Quantitative Evaluation of Impact Damage to Apple by Hyperspectral Imaging and Mechanical Parameters

Xu, Duohua; Wang, Huaiwen; Ji, Hongwei; Zhang, Xiaochuan; Cerbu, Camelia; Hu, Eric; Dong, Fuyuan

doi:10.1007/s12161-018-1369-9

Cited by 19 publications

(7 citation statements)

References 18 publications

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“…It was found that CARS‐PLSR had the best prediction effect on mechanical parameters. Xu et al 16 established a PLSR model by combining the spectral data collected in the wavelength range of 900–1700 nm with the mechanical parameters measured by pressure sensitive film technology, and the quantitative prediction of mechanical parameters was realized. Li et al 17 established PLSR and SVR models by combining mechanical parameters obtained from pendulum collision device and intelligent data acquisition system with reflectance, absorbance, and Kubelka‐Munk spectra.…”

Section: Introductionmentioning

confidence: 99%

Quantitative study on impact damage of honey peaches based on reflection, absorbance, and Kubelka‐Munk spectrum combined with color characteristics

Li,

Zou,

et al. 2024

Journal of Chemometrics

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Impact damage is one of the key factors affecting the quality of honey peaches. Quantitative study of impact damage is of great significance for the sorting of postharvest quality of honey peaches. In order to realize the quantitative prediction of impact damage of honey peaches, the impact damage of honey peaches was quantitatively studied based on the fusion of color characteristics with reflection spectra (R), absorbance spectra (A), and Kubelka‐Munk spectra (K‐M). The mechanical parameters of honey peaches during collision were obtained using a single pendulum collision device. Reflectance spectra and color characteristics of damaged honey peaches were obtained by a hyperspectral imaging system. The R spectra were converted into A and K‐M spectra, and the partial least squares regression (PLSR) model was built based on the three spectra and the three spectra combined with color characteristics for quantitative prediction of mechanical parameters. The results show that the prediction performance of the PLSR model is improved by combining color features with spectral information. In order to eliminate the redundant information in the spectral data, the competitive adaptive reweighted sampling (CARS) algorithm was used to select the characteristic wavelengths of the three spectra, and the selected characteristic wavelengths were fused with the color features to establish the PLSR model. The results show that the PLSR model built by the characteristic wavelengths of the A spectrum combined with the color features has the best prediction performance for the mechanical parameters. The RP value for maximum force is 0.862, and the RP value for damage depth is 0.894. The results of this study not only provide the theoretical support for the quality sorting, packaging, and transportation of honey peaches but also provide the reference for the biomechanical properties of various agricultural products.

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Section: Introductionmentioning

confidence: 99%

Quantitative study on impact damage of honey peaches based on reflection, absorbance, and Kubelka‐Munk spectrum combined with color characteristics

Li,

Zou,

et al. 2024

Journal of Chemometrics

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“…However, this method can only give the bruise area. It is not intuitively precise and intuitive compared with bruise volume (Xu et al, 2019). A more precise measurement of the bruise volume requires micro element segmentation; some ideas are provided by the development and application of numerical methods, and finite element method (FEM) is one of the excellent methods.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the bruise indexes are inseparable from the measurement of bruise volume (Opara & Pathare, 2014). The methods for evaluating fruit bruise generally include bruise volume estimating method (Kabas, 2010), pressure-sensitive film method (Xu et al, 2019), and scanning electron microscope method (Gao et al, 2021). Bruise volume estimating method manually measured the depth, length, and width of the bruised part, and brought the data into the volume estimation model to calculate the volume of the bruise.…”

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confidence: 99%

Study on the mechanism of local compression bruising in kiwifruit based on FEM

Mao,

Xie,

Wang

et al. 2023

J Food Process Engineering

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This study focuses on the relationship between local compression and local bruise volume of kiwifruits by means of finite element method (FEM). The effects of four indenter shapes and three compression directions on the local kiwifruit bruise were considered. The local bruise volume and the irregular cross section area of kiwifruit were calculated. Multi‐scale kiwifruit 3D modelling based on irregular cross‐sectional area computed by slice‐integration method. Local compression bruise was simulated by FEM. The results of the local bruise test show that the contact force and the bruise volume of kiwifruit are positive linear correlation. Comparing the simulation with the experimental, the mean absolute percentage error (MAPE) of the reconstructed model is 0.0394, and the R2 of contact force–bruise volume curve is 0.8203. The maximum equivalent forces and abrasions occur in the 0° and 90° loading directions with the square indenter has been showed by FEM results.Practical applicationsSe‐enriched kiwifruit has high nutrition and economic value. Kiwifruits are often influenced by a variety of factors and processes from harvest to consumption time. Cleaning, transport, and various processing operations including peeling and slicing in the kiwifruit industry are responsible for local bruise to kiwifruit. Therefore, understanding the mechanism of local bruise caused by local contact force of kiwifruit plays an important role in reducing kiwifruit waste in the postharvest stage. Local bruise mechanisms can be used in harvesting and post‐harvest mechanical design and product transportation and positioning equipment.

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“…22,23 However, there are few studies based on hyperspectral imaging and mechanical parameters to characterize the damage degree of fruit. Xu et al 24 measured the mechanical parameters of apples during dropping by pressure sensitive lm technology and collected hyperspectral data in the range of 900-1700 nm and established a quantitative prediction model based on the mechanical parameters of apples. Zhang et al 25 obtained the absorbed energy, maximum force and damage area during apple dropping by pressure-sensitive lm technique and highspeed camera, and Full-SVM, PCA-SVM and SPA-SVM quantitative prediction models were established.…”

Section: Introductionmentioning

confidence: 99%

Quantitative study of impact damage on yellow peaches based on reflectance, absorbance and Kubelka–Munk spectral data

Li¹,

Zhang²,

Liu³

et al. 2022

RSC Adv.

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Quantitative Evaluation of Impact Damage to Apple by Hyperspectral Imaging and Mechanical Parameters

Cited by 19 publications

References 18 publications

Quantitative study on impact damage of honey peaches based on reflection, absorbance, and Kubelka‐Munk spectrum combined with color characteristics

Quantitative study on impact damage of honey peaches based on reflection, absorbance, and Kubelka‐Munk spectrum combined with color characteristics

Study on the mechanism of local compression bruising in kiwifruit based on FEM

Quantitative study of impact damage on yellow peaches based on reflectance, absorbance and Kubelka–Munk spectral data

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