Keywords
component-based modelling, phenology, crop development, growth stages, model reusability
Start Date
1-7-2012 12:00 AM
Abstract
Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet phenological responses to water deficits have rarely been quantified. This paper describes the development and statistical evaluation of the PhenologyMMS V1.2 software component for simulating the phenology of various crops at different levels of soil water content. The component is intended to be simple to use, requires minimal information for calibration, and can be easily incorporated into other crop simulation models. PhenologyMMS evaluation consisted of utilizing data from a variety of field experiments to test algorithms for different crops (using “generic” phenology parameters with no calibration for specific cultivars) to predict developmental events such as seedling emergence and physiological maturity. Results demonstrated that the PhenologyMMS component has general applicability for predicting crop phenology and has the potential, if coupled to mechanistic cropping system models (e.g., DSSAT and APSIM), to improve model ability to simulate phenological responses to environmental factors.
Simulating Crop Phenological Responses to Water Stress using the PhenologyMMS Software Component
Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet phenological responses to water deficits have rarely been quantified. This paper describes the development and statistical evaluation of the PhenologyMMS V1.2 software component for simulating the phenology of various crops at different levels of soil water content. The component is intended to be simple to use, requires minimal information for calibration, and can be easily incorporated into other crop simulation models. PhenologyMMS evaluation consisted of utilizing data from a variety of field experiments to test algorithms for different crops (using “generic” phenology parameters with no calibration for specific cultivars) to predict developmental events such as seedling emergence and physiological maturity. Results demonstrated that the PhenologyMMS component has general applicability for predicting crop phenology and has the potential, if coupled to mechanistic cropping system models (e.g., DSSAT and APSIM), to improve model ability to simulate phenological responses to environmental factors.
