Computer Vision as a Complementary Method to Vigour Analysis in Maize Seeds

André Dantas de Medeiros *

Universidade Federal de Viçosa, Av. PH. Rolfs S/n, 36570000, Viçosa, MG, Brazil

Márcio Dias Pereira

Universidade Federal do Rio Grande do Norte, Distrito de Jundiaí, 59280000 - Macaíba, RN, Brazil

Tássia Fernanda Santos Neri Soares

Universidade Federal de Viçosa, Av. PH. Rolfs S/n, 36570000, Viçosa, MG, Brazil

Bruno Gomes Noronha

Universidade Federal do Rio Grande do Norte, Distrito de Jundiaí, 59280000 - Macaíba, RN, Brazil

Daniel Teixeira Pinheiro

Universidade Federal de Viçosa, Av. PH. Rolfs S/n, 36570000, Viçosa, MG, Brazil

*Author to whom correspondence should be addressed.


Abstract

Rapid and accurate evaluation of seed lot physiological potential is strongly desirable for the success of quality control programs conducted by seed industry. This study aims to evaluate the efficiency of computer vision through a free software of processing seedling digital images, in order to characterise maize seeds physiological potential and make comparisons among routine vigour tests, recommended for this species. So that, germination test, first germination count, seedling emergence, cold test, germination speed index and electrical conductivity test were used for featuring the physiological potential of maize seed lots. Then, these tests' results were compared with data collected, using an image analysis technique, through SAPL® software. Seedlings growth were evaluated by photographs on the seventh day and obtained the values of the primary root, coleoptile, and whole seedlings length, as well as growth, uniformity, vigour and corrected vigour indices. The computerised images analysis of seedlings through SAPL® is a consistent and promising alternative for evaluating the physiological potential of maize seeds. Its efficiency was proved in this study, being equivalent to what verified in routine tests for vigour determination.

Keywords: Free software, seed technology, vigour, Zea mays


How to Cite

Dantas de Medeiros, André, Márcio Dias Pereira, Tássia Fernanda Santos Neri Soares, Bruno Gomes Noronha, and Daniel Teixeira Pinheiro. 2018. “Computer Vision As a Complementary Method to Vigour Analysis in Maize Seeds”. Journal of Experimental Agriculture International 25 (5):1-8. https://doi.org/10.9734/JEAI/2018/43464.

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