Use of hyperspectral imaging devices for the measurement of small granular samples: Evaluation of grape seed protein concentrates

Abstract

Hyperspectral imaging is a well-known technique for quality control of food and agricultural products. This technique is often applied to the measurement of large and heterogeneous samples, where chemical imaging is extremely useful. In addition, when the amount of sample is limited by different factors (price, other analyses, sample production, etc.) hyperspectral imaging is an alternative to traditional spectroscopes for acquiring its spectral information.In this study, a new and specific methodology to acquire hyperspectral information from small amounts of granular samples has been developed. For this purpose, two different hyperspectral devices (400–1100 nm, 900–1700 nm) have been used. A statistical procedure has been followed to test the proposed method. In grape seed protein concentrates, NIR radiation (900–1700 nm) penetrates deeper into the sample than VisNIR radiation (400–1100 nm). Therefore, the minimum amount of sample needed to measure in the NIR range is larger than that needed to measure in the VisNIR range. Finally, different calibration models have been developed for the control of protein content in the tested samples. Standard errors of prediction obtained in external validation are similar to those reported in the literature when sample amount is not an issue (9–10 %).