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Application of Natural Frequencies for Prediction of Apple Texture Based on Partial Least Squares Regression

  • Jumin Hou , Yonghai Sun EMAIL logo , Fangyuan Chen , Lu Wang , Xue Bai , Minghui Wang and Qian Mao
Published/Copyright: August 12, 2017

Abstract

Experimental modal analysis was performed to identify natural frequencies to predict the texture of inhomogeneous tissues of apple (Malus domestina cv. ‘Golden Delicious’). Partial least squares calibration models based on natural frequencies with or without weight and density were created for predicting apple texture representing by yield gradient and initial modulus. The prediction models shown good prediction ability for texture of skin but impossible for flesh (all determination coefficients for skin models were more than 0.5 while for flesh models less than 0.5). A nondestructive and rapid method was provided to evaluate the fruit texture.

Acknowledgments

This work was supported by National Natural Science Foundation of China (grant numbers 3127 1861) and Talent Development Foundation of Jilin Province. The authors wish to thank the Institute of Agro-food Technology, Jilin Academy of Agricultural Sciences and Changchun University.

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Supplemental Material

The online version of this article offers supplementary material (DOI: https://doi.org/10.1515/ijfe-2016-0390).


Published Online: 2017-8-12

© 2017 Walter de Gruyter GmbH, Berlin/Boston

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