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Compression damage mechanism and damage detection of Aronia melanocarpa based on nuclear magnetic resonance tests

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Abstract

In the process of mechanization production and processing of Aronia melanocarpa, mechanical damage will be caused by compression, which is difficult to identify. Therefore, it is of great significance to explore the mechanism of fruit damage and detect the internal damage. In this study, the relationship between indentation area ratio and fruit damage degree was established. The effects of different factors on fruit damage were investigated through compression tests. The NMR (nuclear magnetic resonance) technology was used to detected and analyze the changes of internal moisture content before and after fruit compression, and the effects of different loading conditions on internal damage of fruit were further investigated. The compression test showed that the fruit was moderately or above damaged when the fruit deformation energy was greater than 6.8457 × 10−3 J and the corresponding indentation area ratio was greater than 0.2683. The loading displacement had a great effect on fruit damage, and an appropriate reduction of fruit moisture content could effectively reduce the damage. The NMR test showed that the brightness of the pseudo-color image decreased significantly after compression, and the moisture in the fruit was lost and migrated. With the increase of loading displacement, the change in signal amplitude of unit mass of bound water increased from 1.584 to 8.435 AU, and that of free water increased from 4.519 to 37.240 AU, indicating that the moisture loss increased and the fruit damage worsens. This study analyzed the effects of different parameters on fruit damage, and provides a new method for the evaluation and detection of fruit damage of Aronia melanocarpa.

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References

  1. W. Zhang, Study on tissue culture and rapid propagation of Aronia melanocarpa. Contemp. Hortic. 45(14), 1–3 (2022). https://doi.org/10.14051/j.cnki.xdyy.2022.14.051

    Article  CAS  Google Scholar 

  2. J. Guo, K. Zhang, J. Pang, Advances in research on functional components and health care effects of Aronia melanocarpa. Beverage Ind. 23(01), 68–71 (2020). https://doi.org/10.3969/j.issn.1007-7871.2020.01.021

    Article  Google Scholar 

  3. E.Y. Platonova, M.V. Shaposhnikov, H.-Y. Lee, J.-H. Lee, K.-J. Min, A. Moskalev, Black chokeberry (Aronia melanocarpa) extracts in terms of geroprotector criteria. Trends Food Sci. Technol. 114, 570–584 (2021). https://doi.org/10.1016/j.tifs.2021.06.020

    Article  CAS  Google Scholar 

  4. L. Wang, X. Li, F. Gao, Y. Liu, S. Lang, C. Wang, D. Zhang, Effect of ultrasound combined with exogenous GABA treatment on polyphenolic metabolites and antioxidant activity of mung bean during germination. Ultrason. Sonochem.. Sonochem. (2023). https://doi.org/10.1016/j.ultsonch.2023.106311

    Article  Google Scholar 

  5. S. Yang, D. Wang, Y. Gao, Functional research progress and application of Aronia melanocarpa. Food Res Dev 42(13), 206–213 (2021). https://doi.org/10.12161/j.issn.1005-6521.2021.13.030

    Article  CAS  Google Scholar 

  6. F. Li, Study on planting and management techniques of Aronia melanocarpa. Seed Sci. Technol. 38(23), 61–62 (2020). https://doi.org/10.3969/j.issn.1005-2690.2020.23.029

    Article  Google Scholar 

  7. Z. Li, F. Miao, J. Andrews, Mechanical models of compression and impact on fresh fruits. Compreh. Rev. Food Sci. Food Saf. 16(6), 1296–1312 (2017). https://doi.org/10.1111/1541-4337.12296

    Article  Google Scholar 

  8. N.K. Mahanti, R. Pandiselvam, A. Kothakota, P.S. Ishwarya, S.K. Chakraborty, M. Kumar, D. Cozzolino, Emerging non-destructive imaging techniques for fruit damage detection: Image processing and analysis. Trends Food Sci. Technol. 120, 418–438 (2022). https://doi.org/10.1016/j.tifs.2021.12.021

    Article  CAS  Google Scholar 

  9. Q.T. Pham, N.-S. Liou, Investigating texture and mechanical properties of Asian pear flesh by compression tests. J. Mech. Sci. Technol. 31(8), 3671–3674 (2017). https://doi.org/10.1007/s12206-017-0707-y

    Article  Google Scholar 

  10. Y. Yang, S. Yu, X. Li, H. Zhang, A. Xiao, Y. Liu, G. Su, Study on the effect of different harvest periods on the static pressure damage of Korla fragrant pear. Packag. Food Mach. 39(04), 6–11 (2021). https://doi.org/10.3969/j.issn.1005-1295.2021.04.002`

    Article  Google Scholar 

  11. Y. Li, X. Du, J. Wang, L. Chai, Mechanical properties of apple picking damage. Agric. Eng. 8(06), 77–80 (2018). https://doi.org/10.3969/j.issn.2095-1795.2018.06.021

    Article  CAS  Google Scholar 

  12. Z. Zheng, J. Chen, W. Tian, C. Zhang, Z. An, Finite element analysis of blueberry stack damage. J. Food Process Eng (2021). https://doi.org/10.1111/jfpe.13840

    Article  Google Scholar 

  13. B. Lu, X. Wang, C. Hu, P. Zhang, Compressive mechanical properties of jujube in brittle ripening stage under different loading speeds. Jiangsu Agric. Sci. 45(21), 244–247 (2017). https://doi.org/10.15889/j.issn.1002-1302.2017.21.069

    Article  Google Scholar 

  14. Y. Lv, L. Wang, Blueberry mechanical damage test design and test research. J. Agric. Mech. Res. 40(12), 199–202 + 211 (2018). https://doi.org/10.13427/j.cnki.njyi.2018.12.038

  15. X. Liu, Z. Cao, L. Yang, H. Chen, Y. Zhang, Research on damage properties of apples based on static compression combined with the finite element method. Foods (2022). https://doi.org/10.3390/foods11131851

  16. J. Zhu, D. Zhu, L. Wang, K. Xue, J. Liao, S. Zhang, Effects of compression damage on mechanical behavior and quality attributes of apple fruit. Food Sci. Technol. Res. 28(1), 53–65 (2022). https://doi.org/10.3136/fstr.FSTR-D-21-00178

    Article  CAS  Google Scholar 

  17. Y. Bao, C. Yang, Y. Zhao, X. Liu, Y. Guo, Collision injury assessment of mechanical harvesting blueberry fruit based on collision deformation energy. Trans. Chin. Soc. Agric. Eng. 33(16), 283–292 (2017). https://doi.org/10.11975/j.issn.1002-6819.2017.16.037

    Article  Google Scholar 

  18. J. Hou, W. Hu, L. Zhang, Z. Ren, Q. Sun, W. Wang, Mechanical properties of mulberry fruit under compression and nuclear magnetic resonance tests. J. Food Process Eng (2021). https://doi.org/10.1111/jfpe.13856

    Article  Google Scholar 

  19. M. Li, Y. Chen, Y. Geng, F. Liu, L. Guo, X. Wang, Convenient use of low field nuclear magnetic resonance to determine the drying kinetics and predict the quality properties of mulberries dried in hot-blast air. LWT (2021). https://doi.org/10.1016/j.lwt.2020.110402

    Article  Google Scholar 

  20. W. Liu, T. Liu, T. Zeng, R. Ma, Y. Cheng, Y. Zheng, J. Qiu, L. Qi, Prediction of internal mechanical damage in pineapple compression using finite element method based on Hooke’s and Hertz’s laws. Sci. Hortic.Hortic. (2023). https://doi.org/10.1016/j.scienta.2022.111592

    Article  Google Scholar 

  21. X. Cao, F. Zhang, D. Zhao, D. Zhu, J. Li, Effects of freezing conditions on quality changes in blueberries. J. Sci. Food Agric. 98(12), 4673–4679 (2018). https://doi.org/10.1002/jsfa.9000

    Article  CAS  PubMed  Google Scholar 

  22. Y. Wang, S. Ji, H. Dai, X. Kong, J. Hao, S. Wang, X. Zhou, Y. Zhao, B. Wei, S. Cheng, Q. Zhou, Changes in membrane lipid metabolism accompany pitting in blueberry during refrigeration and subsequent storage at room temperature. Front. Plant Sci. 10, 829 (2019). https://doi.org/10.3389/fpls.2019.00829

    Article  PubMed  PubMed Central  Google Scholar 

  23. S. Qiao, Y. Tian, P. Song, K. He, S. Song, Analysis and detection of decayed blueberry by low field nuclear magnetic resonance and imaging. Postharvest Biol. Technol. (2019). https://doi.org/10.1016/j.postharvbio.2019.110951

    Article  Google Scholar 

  24. M. Suchanek, M. Kordulska, Z. Olejniczak, H. Figiel, K. Turek, Application of low-field MRI for quality assessment of ‘Conference’ pears stored under controlled atmosphere conditions. Postharvest Biol. Technol. 124, 100–106 (2017). https://doi.org/10.1016/j.postharvbio.2016.10.010

    Article  Google Scholar 

  25. L. Zhang, M.J. McCarthy, NMR relaxometry study of development of freeze damage in mandarin orange. J. Sci. Food Agric. 96(9), 3133–3139 (2016). https://doi.org/10.1002/jsfa.7491

    Article  CAS  PubMed  Google Scholar 

  26. M.S. Razavi, A. Asghari, M. Azadbakh, H.-A. Shamsabadi, Analyzing the pear bruised volume after static loading by magnetic resonance imaging (MRI). Sci. Hortic.Hortic. 229, 33–39 (2018). https://doi.org/10.1016/j.scienta.2017.10.011

    Article  Google Scholar 

  27. Y. He, Q. Xiao, X. Bai, L. Zhou, F. Liu, C. Zhang, Recent progress of nondestructive techniques for fruits damage inspection: a review. Crit. Rev. Food Sci. Nutr.Nutr. 62(20), 5476–5494 (2022). https://doi.org/10.1080/10408398.2021.1885342

    Article  Google Scholar 

  28. X. Yue, Y. Bai, Z. Wang, P. Song, Low-field nuclear magnetic resonance of maize seed germination process under salt stress. Trans. Chin. Soc. Agric. Eng. 36(24), 292–300 (2020). https://doi.org/10.11975/j.issn.1002-6819.2020.24.034

    Article  Google Scholar 

  29. X. Zhang, S. Bai, W. Jin, M. Yu, J. Yan, Z. Zhang, Experimental study on material characteristics of red jujube in dwarf dense planting mode. J. Chin. Agric. Mech. 40(8), 68–72 (2019). https://doi.org/10.13733/j.jcam.issn.2095-5553.2019.08.12

    Article  CAS  Google Scholar 

  30. S. Wen, J. Zhang, Z. He, M. Wang, G. Cui, Y. Cui, Study on physical and mechanical properties of olive fruit. J. Agric. Mech. Res. 44(05), 132–139 (2022). https://doi.org/10.13427/j.cnki.njyi.2022.05.025

    Article  Google Scholar 

  31. P. Song, Y. Peng, G. Wang, P. Song, K. Wang, T. Yang, Determination of water flow in maize seeds during germination by low field NMR. Trans. Chin. Soc. Agric. Eng. 34(10), 274–281 (2018). https://doi.org/10.11975/j.issn.1002-6819.2018.10.035

    Article  Google Scholar 

  32. Q. Zeng, B. Bie, Q. Guo, Y. Yuan, Q. Han, X. Han, M. Chen, X. Zhang, Y. Yang, M. Liu, P. Liu, H. Deng, X. Zhou, Hyperpolarized Xe NMR signal advancement by metal-organic framework entrapment in aqueous solution. Proc. Natl. Acad. Sci. U.S.A. 117(30), 17558–17563 (2020). https://doi.org/10.1073/pnas.2004121117

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. M. Li, B. Li, W. Zhang, Rapid and non-invasive detection and imaging of the hydrocolloid-injected prawns with low-field NMR and MRI. Food Chem. 242, 16–21 (2018). https://doi.org/10.1016/j.foodchem.2017.08.086

    Article  CAS  PubMed  Google Scholar 

  34. X. An, Z. Li, M. Zude-Sasse, F. Tchuenbou-Magaia, Y. Yang, Characterization of textural failure mechanics of strawberry fruit. J. Food Eng. (2020). https://doi.org/10.1016/j.jfoodeng.2020.110016

    Article  Google Scholar 

  35. R. Bian, R. Cao, L. Zhao, Q. Liu, D. Ren, Changes in moisture status of Cololabis saira during salting and drying by low-field nuclear magnetic resonance. J. Food Saf. Qual. 8(05), 1698–1703 (2017). https://doi.org/10.19812/j.cnki.jfsq11-5956/ts.2017.05.029

    Article  Google Scholar 

  36. F. Xu, X. Jin, L. Zhang, X.D. Chen, Investigation on water status and distribution in broccoli and the effects of drying on water status using NMR and MRI methods. Food Res. Int. 96, 191–197 (2017). https://doi.org/10.1016/j.foodres.2017.03.041

    Article  CAS  PubMed  Google Scholar 

  37. Y. Zhang, J.-H. Zhao, Y. Ding, H.-W. Xiao, S.S. Sablani, Y. Nie, S.-J. Wu, X.-M. Tang, Changes in the vitamin C content of mango with water state and ice crystals under state/phase transitions during frozen storage. J. Food Eng. 222, 49–53 (2018). https://doi.org/10.1016/j.jfoodeng.2017.11.003

    Article  CAS  Google Scholar 

  38. Q. Shicheng, T. Youwen, W. Qinghu, S. Shiyuan, S. Ping, Nondestructive detection of decayed blueberry based on information fusion of hyperspectral imaging (HSI) and low-field nuclear magnetic resonance (LF-NMR). Comput. Electron. Agric.. Electron. Agric. (2021). https://doi.org/10.1016/j.compag.2021.106100

    Article  Google Scholar 

  39. Y. Sun, M. Zhang, A.S. Mujumdar, D. Yu, Pulse-spouted microwave freeze drying of raspberry: control of moisture using ANN model aided by LF-NMR. J. Food Eng. (2021). https://doi.org/10.1016/j.jfoodeng.2020.110354

    Article  Google Scholar 

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Acknowledgements

This research was supported by Natural Science Foundation of Liaoning Province of China (LJKMZ20221002), the authors thank relevant scholars for their assistance in the literature.

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Authors and Affiliations

  1. Shenyang Agricultural University, Shenyang, China

    Junming Hou, Zhenhu He, Ziyuan Tang, Deyu Liu, Zhenghang Long, Ziang Zhu, Ren Zhang & Wei Wang

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  1. Junming Hou
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  2. Zhenhu He
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  3. Ziyuan Tang
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  8. Wei Wang
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Contributions

JH: Funding acquisition; project administration; resources; supervision; writing—original draft; writing—review and editing. ZH: Methodology; writing—original draft; writing—review and editing. ZT: writing—review and editing; data curation; data analysis. DL: Data analysis; validation. ZL: Data curation; software. ZZ: Investigation; software. RZ: Conceptualization. WW: Supervision.

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Correspondence to Junming Hou.

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Hou, J., He, Z., Tang, Z. et al. Compression damage mechanism and damage detection of Aronia melanocarpa based on nuclear magnetic resonance tests. Food Measure 18, 1090–1106 (2024). https://doi.org/10.1007/s11694-023-02213-y

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