Abstract. Ozone (O3) air pollution is well known to adversely affect both the grain and protein yield of wheat, an important staple crop. This study aims to identify and model the key plant processes influencing the effect of O3 on wheat protein. The DO3SE-Crop model was modified in this work to incorporate nitrogen (N) processes, and we parameterised the O3 effect on stem, leaf, and grain N using O3 fumigation datasets spanning 3 years and four O3 treatments. These modifications mean that the newly developed DO3SE-CropN model is the first crop model to include O3 effects on N processes, making it a valuable tool for understanding O3 effects on wheat quality. Our results show that the new model captures the O3 effect on grain N concentrations and the anthesis leaf and stem concentrations well, with an R2 of 0.6 for the increase in grain N concentration and an R2 of 0.3 for the decrease in grain N content under O3 exposure. However, the O3 effect on harvest leaf and stem N is exaggerated. Overestimations of harvest leaf N range from ∼20 % to 120 %, while overestimations of harvest stem N range from ∼40 % to 120 %. Further, a sensitivity analysis revealed that, irrespective of O3 treatment, early senescence onset (simulated as being ∼13 d earlier in the treatment with very high O3 vs. the low-O3 treatment) was the primary plant process affecting grain N. This finding has implications for the breeding of stay-green cultivars for maintaining yield, as well as quality, under O3 exposure. This modelling study therefore demonstrates the capability of the DO3SE-CropN model to simulate processes by which O3 affects N content and, thereby, determines that senescence onset is the main driver of O3 reductions in grain protein yield. The implication of the sensitivity analysis is that breeders should focus their efforts on stay-green cultivars that do not experience a protein penalty when developing O3-tolerant lines, to maintain both wheat yield and nutritional quality under O3 exposure. This work supports the second phase of the Tropospheric Ozone Assessment Report (TOAR) by investigating the impacts of tropospheric O3 on wheat, with a focus on wheat quality impacts that will subsequently affect human nutrition.
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Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
Abstract. Elevated surface ozone (O3) concentrations can negatively impact growth and development of crop production by reducing photosynthesis and accelerating leaf senescence. Under unabated climate change, future global O3 concentrations are expected to increase in many regions, adding additional challenges to global agricultural production. Presently, few global process-based crop models consider the effects of O3 stress on crop growth. Here, we incorporated the effects of O3 stress on photosynthesis and leaf senescence into the Decision Support System for Agrotechnology Transfer (DSSAT) crop models for maize, rice, soybean, and wheat. The advanced models reproduced the reported yield declines from observed O3-dose field experiments and O3 exposure responses reported in the literature (O3 relative yield loss RMSE <10 % across all calibrated models). Simulated crop yields decreased as daily O3 concentrations increased above 25 ppb, with average yield losses of 0.16 % to 0.82 % (maize), 0.05 % to 0.63 % (rice), 0.36 % to 0.96 % (soybean), and 0.26 % to 1.23 % (wheat) per ppb O3 increase, depending on the cultivar O3 sensitivity. Increased water deficit stress and elevated CO2 lessen the negative impact of elevated O3 on crop yield, but potential yield gains from CO2 concentration increases may be counteracted by higher O3 concentrations in the future, a potentially important constraint to global change projections for the latest process-based crop models. The improved DSSAT models with O3 representation simulate the effects of O3 stress on crop growth and yield in interaction with other growth factors and can be run in the parallel DSSAT global gridded modeling framework for future studies on O3 impacts under climate change and air pollution scenarios across agroecosystems globally.
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- Award ID(s):
- 2129627
- PAR ID:
- 10540014
- Publisher / Repository:
- Geoscientific Model Development
- Date Published:
- Journal Name:
- Geoscientific Model Development
- Volume:
- 17
- Issue:
- 7
- ISSN:
- 1991-9603
- Page Range / eLocation ID:
- 2547 to 2567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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