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Title: Simulating crop phenological responses to water stress using the phenology mms software component

Author
item McMaster, Gregory
item Ascough Ii, James
item Edmunds, Debora
item Nielsen, David
item PRASAD, P.V. - Kansas State University

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/8/2013
Publication Date: 4/26/2013
Citation: Mcmaster, G.S., Ascough II, J.C., Edmunds, D.A., Nielsen, D.C., Prasad, P.V. 2013. Simulating crop phenological responses to water stress using the phenology mms software component. Applied Engineering in Agriculture. Vol. 29(2): 233-249.

Interpretive Summary: Understanding how crops grow and development throughout the growing season is fundamental to crop production and quality management. Knowledge of crop phenology is increasingly influencing many agricultural management practices by improving the efficacy and reducing negative environmental and social impacts. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet the phenological responses to water deficits have rarely been quantified. The objective of this paper is to describe and test the science of the PhenologyMMS software component for simulating the phenology of various crops at varying 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. The complete developmental sequence of the shoot apex correlated with phenological events, and the response to soil water availability for winter and spring wheat (Triticum aestivum L.), winter and spring barley (Hordeum vulgare L.), corn (Zea mays L.), sorghum (Sorghum bicolor L.), proso millet (Panicum milaceum L.), hay/foxtail millet [Setaria italica (L.) P. Beauv.], and sunflower (Helianthus annus L.) were created based on experimental data and the literature. Component evaluation results demonstrated that the PhenologyMMS component has general applicability for predicting crop phenology and has the potential, if coupled to mechanistic models, to improve their ability to simulate the effects of environmental factors such as limited soil water.

Technical 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 the phenological responses to water deficits have rarely been quantified. The objective of this paper is to describe the development and statistical evaluation of the PhenologyMMS software component for simulating the phenology of various crops at varying 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. The complete developmental sequence of the shoot apex correlated with phenological events, and the response to soil water availability for winter and spring wheat (Triticum aestivum L.), winter and spring barley (Hordeum vulgare L.), corn (Zea mays L.), sorghum (Sorghum bicolor L.), proso millet (Panicum milaceum L.), hay/foxtail millet [Setaria italica (L.) P. Beauv.], and sunflower (Helianthus annus L.) were created based on experimental data and the literature. Component evaluation consisted of testing algorithms using “generic” default phenology parameters for a crop (i.e., no calibration for specific cultivars was used) for a variety of field experiments to predict developmental events such as seedling emergence, floral initiation, initiation of stem elongation, flowering, and physiological maturity. Results demonstrated that the PhenologyMMS component has general applicability for predicting crop phenology and has the potential, if coupled to mechanistic models such as DSSAT and APSIM containing phenology submodels for certain crops, to improve their ability to simulate the effects of environmental factors such as limited soil water.