期刊
JOURNAL OF FOOD ENGINEERING
卷 108, 期 1, 页码 194-200出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jfoodeng.2011.05.002
关键词
Non-destructive; Hyperspectral; Maturity; PLS; MLR; PCA
资金
- Canadian International Development Agency
- AICRP on Post Harvest Technology, India
Banana fruit quality and maturity stages were studied at three different temperatures, viz., 20, 25, and 30 degrees C by using hyperspectral imaging technique in the visible and near infrared (400-1000 nm) regions. The quality parameters like moisture content, firmness and total soluble solids were determined and correlated with the spectral data. The spectral data were analyzed using the partial least square analysis. The optimal wavelengths were selected using predicted residual error sum of squares. The principal component analysis was also used to test the variability of the observed data. By using multiple linear regressions (MLR), models were established based on the optimal wave lengths to predict the quality attributes. The coefficient of determination was found to be 0.85, 0.87, and 0.91 for total soluble solids, moisture and firmness of the banana fruits, respectively. The change in TSS and firmness of banana fruits stored at different temperatures, viz, 20, 25, and 30 degrees C during the ripening process followed the polynomial relationships and the change in moisture content followed a linear relationship at different maturity stages. (C) 2011 Elsevier Ltd. All rights reserved.
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