This paper considers the application of quantum algorithms to the problem of resource allocation optimization in agriculture. In this paper, the approach of applying the quantum algorithm Quantum Approximate Optimization Algorithm to the problem of resource allocation optimization in agriculture was investigated. The paper develops an algorithm for applying Quantum Approximate Optimization Algorithm to the problem of resource allocation optimization. This algorithm includes creating a quantum chain representing the optimization problem, applying evolution operators and measurements to find the state corresponding to the optimal solution to the problem. The application of Quantum Approximate Optimization Algorithm has proven its effectiveness in solving complex optimization problems in agriculture. Quantum Approximate Optimization Algorithm is able to take into account many factors, such as resource availability, crop requirements and other constraints, which allows obtaining optimal solutions to the resource allocation problem.