Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains

In this paper, the feasibility of using spectral profiles for modeling water activity a_w in white quinoa grains (Chenopodium quinoa Willd.) is studied. For this purpose, five hundred samples of five white varieties were stabilized at different a_w values using the isopiestic method. Next, hyperspectral images (HSIs) of ten grains for each combination (variety, a_w value), covering the range of 400–1000 nm were acquired, and mean spectral for each grain extracted. Then, due to a linear relationship that the spectral profiles are shown, the modeling was performed with a_w values over 0.741 using partial least square regression (PLSR). From total spectra, three hundred spectrum were selected and randomly divided into training and validation sets. The results shown coefficient of determination from 0.59 to 0.834 concluding than for a_w over 0.741, HSI + PLSR show potential for a_w prediction in white quinoa grains.