Simulating the development and growth of lentil using the CSM‐CROPGRO model

Author:

Jing Qi1ORCID,Boote Kenneth J.2ORCID,Liu Kui3,Hoogenboom Gerrit2ORCID,White Jeffrey W.2,Smith Ward1,Jégo Guillaume4ORCID,Grant Brian1,Crépeau Marianne4ORCID,Shang Jiali1,Liu Jiangui1,Chipanshi Aston5,Qian Budong1

Affiliation:

1. Science and Technology Branch Agriculture and Agri‐Food Canada Ottawa Ontario Canada

2. Department of Agricultural and Biological Engineering University of Florida Gainesville Florida USA

3. Science and Technology Branch Agriculture and Agri‐Food Canada Swift Current Saskatchewan Canada

4. Science and Technology Branch Agriculture and Agri‐Food Canada Quebec City Quebec Canada

5. Science and Technology Branch Agriculture and Agri‐Food Canada Regina Saskatchewan Canada

Abstract

AbstractThe pulse crop lentil (Lens culinaris Medik.) is often grown in crop rotations to provide nitrogen (N) and water benefits for subsequent crops. Lentil yields vary greatly with environmental factors and management. A reliable crop model for lentil could assist efforts to assess the effects of management practices to mitigate environmental stresses and maximize lentil yields. However, few crop models simulate the development and growth of lentil. In this study, we adapted the CSM‐CROPGRO model in the Decision Support System for Agrotechnology Transfer to simulate lentil development and growth based on data collected from six experiments conducted from 2001 to 2021 globally. The initial parameter values taken from faba bean (Vicia faba L.) were modified based on reported information and analysis of observed data. Those values were fine‐tuned to minimize the gaps between the simulated and observed crop attributes. The model simulated well development stages with root mean square error (RMSE) of 4 days and aboveground biomass with normalized root mean square error (nRMSE ≤ 23%). Seed yields were generally well simulated across experiments in calibration and validation (nRMSE = 19%) datasets, except for overestimation under the humid environment of Quebec in Canada, which may have resulted from excessive vegetative growth. The underlying mechanisms leading to excessive vegetative growth need to be explored further and included in the model for evaluating the adaptability of lentils to specific regions. Overall, the CSM‐CROPGRO‐Lentil model is ready for simulating lentil production under various scenarios, which may identify ways to improve the productivity and resiliency of cropping systems that include lentil.

Publisher

Wiley

Reference49 articles.

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