Comparison of near infra-red spectroscopy, neutral detergent fibre assay and in-vitro organic matter digestibility assay for rapid determination of the biochemical methane potential of meadow grasses

► NIRS, IVOMD assay and NDF assay have been investigated as rapid biochemical methane potential assessment methods. ► Models have been built to predict the BMPs of meadow grasses using NIRS, IVOMD and NDF. ► Amongst the three methods, NIRS shows the best prediction results and seems to be a promisin...

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Bibliographic Details
Published in:Bioresource technology 2011-09, Vol.102 (17), p.7835-7839
Main Authors: Raju, Chitra Sangaraju, Ward, Alastair James, Nielsen, Lisbeth, Møller, Henrik Bjarne
Format: Article
Language:English
Subjects:
Anaerobic digestion
Assays
Biofuel production
Biogas
Biological and medical sciences
Biological treatment of sewage sludges and wastes
Biotechnology
Detergents - chemistry
Energy
Environment and pollution
Fundamental and applied biological sciences. Psychology
Industrial applications and implications. Economical aspects
IVOMD
Methane - biosynthesis
NDF
NIR
Poaceae - metabolism
Spectroscopy, Near-Infrared - methods
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Summary:► NIRS, IVOMD assay and NDF assay have been investigated as rapid biochemical methane potential assessment methods. ► Models have been built to predict the BMPs of meadow grasses using NIRS, IVOMD and NDF. ► Amongst the three methods, NIRS shows the best prediction results and seems to be a promising option. This paper investigates near infra-red spectroscopy (NIRS) as an indirect and rapid method to assess the biochemical methane potential (BMP) of meadow grasses. Additionally analytical methods usually associated with forage analysis, namely, the neutral detergent fibre assay (NDF), and the in-vitro organic matter digestibility assay (IVOMD), were also tested on the meadow grass samples and the applicability of the models in predicting the BMP was studied. Based on these, regression models were obtained using the partial least squares (PLS) method. Various data pre-treatments were also applied to improve the models. Compared to the models based on the NDF and IVOMD predictions of BMP, the model based on the NIRS prediction of BMP gave the best results. This model, with data pre-processed by the mean normalisation method, had an R2 value of 0.69, a root mean square error of prediction (RMSEP) of 37.4 and a residual prediction deviation (RPD) of 1.75.
ISSN:0960-8524
1873-2976
DOI:10.1016/j.biortech.2011.05.049