Rapid Prediction for the Firmness of Guichang Kiwifruit by Hyperspectral Imaging

被引：0

作者：

Shang J. ^{[1
,2
]}

Feng S. ^{[1
]}

Tan T. ^{[1
]}

Wu M. ^{[1
]}

Chen H. ^{[1
]}

Meng Q. ^{[1
,2
]}

机构：

[1] Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang

[2] Research Center of Nondestructive Testing for Agricultural Products of Guizhou Province, Guiyang

来源：

Science and Technology of Food Industry | 2023年 / 44卷 / 06期

关键词：

chemometrics; firmness; Guichang kiwifruit; hyperspectral imaging; nondestructive detection;

D O I：

10.13386/j.issn1002-0306.2022060168

中图分类号：

学科分类号：

摘要：

The work aimed to improve the prediction efficiency in rapid determination of the firmness of kiwifruit. A Vis/NIR (390~1030 nm) hyperspectral imaging system was applied to obtain the images of Guichang kiwifruit, and the reflective spectrum in the regions of interest on each sample was acquired. Noise from original reflective spectrum was reduced by the standard normal variation method. The competitive adaptive reweighted sampling (CARS) and the successive projection algorithm were applied to select feature variables. Finally an error back propagation neural network and a multi linear regression (MLR) model were constructed to predict the firmness of kiwifruit. A total of 35 feature variables were selected by CARS from 256 variables. The working efficiency of the final prediction model was improved by 11-fold, with the runtime dropped from 5.84 s to 0.54 s. Overall, the CARS-MLR model showed a relatively good detection capability (rc =0.95, rp =0.92, RMSEC=1.65 kg/cm2, RMSEP=1.99 kg/cm2, RPD above 2). This study demon-strated the application potential of the nondestructive hyperspectral imaging technology for fast determination of the firmness of kiwifruit. © 2023, Editorial Department of Science and Technology of Food Science. All rights reserved.

引用

页码：345 / 350

页数：5

共 26 条

[1] WANG J H, DU C, LIANG C, Et al., Extraction and antioxidant activity of polysaccharides from Guichang kiwifruit[J], Food Science, 37, 20, (2016)
[2] ZHANG C, LI M, LONG Y H, Et al., Control of soft rot in ki-wifruit by pre-harvest application of chitosan composite coating and its effect on preserving and improving kiwifruit quality[J], Food Science, 37, 22, (2016)
[3] JIN Z S, NIU B, LIU R L, Et al., Effects of drying methods on the quality of dried ki-wifruit[J], Science and Technology of Food Industry, 43, 24, (2022)
[4] CAO N N, LIU Q, PENG J, Et al., Study on quantitative detection of soluble solids and firmness of yellow peach chips by near-infrared spectroscopy[J], Food Machinery, 37, 3, pp. 51-57, (2021)
[5] HU Y L, JIANG H Z, ZHOU H P, Et al., Research progress on nondestructive detection of fruit maturity by near infrared spectroscopy and hyperspectral imaging[J], Science and Technology of Food Industry, 42, 20, (2021)
[6] DEVASSY B M, GEORGE S., Estimation of strawberry firmness using hyperspectral imaging: A comparison of regression mod-els[J], Journal of Spectral Imaging, 10, a3, pp. 1-14, (2021)
[7] XU L J, CHEN M, WANG Y C, Et al., Study on non-destructive detection method of kiwifruit sugar content based on hyperspectral imaging technology[J], Spectroscopy and Spectral Analysis, 41, 7, pp. 2188-2195, (2021)
[8] HU W H, SUN D W, BLASCO J., Rapid monitoring 1-MCP-induced modulation of sugars accumulation in ripening 'Hayward' kiwifruit by Vis/NIR hyperspectral imaging[J], Postharvest Biology and Technology, 125, (2017)
[9] ZHANG H L, ZHAN B S, PAN F, Et al., Determination of soluble solids content in oranges using visible and near infrared full transmittance hyperspectral imaging with comparative analysis of mo-dels[J], Postharvest Biology and Technology, 163, pp. 1-9, (2020)
[10] LI X L, WEI Y Z, XU J, Et al., SSC and pH for sweet assessment and maturity classification of harvested cherry fruit based on NIR hyperspectral imaging technology[J], Postharvest Biology and Technology, 143, (2018)

← 1 2 3 →