Combined strategies for reducing soil salinization and the mechanism of their interactive effects on crop growth
Abstract
Soil salinization is a serious environmental problem affecting more than 100 countries and one billion ha of soil resources worldwide, which has become great challenge to agricultural sustainable development and global food security. Present methods for soil salt treatment mainly only focus on the view of soil and remove soil salt by flood irrigation or some pure engineering method such as pipe drainage and ditch. However, previous methods about salt treatment ignored the interactions among crop growths, crop salt tolerance, and salt treatments, which may not only decrease the effectiveness of salt treatments, but also cause adverse effects of environment. Therefore, it is important to do systematic soil salt treatment by integrating different methods (e.g. engineering and biological ways). Meanwhile, studies of the salt stress response and salt tolerance mechanisms of cultivated plants have a great importance in agriculture for salt affected regions. Responses to salt stress are usually not linear pathways, but complex integrated circuits involving multiple pathways functioning in specific cellular compartments and tissues as well as the interaction of additional cofactors and/or signaling molecules which enable highly coordinated responses to a given stimulus. The China research team has conducted many related studies, especially about salt treatments experiments while the German research team has strong background about crop science and crop growth modeling. Therefore, this project aims to combine, in a long-term partnership, the advantages of both China and German research teams to develop combined strategies to reduce soil salinization, find out the coupling mechanism among crop, soil, and salt treatments, and establish crop models for the combined salt treatments. All the achievements will not only have high economic values for China and Germany, but also benefit the salinization control and sustainable agricultural development in the world.
Persons in charge
Amit Srivastava, Thuy Nguyen, Dominik Behrend, Murilo Vianna, Thomas Gaiser
Runtime
15.2.2024-14.8.2025
Funding
DFG/Sino-German Research Centre
Cooperating partners
Prof. Wenzhi Zeng
Wuhan University (Wuhan, China) and Hohai University (Nanjing, China)
Publications
Dong, J., Zeng, W., Wu, L., Huang, J., Gaiser, T., Srivastava, A.K. (2023): Enhancing short-term forecasting of daily precipitation using numerical weather prediction bias correcting with XGBoost in different regions of China, Engineering Applications of Artificial Intelligence, https://doi.org/10.1016/j.engappai.2022.105579
Gao, J., Zeng, W., Ren, Z., Ao, C., Lei, G., Gaiser, T., Srivastava, A.K. (2023): A Fertilization Decision Model for Maize, Rice, and Soybean Based on Machine Learning and Swarm Intelligent Search Algorithms. Agronomy. https://doi.org/10.3390/agronomy13051400
Lei, G., Zeng, W., Huu Nguyen, T., Zeng, J., Chen, H., Srivastava, A.K., Gaiser,T., Wu,J., Huang, J. (2023) Relating soil-root hydraulic resistance variation to stomatal regulation in soil-plant water transport modeling. Journal of Hydrology 617, 128879. https:// doi.org/10.1016/j.jhydrol.2022.128879
Srivastava, A.K., Ewert, F., Akinwumiju, A.S., Zeng, W., Ceglar, A., Ezui, K.S., Adelodun, A., Adebayo, A., Sobamowo, J., Singh, M., Rahimi, J., Gaiser, T. (2023). Cassava yield gap – A model-based assessment in Nigeria, Front. Sustain. Food Syst. 6:1058775. https://doi.org/10.3389/fsufs.2022.1058775