Using CROPGRO to Simulate Impact of High Temperature and Water Stress on Peanut.
Vijaya G. Kakani, Univ of Florida-Agronomy Dept, 117 Dorman Hall, Box 9555, Mississippi State, MS 39762, Kenneth Boote, Univ. Of FL-Agronomy Dept., Gainesville, FL 32611-0500, P.V. V. Prasad, Kansas State Univ, 2004 Throckmorton Hall, Manhattan, KS 66506, Peter Craufurd, Shinfield, ENGLAND,Univ. of Reading, Univ. of Reading Dep. of Ag., Plant Envvironment Lab Cutbush Ln, Reading, RG29AF, ENGLAND, Timothy R. Wheeler, Univ of Reading, Dept of Agriculture, Plant Environment Lab Cutbush Ln, Shinfield, Reading, RG2 9AF, England, and Rao C.N. Rachaputi, Dept of Primary Industries, J Bjelke Petersen Research Station, Goodger Rd, P.O Box 23, Kingaroy, Qld4610, Australia.
A projected increase in Earth’s mean temperature by 1.5 to 5.8 ºC due to climate change in the coming century will expose sensitive reproductive stages of crop plants to supra-optimal temperatures. Crop simulation models may play a critical role in predicting and understanding of crop growth and yield processes in future climates and act as surrogates to field experimentation. However, the use of crop models will depend on how well the models simulate crop growth under stress conditions. The objectives of this research were to investigate the effects of water stress and high temperature on growth and yield of two peanut cultivars under field conditions and evaluate the ability of CROPGRO-Peanut model to predict the observed effects of high temperature and water stress on peanut. Results showed that temperature and water stress decreased pod yield and cultivars differed in their responses to stress. High temperature reduced pod yield by >70% in TMV 2, but only by 23% in ICGS 11. Comparison of model simulations with observed field data showed that model was under-predictingthe stress effects. This suggests the need to modify temperature response functions to increase precision of simulations. Flower production and rate of pod addition in CROPGRO-Peanut model are currently based on curvilinear functions of temperature and the amount of assimilates available for addition of new sites on a daily basis, and the decision point is during pod formation. Our previous research has shown that the decision point occurs 10 days prior to flowering and at the time of anthesis. Therefore, we propose changes in the model code to account and predict for temperature affects during flowering. In addition, differential cultivar temperature sensitivity thresholds would prove beneficial. These changes should improve predictive ability of the CROPGRO-Peanut modelto simulate impact of climate change on peanut yields.