Abstract
[Objective] To achieve precise non-destructive detection and sorting of blueberry quality. [Methods] An online evaluation system for blueberry quality based on near-infrared spectroscopy and visible light image fusion is designed.The system consists of a fruit box chain conveyor module, a linear array image detection module, a near-infrared spectroscopy detection module, and a control system. A diffuse reflection optical path is designed by the near-infrared spectroscopy detection module, and a partial least squares regression model is established to predict the soluble solids content in blueberries through S-G convolution smoothing, second-order derivative connection preprocessing, and sequential projection algorithm for feature variable extraction. [Results] The developed system shows an average relative error of 0.093 in determining the individual diameter of blueberries and the accuracy of 91.85% in measuring fruit diameter uniformity. The predicted correlation coefficients for superior, first-class, and second-class blueberries are 0.843 4, 0.782 2, and 0.723 7, respectively, with predicted root mean square errors of 0.831 6, 0.951 0, and 1.070 5, respectively. [Conclusion] The overall evaluation accuracy of the decision tree quality evaluation model for blueberries, integrating both external and internal quality, reaches 89.55%.
Publication Date
1-13-2026
First Page
82
Last Page
90
DOI
10.13652/j.spjx.1003.5788.2025.80160
Recommended Citation
Shihu, XUN; Jiawei, XIAN; Weina, WANG; Linying, SHI; Qiuxi, CHEN; and Wei, FAN
(2026)
"Design and application of an online evaluation system for blueberry quality based on spectral image fusion technology,"
Food and Machinery: Vol. 41:
Iss.
12, Article 11.
DOI: 10.13652/j.spjx.1003.5788.2025.80160
Available at:
https://www.ifoodmm.cn/journal/vol41/iss12/11
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