Abstract
Predicting forage feed value is a vital part of estimating ruminant performances. Most near-infrared (NIR) reflectance calibration models have been developed on oven-dried green forages, but preserved forages such as hays or silages are a significant part of real-world farm practice. Fresh and preserved forages give largely similar fodder, but drying or ensiling processes could modify preserved forage spectra which would make the oven-dried green forage model unsuitable to use on preserved forage samples. The aim of this study was to monitor the performance of oven-dried green forage calibration models on a set of hay and silage to predict their nutritive value. Local and global approaches were tested and 1025 green permanent grassland forages, 46 types of hay, and 27 types of silage were used. The samples were scanned by NIR spectroscopy and analyzed for nitrogen, neutral detergent fiber, acid detergent fiber, and pepsin–cellulase dry matter digestibility (PCDMD). Local and global calibrations were developed on 975 oven-dried green forage spectra and tested on 50 samples of oven-dried green forages, 46 samples of hay, and 27 samples of silage. For oven-dried green forage and hay validation sets, Mahalanobis distance (H) between these samples and the calibration population center was lower than 3. No significant standard error of prediction differences was obtained when calibration models were applied to oven-dried green forage and hay validation sets. For silage, the H-distance was higher than 3, meaning that calibration models built from oven-dried green forages cannot be applied to silage samples. We conclude that local calibration outperforms global strategy on predicting the PCDMD of oven-dried green forages and hay.
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