Crop modelling

Published: 21 February 2021
Last edited: 21 February 2021

Crop modelling to simulate yield gain of lentil has further helped to manipulate planting date and lentil phenology in the target region.

Classifications

Category
Collection of baseline and monitoring data and knowledge
Evaluation, effectiveness measures and learning
Technical interventions and infrastructure
Scale of implementation
Local
National
Phase of solution
Entirety

Enabling factors

  • Seed hub for informal seed production as a sustainable way to tackle local development of lentil production
  • Regular and close monitoring by creating farmer groups 
  • Strong support and increased seed availability was achieved by strengthening informal and formal seed systems
  • Digitization through remote base sensing and real time mapping

Lessons learned

Knowledge of environment and genotype × environment interactions are important to develop stable biofortified cultivars or to design location-specific breeding in any biofortification program. In lentils, accumulation of Fe, and Zn in the seeds varies with the weather, location, and soil conditions such as nutrient hungry soil, high pH, temperature, precipitation, and soil organic matter. Multilocation testing of varieties/advanced lines of lentil in Bangladesh, Ethiopia, India, Nepal, and Syria showed significant genotype × environment (G × E) interaction for Fe and Zn. It has been observed that Fe concentration is more sensitive to environmental fluctuations compared to seed Zn concentration. Our study also suggested that high iron and zinc can be combined in short duration varieties without compromising the grain yield.