Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)

Abstract

High throughput techniques for phenotyping quality traits in root and tuber crops are useful in breeding programs where thousands of genotypes are screened at the early stages. This study assessed the effects of sample preparation on the prediction accuracies of dry matter, protein, and starch content in fresh yam using Near-Infrared Reflectance Spectroscopy (NIRS). Fresh tubers of Dioscorearotundata (D. rotundata) and Dioscoreaalata (D. alata) were prepared using different sampling techniques—blending, chopping, and grating. Spectra of each sample and reference data were used to develop calibration models using Modified Partial Least Square (MPLS). The performance of the model developed from the blended yam samples was tested using a new set of yam samples (N = 50) by comparing their wet laboratory results with the predicted values from NIRS. Blended samples had the highest coefficient of prediction (R2pre) for dry matter (0.95) and starch (0.83), though very low for protein (0.26), while grated samples had the lowest R2pre of 0.87 for dry matter and 0.50 for starch. Results showed that blended samples gave a better prediction compared with other methods. The feasibility of NIRS for the prediction of dry matter and starch content in fresh yam was highlighted.

Application of Spectroscopy in Food Analysis: Volume II

“…The coupling of FT-NIR and PLS was also exploited in the work published by Alamu et al [8] who have relied this efficient combination for the quantification of dry matter, protein, and starch content in fresh yam samples. Eventually, they demonstrated that the coupling of FT-NIR (collected on blended yam) and PLS represents a suitable alternative to the wet-chemistry procedure.…”