Characterization and phenological prediction of tropical black bean genotypes

Authors

  • Héctor Daniel Inurreta-Aguirre Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700 , Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700
  • Oscar Hugo Tosquy-Valle Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700 , Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700
  • Víctor Manuel Rodríguez-Moreno Campo Experimental Pabellón-INIFAP. Carretera Aguascalientes-Zacatecas km 32.5, Pabellón de Arteaga, Aguascalientes, México. CP. 20678 , Campo Experimental Pabellón-INIFAP. Carretera Aguascalientes-Zacatecas km 32.5, Pabellón de Arteaga, Aguascalientes, México. CP. 20678
  • Francisco Javier Ibarra-Perez Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700 , Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700
  • Rigoberto Zetina-Lezama Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700 , Campo Experimental Cotaxtla-INIFAP. Carretera Veracruz-Córdoba km 34.5, Medellín de Bravo, Veracruz, México. CP. 91700

DOI:

https://doi.org/10.29312/remexca.v17i2.4244

Keywords:

Phaseolus vulgaris L., canopy temperature, heat units, stages of crop development

Abstract

The phenological characterization of black bean varieties generated by the Bean Program of the National Institute of Forestry, Agricultural and Livestock Research for southeastern Mexico is conducted by quantifying the number of days after sowing required to reach the different stages of development. This characterization is imprecise for contrasting environments. This study aimed to characterize nine advanced lines and two varieties of opaque black beans by using the number of days after sowing and the index of growing degree-days necessary to achieve the stages of flowering and physiological maturity and to compare the accuracy of the number of days after sowing and the growing degree-days to predict phenology. The number of days after sowing and the growing degree-days required by the genotypes to reach the flowering and physiological maturity stages were quantified across nine environments in southeastern Mexico. The ability of five mixed models was evaluated, considering the number of days after sowing, growing degree-days and environment as fixed effects and genotype as a random effect, to predict the phenological stages of the lines and varieties. Four lines were earlier than Negro Grijalva (1 892 growing degree-days), with an average of 1 859 growing degree-days; in contrast, four others obtained an average of 1 902 growing degree-days, higher than Negro Grijalva but lower than Negro Comapa (1 920 growing degree-days) and only one line was later than both varieties (1 976 growing degree-days). The best model for predicting phenology was the one that considered only the growing degree-days, regardless of the environment. It was concluded that growing degree-days are more accurate than the number of days after sowing for predicting the flowering and physiological maturity of the genotypes in the different evaluation environments.

Downloads

Download data is not yet available.

References

Ahmad, L.; Habib-Kanth, R.; Parvaze, S. and Sheraz-Mahdi, S. 2017. Growing degree days to forecast crop stages. In: Ahmad, L.; Habib Kanth, R.; Parvaze, S. and Sheraz Mahdi, S. Ed. Experimental agrometeorology: a practical manual. Springer, Cham. Cham, Switzerland. 95-98 pp.

Akaike, H. 1998. A Bayesian analysis of the minimum AIC procedure. In: Parzen, E.; Tanabe, K. and Kitagawa, G. Ed. Selected papers of hirotugu akaike. Springer, New York, NY. 275-280 pp.

Bonhomme, R. 2000. Bases and limits to using ‘degree day’ units. Eur. J. Agron. 13(1):1-10. https://doi.org/10.1016/S1161-0301(00)00058-7.

Fernández, F.; Gepts, P. y López, M. 1986. Etapas de desarrollo de la planta de frijol común (Phaseolus vulgaris L.). Centro Internacional de Agricultura Tropical (CIAT). Cali, Colombia. 7-33 pp.

FIRA. 2016. Fideicomiso Instituido en Relación a la Agricultura. Panorama agroalimentario. Dirección de Investigación y Evaluación Económica y Sectorial. Frijol. FIRA. México. 11-13 pp.

López, S. E.; Tosquy, V. O. H.; Acosta, G. J. A.; Villar, S. B. and Ugalde, A. F. J. 2011b. Drought resistance of tropical dry black bean lines and cultivars. Trop. Subtrop. Agroecosyst. 14(2):749-755.

López, S. E.; Tosquy, V. O. H.; Jiménez, H. Y.; Salinas, P. R. A.; Villar, S. B. y Acosta, G. J. A. 2012. Rendimiento y adaptación de la variedad de frijol Negro Comapa en dos regiones de México. Revista Fitotecnia Mexicana. 35(4):309-315. https://doi.org/10.35196/rfm.2012.4.309.

Neukam, D.; Ahrends, H.; Luig, A.; Manderscheid, R. and Kage, H. 2016. Integrating wheat canopy temperatures in crop system models. Agronomy 6(1):7-19. https://doi.org/10.3390/agronomy6010007.

Paleari, L.; Vesely, F. M.; Ravasi, R. A.; Movedi, E.; Tartarini, S.; Invernizzi, M. and Confalonieri, R. 2020. Analysis of the similarity between in silico ideotypes and phenotypic profiles to support cultivar recommendation-a case study on Phaseolus vulgaris. L. Agronomy 10(11):1733-20. https://doi.org/10.3390/agronomy10111733.

Rai, A.; Sharma, V. and Heitholt, J. 2020. Dry bean [Phaseolus vulgaris L.] growth and yield response to variable irrigation in the arid to semi-arid climate. Sustainability 12(9):3851-25. https://doi.org/10.3390/su12093851.

Salazar-Gutierrez, M. R.; Johnson, J.; Chaves-Cordoba, B. and Hoogenboom, G. 2013. Relationship of base temperature to development of winter wheat. International Journal of Plant Production. 7(4):741-762. https://dx.doi.org/10.22069/ijpp.2013.1267.

Seguin, B. and Itier, B. 1983. Using midday surface temperature to estimate daily evaporation from satellite thermal IR data. Int. J. Remote Sens. 4(2):371-383. https://doi.org/10.1080/01431168308948554.

Tosquy, V. O. H.; López, S. E.; Francisco, N. N.; Acosta, G. J. A. y Villar, S. B. 2014. Genotipos de frijol negro opaco resistentes a sequía terminal. Revista Mexicana de Ciencias Agrícolas. 5(7):1205-1217. https://doi.org/10.29312/remexca.v5i7.866.

Tosquy, V. O. H.; Villar, S. B.; Rodríguez, R. J. R.; Ibarra, P. F. J.; Zetina, L. R.; Meza, P. A. y Anaya-López, J. L. 2019. Adaptación de genotipos de frijol negro a diferentes ambientes de Veracruz y Chiapas. Revista Mexicana de Ciencias. Agrícolas. 10(6):1301-1312. https://doi.org/10.29312/remexca.v10i6.1658.

Villar, S. B.; López, S. E. y Tosquy, V. O. H. 2009. Negro Grijalva, nuevo cultivar de frijol para el trópico húmedo de México. Agricultura Técnica en México. 35(3):349-352.

Weijers, S.; Pape, R.; Löffler, J. and Myers-Smith, I. H. 2018. Contrasting shrub species respond to early summer temperatures leading to correspondence of shrub growth patterns. Environmental Research Letters. 13(3):1-11. http://dx.doi.org/10.1088/1748-9326/aaa5b8.

Willmott, C. J. and Matsuura, K. 2005. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim. Res. 30(1):79-82. http://dx.doi.org/10.3354/cr030079.

Willmott, C. J.; Matsuura, K. and Robeson, S. M. 2009. Ambiguities inherent in sums-of-squares-based error statistics. Atmos. Environ. 43(3):749-752. https://doi.org/10.1016/j.atmosenv.2008.10.005.

Published

2026-04-13

Issue

Section

Articles

How to Cite

Inurreta-Aguirre, Héctor Daniel, Oscar Hugo Tosquy-Valle, Víctor Manuel Rodríguez-Moreno, Francisco Javier Ibarra-Perez, and Rigoberto Zetina-Lezama. 2026. “Characterization and Phenological Prediction of Tropical Black Bean Genotypes”. Revista Mexicana De Ciencias Agrícolas 17 (2): e4244. https://doi.org/10.29312/remexca.v17i2.4244.

Most read articles by the same author(s)

1 2 > >>