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农业研究通常投入大 ,见效慢。用作物生长模型模拟技术 ,是解决这一问题的理想方法。为了用CERES玉米模型模拟优质蛋白玉米品种叶片增长 ,在泰国清迈大学进行品种×播种期的双因素试验。试验有 3参试种 ,3个播种期 ,共 9个处理。试验结果表明 ,用CERES玉米模型模拟的最大叶面积指数、总叶片数、叶片干物质重 ,模拟值均高于实际值 ,这主要是因为准确的土壤和气候数据不易得到所致 ,因此只有当土壤和气候数据可靠时 ,CERES玉米模型才能用于指导研究和其他工作。
Agricultural research is often costly and slow-acting. Using crop growth model simulation techniques is the ideal solution to this problem. In order to simulate the leaf growth of high-quality protein maize varieties with a CERES corn model, a two-factor test of variety × sowing date was conducted at Chiang Mai University, Thailand. There are 3 test varieties tested, 3 sowing period, a total of 9 treatment. The results showed that the maximum leaf area index, the total number of leaves, the dry matter weight and the simulated value of leaves simulated by CERES model were higher than the actual values. This was mainly because the accurate soil and climate data were not easily obtained. Therefore, CERES corn models can be used to guide research and other work when soil and climate data are reliable.