Modelling ozone-induced changes in wheat amino acids and protein quality using a process-based crop model
Cook, Jo ORCID: https://orcid.org/0000-0002-2499-0083; Yadav, Durgesh Singh
ORCID: https://orcid.org/0000-0003-3896-1520; Hayes, Felicity
ORCID: https://orcid.org/0000-0002-1037-5725; Booth, Nathan
ORCID: https://orcid.org/0009-0002-2451-907X; Bland, Sam; Pande, Pritha
ORCID: https://orcid.org/0000-0001-6923-4276; Thankappan, Samarthia
ORCID: https://orcid.org/0000-0002-0802-0642; Emberson, Lisa.
2025
Modelling ozone-induced changes in wheat amino acids and protein quality using a process-based crop model [in special issue: Tropospheric ozone assessment report phase II (TOAR-II) community special issue (ACP/AMT/BG/GMD inter-journal SI)]
Biogeosciences, 22 (4).
1035-1056.
10.5194/bg-22-1035-2025
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Abstract/Summary
Ozone (O3) pollution reduces wheat yields as well as the protein and micronutrient yield of the crop. O3 concentrations are particularly high in India and are set to increase, threatening wheat yields and quality in a country already facing challenges to food security. This study aims to improve the existing DO3SE-CropN model to simulate the effects of O3 onIndian wheat quality by incorporating antioxidant processes to simulate protein and the concentrations of nutritionally relevant amino acids. As a result, the improved model can now capture the decrease in protein concentration that occurs in Indian wheat exposed to elevated O3. The structure of the modelling framework is transferrable to other abiotic stressors and easily integrable into other crop models, provided they simulate leaf and stem nitrogen (N), demonstrating the flexibility and usefulness of the framework developed in this study. Further, the modelling results can be used to simulate the dietary indispensable amino acid score (DIAAS), the metric for measuring protein quality recommended by the Food and Agriculture Organization (FAO) of the United Nations, setting up a foundation for nutritionbased risk assessments of O3 effects on crops. The resulting model was able to capture grain protein, lysine and methionine concentrations reasonably well. As a proportion of dry matter, the simulated percentages ranged from 0.26% to 0.38% for lysine and from 0.13% to 0.22% for methionine, while the observed values were 0.16% to 0.38% and 0.14% to 0.22%, respectively. For grain and leaf protein simulations, the interdependence between parameters reduced the accuracy of their respective relative protein loss under O3 exposure. Additionally, the decrease in lysine and methionine concentrations under O3 exposure was underestimated by 10 percentage points for methionine for both cultivars and by 37 and 19 percentage points for lysine for HUW234 and HD3118, respectively. This underestimation occurs despite simulations of relative yield loss being fairly accurate (average deviation of 2.5 percentage points excluding outliers). To provide a further mechanistic understanding of O3 effects on wheat grain quality, future experiments should measure N and protein concentrations in leaves and stems, along with the proportion of N associated with antioxidants, which will aid in informing future model development. Additionally, exploring how grain protein relates to amino acid concentrations under O3 will enhance the model’s accuracy in predicting protein quality and provide more reliable estimates of the influence of O3 on wheat quality. This study builds on the work of Cook et al. (2024) and supports the second phase of the Tropospheric Ozone Assessment Report (TOAR) by investigating the impacts of tropospheric O3 on Indian wheat and the potential of this to exacerbate existing malnutrition in India.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | 10.5194/bg-22-1035-2025 |
UKCEH and CEH Sections/Science Areas: | Land-Atmosphere Interactions (2025-) |
ISSN: | 1726-4189 |
Additional Information. Not used in RCUK Gateway to Research.: | Open Access paper - full text available via Official URL link. |
NORA Subject Terms: | Agriculture and Soil Science Atmospheric Sciences |
Related URLs: | |
Date made live: | 28 Feb 2025 10:20 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/538985 |
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