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Root phenotyping and root water uptake calculation using soil water contents measured in a winter wheat field

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  • Huang, Zhongdong
  • Zhang, Xiaoxian
  • Ashton, Rhys W.
  • Hawkesford, Malcom J.
  • Richard Whalley, W.

Abstract

Non-destructive phenotyping of roots and measurement of root water uptake from different soil layers in the field are vital for improving water management and facilitating the development of drought-resistant crop varieties, but difficult because of their opaqueness. As a result, indirect methods using easy-to-measure variables such as soil water content have been used as alternatives. However, the inherent measurement errors could undermine the robustness and reliability of these methods. This paper proposes a new method to bridge this knowledge gap by using soil water content profiles measured at two time points to calculate root uptake and root-length density. It is based on the Richards' equation by treating root uptake from different soil layers between the two time points as random unknown numbers; their distributions are calculated using the Bayesian framework, solved by the Markov Chain Monte Carlo method. We applied the method to 39 winter wheat lines grown in a silt-clay loam field. Soil water content profile measured at the first time point from each plot served as the initial condition, and water content measured at the second time point was the target to match the model for calculating average root water uptake and root-length density between the two time points. The results show that the measured soil water contents fall within the 95% confidence interval of the calculated soil water contents. The inherent soil water measurement errors lead to uncertainties in the calculated root water uptake for all lines, but such uncertainties decrease with soil depth. Although the soil types and agronomic management were the same for all 39 lines, their root water uptake from different soil layers varies considerably, with some lines more capable of using subsoil water than others. Generally, the calculated and measured root-length densities agree well, albeit the degree of the agreement varies with lines. While this paper focuses on methodology and applies the method to one growth stage spanning one month only, the consistent results for all 39 lines indicates the method is robust and can be applied to other crops cultivated in different conditions. Given the growing interest in improving root traits to enhance water use efficiency, the proposed method has important implications as phenotyping roots and understanding their water uptake from different soil layers in the field is a prerequisite to achieve this crucial target.

Suggested Citation

  • Huang, Zhongdong & Zhang, Xiaoxian & Ashton, Rhys W. & Hawkesford, Malcom J. & Richard Whalley, W., 2023. "Root phenotyping and root water uptake calculation using soil water contents measured in a winter wheat field," Agricultural Water Management, Elsevier, vol. 290(C).
  • Handle: RePEc:eee:agiwat:v:290:y:2023:i:c:s0378377423004729
    DOI: 10.1016/j.agwat.2023.108607
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    References listed on IDEAS

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    1. Chen, Han & Huang, Jinhui Jeanne & McBean, Edward, 2020. "Partitioning of daily evapotranspiration using a modified shuttleworth-wallace model, random Forest and support vector regression, for a cabbage farmland," Agricultural Water Management, Elsevier, vol. 228(C).
    2. Scott Jasechko & Zachary D. Sharp & John J. Gibson & S. Jean Birks & Yi Yi & Peter J. Fawcett, 2013. "Terrestrial water fluxes dominated by transpiration," Nature, Nature, vol. 496(7445), pages 347-350, April.
    3. Lei Cheng & Lu Zhang & Ying-Ping Wang & Josep G. Canadell & Francis H. S. Chiew & Jason Beringer & Longhui Li & Diego G. Miralles & Shilong Piao & Yongqiang Zhang, 2017. "Recent increases in terrestrial carbon uptake at little cost to the water cycle," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    4. M., Angaleeswari & V., Ravikumar, 2019. "Estimating evapotranspiration parameters by inverse modelling and non-linear optimization," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    5. Šimůnek, Jiří & Hopmans, Jan W., 2009. "Modeling compensated root water and nutrient uptake," Ecological Modelling, Elsevier, vol. 220(4), pages 505-521.
    6. Xu, Jing & Guo, Ziyan & Li, Zhimin & Li, Fangjian & Xue, Xuanke & Wu, Xiaorong & Zhang, Xuemei & Li, Hui & Zhang, Xudong & Han, Qingfang, 2021. "Stable oxygen isotope analysis of the water uptake mechanism via the roots in spring maize under the ridge–furrow rainwater harvesting system in a semi-arid region," Agricultural Water Management, Elsevier, vol. 252(C).
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