|
Ramirez-Villegas, J., Watson, J., & Challinor, A. J. (2015). Identifying traits for genotypic adaptation using crop models. J. Experim. Bot., 66(12), 3451–3462.
Abstract: Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation.
|
|
|
Pilbeam, D. J. (2015). Breeding crops for improved mineral nutrition under climate change conditions. J. Experim. Bot., 66(12), 3511–3421.
Abstract: Improvements in understanding how climate change may influence chemical and physical processes in soils, how this may affect nutrient availability, and how plants may respond to changed availability of nutrients will influence crop breeding programmes. The effects of increased atmospheric CO2 and warmer temperatures, both individually and combined, on soil microbial activity, including mycorrhizas and N-fixing organisms, are evaluated, together with their implications for nutrient availability. Potential changes to plant growth, and the combined effects of soil and plant changes on nutrient uptake, are discussed. The organization of research on the efficient use of macro- and micronutrients by crops under climate change conditions is outlined, including analysis of QTLs for nutrient efficiency. Suggestions for how the information gained can be used in plant breeding programmes are given.
|
|
|
Martre, P., He, J., Le Gouis, J., & Semenov, M. A. (2015). In silico system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management. J. Experim. Bot., 66(12), 3581–3598.
Abstract: Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work.
|
|
|
McKersie, B. (2015). Planning for food security in a changing climate. J. Experim. Bot., 66(12), 3435–3450.
Abstract: The Intergovernmental Panel on Climate Change and other international agencies have concluded that global crop production is at risk due to climate change, population growth, and changing food preferences. Society expects that the agricultural sciences will innovate solutions to these problems and provide food security for the foreseeable future. My thesis is that an integrated research plan merging agronomic and genetic approaches has the greatest probability of success. I present a template for a research plan based on the lessons we have learned from the Green Revolution and from the development of genetically engineered crops that may guide us to meet this expectation. The plan starts with a vision of how the crop management system could change, and I give a few examples of innovations that are very much in their infancy but have significant potential. The opportunities need to be conceptualized on a regional basis for each crop to provide a target for change. The plan gives an overview of how the tools of plant biotechnology can be used to create the genetic diversity needed to implement the envisioned changes in the crop management system, using the development of drought tolerance in maize (Zea mays L.) as an example that has led recently to the commercial release of new hybrids in the USA. The plan requires an interdisciplinary approach that integrates and coordinates research on plant biotechnology, genetics, physiology, breeding, agronomy, and cropping systems to be successful.
|
|
|
Jabloun, M., Schelde, K., Tao, F., & Olesen, J. E. (2015). Effect of temperature and precipitation on nitrate leaching from organic cereal cropping systems in Denmark. European Journal of Agronomy, 62, 55–64.
Abstract: The effect of variation in seasonal temperature and precipitation on soil water nitrate (NO3-N) concentration and leaching from winter and spring cereals cropping systems was investigated over three consecutive four-year crop rotation cycles from 1997 to 2008 in an organic farming crop rotation experiment in Denmark. Three experimental sites, varying in climate and soil type from coarse sand to sandy loam, were investigated. The experiment included experimental treatments with different rotations, manure rate and cover crop, and soil nitrate concentrations was monitored using suction cups. The effects of climate, soil and management were examined in a linear mixed model, and only parameters with significant effect (P < 0.05) were included in the final model. The model explained 61% and 47% of the variation in the square root transform of flow-weighted annual NO3-N concentration for winter and spring cereals, respectively, and 68% and 77% of the variation in the square root transform of annual NO3-N leaching for winter and spring cereals, respectively. Nitrate concentration and leaching were shown to be site specific and driven by climatic factors and crop management. There were significant effects on annual N concentration and NO3-N leaching of location, rotation, previous crop and crop cover during autumn and winter. The relative effects of temperature and precipitation differed between seasons and cropping systems. A sensitivity analysis revealed that the predicted N concentration and leaching increased with increases in temperature and precipitation. (C) 2014 Elsevier B.V. All rights reserved.
|
|