Phenotypic characterization of sweet potato [Ipomoea batatas (L.) Lam.] genotypes in relation to prediction of chemical quality constituents by NIRS equations

Abstract

With 5 figures and 3 tables AbstractThis study evaluates the potential of NIRS (near‐infrared reflectance spectroscopy) to predict the major constituents (starch, sugars, cellulose, proteins and minerals) of the sweet potato root. Overall, 240 accessions were morphologically described, chemically analysed and their NIR spectra recorded. No correlations were observed between aerial and underground traits, and between morphological traits and major constituents. Calibration equations, developed on 190 accessions, showed high explained variances in cross‐validation (r2cv) for starch (0.82), sugars (0.91), proteins (0.89) and minerals (0.74) but no response for cellulose (0.21). The predictions were tested on an independent set of 50 randomly selected accessions. The r2pred values for starch, sugars and proteins were, respectively, of 0.71, 0.82 and 0.87 with ratios of performance to deviation (RPD) of 2.11, 2.29 and 2.93. New calibration equations developed on 240 accessions showed improved RPD values for starch (2.65), sugars (2.75), cellulose (1.58), proteins (3.47) and minerals (2.34), indicating that larger sets could improve prediction. NIRS could be used in sweet potato breeding programmes to predict starch, sugars and proteins contents in the roots.