Modeling the grain yield loss and quality assessment of some durum wheat (Triticum durum Desf.) genotypes under semi-arid conditions
Modelización de la pérdida de rendimiento de grano y evaluación de la calidad de algunos genotipos de trigo duro (Triticum durum Desf.) que crecen en condiciones semiáridas
DOI:
https://doi.org/10.15446/rfnam.v77n1.108026Keywords:
Durum wheat, Grain moisture, Grain yield, Mathematical model, Technological quality (en)Trigo duro, Humedad de grano, Producción de grano, Modelo matemático , Calidad tecnológica (es)
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This study was conducted at the Experimental Station for Field Crops ITGC in Setif -Algeria during the growing season (2020-2021), to evaluate the parameters of the technological quality efficiency of three durum wheat genotypes {Boussellam (BOS), Oued El Bared (OB), and GTA dur (GTA)} and the efficiency of using mathematical models based on the relation between grain moisture in the field and grain yield to estimate grain yield loss caused by the delayed harvest according to the randomized blocks design with three replications. Results demonstrated that the genotype effects were significant for all technological parameters, the protein content varied from 13.70 to 15.4%; the highest content of protein registered by (OB) was 15.4%. In addition, the values of test weight varied between 79.47 and 81.97 kg hL-1, with a general mean of 80.96 kg hL-1. The study of correlations test showed that there was a significant and positive correlation between the decreased grain moisture in the field and the loss in final grain yield, which suggests that the final grain yield decreases as the grain moisture decreases. This loss can be predicted using a mathematical regression model. The statistical analysis revealed the best agreement between measured and simulated grain yield, with low average absolute error and root mean square error. The grain yield was also well simulated with the observed yield giving a coefficient of efficiency (E) of 0.76, i.e., with a simulation capacity of 76%. Overall, and after the physiological maturity of the grains the mathematical model proved that with the 1% loss of grain moisture, there is a loss of about 0.290 t ha-1 of grain yield.
El objetivo de este estudio fue evaluar la eficiencia del uso de modelos matemáticos para estimar la pérdida de rendimiento de grano en algunos genotipos de trigo duro que crecen en condiciones semiáridas en función de la relación entre la humedad del grano en el campo y el rendimiento de grano final. Los resultados de ANOVA demostraron que los efectos de los genotipos fueron significativos para todos los parámetros tecnológicos, el contenido de proteína varió de 13,70 a 15,4%; el mayor contenido de proteína registrado por Oued El Bared fue 15,4%. Además, los valores de peso hectolítrico oscilaron entre 79,47 y 81,97 kg hL-1, con media general de 80,96 kg hL-1. El estudio de la prueba de correlaciones indicó que hubo una correlación significativa y positiva entre la disminución de la humedad del grano en el campo y la pérdida en el rendimiento final del grano, lo que sugiere que el rendimiento final del grano disminuyó a medida que disminuye la humedad del grano. Esta pérdida puede predecirse utilizando un modelo de regresión matemática. El análisis estadístico reveló la mejor concordancia entre el rendimiento de grano medido y el simulado, con un error absoluto promedio y un error cuadrático medio bajo. El rendimiento de grano también fue simulado con el rendimiento observado dando un coeficiente de eficiencia (E) de 0,76, es decir, con una capacidad de simulación del 76%. En general, y después de la madurez fisiológica de los granos, el modelo matemático demostró que a partir del 1% de pérdida de humedad del grano, se pierde alrededor de 0,290 t ha-1 de rendimiento de grano.
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1. Sarah Benkadja, Abdelmalek Oulmi, Ali Guendouz, Benalia Frih. (2024). Assessment of agro-physiological traits for identifying drought-tolerant durum wheat (Triticum durum Desf.) genotypes under rainfed conditions. Revista Facultad Nacional de Agronomía Medellín, 77(2), p.10717. https://doi.org/10.15446/rfnam.v77n2.108152.
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