Chickpea seed vigor evaluated by computerized seedling analysis
DOI:
https://doi.org/10.5433/1679-0359.2021v42n1p71Keywords:
Cicer arietinum L., Image analysis, Physiological quality, Seedling length.Abstract
Computerized seedling analysis is a promising tool for assessing seed vigor, providing reliable and less subjective results. The aim of this study was to define a method for evaluating the vigor of chickpea seeds through computerized image analysis, using the Seedling Analysis System (Sistema de Análise de Plântula - SAPL®) as a basis. Two chickpea cultivars were evaluated, consisting of five seed lots of cv. BRS Aleppo and four seed lots of cv. Cícero. Test were performed on the seeds of each cultivar for initial characterization of the physiological potential of the lots, and the results were compared with the determinations made via SAPL®. The results showed high correlations between the variables obtained from computerized analysis and from traditional vigor tests, especially for the close relationship between the cold test and low temperature germination test with the corrected vigor index (r > 0.9) evaluated on the fourth day after the beginning of the test. The total length of seedlings, length of the primary root, and growth and corrected vigor indices obtained through computerized analysis of seedlings on the 4th day after sowing allowed separation of the lots regarding vigor. Computerized analysis of seedlings using SAPL® is effective in determining the vigor of chickpea seed lots.Downloads
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References
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Caldeira, C. M., Carvalho, M. L. M., Oliveira, J. A., Coelho, S. V. B., & Kataoka, V. Y. (2014). Vigor de sementes de girassol pela análise computadorizada de plântulas. Científica, 42(4), 346-353. doi: 10. 15361/1984-5529.2014v42n4p346-353
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Castan, D. O. C., Gomes, F. G., Jr., & Marcos, J., Fº. (2018). Vigor-S, a new system for evaluating the physiological potential of maize seeds. Scientia Agricola, 75(2), 167-172. doi: 10.1590/1678-992x-2016-0401
Chiquito, A. A., Gomes, F. G., Jr., & Marcos, J., Fº. (2012). Assessment of physiological potential of cucumber seeds using the software Seedling Vigor Imaging System® (SVIS®). Revista Brasileira de Sementes, 34(2), 255-263. doi: 10.1590/S0101-31222012000200010
Dias, D. C. F. S., & Alvarenga, E. M. (1999). Teste de germinação a baixa temperatura. In F. C. Krzyzanowski, R. D. Vieira, J. B. França-Neto (Ed.). Vigor de sementes: conceitos e testes (cap.7, pp. 1-4). Londrina, PR: Abrates.
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Leão-Araújo, E. F., Santos, J. F., Silva, C. B., Marcos, J., Fº., & Vieira, R. D. (2017). Controlled deterioration test and use of the Seed Vigor Imaging System (SVIS®) to evaluate the physiological potential of crambe seeds. Journal of Seed Science, 39(4), 393-400. doi: 10.1590/2317-1545v39n4177911
Lima, J. M. E., Smiderle, O. J., Oliveira, J. A., & Carvalho, M. L. M. (2018). Técnicas de análise de imagem para caracterização da qualidade de sementes de paricarana (Bowdichia virgilioides Kunth). Ciência Florestal, 28(3), 1202-1216. doi: 10.5902/1980509833367
Maguire, J. D. (1962). Speed of germination - aid in selection and evaluation for seedling emergence and vigor. Crop Science, 2(2), 176-177. doi: 10.2135/cropsci1962.0011183X000200020033x
Marchi, J. L., & Cicero, S. M. (2017). Use of the software Seed Vigor Imaging System (SVIS®) for assessing vigor of carrot seeds. Scientia Agricola, 74(6), 469-473. doi: 10.1590/1678-992x-2016-0220
Marcos, J., Fº. (2015). Fisiologia de sementes de plantas cultivadas. Londrina, PR: Abrates.
Medeiros, A. D., & Pereira, M. D. (2018). SAPL®: a free software for determining the physiological potential in soybean seeds. Pesquisa Agropecuária Tropical, 48(3), 222-228. doi: 10.1590/1983-40632018v4852 340
Medeiros, A. D., Pereira, M. D., & Silva, J. A. (2018). Processamento digital de imagens na determinação do vigor de sementes de milho. Revista Brasileira de Ciências Agrárias, 13(3), 1-7. doi: 10.5039/agraria. v13i3a5540
Medeiros, A. D., Pereira, M. D., Silva, I. R. F., Capobiango, N. P., & Flores, M. E. P. (2019a). Vigor of maize seeds determined by a free image analysis system. Revista Ciência Agronômica, 50(4), 616-624. doi: 10. 5935/1806-6690.20190073
Medeiros, A. D., Silva, L. J., Capobiango, N. P., Fialho, C. A., & Dias, D. C. F. S. (2019b). Assessing the physiological quality of common bean seeds using the Vigor-S® system and its relation to the accelerated aging test. Journal of Seed Science, 41(2), 187-195. doi: 10.1590/2317-1545v41n2211401
Medeiros, A. D., Silva, J. A., Oliveira, A. M. S., & Dias, D. C. F. S. (2020). High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images. Annals of the Brazilian Academy of Sciences, 92(1), 1-17. doi: 10.1590/0001-3765202020190209
Ministério da Agricultura, Pecuária e Abastecimento (2009). Regras para análise de sementes. Brasília: MAPA/ACS. Recuperado de http://www.agricultura.gov.br/assuntos/insumos-agropecuarios/arquivos-publicacoes-insumos/2946_regras_analise__sementes.pdf
Ministério da Agricultura, Pecuária e Abastecimento (2012). Portaria Nº 111, de 4 de setembro de 2012. Secretaria de Defesa Agropecuária. Brasília: MAPA. Recuperado de http://www.lex.com.br/legis 2369 4506_PORTARIA_N_111_DE_4_DE_SETEMBRO_DE_2012.aspx
Nakagawa, J. (1999). Testes de vigor baseados no desempenho das plântulas. In F. C. Krzyzanowski, R. D. Vieira, J. B. França-Neto (Eds.), Vigor de sementes: conceitos e testes (cap.2, pp. 1-24). Londrina, PR: Abrates.
Nascimento, W. M., & Silva, P. P. (2019). Grão-de-bico: nova aposta do agronegócio brasileiro. Revista Seed News, 23(3), 18-22. Recuperado de https://seednews.com.br/artigos/2969-grao-de-bico-nova-aposta-do-agronegocio-brasileiro-edicao-maio-2019
R Core Team (2018). R: A Language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Recuperado de http://www.R-project.org/
Sako, Y., McDonald, M. B., Fujimura, K., Evans, A. F., & Bennett, M. A. (2001). A system for automated seed vigour assessment. Seed Science and Technology, 29(3), 625-636. Recuperado em https://www. eurofinsus.com/media/162083/seed-vigor-imaging-system.pdf
Silva, L. J., Medeiros, A. D., & Oliveira, A. M. S. (2019a). SeedCalc, a new automated R software tool for germination and seedling length data processing. Journal of Seed Science, 41(2), 250-257. doi: 10.1590/ 2317-1545v42n2217267
Silva, J. A., Medeiros, A. D., Pinheiro, D. T., Pereira, M. D., Silva, L. J., Ribeiro, J. P., Gomes, I. R. F. (2019b). Semi-automated Phenotyping of soybean seedling and its relation with physiological seed quality. Journal of Agriculture Science, 11(16), 1-10. doi: 10.5539/jas.v11n16p1
Singh, V. K., Khan, A. W., Jaganathan, D., Thudi, M., Roorkiwal, M., Takagi, H., Varshney, R. K. (2016). QTL‐seq for rapid identification of candidate genes for 100‐seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea. Plant Biotechnology Journal, 14(11), 2110-2119. doi: 10.1111 /pbi.12567
Trujillo, H. A., Gomes, F. G., Jr., & Cicero, S. M. (2019). Digital images of seedling for evaluating coffee seed vigor. Journal of Seed Science, 41(1), 60-68. doi: 10.1590/2317-1545v41n1204651
Yagushi, J. T., Costa, D. S., & França, J. B., Neto. (2014). Saturated salt accelerated aging and computerized analysis of seedling images to evaluate soybean seed performance. Journal of Seed Science, 36(2), 213-221. doi: 10.1590/2317-1545v32n2935
Barbosa, R. M., Vieira, B. G. T. L., Gomes, F. G., Jr., & Vieira, R. D. (2016). Image analysis and peanut seeds performance during the production process. Científica, 44(3), 412-420. doi: 10.15361/1984-5529.2016 v44n3p412-420
Brunes, A. P., Araújo, A. S., Dias, L. W., Antoniolli, J., Gadotti, G. I., & Villela, F. A. (2019). Rice seeds vigor through image processing of seedlings. Ciência Rural, 49(8), 1-6. doi: 10.1590/0103-8478cr2018 0107
Brunes, A. P., Araújo, A. S., Dias, L. W., Villela, F. A., & Aumonde, T. Z. (2016). Seedling length in wheat determined by image processing using mathematical tools. Revista Ciência Agronômica, 47(2), 374-379. doi: 10.5935/1806-6690.20160044
Caldeira, C. M., Carvalho, M. L. M., Oliveira, J. A., Coelho, S. V. B., & Kataoka, V. Y. (2014). Vigor de sementes de girassol pela análise computadorizada de plântulas. Científica, 42(4), 346-353. doi: 10. 15361/1984-5529.2014v42n4p346-353
Camargo, A. C., Favero, B. T., Morzelle, M. C., Franchin, M., Alvarez-Parrilla, E., de la Rosa, L. A.,... Schwember, A. R. (2019). Is chickpea a potential substitute for soybean? Phenolic bioactives and potential health benefits. International Journal of Molecular Sciences, 20(11), 1-42. doi: 10.3390/ijms20112644
Castan, D. O. C., Gomes, F. G., Jr., & Marcos, J., Fº. (2018). Vigor-S, a new system for evaluating the physiological potential of maize seeds. Scientia Agricola, 75(2), 167-172. doi: 10.1590/1678-992x-2016-0401
Chiquito, A. A., Gomes, F. G., Jr., & Marcos, J., Fº. (2012). Assessment of physiological potential of cucumber seeds using the software Seedling Vigor Imaging System® (SVIS®). Revista Brasileira de Sementes, 34(2), 255-263. doi: 10.1590/S0101-31222012000200010
Dias, D. C. F. S., & Alvarenga, E. M. (1999). Teste de germinação a baixa temperatura. In F. C. Krzyzanowski, R. D. Vieira, J. B. França-Neto (Ed.). Vigor de sementes: conceitos e testes (cap.7, pp. 1-4). Londrina, PR: Abrates.
Gomes, F. G., Jr., Chamma, H. M. C. P., & Cicero, S. M. (2014). Automated image analysis of seedlings for vigor evaluation of common bean seeds. Acta Scientiarum. Agronomy, 36(2), 195-200. doi: 10.4025/ actasciagron.v36i2.21957
Leão-Araújo, E. F., Santos, J. F., Silva, C. B., Marcos, J., Fº., & Vieira, R. D. (2017). Controlled deterioration test and use of the Seed Vigor Imaging System (SVIS®) to evaluate the physiological potential of crambe seeds. Journal of Seed Science, 39(4), 393-400. doi: 10.1590/2317-1545v39n4177911
Lima, J. M. E., Smiderle, O. J., Oliveira, J. A., & Carvalho, M. L. M. (2018). Técnicas de análise de imagem para caracterização da qualidade de sementes de paricarana (Bowdichia virgilioides Kunth). Ciência Florestal, 28(3), 1202-1216. doi: 10.5902/1980509833367
Maguire, J. D. (1962). Speed of germination - aid in selection and evaluation for seedling emergence and vigor. Crop Science, 2(2), 176-177. doi: 10.2135/cropsci1962.0011183X000200020033x
Marchi, J. L., & Cicero, S. M. (2017). Use of the software Seed Vigor Imaging System (SVIS®) for assessing vigor of carrot seeds. Scientia Agricola, 74(6), 469-473. doi: 10.1590/1678-992x-2016-0220
Marcos, J., Fº. (2015). Fisiologia de sementes de plantas cultivadas. Londrina, PR: Abrates.
Medeiros, A. D., & Pereira, M. D. (2018). SAPL®: a free software for determining the physiological potential in soybean seeds. Pesquisa Agropecuária Tropical, 48(3), 222-228. doi: 10.1590/1983-40632018v4852 340
Medeiros, A. D., Pereira, M. D., & Silva, J. A. (2018). Processamento digital de imagens na determinação do vigor de sementes de milho. Revista Brasileira de Ciências Agrárias, 13(3), 1-7. doi: 10.5039/agraria. v13i3a5540
Medeiros, A. D., Pereira, M. D., Silva, I. R. F., Capobiango, N. P., & Flores, M. E. P. (2019a). Vigor of maize seeds determined by a free image analysis system. Revista Ciência Agronômica, 50(4), 616-624. doi: 10. 5935/1806-6690.20190073
Medeiros, A. D., Silva, L. J., Capobiango, N. P., Fialho, C. A., & Dias, D. C. F. S. (2019b). Assessing the physiological quality of common bean seeds using the Vigor-S® system and its relation to the accelerated aging test. Journal of Seed Science, 41(2), 187-195. doi: 10.1590/2317-1545v41n2211401
Medeiros, A. D., Silva, J. A., Oliveira, A. M. S., & Dias, D. C. F. S. (2020). High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images. Annals of the Brazilian Academy of Sciences, 92(1), 1-17. doi: 10.1590/0001-3765202020190209
Ministério da Agricultura, Pecuária e Abastecimento (2009). Regras para análise de sementes. Brasília: MAPA/ACS. Recuperado de http://www.agricultura.gov.br/assuntos/insumos-agropecuarios/arquivos-publicacoes-insumos/2946_regras_analise__sementes.pdf
Ministério da Agricultura, Pecuária e Abastecimento (2012). Portaria Nº 111, de 4 de setembro de 2012. Secretaria de Defesa Agropecuária. Brasília: MAPA. Recuperado de http://www.lex.com.br/legis 2369 4506_PORTARIA_N_111_DE_4_DE_SETEMBRO_DE_2012.aspx
Nakagawa, J. (1999). Testes de vigor baseados no desempenho das plântulas. In F. C. Krzyzanowski, R. D. Vieira, J. B. França-Neto (Eds.), Vigor de sementes: conceitos e testes (cap.2, pp. 1-24). Londrina, PR: Abrates.
Nascimento, W. M., & Silva, P. P. (2019). Grão-de-bico: nova aposta do agronegócio brasileiro. Revista Seed News, 23(3), 18-22. Recuperado de https://seednews.com.br/artigos/2969-grao-de-bico-nova-aposta-do-agronegocio-brasileiro-edicao-maio-2019
R Core Team (2018). R: A Language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Recuperado de http://www.R-project.org/
Sako, Y., McDonald, M. B., Fujimura, K., Evans, A. F., & Bennett, M. A. (2001). A system for automated seed vigour assessment. Seed Science and Technology, 29(3), 625-636. Recuperado em https://www. eurofinsus.com/media/162083/seed-vigor-imaging-system.pdf
Silva, L. J., Medeiros, A. D., & Oliveira, A. M. S. (2019a). SeedCalc, a new automated R software tool for germination and seedling length data processing. Journal of Seed Science, 41(2), 250-257. doi: 10.1590/ 2317-1545v42n2217267
Silva, J. A., Medeiros, A. D., Pinheiro, D. T., Pereira, M. D., Silva, L. J., Ribeiro, J. P., Gomes, I. R. F. (2019b). Semi-automated Phenotyping of soybean seedling and its relation with physiological seed quality. Journal of Agriculture Science, 11(16), 1-10. doi: 10.5539/jas.v11n16p1
Singh, V. K., Khan, A. W., Jaganathan, D., Thudi, M., Roorkiwal, M., Takagi, H., Varshney, R. K. (2016). QTL‐seq for rapid identification of candidate genes for 100‐seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea. Plant Biotechnology Journal, 14(11), 2110-2119. doi: 10.1111 /pbi.12567
Trujillo, H. A., Gomes, F. G., Jr., & Cicero, S. M. (2019). Digital images of seedling for evaluating coffee seed vigor. Journal of Seed Science, 41(1), 60-68. doi: 10.1590/2317-1545v41n1204651
Yagushi, J. T., Costa, D. S., & França, J. B., Neto. (2014). Saturated salt accelerated aging and computerized analysis of seedling images to evaluate soybean seed performance. Journal of Seed Science, 36(2), 213-221. doi: 10.1590/2317-1545v32n2935
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2021-01-19
How to Cite
Araújo, J. de O., Dias, D. C. F. dos S., Medeiros, A. D. de, Silva, L. J. da, & Nascimento, W. M. (2021). Chickpea seed vigor evaluated by computerized seedling analysis. Semina: Ciências Agrárias, 42(1), 71–86. https://doi.org/10.5433/1679-0359.2021v42n1p71
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