Abstract
Lupins (Lupinus angustifolius) are a type of pulse known for their high protein content, nutritional benefits and versatile uses in food. Lupins have a characteristic thick outer hull which may impact the development and application of NIR (near infrared) calibrations for assessing compositional traits. This study seeks to compare the predictive abilities of models based on wholegrain and ground grist for key quality traits, specifically protein and moisture content. To determine if the thick outer hull poses an obstacle for NIR light to penetrate and reflect from the seed, NIR spectroscopy of lupin samples was conducted for both wholegrain and ground grist forms. The same set of 120 samples was used to construct two prediction models (with a calibration set of 96 samples and an independent validation set of 24 samples). The results show that the predictions for moisture content were comparable between wholegrain and grist for the validation set, achieving r2 values of 0.99 for both models. The models for protein content exhibited a greater distinction between wholegrain and grist, yielding r2 values of 0.91 and 0.96, respectively. Overall, both sets of models exhibited high correlations with protein and moisture constituents and are indicative that calibrations developed on intact lupin hull using wholegrain NIR spectra can be used to predict protein content. Despite a decline in accuracy when compared with the grist results, the benefit of applying the wholegrain calibration outweighs the time taken to prepare the grist samples for NIR analysis.
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