Quantitative Detection of the Quality of Peach Fruit during Low Temperature Storage Based on Near Infrared Spectroscopy

被引：0
|
作者：
Zhang P. [1 ,2 ,3 ]
Wang Y. [1 ,2 ,3 ]
Li G. [1 ,2 ,3 ]
Shan Y. [1 ,2 ,3 ]
Su D. [4 ]
Zhu X. [1 ,2 ,3 ]
机构：
[1] Longping Branch, Graduate School of Hunan University, Changsha
[2] Agricultural Products Processing Institute, Hunan Academy of Agricultural Sciences, Changsha
[3] Hunan Key Lab of Fruits & Vegetables Storage, Processing, Quality and Safety, Changsha
[4] Fruit and Vegetable Processing and Quality Safety Hunan International Joint Laboratory, Changsha
来源：
Journal of Chinese Institute of Food Science and Technology | 2021年 / 21卷 / 05期
关键词：
Chemometrics; Low temperature storage; Near infrared spectroscopy; Non-destructive testing; Peach fruit;
D O I：
10.16429/j.1009-7848.2021.05.042
中图分类号：
学科分类号：
摘要：
In this study, soluble solids content (SSC), total acid (TA), sugar-acid ratio and firmness of postharvest peach fruits were determined by near infrared spectroscopy. The effects of different spectral pretreatment methods on the models were discussed. Partial least squares (PLS) models of the physical-chemical properties of peach fruit were established and predicted. Before modeling, variance analysis and Pearson correlation analysis were used to study the relationship between several indexes and storage time. For SSC, TA, sugar-acid ratio and firmness, the correlation coefficient of calibration set (Rc) of SSC, TA, sugar-acid ratio and firmness optimal PLS model were 0.93, 0.69, 0.74 and 0.97, respectively, and correlation coefficients of the validation set (Rp) were 0.79, 0.69, 0.68 and 0.95, respectively. The root mean square error of cross validation (RMSECV) were 0.56, 0.11, 4.24 and 8.81, respectively. The root mean square error of prediction (RMSEP) were 0.89, 0.10, 6.02 and 16.22, respectively. The results showed that near infrared spectroscopy was feasible for the rapid detection of SSC and firmness of peach fruit, while the quantitative models of TA and sugar-acid ratio needed to be further optimized. This study provides a technical reference for the non-destructive determining and quality control of juicy peach during low-temperature storage in practical production. © 2021, Editorial Office of Journal of CIFST. All right reserved.
引用
收藏
页码：355 / 362
页数：7
相关论文
共 28 条
  • [1] CHEN H, AN X J, YU M L, Et al., Effect of combined heat and 1-MCP treatment on the quality and antioxidant level of peach fruit during storage, Postharvest Biology and Technology, 145, pp. 193-202, (2018)
  • [2] 4
  • [3] 3
  • [4] 4
  • [5] PASQUINI C., Near infrared spectroscopy: A mature analytical technique with new perspectives-A review, Analytica Chimica ACTA, 1026, pp. 8-36, (2018)
  • [6] SHEELA K, KNADEL M, NORGAARD T, Et al., Predicting the dry bulk density of soils across Denmark: Comparison of single-parameter, multi-parameter, and vis-NIR based models, Geoderma, 361, (2020)
  • [7] PINO-TORRES C, MASPOCH S, CASTILLO-FELICES R, Et al., Evaluation of NIR and raman spectroscopies for the quality analytical control of a solid pharmaceutical formulation with three active ingredients, Microchemical Journal, 154, 5, (2019)
  • [8] CAYUELA J A, GARCIA J F., Sorting olive oil based on alpha-tocopherol and total tocopherol content using near-infra-red spectroscopy (NIRS) analysis, Journal of Food Engineering, 202, pp. 79-88, (2017)
  • [9] GRAHAM S F, HAUGHEY S A, ERVIN R M, Et al., The application of near-infrared (NIR) and Raman spectroscopy to detect adulteration of oil used in animal feed production, Food Chemistry, 132, 3, pp. 1161-1614, (2012)
  • [10] RODIONOVA O Y, BALYKLOVA K S, TITOVA A V, Et al., Application of NIR spectroscopy and chemometrics for revealing of the 'high quality fakes' among the medicines, Forensic Chemistry, 8, pp. 82-89, (2018)
123