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Gabaldón-Leal, C., Webber, H., Otegui, M. E., Slafer, G. A., Ordonez, R. A., Gaiser, T., et al. (2016). Modelling the impact of heat stress on maize yield formation. Field Crops Research, 198, 226–237.
Abstract: The frequency and intensity of extreme high temperature events are expected to increase with climate change. Higher temperatures near anthesis have a large negative effect on maize (Zea mays, L.) grain yield. While crop growth models are commonly used to assess climate change impacts on maize and other crops, it is only recently that they have accounted for such heat stress effects, despite limited field data availability for model evaluation. There is also increasing awareness but limited testing of the importance of canopy temperature as compared to air temperature for heat stress impact simulations. In this study, four independent irrigated field trials with controlled heating imposed using polyethylene shelters were used to develop and evaluate a heat stress response function in the crop modeling framework SIMPLACE, in which the Lintul5 crop model was combined with a canopy temperature model. A dataset from Argentina with the temperate hybrid Nidera AX 842 MG (RM 119) was used to develop a yield reduction function based on accumulated hourly stress thermal time above a critical temperature of 34 degrees C. A second dataset from Spain with a FAO 700 cultivar was used to evaluate the model with daily weather inputs in two sets of simulations. The first was used to calibrate SIMPLACE for conditions with no heat stress, and the second was used to evaluate SIMPLACE under conditions of heat stress using the reduction factor obtained with the Argentine dataset. Both sets of simulations were conducted twice; with the heat stress function alternatively driven with air and simulated canopy temperature. Grain yield simulated under heat stress conditions improved when canopy temperature was used instead of air temperature (RMSE equal to 175 and 309 g m(-2), respectively). For the irrigated and high radiative conditions, raising the critical threshold temperature for heat stress to 39 degrees C improved yield simulation using air temperature (RMSE: 221 gm(-2)) without the need to simulate canopy temperature (RMSE: 175 gm(-2)). However, this approach of adjusting thresholds is only likely to work in environments where climatic variables and the level of soil water deficit are constant, such as irrigated conditions and are not appropriate for rainfed production conditions. (C) 2016 Elsevier B.V. All rights reserved.
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Lizaso, J. I., Ruiz-Ramos, M., Rodriguez, L., Gabaldon-Leal, C., Oliveira, J. A., Lorite, I. J., et al. (2017). Modeling the response of maize phenology, kernel set, and yield components to heat stress and heat shock with CSM-IXIM. Field Crops Research, 214, 239–252.
Abstract: The available evidence suggests that the current increasing trend in global surface temperatures will continue during this century, which will be accompanied by a greater frequency of extreme events. The IPCC has projected that higher temperatures may outscore the known optimal and maximum temperatures for maize. The purpose of this study was to improve the ability of the maize model CSM-IXIM to simulate crop development, growth, and yield under hot conditions, especially with regards to the impact of above-optimal temperatures around anthesis. Field and greenhouse experiments that were performed over three years (2014-2016) using the same short-season hybrid, PR37N01 (FAO 300), provided the data for this work. Maize was sown at a target population density of 5 plants M-2 on two sowing dates in 2014 and 2015 and on one in 2016 at three locations in Spain (northern, central, and southern Spain) with a well-defined thermal gradient. The same hybrid was also sown in two greenhouse chambers with daytime target temperatures of approximately 25 and above 35 degrees C. During the nighttime, the temperature in both chambers was allowed to equilibrate with the outside temperature. The greenhouse treatments consisted of moving 18 plants at selected phenological stages (V4, V9, anthesis, lag phase, early grain filling) from the cool chamber to the hot chamber over a week and then returning the plants back to the cool chamber. An additional control treatment remained in the cool chamber all season, and in 2015 and 2016, one treatment remained permanently in the hot chamber. Two maize models in the Decision Support System for Agrotechnology Transfer (DSSAT) V4.6 were compared, namely CERES and IXIM. The HUM version included additional components that were previously developed to improve the crop N simulation and to incorporate the anthesis-silking interval (ASI). A new thermal time calculation, a heat stress index, the impact of pollen-sterilizing temperatures, and the explicit simulation of male and female flowering as affected by the daily heat conditions were added to IXIM. The phenology simulation in field experiments by IXIM improved substantially. The RMSE for silking and maturity in CERES were 7.9 and 13.7 days, decreasing in DCIM to 2.8 and 7.3 days, respectively. Similarly, the estimated kernel numbers, kernel weight, grain yield and final biomass were always closer to the measurements in HUM than in CERES. The worst simulations were for kernel weight, and for that reason, the differences in grain yield between the models were small (the RMSE in CERES was 1219 kg ha(-1) vs. 1082 kg ha(-1) in IXIM). The greenhouse results also supported the improved estimations of crop development by IXIM (RMSE of 2.6 days) relative to CERES (7.4 days). The impact of the heat treatments on grain yield was consistently overestimated by CERES, while HUM captured the general trend. The new HUM model improved the CERES simulations when elevated temperatures were included in the evaluation data. Additional model testing with measurements from a wider latitudinal range and relevant heat conditions are required.
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Lizaso, J. I., Ruiz-Rarnos, M., Rodriguez, L., Gabaldon-Leal, C., Oliveira, J. A., Lorite, I. J., et al. (2018). Impact of high temperatures in maize: Phenology and yield components. Field Crops Research, 216, 129–140.
Abstract: Heat stress is a main threat to current and future global maize production. Adaptation of maize to future warmer conditions requires improving our understanding of crop responses to elevated temperatures. For this purpose, the same short-season (FAO 300) maize hybrid PR37N01 was grown over three years of field experiments on three contrasting Spanish locations in terms of temperature regime. The information complemented three years of greenhouse experiments with the same hybrid, applying heat treatments at various critical moments of the crop cycle. Crop phenology, growth, grain yield, and yield components were monitored. An optimized beta function improved the calculation of thermal time compared to the linear-cutoff estimator with base and optimum temperatures of 8 and 34 degrees C, respectively. Our results showed that warmer temperatures accelerate development rate resulting in shorter vegetative and reproductive phases (ca. 30 days for the whole cycle). Heat stress did not cause silking delay in relation to anthesis (extended anthesis-silking interval), at least in the range of temperatures (maximum temperature up to 42.9 degrees C in the field and up to 52.5 degrees C in the greenhouse) considered in this study. Our results indicated that maize grain yield is reduced under heat stress mainly via pollen viability that in turn determines kernel number, although a smaller but significant effect of the female component has been also detected.
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Mäkinen, H., Kaseva, J., Trnka, M., Balek, J., Kersebaum, K. C., Nendel, C., et al. (2018). Sensitivity of European wheat to extreme weather. Field Crops Research, 222, 209–217.
Abstract: The frequency and intensity of extreme weather is increasing concomitant with changes in the global climate change. Although wheat is the most important food crop in Europe, there is currently no comprehensive empirical information available regarding the sensitivity of European wheat to extreme weather. In this study, we assessed the sensitivity of European wheat yields to extreme weather related to phenology (sowing, heading) in cultivar trials across Europe (latitudes 37.21 degrees to 61.34 degrees and longitudes- 6.02 degrees to 26.24 degrees) during the period 1991-2014. All the observed agro-climatic extremes (>= 31 degrees C, >= 35 degrees C, or drought around heading; >= 35 degrees C from heading to maturity; excessive rainfall; heavy rainfall and low global radiation) led to marked yield penalties in a selected set of European cultivars, whereas few cultivars were found to with no yield penalty in such conditions. There were no European wheat cultivars that responded positively (+ 10%) to drought after sowing, or frost during winter (- 15 degrees C and – 20 degrees C). Positive responses to extremes were often shown by cultivars associated with specific regions, such as good performance under high temperatures by southern-origin cultivars. Consequently, a major future breeding challenge will be to evaluate the potential of combining such cultivar properties with other properties required under different growing conditions with, for example, long day conditions at higher latitudes, when the intensity and frequency of extremes rapidly increase.
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Korhonen, P., Palosuo, T., Persson, T., Höglind, M., Jego, G., Van Oijen, M., et al. (2018). Modelling grass yields in northern climates – a comparison of three growth models for timothy. Field Crops Research, 224, 37–47.
Abstract: During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratertse L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil -crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development.
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