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The study on the crop growth model parallel algorithm is help to improve the computing efficiency of models in the low-cost PC cluster environment. According to the positive feedback characteristic of the crop development simulation model, this study used the partitioning and pipelining technology, and raised the two parallel algorithms, which are the single-node parallel job scheduling algorithm based on OpenMP and the multi-node parallel job scheduling algorithm based on MPI/OpenMP. The performance measurement and analysis is done in the windows Compute Cluster Server 2003 cluster environment. The result shows that the two parallel algorithms can improve the computing efficiency of the wheat growth development simulation effectively. The first algorithm is simple and easy to realize. The second algorithm has a better computing efficiency and is it suitable for large amount of data computing, the speed-up ratio of the second algorithm is about double to the first algorithm.