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| Near-Infrared Spectroscopy Prediction of the Optimal Harvest Date for Autumn Moon Pear: Considering the Correction of Ambient Light Changes and Inter-Instrument Differences |
| SUN Xu-dong1, LONG Tao1, WANG Jia-hua2, FENG Shao-ran3, ZENG Ti-wei4, XIE Dong-fu1, FU Wei1 |
1. School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
2. School of Food Science and Engineering, Wuhan University of Light Industry, Wuhan 430023, China
3. Beijing Sunshine Yishida Technology Co., Ltd., Beijing 100021, China
4. School of Information and Software Engineering, East China Jiaotong University, Nanchang 330013, China
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Abstract Timely harvesting is an important scientific exploration to improve the high-quality rate of autumn moon pear fruit harvest and storage quality. The influence of light changes in the orchard environment and inter-instrument differences can lead to a decline in the performance of the mathematical model established in the laboratory when predicting the quality of fruits on the tree. This study simultaneously considers the influence of light changes in the orchard environment and inter-instrument differences. It utilizes the global model and external parameter orthogonalization (EPO) method to correct for the influence of environmental light and inter-instrument differences, thereby predicting the optimal harvest date of autumn moon pears. The experiment used 599 autumn moon pear samples collected between 2019 and 2020 for modeling, 80 autumn moon pears as difference matrix samples, and 120 autumn moon pears collected from July to September 2023 as the prediction set. After global model and EPO correction, the predictive ability of the partial least squares regression (PLSR) model was improved, with the global model being the best and EPO being the second. After global model correction, the model of instrument A predicted the data of instrument B, and the coefficient of determination increased from 0.11 to 0.68, and the root mean square error of prediction (RMSEP) of soluble solid content (SSC) decreased from 1.2% to 0.69%. After simultaneous correction of inter-instrument differences and ambient light changes using the global model, the coefficient of determination increased from 0.46 to 0.79, and RMSEP decreased from 1.23% to 0.70%. The best model corrected by the global model, was used to predict the optimal harvest date, and the prediction results from the handheld instrument were consistent with the destructive analysis results. The optimal harvest period of the experimental orchard was August 26, 2023, and 55% of the sampled autumn moon pears had an SSC content exceeding 12%, meeting the harvest standard. The results demonstrate that global model correction can effectively mitigate the impact of inter-instrument differences and ambient light changes on the model's predictive performance. At the same time, this study verified that harvest date prediction can improve the harvest quality of autumn moon pears, providing a feasible reference for non-destructive prediction of the optimal harvest date of autumn moon pears.
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Received: 2025-01-06
Accepted: 2025-06-06
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