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PhenologyMMS: A program to simulate crop phenological responses to water stress
Authors:Gregory S McMaster  DA EdmundsWW Wilhelm  DC NielsenPVV Prasad  JC Ascough II
Institution:a USDA-ARS-NPA, Agricultural Systems Research Unit, 2150 Centre Ave., Bldg. D, Suite 200, Fort Collins, CO 80526, USA
b USDA-ARS-NPA, Agroecosystems Management Research Unit, 120 Keim Hall, University of Nebraska, Lincoln, NE 68583, USA
c USDA-ARS-NPA, Central Plains Resource Management Unit, Central Great Plains Research Station, 40335 County Rd. GG, Akron, CO 80720, USA
d Dept. of Agronomy, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
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 FORTRAN science modules to simulate phenological responses. 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 wheat (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.
Keywords:Simulation model  Decision support systems  Crop development  Growth stages  Crop management  Seedling emergence
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