THE USE OF NEAR-INFRARED REFLECTANCE SPECTROSCOPY (NIRS) ON UNDRIED SAMPLES OF GRASS-SILAGE TO PREDICT CHEMICAL-COMPOSITION AND DIGESTIBILITY PARAMETERS
Rs. Park et al., THE USE OF NEAR-INFRARED REFLECTANCE SPECTROSCOPY (NIRS) ON UNDRIED SAMPLES OF GRASS-SILAGE TO PREDICT CHEMICAL-COMPOSITION AND DIGESTIBILITY PARAMETERS, Animal feed science and technology, 72(1-2), 1998, pp. 155-167
Near infrared reflectance spectroscopy (NIRS) has become increasingly
used as a rapid, accurate method of evaluating some chemical constitue
nts in cereals and dried animal forages. However relatively few studie
s have been carried out to evaluate the potential of NIRS to predict c
hemical constituents and digestibility parameters in undried forages.
The predictive accuracy of NIRS relies heavily upon obtaining a calibr
ation set which represents the variation in the main population, accur
ate laboratory analyses and the application of the best mathematical p
rocedures. This study was undertaken to examine the potential of NIRS
to accurately determine the chemical composition and a range of digest
ibility parameters of undried grass silage with the objective of chara
cterising the feeding value of forage to the ruminant animal. A repres
entative population of 136 grass silages covering a wide distribution
in chemical and digestibility parameters formed the database for this
investigation. A comprehensive chemical profile of the silages was det
ermined and a range of digestibility parameters was measured through 7
2 wether sheep. Undried finely chopped silage samples were scanned at
2 nm intervals over the wavelength range 400-2500 nm and the optical d
ata recorded as log 1/Reflectance (log 1/R). The spectral data were re
gressed against a range of chemical and digestibility parameters using
modified partial least squares (MPLS) multivariate analysis in conjun
ction with first and second order derivatization, with and without thr
ee scatter correction procedures to reduce the effect of extraneous no
ise. Cross validation was used to avoid overfitting of the equations,
The optimum calibrations were selected on the basis of minimizing the
standard error of cross validation (SECV). The SD/SECV (standard devia
tion of the constituent data/standard error of cross validation) ratio
was also calculated to evaluate the calibrations independent of their
units (ratios > 2.5 are acceptable for quality screening). In the cas
e of the digestibility data a sub-calibration set of 90 samples and a
validation set of 46 samples were selected on the basis of their spect
ral variation, and the optimum mathematical treatment for the 136 was
applied. The results of this study show that NIRS predicted the main c
hemical parameters with a very high degree of accuracy (i.e., the corr
elation coefficient of cross validation (R-cv(2)) ranged from 0.81-0.9
6) in all cases, except for buffering capacity which had a R-cv(2) 0.6
8 and a SD/SECV ratio of 2.19. The nitrogen fractions all formed calib
rations with R-cv(2) ranging from 0.87 to 0.94 for amino acid nitrogen
and kjeldhal nitrogen, respectively and all SD/SECV ratios were great
er than 2.5. The alcohol and volatile fatty acid calibrations produced
slightly poorer calibrations with butyric and lactic acid and ethanol
, giving the highest correlations. The in vivo digestibility parameter
s were predicted with considerable accuracy R-cv(2) 0.79-0.85 (n = 136
) and the standard errors of prediction (SEP) for the validation set c
ompared favourably with the SECV statistic for calibrations based on t
he 136 samples. This study found that NIRS calibrations based on undri
ed grass silage spectra have the capability of predicting a wide range
of chemical and digestibility parameters which would afford a rapid a
ssessment of the forage for diet formulation. (C) 1998 Elsevier Scienc
e B.V.