Preprints
https://doi.org/10.5194/egusphere-2024-2968
https://doi.org/10.5194/egusphere-2024-2968
10 Oct 2024
 | 10 Oct 2024
Status: this preprint is open for discussion.

Modelling the nutritional implications of ozone on wheat protein and amino acids

Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson

Abstract. 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 on Indian 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 N, demonstrating the flexibility and usefulness of the framework developed in this study. Further, the modelling results can be used to simulate the FAO recommended metric for measuring protein quality, the DIAAS, setting up a foundation for nutrition-based 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 further mechanistic understanding of O3 effects on wheat grain quality, future experiments should measure nitrogen (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 O3 assessment report (TOAR) by investigating the impacts of tropospheric O3 on Indian wheat and the potential of this to exacerbate existing malnutrition in India.

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Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson

Status: open (until 29 Nov 2024)

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  • RC1: 'Comment on egusphere-2024-2968', Anonymous Referee #1, 28 Oct 2024 reply
  • RC2: 'Comment on egusphere-2024-2968', Anonymous Referee #2, 06 Nov 2024 reply
Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson
Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson

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Short summary
Ozone (O3) pollution reduces wheat yields and quality in India, affecting amino acids essential for nutrition, like lysine and methionine. Here, we improve the DO3SE-CropN model to simulate wheat’s protective processes against O3 and their impact on protein and amino acid concentrations. While the model captures O3-induced yield losses, it underestimates amino acid reductions. Further research is needed to refine the model, enabling future risk assessments of O3's impact on yields and nutrition.