Optimization and compensation of models on tomato soluble solids content assessment with online Vis/NIRS diffuse transmission system
文献类型： 外文期刊
作者： Yang, Yi 1 ; Zhao, Chunjiang 1 ; Huang, Wenqian 1 ; Tian, Xi 1 ; Fan, Shuxiang 1 ; Wang, Qingyan 1 ; Li, Jiangbo 1 ;
作者机构： 1.Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China; Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China; Natl Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China
关键词： Tomato; Soluble solids content; Online detection; Fruit orientation; Compensation model
期刊名称：INFRARED PHYSICS & TECHNOLOGY （ 影响因子：2.997； 五年影响因子：2.962 ）
ISSN： 1350-4495
年卷期： 2022 年 121 卷
页码：
收录情况： SCI
摘要： This study developed an efficient and compensable model for predicting soluble solids content (SSC) of tomato, based on the self-developed online Vis/NIRS diffuse transmission system. The fruit stem-calyx axis horizontal coupled with suitable light settings (path and intensity) was determined as the best measurement parameters, which significantly reduce the stray light and also optimize the light propagation inside tomato. The pretreatment method of Savitzky-Golay smoothing (SGS) combined with multiplicative scatter correction (MSC) could eliminate the spectral difference between samples and the inherent system noise in the raw spectral of tomato. The partial least squares regression (PLSR) model based on the 22 key wavelengths selected by competitive adaptive reweighted sampling (CARS) had better model performance than the full wavelength model. Finally, the CARS-PLSR model was further optimized by compensating physiological traits of height and weight with Rp of 0.91 and RMSEp of 0.17%. Our results in the present study demonstrated the potential of using online Vis/NIRS diffuse transmission spectra combined with model optimization and compensation as a valuable method for tomato SSC assessment.
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