ORIGINAL PAPER
Prediction of the nutritive value of wet whole-crop sorghum silage according to the INRA feeding system by near-infrared spectroscopy
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University of Agriculture in Krakow, Department of Animal Nutrition and Feed Management, al. Mickiewicza 24/28, 30-059 Krakow, Poland
 
 
Publication date: 2013-09-09
 
 
Corresponding author
J. Kański   

University of Agriculture in Krakow, Department of Animal Nutrition and Feed Management, al. Mickiewicza 24/28, 30-059 Krakow, Poland
 
 
J. Anim. Feed Sci. 2013;22(4):360-365
 
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ABSTRACT
The aim of the study was to determine the usefulness of near-infrared spectroscopy (NIRS) for direct estimation of energy, protein and fillunits as well as organic matter digestibility (OMD) for wet whole-crop sorghum silages according to the French feeding system for ruminants INRA (1988). Fifty-eight whole-crop sorghum silages ensiled alone or with the addition of wheat bran, rapeseed meal, or whole-crop maize were used to create a calibration data set. Wet samples of silage were scanned using a spectrophotometer (570–1850 nm). The spectral data were transformed to the first derivative. For scatter correction, standard normal variate and detrending methods were used. The calibration equations were developed using modified partial least squares regression.The accuracy of each equation was evaluated based on the coefficient of determination of calibration (R2), standard error of calibration, and standard error of cross validation (SECV). High R2 (> 0.93) were shown for all parameters except OMD (R2 = 0.83).The highest SECV (0.62) was observed for protein units, but all errors were within acceptable values. The results of the study suggest that NIRS may be used for direct prediction of nutritive value of sorghum silages in INRA system units. Furthermore, these results suggest that the NIRS technique may be successfully used for direct estimation of feed units for ruminants in wet silages.
 
CITATIONS (2):
1.
Optimisation of dry matter and nutrients in feed rations through use of a near-infrared spectroscopy system mounted on a self-propelled feed mixer
Ehab Mostafa, Philipp Twickler, Alexander Schmithausen, Christian Maack, Abdelkader Ghaly, Wolfgang Buescher
Animal Production Science
 
2.
Lidar Monitoring of Moisture in Biological Objects
M. Grishin, V. Lednev, P. Sdvizhenskii, D. Pavkin, E. Nikitin, A. Bunkin, S. Pershin
Doklady Physics
 
ISSN:1230-1388
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