ORIGINAL PAPER
Prediction of silage digestibility by near infrared reflectance spectroscopy
X. Liu 1  
,   L. Han 1  
,   Z. Yang 1,   Ch. Xu 1
 
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College of Engineering, China Agricultural University, Beijing 100083, P.R. China
CORRESPONDING AUTHOR
X. Liu   

College of Engineering, China Agricultural University, Beijing 100083, P.R. China
L. Han   

College of Engineering, China Agricultural University, Beijing 100083, P.R. China
Publication date: 2008-10-27
 
J. Anim. Feed Sci. 2008;17(4):631–639
 
KEYWORDS
ABSTRACT
A total of 142 silage samples were used to evaluate the ability of near infrared reflectance spectroscopy (NIRS) to predict dry matter (DM) and neutral detergent fibre (NDF) digestibility. Three techniques, Partial Least Square (PLS), Principal Component Regression (PCR) and Multivariate Linear Regression (MLR), and a series of mathematical treatments were applied to establish the NIRS calibrations. The F-test and T-test of correlativity between reference and NIRS values of silage samples in validation set were carried out to verify the models. Results showed the PLS technique gave the best prediction and calibrations, and that the calibrations developed from the combination of smooth and first-order derivative treatment were largely acceptable. The prediction of DM digestibility of dried samples was good with the determination coefficient of validation (r²) being greater than 0.80. The prediction of dried samples was better than that of fresh samples. The relative standard deviation (RSD) values of DM digestibility for dried and fresh samples were 8.25 and 11.26%, respectively. As for NDF digestibility, the RSD values were higher, being of 22.87 and 23.50% for dried and fresh samples, respectively.
 
CITATIONS (6):
1.
Transfer of near infrared spectrometric models for silage crude protein detection between different instruments
X. Liu, L.J. Han, Z.L. Yang
Journal of Dairy Science
 
2.
Measurement of rumen dry matter and neutral detergent fiber degradability of feeds by Fourier-transform infrared spectroscopy
A. Belanche, M.R. Weisbjerg, G.G. Allison, C.J. Newbold, J.M. Moorby
Journal of Dairy Science
 
3.
Prediction of Chemical Composition and Fermentation Parameters in Forage Sorghum and Sudangrass Silage using Near Infrared Spectroscopy
Hyung-Soo Park, Sang-Hoon Lee, Ki-Choon Choi, Ji-Hye Kim, Min-Jeong So, Hyeon-Seop Kim
Journal of The Korean Society of Grassland and Forage Science
 
4.
NIRS-aided monitoring and prediction of biogas yields from maize silage at a full-scale biogas plant applying lumped kinetics
H. Fabian Jacobi, Susanne Ohl, Eiko Thiessen, Eberhard Hartung
Bioresource Technology
 
5.
Near Infrared Reflectance Spectroscopy (NIRS) for rapid determination of biochemical methane potential of plant biomass
Jin M. Triolo, Alastair J. Ward, Lene Pedersen, Mette M. Løkke, Haiyan Qu, Sven G. Sommer
Applied Energy
 
6.
Multi-block SO-PLS approach based on infrared spectroscopy for anaerobic digestion process monitoring
L. Awhangbo, R. Bendoula, J.M. Roger, F. Béline
Chemometrics and Intelligent Laboratory Systems
 
ISSN:1230-1388