Journal of Agricultural Big Data >
Modeling Table Grapes: Physicochemical Indexes and Sensory Quality Based on PCA-GA-SVR during Transportation Process
Received date: 2022-01-14
Online published: 2022-06-29
The regionality and seasonality of fresh fruits and vegetables mean that this produce is subjected to logistics and transportation processes after harvesting and before reaching the hands of consumers. During these processes, several external factors cause physiological changes in fresh fruits and vegetables, which will affect their taste. This paper considers the case of table grapes, and conducts simulation experiments and sensory experiments in the laboratory based on monitoring of the actual transportation process. After obtaining a suitable dataset, a model of the relationship between the physicochemical indicators and the sensory quality of the grapes is constructed based on an improved support vector regression (SVR) algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the physical and chemical indicators, and a genetic algorithm (GA) is used to optimize the SVR model parameters. An examination of three transportation modes (normal-temperature transportation, cold-storage transportation, and cold-chain transportation) and mixed dataset testing shows that the improved PCA-GA-SVR model offers significantly improved accuracy and precision, reflecting the nonlinear mapping relationship between the physicochemical indexes and sensory quality of table grapes. The mean absolute error, mean squared error, and root mean squared error achieved by the PCA-GA-SVR model are all less than 0.5, and the R2 values are all greater than 0.96. This study shows that the relationship between physical and chemical index data and sensory quality is not significantly affected by the transportation mode. The sensory quality evaluation model proposed in this study can be applied to any transportation mode to assist the quality of fresh agricultural products in the control and management of the logistics process.
Miao He, Xin Li, Zhiqiang Zhu, Jianying Feng . Modeling Table Grapes: Physicochemical Indexes and Sensory Quality Based on PCA-GA-SVR during Transportation Process[J]. Journal of Agricultural Big Data, 2022 , 4(1) : 98 -108 . DOI: 10.19788/j.issn.2096-6369.220111
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