Development of NIRS Calibrations for Seed Content of Lipids and Proteins in Contrasting White Lupin Germplasm

Abstract

White lupin (L. albus) has high potential interest as a high-protein food or feed crop. In addition, the oil of its seed has high quality for human nutrition. Crop improvement for these traits would profit of low-cost, NIRS-based evaluation methods that could be applied to large numbers of genotypes. The aim of this work was developing and assessing calibration models for NIRS prediction of these traits, envisaging analyses either on whole grain samples or on ground samples. Samples for the reference analyses were chosen by applying the Kennard-Stone algorithm to the whole set of spectra recorded from 2342 samples, both for seeds and flours. A group of 146 samples was selected to calculate calibration models based on chemical analyses for lipid and protein contents (Soxhlet extraction and Dumas method, respectively). After chemometric elaborations of the collected NIR spectra, with a repeated double cross-validation, the best results were obtained with lupin flours spectra for the estimation of protein content, using 4 LV and a mean centering as pretreatment, with performances which are good enough for breeding purposes (RPD = 3.30). Predictions were somewhat worse with lupin flours spectra for oil content, which attained RPD = 2.46 with 2 LV and first derivative and mean center as pretreatments. Results were less satisfying for predicting protein or oil content based on whole seed spectra, a non-destructive sample scenario of special interest for selection based on individual seeds.