Utilizing full transmittance Vis/NIR spectroscopy for online detection of soluble solids and anthocyanin content in blood oranges
文献类型： 外文期刊
作者： Liu, Xuefeng 1 ; Tian, Xi 2 ; Hu, Deyu 4 ; Yuan, Xiangcheng 1 ; Ma, Xiaoli 1 ; Xiang, Pingwei 1 ; Liao, Shumei 1 ;
作者机构： 1.Chongqing Three Gorges Acad Agr Sci, Chongqing 404155, Peoples R China
2.Univ Sci & Technol Beijing, Res Inst Biol & Agr, Beijing 100096, Peoples R China
3.Beijing Acad Agr & Forestry Sci, Res Ctr Intelligent Equipment, Beijing 100097, Peoples R China
4.Chongqing Wanzhou Dist Econ Crops Dev Ctr, Chongqing 404120, Peoples R China
关键词： Blood oranges; Soluble solids content; Anthocyanin content; Online detection; Full transmittance Vis/NIR spectroscopy
期刊名称：JOURNAL OF FOOD COMPOSITION AND ANALYSIS （ 影响因子：4.6； 五年影响因子：4.6 ）
ISSN： 0889-1575
年卷期： 2025 年 145 卷
页码：
收录情况： SCI
摘要： Traditional methods for detecting soluble solids content (SSC) and anthocyanin content required damaging samples and were time-consuming. In this study, multi-point full transmittance Vis/NIR spectra combined with variable selection method were used to nondestructive detect the SSC and anthocyanin content of blood oranges. Firstly, three different preprocessing methods, including 9-point moving average smoothing (MAS), mean normalization (MN), and standard normal variate transformation (SNV), were employed to improve spectral quality. Then, characteristic wavelengths for SSC and anthocyanin content prediction were selected by successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and bootstrapping soft shrinkage (BOSS). Finally, partial least squares regression (PLSR) prediction models for SSC and anthocyanin content were constructed. The results indicated that the preprocessed spectra based on the SNV algorithm yielded the best prediction performance. The PLSR model established using 28 characteristic wavelengths selected by CARS had the highest prediction accuracy for SSC in blood oranges, with Rpre= 0.862, RMSEP= 0.558 degrees Brix, and RPD= 1.965. The PLSR model based on 10 characteristic wavelengths selected by CARS showed the best prediction performance for anthocyanin content in blood oranges, with Rpre= 0.845, RMSEP= 1.824 mg & sdot;100 ml- 1, and RPD= 1.790. This proves that multi-point full transmittance Vis/NIR spectroscopy can be effectively used for the detection of SSC and anthocyanin content in blood oranges.
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