Non-destructive Classification for Maturity of Pomelo CV. Tubtim Siam

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นางสาวทิพย์วรรณ สวัสดิ์พานิช
รศ.ดร.อนุพันธ์ เทอดวงศ์วรกุล
อ.ดร.แก้วกานต์ พวงสมบัติ
อ.ดร.อาทิตย์ พวงสมบัติ


This research studied application of near infrared spectroscopy (NIRS) technique, visible (VIS) light reflectance and fruit frequency after tapping for evaluation of maturity of pomelo cv. Tubtim Siam. In this research equations to predict soluble solids content (SSC) and to discriminate samples into maturity classes using 140 smaples from 4 groups of different maturity. After equation development, it was found that prediction of SSC using the equation derived by partial least squares regression technique resulted in low accuracy (regression coefficient = 0.6 standard error of prediction = 0.54 °Brix). Regarding discriminant analysis to develop maturity classifying equation, the results showed that the optimal classifying equation was based on NIR absorbance data pretreated by standard normal variate (SNV), which was averaged from four measurements around a sample, in combination with VIS reflectance spectra pretreated with SNV. The optimal classifying equation was able to separate all samples into correct maturity groups with accuracy of 100%.


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Post-harvest and food engineering


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