Thiago Berton Ferreira, W. Pavan, J. M. Fernandes, S. Asseng, F. Oliveira, Carlos Amaral Ho¨lbig, D. Pequeno, G. A. Dalmago, A. L. Zanatta, G. Hoogenboom
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引用次数: 2
Abstract
HighlightsCSM-NWheat, a DSSAT wheat crop model, was coupled with a pest module named PEST.The coupled model can simulate the impact of pest and disease damage on wheat crops.Pest damage is expressed in daily steps by communication links called coupling points.Coupling points are linked with state variables at which pest damage can be applied.Field pest-scouting reports and linear interpolation are used to compute damage rates.Abstract. Wheat is one of the most important global staple crops and is affected by numerous pests and diseases. Depending on their intensity, pests and diseases can cause significant economic losses and even crop failures. Pest models can assist decision-making, thus helping reduce crop losses. Most wheat simulation models account for abiotic stresses such as drought and nutrients, but they do not account for biotic stresses caused by pests and diseases. Therefore, the objective of this study was to couple a dynamic pest and disease damage module to the DSSAT model CSM-NWheat. Coupling points were integrated into the CSM-NWheat model for applying daily damage to all plant components, including leaves, stems, roots, and grains, the entire plant, and to the assimilate supply. The coupled model was tested by simulating a wheat crop with virtual damage levels applied at each coupling point. Measured foliar damage caused by tan spot (Pyrenophora tritici-repentis) was also simulated. The modified model accurately estimated the reduction in leaf area growth and the yield loss when compared with observed data. With the incorporation of the pest module, CSM-NWheat can now predict the potential impact of pests and diseases on wheat growth and development, and ultimately economic yield. Keywords: Biotic stress, Decision support, DSSAT, Model coupling, Yield loss.
期刊介绍:
This peer-reviewed journal publishes research that advances the engineering of agricultural, food, and biological systems. Submissions must include original data, analysis or design, or synthesis of existing information; research information for the improvement of education, design, construction, or manufacturing practice; or significant and convincing evidence that confirms and strengthens the findings of others or that revises ideas or challenges accepted theory.