Mechanical damage characteristics and nondestructive testing techniques of fruits: a review

HOU, Junming; HE, Zhenhu; LIU, Deyu; ZHU, Ziang; LONG, Zhenghang; YUE, Xiang; WANG, Wei

doi:10.1590/fst.001823

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Food Science and Technology

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Review Article • Food Sci. Technol 43 • 2023 • https://doi.org/10.1590/fst.001823 copy

Mechanical damage characteristics and nondestructive testing techniques of fruits: a review

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Fruits will be subjected inevitably to various external forces in the process of harvesting, transportation, processing, and storage, which will cause mechanical damage. The research on mechanical properties and damage mechanisms of fruit can effectively control its loss. In this study, fruits are divided into different types according to their morphology and structure. The impact, vibration, static pressure, and other mechanical damage on fruits are studied. It is important to identify the damaged parts of fruit after damage quickly and accurately. Therefore, this study analyzes the application of nondestructive testing technologies such as spectral detection technology, NMR (nuclear magnetic resonance) detection technology, and acoustic and electrical characteristics detection technology in fruit damage detection.

Keywords:
fruit; mechanical damage; nondestructive testing; impact characteristic; vibration harvesting

Softening degree	Deformation energy (E/×10^-3 J)	Damage evaluation
No change	(0,0.68)	No damage
mild	(0.68,2.72)	Slightly damaged
moderate	(2072,7.86)	Moderate damage
severe	(7.86,10.4)	Severe damage
rupture	10.4	rupture

Fruit species	Select factors	The damage index	Conclusion
Blueberries	Angle of fruiting plate	Fruit deformation energy	When the distance between the fruit and the fruiting plate was close to 600 mm and the Angle of the fruiting plate was close to l5°, the damage degree was minimal.
	Drop height
	The fruit quality
Litchi	Drop height	The compressed volume	The damage sensitivity decreases with the increase in drop height. 'Nuomici' is more resistant to impact damage than 'Guiwei' when the drop height is changed from 600 mm to 800 mm.
Grapes	Impact velocity	Coefficient of collision recovery	When the collision speed was less than 1.5 m/s, the damage inside the grape was small. When the collision velocity was 1.5 m/s, the maximum stress inside the grape was 0.19 MPa, and the grape began to suffer great damage.
Wolfberry	Drop height	Fruit bruising rate	When the drop height is 0.2-0.5 m, the impact Angle is 10-30°, and the impact materials are wood, foam board, and nylon board, the fruit will not be damaged.
	The impact Angle
	Material of impact
Pomegranate	Drop height	Sensitivity to damage	The bruised area and volume of pomegranate fruits increased significantly with the increase in drop height and cold storage time.
Kiwi fruit	Drop height	Sensitivity to damage	Damage is more likely to occur in the horizontal direction, and the damage volume and sensitivity errors measured by simulation and experiment are less than 17.1% and 18.3%, respectively.

Fruit	Vibration parameters	Conclusion	Reference
Cherry	Frequency	The speed of fruit removal was faster at high frequencies, and the damage rate was the lowest (47.1%) at 14 Hz.	Zhou et al. (2016a)
Apricot	Frequency	When the almond tree was excited at 11.56 Hz, the acceleration value of each detection point reached the maximum.	San et al. (2018)San, J., Yang, H., Wang, X., River, N., Guo, W., & Hou, S. (2018). Effects of vibration mode and frequency on vibration harvesting of apricot trees. Transactions of the Chinese Society of Agricultural Engineering, 34(08), 10-17. http://dx.doi.org/10.11975/j.issn.1002-6819.2018.08.002. http://dx.doi.org/10.11975/j.issn.1002-6...
Red Jujube	Frequency amplitude	When the amplitude was 7 mm and the frequency was 17 Hz, the force transfer effect was better in the process of vibrational harvesting.	Fu et al. (2017)Fu, W., Zhang, Z., Liu, Y., Pan, J., Cui, J., Ding, K., & Zhang, H. (2017). Simulation experiment in lab on force transfer effect of jujube under vibration excitation. Transactions of the Chinese Society of Agricultural Engineering, 33(17), 65-72. http://dx.doi.org/10.11975/j.issn.1002-6819.2017.17.009. http://dx.doi.org/10.11975/j.issn.1002-6...
Red Jujube	Frequency	When the excitation frequency was 16.5-17.4 Hz, the net harvest rate was more than 90% and the damage rate was less than 8%.	Ding et al. (2019)Ding, K., Zhang, B., Diao, X., Zhang, H., Fu, H., & Za, K. (2019). Red harvester vibration device vibration frequency optimization and test. Journal of Agricultural Mechanization Research, 41(3), 21-33. http://dx.doi.org/10.13427/j.cnki.njyi.2019.03.004. http://dx.doi.org/10.13427/j.cnki.njyi.2...
Winter Jujube	Frequency	At frequencies of 15 Hz, 20 Hz, and 25 Hz, the proportion of the number of fruit dropped in the rotation type was 81%, 66%, and 78%, respectively.	Fu et al. (2018)

Fruit	Damage index	Conclusion	Reference
Apple	Sensitivity to damage	In the range of impact velocity where damage occurs (0.75-1.5 m /s), the damage sensitivity increases with the increase of impact velocity.	Stropek & Gołacki (2016)Stropek, Z., & Gołacki, K. (2016). Quantity assessment of plastic deformation energy under impact loading conditions of selected apple cultivars. Postharvest Biology and Technology, 115, 9-17. http://dx.doi.org/10.1016/j.postharvbio.2015.12.011. http://dx.doi.org/10.1016/j.postharvbio....
	Damage threshold	The damage threshold and anti-damage properties of apples can quickly and effectively evaluate the degree of fruit damage.	Stopa et al. (2018)Stopa, R., Szyjewicz, D., Komarnicki, P., & Kuta, Ł. (2018). Determining the resistance to mechanical damage of apples under impact loads. Postharvest Biology and Technology, 146, 79-89. http://dx.doi.org/10.1016/j.postharvbio.2018.08.016. http://dx.doi.org/10.1016/j.postharvbio....
	Damage volume	The impact damage of the apple decreased with the increase of the horizontal velocity of the impact material, and the maximum damage of the apple and rubber plate could be reduced to 51.43% of that of the rubber plate at rest.	Hu et al. (2021)Hu, G., Bu, L., Zhang, E., Kou, Q., Cheng, Y., Zhao, J., & Chen, J. (2021). Apple two anisotropic mechanical properties and drop test study. Journal of Agricultural Mechanization Research, 43(4), 154-160. http://dx.doi.org/10.13427/j.cnki.njyi.2021.04.028. http://dx.doi.org/10.13427/j.cnki.njyi.2...
Pear	Sensitivity to damage	The peak deformation of the two varieties was 42% and 39% of the scratch depth on average. The contact width was 146% and 135% of the scratch width on average.	Stropek & Gołacki. (2020)Stropek, Z., & Gołacki, K. (2020). Bruise susceptibility and energy dissipation analysis in pears under impact loading conditions. Postharvest Biology and Technology, 163, 111120. http://dx.doi.org/10.1016/j.postharvbio.2020.111120. http://dx.doi.org/10.1016/j.postharvbio....

Detection object	Spectral range (nm)	Detection method	Evaluation	Reference
Apple	1000-2500	PLS	94.4%	Keresztes et al. (2016)Keresztes, J. C., Goodarzi, M., & Saeys, W. (2016). Real-time pixel based early apple bruise detection using short wave infrared hyperspectral imaging in combination with calibration and glare correction techniques. Food Control, 66, 215-226. http://dx.doi.org/10.1016/j.foodcont.2016.02.007. http://dx.doi.org/10.1016/j.foodcont.201...
Blueberry	950-1650	SVM	94%	Jiang et al. (2016)Jiang, Y., Li, C., & Takeda, F. (2016). Nondestructive detection and quantification of blueberry bruising using Near-infrared (NIR) hyperspectral reflectance imaging. Scientific Reports, 6(1), 35679. http://dx.doi.org/10.1038/srep35679. PMid:27767050. http://dx.doi.org/10.1038/srep35679...
Pear	400-1000	PCA	87.5%	Fang et al. (2020)Fang, Y., Yang, F., & Li, X. (2020). Detection of damage on the surface of korla fragrant pear using hyperspectral images. Laser & Optoelectronics Progress, 57(14), 173-179. http://dx.doi.org/10.3788/LOP57.141017. http://dx.doi.org/10.3788/LOP57.141017...
Strawberry	650-720	SVM	96.91%	Liu et al. (2018a)Liu, Q., Sun, K., Peng, J., Xing, M., Pan, L., & Tu, K. (2018a). Identification of bruise and fungi contamination in strawberries using hyperspectral imaging technology and multivariate analysis. Food Analytical Methods, 11(5), 1518-1527. http://dx.doi.org/10.1007/s12161-017-1136-3. http://dx.doi.org/10.1007/s12161-017-113...
Jujube	918-1678	PCA	100%	Wu et al. (2015)Wu, L., Wang, S., Kang, N., He, J., & He, X. (2015). Non-destructive detection of defects in Zizphus jujube Mill cv.Lingwu changzao based on near-infrared hyperspectral imaging. Transactions of the Chinese Society of Agricultural Engineering, 31(20), 281-286. http://dx.doi.org/10.11975/j.issn.1002-6819.2015.20.039. http://dx.doi.org/10.11975/j.issn.1002-6...

Detection object	Spectral range (nm)	Detection method	Evaluation	Reference
Peach	350-1150	LS-SVM	100%	Liu et al. (2016b) Liu, Y., Wu, M., Sun, X., Zhu, D., Li, Y., & Zhang, Z. (2016b). Simultaneous detection of surface deficiency and soluble solids content for Amygdalus persica by online visible near infrared transmittance spectroscopy. Transactions of the Chinese Society of Agricultural Engineering, 32(6), 289-295. http://dx.doi.org/10.11975/j.issn.1002-6819.2016.06.040. http://dx.doi.org/10.11975/j.issn.1002-6...
Peach	900-2500	PLS	82.26%	Huang et al. (2017)Huang, L., Meng, L., Zhu, N., & Wu, D. (2017). A primary study on forecasting the days before decay of peach fruit using near-infrared spectroscopy and electronic nose techniques. Postharvest Biology and Technology, 133, 104-112. http://dx.doi.org/10.1016/j.postharvbio.2017.07.014. http://dx.doi.org/10.1016/j.postharvbio....
Plum	4000-12500	PCA	100%,98.75%	Zhao et al. (2016)Zhao, Z., Wang, Y., Guo, D., Niu, X., Cheng, W., & Gu, Y. (2016). Identification of plum fruit Browning by near-infrared spectroscopy. Spectroscopy and Spectral Analysis, 36(7), 2089-2093. http://dx.doi.org/10.3964/j.issn.1000-0593(2016)07-2089-05. http://dx.doi.org/10.3964/j.issn.1000-05...
Citrus	200-900	SVM	>90.8%	Zhang et al. (2018)
Kiwifruit	400-1000	PCA	qualitative	Wang et al. (2020d)
Apple	350-1100	PLS	qualitative	Grandón et al. (2019)

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[1] *Corresponding author:syndhjm@syau.edu.cn