CERES-Maize model for simulating genotype-by-environment interaction of maize and its stability in the dry and wet savannas of Nigeria

• Published in: Field crops research Vol. 253; p. 107826
• Main Authors: Adnan, A.A, Diels, J., Jibrin, J.M., Kamara, A.Y, Shaibu, A.S, Craufurd, P, Menkir, Abebe
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.08.2020; Elsevier Scientific Pub. Co
• Subjects: CERES-Maize model; Genotype by environment interaction; Stability analysis; Genotype by environment interaction; Stability analysis; CERES-Maize model
• ISSN: 0378-4290; 1872-6852
• DOI: 10.1016/j.fcr.2020.107826

•Genotype by Environment Interaction (GEI) makes it difficult for breeders and growers to select stable, high yielding varieties across different environments thereby reducing the effectiveness of the selection process.•Determining the magnitude of GEI and the stability of varieties can be challenging, as such, crop models can be employed to complement this process.•Dynamic models that can simulate the response of growth and development of crops to varying abiotic environmental factors have the potential to explain yield differences due to temporal and spatial variability.•Crop Simulation Models were used to complement multi environment trials (METs) with a view to enhancing selection of high yielding varieties across multiple locations.•The model simulations matched actual observations and produced similar ranking, indicating that properly calibrated and evaluated CERES-Maize model can complement METs. When properly calibrated and evaluated, dynamic crop simulation models can provide insights into the different components of genotype by environment interactions (GEIs). Modelled outputs could be used to complement data from multi-environment trials. Field experiments were conducted in the rainy and dry seasons of 2015 and 2016 across four locations in maize growing regions of Northern Nigeria using 16 maize varieties planted under near-optimal conditions of moisture and soil nitrogen. The CERES-Maize model was calibrated using data from three locations and two seasons (rainy and dry) and evaluated using data from one location and two seasons all in 2015. Observed data from the four locations and two seasons in 2016 was used to create eight different environments. Two profile pits were dug in each location and were used separately in the simulations for each environment to provide replicated data for stability analysis in a combined ANOVA. The effects of the environment, genotype and GEI were highly significant (p = 0.001) for both observed and simulated grain yields. The environment explained 67 % and 64 % of the variations in observed and simulated grain yields respectively. The variance component of GEI (13 % for observed and 15 % for simulated) were lower but still considerable when compared to that of genotypes (19 % for observed and 21 % for simulated). From the stability analysis of the observed and simulated grain yields using six different stability models, three models (ASV, Ecovalence, and Sigma) ranked Ife Hybrid as the most stable variety. The slope of the regression (bi) model ranked Sammaz 11 as the most stable variety, while the Shukla model ranked Sammaz 28 as the most stable variety. Long-term seasonal analysis with the CERES-Maize model revealed that early and intermediate maturing varieties produce high yields in both wet and dry savannas, early and extra-early varieties produce high yields only in the dry savannas, while late maturing varieties produce high yields only in the wet savannas. When properly calibrated and evaluated, the CERES-Maize model can be used to generate data for GEI and stability studies of maize genotype in the absence of observed field data.