2018Agronomy monograph/AgronomyRequires access

Modeling the Effects of Genotypic and Environmental Variation on Maize Phenology: The Phenology Subroutine of the AgMaize Crop Model

M. Tollenaar, K.A. Dzotsi, S. Kumudini, Kenneth J. Boote, Keru Chen, Jerry L. Hatfield, James W. Jones, Jon Lizaso, Robert Nielsen, Peter R. Thomison, Dennis Timlin, Oscar Valentinuz, Tony J. Vyn, Haishan Yang

Open publisher page 8 citations

Abstract

The predictive ability of process-based maize models is predicated on accurate prediction of phenology in terms of maize hybrids (genetics), abiotic factors affecting maize development (environment), and genotype × environment interactions. This chapter describes the phenology routines of a new process-based maize model, AgMaize, being implemented in the Decision Support System for Agrotechnology Transfer (DSSAT). It evaluates the model using a large number of diverse datasets and compares the outcome of the evaluation to predictions by the existing maize phenology model in DSSAT: the CERES-Maize phenology model. The life cycle of maize in AgMaize is divided into three phases: the pre-flowering, the flowering, and the post-flowering or grain-filling period. Except for germination, rate of development during the pre-flowering phase is based on the relationship between rate of leaf appearance and temperature. Predictions of phase duration by CERES-Maize were similar to those by AgMaize when the models were calibrated by modifying genotype coefficients.

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The predictive ability of process-based maize models is predicated on accurate prediction of phenology in terms of maize hybrids (genetics), abiotic factors affecting maize development (environment), and genotype × environment interactions. This chapter describes the phenology routines of a new process-based maize model, AgMaize, being implemented in the Decision Support System for Agrotechnology Transfer (DSSAT). It evaluates the model using a large number of diverse datasets and compares the outcome of the evaluation to predictions by the existing maize phenology model in DSSAT: the CERES-Maize phenology model. The life cycle of maize in AgMaize is divided into three phases: the pre-flowering, the flowering, and the post-flowering or grain-filling period. Except for germination, rate of development during the pre-flowering phase is based on the relationship between rate of leaf appearance and temperature. Predictions of phase duration by CERES-Maize were similar to those by AgMaize when the models were calibrated by modifying genotype coefficients.

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Available abstract

The predictive ability of process-based maize models is predicated on accurate prediction of phenology in terms of maize hybrids (genetics), abiotic factors affecting maize development (environment), and genotype × environment interactions. This chapter describes the phenology routines of a new process-based maize model, AgMaize, being implemented in the Decision Support System for Agrotechnology Transfer (DSSAT). It evaluates the model using a large number of diverse datasets and compares the outcome of the evaluation to predictions by the existing maize phenology model in DSSAT: the CERES-Maize phenology model. The life cycle of maize in AgMaize is divided into three phases: the pre-flowering, the flowering, and the post-flowering or grain-filling period. Except for germination, rate of development during the pre-flowering phase is based on the relationship between rate of leaf appearance and temperature. Predictions of phase duration by CERES-Maize were similar to those by AgMaize when the models were calibrated by modifying genotype coefficients.

Key concepts: Phenology, DSSAT, Agronomy, Abiotic component, Biology, Crop, Germination, Crop simulation model

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Modeling the Effects of Genotypic and Environmental Variation on Maize Phenology: The Phenology Subroutine of the AgMaize Crop Model — Research Paper | ScholarLens