Prediction of α-Solanine and α-Chaconine in Potato Tubers from Hunter Color Values and VIS/NIR Spectra

Autor: Shimeles Tilahun, Hee Sung An, In Geun Hwang, Jong Hang Choi, Min Woo Baek, Han Ryul Choi, Do Su Park, Cheon Soon Jeong
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Food Quality, Vol 2020 (2020)
Druh dokumentu: article
ISSN: 0146-9428
1745-4557
DOI: 10.1155/2020/8884219
Popis: The glycoalkaloids contents of potato tubers are usually measured by the destructive analysis that consumes time and requires expensive high-performance equipment. This study was carried out to determine the possibility of nondestructive estimation of α-solanine and α-chaconine content in potato tubers. Visible/near-infrared (VIS/NIR) spectra, color values, and the reference α-solanine and α-chaconine were measured from 180 tubers of ‘Atlantic’ and ‘Trent’ potato cultivars with eight replications at two-week intervals during the storage up to ten weeks. The partial least square (PLS) regression method was used to develop models correlating color and spectra data to the measured reference data. Regression coefficient (r) between color variables (Hunter a∗, a∗/b∗, and (a∗/b∗)2) and the actual measured values of a-solanine and a-chaconine content were 0.74, 0.62, and 0.62 and 0.70, 0.58, and 0.57, respectively, for the prediction set. Concurrently, equations were developed from color variables in multiple regression with r-values of 0.76 and 0.71 for α-solanine and α-chaconine, respectively. Additionally, the selected PLS model of VIS/NIR spectra had promising predictive power for α-solanine and α-chaconine with r-values of 0.68 and 0.63, respectively, between measured and predicted samples. Taken together, although it requires further studies to improve the prediction power of the developed models, the results of this study revealed the possibility of using VIS/NIR spectra and color variables for the prediction of α-solanine and α-chaconine contents from intact unpeeled potato tubers with chemical-free, fast, and cheap assessment methods.
Databáze: Directory of Open Access Journals
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