In-field measurement of starch content of cassava tubers using handheld vis-near infrared spectroscopy implemented for breeding programmes

Abstract

This paper involves the prediction of cassava tuber starch content (SC) using near-infrared (NIR) spectroscopy, aiming to follow the change of SC in individual tubers utilised for a breeding programme. This study applies a portable NIR spectrometer at wavelengths of 570–1031 nm in the evaluation of SC in fresh cassava tubers. The prediction models are established using partial least squares (PLS) regression with NIR spectra obtained in the interactance mode. The effective model was developed from the wavelength region of 600–1000 nm with spectral pre-processing of the second derivative, giving the coefficient of determination of prediction set (r2) and root mean square error of prediction (RMSEP) of 0.62 and 2.21%, respectively. The effect of tuber section (including head, middle and tail) on the performance of the SC model was investigated. The individual head, middle and tail models were acceptable for screening. However, the performances of the combined model (which is the model developed a mix of all individual section samples) and the individual section model were not significantly different. Therefore, the combined model was suitable in real application because of the ease of in-field scanning. The result demonstrates that the SCs of cassava tubers can be measured by a NIR spectroscopy method. Furthermore, it can be used as an alternative tool which is appropriate for breeders to use to follow the behaviour of SC during breeding.