Contribution of Crop Models to Adaptation in Wheat. (June 2017)

• Record Type: Journal Article
• Authors: Chenu, Karine; Porter, John Roy; Martre, Pierre; Basso, Bruno; Chapman, Scott Cameron; Ewert, Frank; Bindi, Marco; Asseng, Senthold
• Is Part Of: Trends in plant science. Volume 22:Number 6(2017)
• Page Start: 472
• Page End: 490
• Publication Date: 2017-06
• Subjects: Botany -- Periodicals; Botanique -- Périodiques; Botany; Periodicals; 580.5
• DOI: 10.1016/j.tplants.2017.02.003
• Languages: English
• ISSNs: 1360-1385

Abstract

Abstract : With world population growing quickly, agriculture needs to produce more with fewer inputs while being environmentally friendly. In a context of changing environments, crop models are useful tools to simulate crop yields. Wheat ( Triticum spp.) crop models have been evolving since the 1960s to translate processes related to crop growth and development into mathematical equations. These have been used over decades for agronomic purposes, and have more recently incorporated advances in the modeling of environmental footprints, biotic constraints, trait and gene effects, climate change impact, and the upscaling of global change impacts. This review outlines the potential and limitations of modern wheat crop models in assisting agronomists, breeders, and policymakers to address the current and future challenges facing agriculture. Trends: Wheat is the most diversely adapted cereal, with yields ranging from <1 t ha −1 in arid hot climates to >15 t ha −1 in cool wet environments. Modern crop simulation models predict growth, development, and yield as affected by soil, climate, crop management and variety. Outputs of models facilitate pre-season planning, in-season management decisions, and forecasting of field, regional, and national yields. In addition to optimizing yield, models are applied to reduce the risks of crop failure, improve grain quality, increase profitability, and/or reduce environmental impacts. More recent trends in crop modeling are in assisting breeders to improve varieties and in predicting adaptation to climate change up to the global scale.