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Title: Phenology MMS: a program to simulate crop phenological responses to water stress

Author
item McMaster, Gregory
item Edmunds, Debora
item Wilhelm, Wallace
item Nielsen, David
item PRASSAD, P - KANSAS STATE UNIVERSITY
item Ascough Ii, James

Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/11/2011
Publication Date: 6/3/2011
Citation: Mcmaster, G.S., Edmunds, D.A., Wilhelm, W.W., Nielsen, D.C., Prassad, P.V., Ascough II, J.C. 2011. Phenology MMS: a program to simulate crop phenological responses to water stress. Computers and Electronics in Agriculture. 77(2011):118-125.

Interpretive Summary: Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Normally only temperature is considered when predicting when developmental stages are reached, yet water availability can also influence when some developmental events are reached and the response varies among different crops. This paper provides an overview of a decision support technology software tool, PhenologyMMS V1.2, developed to simulate the phenology of various crops for varying levels of soil water. The program is intended to be simple to use, requires minimal information for calibration, and can be incorporated into other crop simulation models. It consists of a Java interface connected to a Fortran science simulation model. 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. Model 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 program has general applicability for predicting crop phenology and an application of the program predicting mean dates of winter wheat phenology across the Central Great Plains based on historical weather records is presented.

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 provide an overview of a decision support technology software tool, PhenologyMMS V1.2, developed to simulate the phenology of various crops for varying levels of soil water. The program is intended to be simple to use, requires minimal information for calibration, and can be incorporated into other crop simulation models. It consists of a Java interface connected to a Fortran science simulation model. 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. Model 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. Results demonstrated that the program has general applicability for predicting crop phenology and can aid in crop management.