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Article

Quantitative Evaluation of Color, Firmness, and Soluble Solid Content of Korla Fragrant Pears via IRIV and LS-SVM

by 1,2,*, 1,2, 1,2, 1,2, 1,2 and 3
1
College of Mechanicaland Electrical Engineering, Tarim University, Alar 843300, China
2
Agricultural Engineering Key Laboratory at Universities of Education Department of Xinjiang Uygur Autonomous Region, Tarim University, Alar 843300, China
3
College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, China
*
Author to whom correspondence should be addressed.
Academic Editor: Isabel Lara
Received: 21 June 2021 / Revised: 23 July 2021 / Accepted: 26 July 2021 / Published: 31 July 2021
Customers pay significant attention to the organoleptic and physicochemical attributes of their food with the improvement of their living standards. In this work, near infrared hyperspectral technology was used to evaluate the one-color parameter, a*, firmness, and soluble solid content (SSC) of Korla fragrant pears. Moreover, iteratively retaining informative variables (IRIV) and least square support vector machine (LS-SVM) were applied together to construct evaluating models for their quality parameters. A set of 200 samples was chosen and its hyperspectral data were acquired by using a hyperspectral imaging system. Optimal spectral preprocessing methods were selected to obtain out partial least square regression models (PLSRs). The results show that the combination of multiplicative scatter correction (MSC) and Savitsky-Golay (S-G) is the most effective spectral preprocessing method to evaluate the quality parameters of the fruit. Different characteristic wavelengths were selected to evaluate the a* value, the firmness, and the SSC of the Korla fragrant pears, respectively, after the 6 iterations. These values were obtained via IRIV and the reverse elimination method. The correlation coefficients of the validation set of the a* value, the firmness, and the SSC measure 0.927, 0.948, and 0.953, respectively. Furthermore, the values of the regression error weight, γ, and the kernel function parameter, σ2, for the same parameters measure (8.67 × 104, 1.21 × 103), (1.45 × 104, 2.93 × 104), and (2.37 × 105, 3.80 × 103), respectively. This study demonstrates that the combination of LS-SVM and IRIV can be used to evaluate the a* value, the firmness, and the SSC of Korla fragrant pears to define their grade. View Full-Text
Keywords: IRIV; LS-SVM; Korla fragrant pear; quality parameter; evaluation IRIV; LS-SVM; Korla fragrant pear; quality parameter; evaluation
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MDPI and ACS Style

Liu, Y.; Wang, T.; Su, R.; Hu, C.; Chen, F.; Cheng, J. Quantitative Evaluation of Color, Firmness, and Soluble Solid Content of Korla Fragrant Pears via IRIV and LS-SVM. Agriculture 2021, 11, 731. https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture11080731

AMA Style

Liu Y, Wang T, Su R, Hu C, Chen F, Cheng J. Quantitative Evaluation of Color, Firmness, and Soluble Solid Content of Korla Fragrant Pears via IRIV and LS-SVM. Agriculture. 2021; 11(8):731. https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture11080731

Chicago/Turabian Style

Liu, Yuanyuan, Tongzhao Wang, Rong Su, Can Hu, Fei Chen, and Junhu Cheng. 2021. "Quantitative Evaluation of Color, Firmness, and Soluble Solid Content of Korla Fragrant Pears via IRIV and LS-SVM" Agriculture 11, no. 8: 731. https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture11080731

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