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Rapid Assessment of Some Physical Parameters of Mangoes Using Monochrome Computer Vision

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Abstract

Mango, the kind of fruits, is a nutraceutical, most popular, unique and high economic value fruit. Quality assessment (sorting/grading) is a must-do step to ensure the desired values (economical, nutraceutical) of mangoes before marketing (local/abroad). A study of real-time physical characterization system for mangoes is, therefore, essential. Using monochrome computer vision (MCV), some physical properties of Chausa and Dahsehari fruits important for design and development of machines were determined. The external diameters [length (L), width (W), thickness (T)] evaluated by MCV were compared with the results obtained from manual method (i.e., digital vernier calipers) using linear regression, paired t test and difference plot method. Coefficient of determination (R2) of diameters (L, W, T) was found between 0.991 and 0.950 for both types of fruits. Difference plot showed differences in diameters were normally distributed and major differences were located between the 95% limits of agreement (i.e., d − 1.92 SD and d + 1.96). In addition, the other parameters (area, perimeter, etc.) of fruits were also evaluated using MCV system and correlated with the mass/volume, using linear (simple and multi) regression technique. Proposed technique, thus, can be applied for the rapid and reliable assessment of mangoes.

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Acknowledgements

This work was supported by the National Agricultural Innovation Project, Indian Council of Agricultural Research, through its subproject entitled “Development of non-destructive system for evaluation of microbial and physico-chemical quality parameters of mango” (C1030).

Funding

Financial support under the World Bank funded National Agricultural Innovation Sub-Project on “Development of non-destructive system for evaluation of microbial and physic-chemical quality parameters of mango” being implemented at the Indian Agricultural Research Institute is duly acknowledged (C1030).

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Authors and Affiliations

  1. Division of Food Science and Post-Harvest Technology, IARI, New Delhi, 110 012, India

    Krishna Kumar Patel & Abhijit Kar

  2. Department of Post-Harvest Engineering and Technology, Aligarh Muslim University, Aligarh, 202002, India

    Krishna Kumar Patel & M. A. Khan

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  1. Krishna Kumar Patel
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Correspondence to Krishna Kumar Patel.

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Patel, K.K., Kar, A. & Khan, M.A. Rapid Assessment of Some Physical Parameters of Mangoes Using Monochrome Computer Vision. Agric Res 10, 468–482 (2021). https://doi.org/10.1007/s40003-020-00517-9

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