non-stabi...
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| Veröffentlicht in: | Bioresource technology 2013-01, Vol.128, p.252-258 |
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| creator | Doublet, J. Boulanger, A. Ponthieux, A. Laroche, C. Poitrenaud, M. Cacho Rivero, J.A. |
| description | ► The use of near infrared spectroscopy (NIRS) to predict the biochemical methane potential (BMP) was investigated. ► The NIRS appears as a suitable method for the fast prediction of BMP. ► The integration of the entire diversity of waste remains nevertheless difficult. ► The NIR model for non-stabilised substrates could be practically used.
The use of near infrared spectroscopy (NIRS) as an alternative method to predict the biochemical methane potential (BMP) of a broad range of organic substrates was investigated. A total of 296 samples including most of the substrates treated by anaerobic co-digestion were used for NIRS calibration and validation. The NIRS predictions of the BMP values were satisfactory (Root Mean Square Error=40mlCH4g−1 VSfed; r2=0.85). The integration of the entire substrate diversity in the model remained nevertheless difficult due to the specific organic matter properties of stabilised substrates and the high level of uncertainty of the BMP values. The elaboration of a model restricted to “fresh” substrates allows the practical use of the NIR technique to design and operate anaerobic co-digestion plants. The addition of more samples in the dataset in order to perform local calibrations would probably make the elaboration of a global NIR-model possible. |
| doi_str_mv | 10.1016/j.biortech.2012.10.044 |
| format | Article |
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The use of near infrared spectroscopy (NIRS) as an alternative method to predict the biochemical methane potential (BMP) of a broad range of organic substrates was investigated. A total of 296 samples including most of the substrates treated by anaerobic co-digestion were used for NIRS calibration and validation. The NIRS predictions of the BMP values were satisfactory (Root Mean Square Error=40mlCH4g−1 VSfed; r2=0.85). The integration of the entire substrate diversity in the model remained nevertheless difficult due to the specific organic matter properties of stabilised substrates and the high level of uncertainty of the BMP values. The elaboration of a model restricted to “fresh” substrates allows the practical use of the NIR technique to design and operate anaerobic co-digestion plants. The addition of more samples in the dataset in order to perform local calibrations would probably make the elaboration of a global NIR-model possible.</description><identifier>ISSN: 0960-8524</identifier><identifier>EISSN: 1873-2976</identifier><identifier>DOI: 10.1016/j.biortech.2012.10.044</identifier><identifier>PMID: 23196247</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Anaerobic digestion ; Bacteria, Anaerobic - metabolism ; Biochemical methane potential ; Biochemistry ; Biological and medical sciences ; Biological treatment of sewage sludges and wastes ; Biotechnology ; Calibration ; Co-digestion ; Computer Simulation ; Environment and pollution ; Fundamental and applied biological sciences. Psychology ; Industrial applications and implications. Economical aspects ; Infrared spectroscopy ; Mathematical models ; Mean square values ; Methane ; Methane - metabolism ; Models, Biological ; Near infrared spectroscopy ; Organic Chemicals - metabolism ; Roots ; Spectroscopy, Near-Infrared - methods ; Uncertainty</subject><ispartof>Bioresource technology, 2013-01, Vol.128, p.252-258</ispartof><rights>2012 Elsevier Ltd</rights><rights>2014 INIST-CNRS</rights><rights>Copyright © 2012 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-910c76981a2647656258605bcc657d64f052f78f587af7a1214c7b757ead06a53</citedby><cites>FETCH-LOGICAL-c431t-910c76981a2647656258605bcc657d64f052f78f587af7a1214c7b757ead06a53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0960852412015465$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,4010,27900,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27081576$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23196247$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Doublet, J.</creatorcontrib><creatorcontrib>Boulanger, A.</creatorcontrib><creatorcontrib>Ponthieux, A.</creatorcontrib><creatorcontrib>Laroche, C.</creatorcontrib><creatorcontrib>Poitrenaud, M.</creatorcontrib><creatorcontrib>Cacho Rivero, J.A.</creatorcontrib><title>Predicting the biochemical methane potential of wide range of organic substrates by near infrared spectroscopy</title><title>Bioresource technology</title><addtitle>Bioresour Technol</addtitle><description>► The use of near infrared spectroscopy (NIRS) to predict the biochemical methane potential (BMP) was investigated. ► The NIRS appears as a suitable method for the fast prediction of BMP. ► The integration of the entire diversity of waste remains nevertheless difficult. ► The NIR model for non-stabilised substrates could be practically used.
The use of near infrared spectroscopy (NIRS) as an alternative method to predict the biochemical methane potential (BMP) of a broad range of organic substrates was investigated. A total of 296 samples including most of the substrates treated by anaerobic co-digestion were used for NIRS calibration and validation. The NIRS predictions of the BMP values were satisfactory (Root Mean Square Error=40mlCH4g−1 VSfed; r2=0.85). The integration of the entire substrate diversity in the model remained nevertheless difficult due to the specific organic matter properties of stabilised substrates and the high level of uncertainty of the BMP values. The elaboration of a model restricted to “fresh” substrates allows the practical use of the NIR technique to design and operate anaerobic co-digestion plants. The addition of more samples in the dataset in order to perform local calibrations would probably make the elaboration of a global NIR-model possible.</description><subject>Anaerobic digestion</subject><subject>Bacteria, Anaerobic - metabolism</subject><subject>Biochemical methane potential</subject><subject>Biochemistry</subject><subject>Biological and medical sciences</subject><subject>Biological treatment of sewage sludges and wastes</subject><subject>Biotechnology</subject><subject>Calibration</subject><subject>Co-digestion</subject><subject>Computer Simulation</subject><subject>Environment and pollution</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Industrial applications and implications. Economical aspects</subject><subject>Infrared spectroscopy</subject><subject>Mathematical models</subject><subject>Mean square values</subject><subject>Methane</subject><subject>Methane - metabolism</subject><subject>Models, Biological</subject><subject>Near infrared spectroscopy</subject><subject>Organic Chemicals - metabolism</subject><subject>Roots</subject><subject>Spectroscopy, Near-Infrared - methods</subject><subject>Uncertainty</subject><issn>0960-8524</issn><issn>1873-2976</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkUtvEzEUhS0EomnhL1TeILGZcO3xY2YHqspDqgQLWFsez53EUcYebIcq_x5HSWHZleWj7x77nkPILYM1A6Y-7NaDj6mg2645MF7FNQjxgqxYp9uG91q9JCvoFTSd5OKKXOe8A4CWaf6aXPGW9YoLvSLhR8LRu-LDhpYt0urqtjh7Z_d0xrK1AekSC4biqxIn-uhHpMmGDZ5uMW1s8I7mw5BLsgUzHY40oE3UhynZak7zgq6kmF1cjm_Iq8nuM769nDfk1-f7n3dfm4fvX77dfXponGhZaXoGTqu-Y5YroZVUXHYK5OCcknpUYgLJJ91NstN20pZxJpwetNRoR1BWtjfk_dl3SfH3AXMxs88O9_u6TzxkwySA1pyDfh7lneA9QN9WVJ1RV9fJCSezJD_bdDQMzKkWszNPtZhTLSe91lIHby9vHIYZx39jTz1U4N0FsLlGX5MLzuf_nIaOSa0q9_HMYQ3vj8dksvMYXO0w1ZTNGP1zf_kLkM-u2Q</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Doublet, J.</creator><creator>Boulanger, A.</creator><creator>Ponthieux, A.</creator><creator>Laroche, C.</creator><creator>Poitrenaud, M.</creator><creator>Cacho Rivero, J.A.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7SU</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>201301</creationdate><title>Predicting the biochemical methane potential of wide range of organic substrates by near infrared spectroscopy</title><author>Doublet, J. ; Boulanger, A. ; Ponthieux, A. ; Laroche, C. ; Poitrenaud, M. ; Cacho Rivero, J.A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-910c76981a2647656258605bcc657d64f052f78f587af7a1214c7b757ead06a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Anaerobic digestion</topic><topic>Bacteria, Anaerobic - metabolism</topic><topic>Biochemical methane potential</topic><topic>Biochemistry</topic><topic>Biological and medical sciences</topic><topic>Biological treatment of sewage sludges and wastes</topic><topic>Biotechnology</topic><topic>Calibration</topic><topic>Co-digestion</topic><topic>Computer Simulation</topic><topic>Environment and pollution</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Industrial applications and implications. Economical aspects</topic><topic>Infrared spectroscopy</topic><topic>Mathematical models</topic><topic>Mean square values</topic><topic>Methane</topic><topic>Methane - metabolism</topic><topic>Models, Biological</topic><topic>Near infrared spectroscopy</topic><topic>Organic Chemicals - metabolism</topic><topic>Roots</topic><topic>Spectroscopy, Near-Infrared - methods</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Doublet, J.</creatorcontrib><creatorcontrib>Boulanger, A.</creatorcontrib><creatorcontrib>Ponthieux, A.</creatorcontrib><creatorcontrib>Laroche, C.</creatorcontrib><creatorcontrib>Poitrenaud, M.</creatorcontrib><creatorcontrib>Cacho Rivero, J.A.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Environmental Engineering Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Bioresource technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Doublet, J.</au><au>Boulanger, A.</au><au>Ponthieux, A.</au><au>Laroche, C.</au><au>Poitrenaud, M.</au><au>Cacho Rivero, J.A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the biochemical methane potential of wide range of organic substrates by near infrared spectroscopy</atitle><jtitle>Bioresource technology</jtitle><addtitle>Bioresour Technol</addtitle><date>2013-01</date><risdate>2013</risdate><volume>128</volume><spage>252</spage><epage>258</epage><pages>252-258</pages><issn>0960-8524</issn><eissn>1873-2976</eissn><abstract>► The use of near infrared spectroscopy (NIRS) to predict the biochemical methane potential (BMP) was investigated. ► The NIRS appears as a suitable method for the fast prediction of BMP. ► The integration of the entire diversity of waste remains nevertheless difficult. ► The NIR model for non-stabilised substrates could be practically used.
The use of near infrared spectroscopy (NIRS) as an alternative method to predict the biochemical methane potential (BMP) of a broad range of organic substrates was investigated. A total of 296 samples including most of the substrates treated by anaerobic co-digestion were used for NIRS calibration and validation. The NIRS predictions of the BMP values were satisfactory (Root Mean Square Error=40mlCH4g−1 VSfed; r2=0.85). The integration of the entire substrate diversity in the model remained nevertheless difficult due to the specific organic matter properties of stabilised substrates and the high level of uncertainty of the BMP values. The elaboration of a model restricted to “fresh” substrates allows the practical use of the NIR technique to design and operate anaerobic co-digestion plants. The addition of more samples in the dataset in order to perform local calibrations would probably make the elaboration of a global NIR-model possible.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>23196247</pmid><doi>10.1016/j.biortech.2012.10.044</doi><tpages>7</tpages></addata></record> |
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| subjects | Anaerobic digestion Bacteria, Anaerobic - metabolism Biochemical methane potential Biochemistry Biological and medical sciences Biological treatment of sewage sludges and wastes Biotechnology Calibration Co-digestion Computer Simulation Environment and pollution Fundamental and applied biological sciences. Psychology Industrial applications and implications. Economical aspects Infrared spectroscopy Mathematical models Mean square values Methane Methane - metabolism Models, Biological Near infrared spectroscopy Organic Chemicals - metabolism Roots Spectroscopy, Near-Infrared - methods Uncertainty |
| title | Predicting the biochemical methane potential of wide range of organic substrates by near infrared spectroscopy |
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