Excessive fertilizer application can inhibit plant growth and even lead to higher mortality of seedlings in the drought environment. Recent studies have shown that irrigation and fertilizer application should be managed simultaneously 4, 6. For example, in Florida, USA 5, the optimization of irrigation and fertilizer strategies can reduce irrigation by 48% and fertilizer application by 26% with the same yield.
In this regard, the optimization of irrigation and fertilizer strategies can not only improve the crop yield but also reduce production costs, protect the environment and save resources 4. Soil hardening and environmental pollution caused by fertilizer application and the shortage of water resources are universally concerned in the world. At the same time, fertilizer application is another important factor in ensuring increased crop yield. Globally, irrigation accounts for 85% of the total water used in agriculture and generates about 40% of the total food production 3. In addition, in arid and semi-arid regions, the use of irrigation water plays a vital role in agricultural production. A study shows that the global demand for food is expected to grow by between 60 and 110 percent between 20 2, which means that it is increasingly important to implement precision crop management. One of the major challenges facing humanity in the twenty-first century is the way to meet the growing demand for food while reducing waste of resources 1. Finally, the experiment produces a better irrigation and fertilization strategy, with water consumption reduced by 44%, nitrogen application reduced by 37%, and economic benefits increased by 7 to 8%. Then, the lower-level screening quickly finds better irrigation and fertilization strategies among thousands of solutions. Subsequently, due to the complexity of the problem, the lower-level optimization uses a data-driven evolutionary algorithm, which combines the fast non-dominated sorting genetic algorithm (NSGA-II), surrogate-assisted model of radial basis function and Decision Support System for Agrotechnology Transfer to handle the expensive objective problem and produce a set of optimal solutions representing a trade-off between conflicting objectives.
Irrigation and fertilization dates are obtained by upper-level screening and upper-level optimization. To enable more precision and effective agricultural management, a bi-level screening and bi-level optimization framework is proposed. Sustainable intensification needs to optimize irrigation and fertilization strategies while increasing crop yield.
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