Non-destructive identification of physical damage in mung bean (Vigna radiata L.) seeds by X-ray image analysis

Authors

  • Thiago Pulici Martins Machado Universidade Federal de Viçosa
  • André Dantas de Medeiros Universidade Federal de Viçosa
  • Daniel Teixeira Pinheiro Universidade federal de Viçosa
  • Laércio Junio da Silva Universidade Federal de Viçosa
  • Denise Cunha Fernandes dos Santos Dias Universidade Federal de Viçosa

DOI:

https://doi.org/10.14393/BJ-v36n3a2020-47783

Keywords:

Radiographic images, Physical quality of seeds, Pulses.

Abstract

Global demand for pulses such as the mung bean has grown in the last years. For successful production of these crops it is necessary to use high quality seeds. Methodologies based on X-ray image analysis have been used as a complementary tool to evaluate the physical quality of seeds due to their speed and potential for automation. The aim of this study was to evaluate the efficiency of X-ray analysis for non-destructive evaluation of the physical quality of Vigna radiata seeds and to relate the variables obtained with their physiological potential. For this, seeds from eight lots were X-rayed and subsequently subject to germination test. In total, 18 physical and physiological parameters were determined. The X-ray image analysis was efficient for evaluating the internal morphology of Vigna radiata seeds and allowed the identification of various damage types. However, it was not possible to relate the physical variables to the seed quality as the lots presented similar germination percentage. Physical variables such as solidity and circularity are related to percentage of root protrusion and length of seedling hypocotyl. Low relative densities indicate deteriorated tissues, related to severe morphological damage and non-viable seeds.

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Published

2020-04-13

How to Cite

MACHADO, T.P.M., MEDEIROS, A.D. de, PINHEIRO, D.T., DA SILVA, L.J. and DIAS, D.C.F. dos S., 2020. Non-destructive identification of physical damage in mung bean (Vigna radiata L.) seeds by X-ray image analysis. Bioscience Journal [online], vol. 36, no. 3, pp. 932–941. [Accessed9 December 2022]. DOI 10.14393/BJ-v36n3a2020-47783. Available from: https://seer.ufu.br/index.php/biosciencejournal/article/view/47783.

Issue

Section

Agricultural Sciences