Potato Processing Quality Characteristics Prediction Based on Multivariate Nonlinear Regression Analysis
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    Abstract:

    Aimming to accurately detect potato processing quality, the distribution of processing quality index dry matter and reducing sugar in potato were investigated. It was concluded that potato dry matter had the ellipsoid distribution in potato and the minimum value was in the center part. The experimental data was analyzed by using quasi-Newton algorithm combined with universal global optimization method, and the regression model of dry matter content of Xisen 3 and Xisen 6 potato about testing point coordinates x, y, and z was received. The determination coefficients of regression models about dry matter content of Xisen 3 and Xisen 6 potato were 0.9099 and 0.9123, respectively, and regression models can effectively predict the potato dry matter content. The content of reducing sugar in the center of potato was the highest, and the reducing sugar content from the center to the epidermis was decreasing. The reducing sugar content in the stem of potato was lower than that on the top of potato. The determination coefficients of multivariate nonlinear regression models about two kinds of potato reducing sugar content were 0.8336 and 0.8246, respectively. The regression models could predict the contents of reducing sugar in potato. According to the analysis of experimental data, the potato close to the epidermis was higher in dry matter and lower in reducing sugar, which was suitable for processing potato chips and French fries. The average content of dry matter of Xisen 6 potato is more than 20%, and the average content of reducing sugar is less than 0.1%, which is suitable for processing. This research can help processors for effective utilization of potato for various types of processing products viz., chips, French fries and flour, and provide a theoretical basis for NIR nondestructive detection of potato processing quality.

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History
  • Received:December 28,2017
  • Revised:
  • Adopted:
  • Online: April 10,2018
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