在不同环境条件下优质蛋白玉米品种的物候期模型

传统农业研究方法的结果通常具有地域性, 且周期长, 且投入大, 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玉米生长模型预测栽培管理措施对不同品种生长发育的影响, 在泰国北部清迈大学农学院的多熟种植中心(北纬18°47′, 东经99°57′, 海拔300m)进行品种×播种期的双因素试验, 参试种为:Across 8763(

Modeling of Phenology for Quality Protein Maize Cultivars under Different Environments

Traditional agricultural research result is recognized as site specific, slow, and expensive. An alternative to solve this problem is to use modeling approach. A nitrogen×variety experiment was conducted in the Research Station of Yunnan Academy of Agricultural Sciences (25°N Lat., 109°E Long., 1900 msl.). There were five nitrogen levels, i.e. 100, 145, 185, 230, and 270 kg ha-1. Three maize varieties, two quality protein maize (QPM), i.e., Across 8763, Poza Rica 8763, and one normal maize Mobei 1, were used. In order to simulate the effects of management practice on growth and development of different maize cultivars by using the Crop-Environment Resource Synthesis (CERES) -Maize model in Northern Thailand, one varieties×planting dates experiment was conducted in the Research Station of the Multiple Cropping Center, Faculty of Agriculture, Chiang Mai University (18°47′N Lat., 99°57′E Long, 300 msl.). The experiment was conducted to generate data set for use in genetic coefficients determination. There were three Planting-date levels: December 20, 1994, January 5, 1995, and Januany 20, 1995. Three maize cultivars were used, Across 8763(QPM), Poza Rica 8763 (QPM), and Suwan 1. The Genotype Coefficients Calculator (GENCAL) was used to determine a set of genetic coefficients for the three cultivars. The CERES-Maize model satisfactorily simulated effects of planting dates on growth and development of different maize cultivars. This set of genetic coefficients was then used to simulate effects of management practices in Yunnan. The CERES-Maize model demonstrated acceptable ability to simulate phenology events, e.g, silking, and physiological maturity dates.