Lentil Variation in Phenology and Yield Evaluated with a Model uri icon

abstract

  • Lentil (Lens culinaris Medik.) is a major crop highly valued in the food and nutritional security of millions of people, as well as a rotation crop. Lentil is grown in areas facing many environmental constraints from low moisture availability and high temperatures to winter cold at high elevations. The use of an appropriate and robust crop model can off er mechanistic bases for exploring and extrapolating the impact of a given plant trait or crop management across a range of environments. First, we used the generic SSM-Legumes model to develop a simple and transparent lentil model. The SSM-Legumes model had a robust predictive capability to assess variation in the phenological development and yield of lentil in three locations in the Middle East (Lebanon and Syria) with large differences in rainfall. The agreement between simulated and observed days to flowering or maturity and yield showed the robustness of the model in predicting lentil growth and yield. Second, we incorporated into SSM-legumes a submodel allowing a more realistic accounting of crop survival at very low soil water content, resulting in more realistic predictions of lentil growth and yield. Third, we used the model to test the potential for increasing lentil yields by the retention of crop residue on the soil surface to decrease soil evaporation. Our results showed yield increases of up to 25% in all three locations from the retention of previous crop residues.
  • Lentil (Lens culinaris Medik.) is a major crop highly valued in the food and nutritional security of millions of people, as well as a rotation crop. Lentil is grown in areas facing many environmental constraints from low moisture availability and high temperatures to winter cold at high elevations. The use of an appropriate and robust crop model can offer mechanistic bases for exploring and extrapolating the impact of a given plant trait or crop management across a range of environments. First, we used the generic SSM-Legumes model to develop a simple and transparent lentil model. The SSM-Legumes model had a robust predictive capability to assess variation in the phenological development and yield of lentil in three locations in the Middle East (Lebanon and Syria) with large differences in rainfall. The agreement between simulated and observed days to flowering or maturity and yield showed the robustness of the model in predicting lentil growth and yield. Second, we incorporated into SSM-legumes a submodel allowing a more realistic accounting of crop survival at very low soil water content, resulting in more realistic predictions of lentil growth and yield. Third, we used the model to test the potential for increasing lentil yields by the retention of crop residue on the soil surface to decrease soil evaporation. Our results showed yield increases of up to 25% in all three locations from the retention of previous crop residues

publication date

  • 2015
  • 2015
  • 2015