Using Near Infrared Reflectance Spectroscopy (NIRS) to predict the protein and energy digestibility of lupin kernel meals when fed to rainbow trout, Oncorhynchus mykiss. (26th February 2014) - Glencross, B.; Bourne, N.; Hawkins, W.; Karopoulos, M.; Evans, D.; Rutherford, N.; McCafferty, P.; Dods, K.; Burridge, P.; Veitch, C.; Sipsas, S.; Buirchell, B.; et al.
Abstract This study examined the potential of using near infrared spectroscopy (NIRS) to predict the nutrient composition, energy density and the digestible protein and digestible energy values of lupin kernel meals when fed to rainbow trout. A series of 136 lupin kernel meals were assessed for their protein and energy digestibilities using the diet‐substitution approach in a series of 10 experiments over a 6‐year period from 2002 to 2008. Two reference diets were also included in each experiment. Minimal variance in the digestibility parameters of both reference diets was observed among the experiments ensuring that there was a high degree of robustness in the across‐experiment evaluations. The same lupin kernel meal samples were also scanned using a diode array near infrared spectrophotometer (DA‐NIRS). The spectra obtained by the DA‐NIRS were chemometrically calibrated against both the chemical composition and the digestible value data using multivariate analysis software. The cross validation tests used in this study provide a valid indication of the potential to predict the nutrient composition, energy value and digestible protein and energy values of the lupin kernel meals as used in diets for rainbow trout. That the standard errors of cross validation (SECV) of the parameters investigated were generally commensurate with the cross trial variation seen in the reference sample indicating robust calibrations for the two target parameters of digestible protein and digestible energy. Therefore this study demonstrates that within one raw material type that not only does significant variability in the digestible value of the raw materials exist, but that it is possible to use NIRS technology to provide rapid estimates of the digestible value of those raw materials in near real‐time.