罗建美, 靳根会, 罗仲朋, 王红营, 齐永青, 刘兴冉, 沈彦俊. 河北平原中低产区小麦与玉米生产现状及增产潜力分析[J]. 中国生态农业学报(中英文), 2016, 24(8): 1123-1134.
引用本文: 罗建美, 靳根会, 罗仲朋, 王红营, 齐永青, 刘兴冉, 沈彦俊. 河北平原中低产区小麦与玉米生产现状及增产潜力分析[J]. 中国生态农业学报(中英文), 2016, 24(8): 1123-1134.
LUO Jianmei, JIN Genhui, LUO Zhongpeng, WANG Hongying, QI Yongqing, LIU Xingran, SHEN Yanjun. Production state and yield potential of wheat and maize in low-medium yield farmlands in Hebei Plain[J]. Chinese Journal of Eco-Agriculture, 2016, 24(8): 1123-1134.
Citation: LUO Jianmei, JIN Genhui, LUO Zhongpeng, WANG Hongying, QI Yongqing, LIU Xingran, SHEN Yanjun. Production state and yield potential of wheat and maize in low-medium yield farmlands in Hebei Plain[J]. Chinese Journal of Eco-Agriculture, 2016, 24(8): 1123-1134.

河北平原中低产区小麦与玉米生产现状及增产潜力分析

Production state and yield potential of wheat and maize in low-medium yield farmlands in Hebei Plain

  • 摘要: 本文基于2000—2013年MODIS/NDVI遥感信息与主要粮食作物的统计数据, 分析了河北平原中低产区冬小麦和玉米生产的时空格局, 并利用各县粮食作物主要生育期累积NDVI的逐年值、14年的最大值及单产统计数据, 采用最小二乘法原理, 进行数值曲线拟合, 构建了单产遥感估测模型, 估算了河北平原中低产区冬小麦和玉米的增产潜力。结果表明: 1)冬小麦在邯郸和衡水的最大生产力水平较高, 在沧州、廊坊及邢台中部的最大生产力水平较低, 即后者挖掘增产潜力之后也很难达到前者的最大生产力水平; 玉米的最大生产力水平普遍较高, 挖掘增产潜力后均可达到较高的生产力水平。2)冬小麦和玉米总产增产潜力在沧州和邯郸较大; 冬小麦单产增产潜力多低于10%, 平均增产356 kghm-2(5.87%); 玉米单产增产潜力多高于10%, 平均增产798 kghm-2(12.33%); 单产增产潜力区域分布不同, 冬小麦为廊坊>保定>沧州>邯郸>邢台>衡水, 玉米为邢台>邯郸>保定>沧州>衡水>廊坊。3)以河北平原近14年来作物累积NDVI的最大值估算的全区冬小麦增产潜力为3.90亿kg, 玉米增产潜力为9.62亿kg, 二者合计可增产13.52亿kg, 约相当于区域冬小麦和玉米理论可达增产潜力的1/5。本文估测粮食作物增产潜力的方法可以应用于估测多尺度范围、不同作物的增产潜力, 研究结果可为相关部门的决策和管理提供依据。

     

    Abstract: As arable lands are highly limited and intensively exploited in China, it has become important to increase crop yield in low-to-medium yield farmlands in order to improve grain output. Forecasting crop yield few months before harvest using remote sensing technique has often been used in most crop yield estimation. In view of the above research condition, the potential productivities of main crops were estimated in low-to-medium yield farmlands in the Lowland Plains of Hebei, where is the area of scientific and technological demonstration of the Bohai Granary project. Using MODIS/NDVI remote sensing data (with 250 m resolution) and crop statistical data from 2000 to 2013 of different regions of the area, the spatiotemporal characteristics of the production areas of winter wheat and summer maize were estimated. A crop yield model was fitted using the least squares theory based on yield statistical data, accumulative annual NDVI and accumulative maxium NDVI for the period of 14 years. The crop yield estimation model used to estimate the potential yields of wheat and maize was a quadratic function. The results showed that: 1) the productivity of winter wheat was higher in Handan and Hengshui regions and lower in other regions of the study area. Even under improved production practices, productivity in the latter regions was always less than in the former regions. The productivity of maize was high in most of the study area even where potential productivity was difficult to attain. 2) The highest yield potential for both winter wheat and maize was in Handan region. The yield gap (the difference between potential yield and actual yield) for winter wheat was generally less than 10%, with an average of 356 kghm-2 (5.87%). Then the yield gap for maize was generally more than 10%, with an average of 798 kghm-2 (12.33%). Yield gaps were different for different regions in the study area. The ranked order for winter wheat in terms of yield gap by region was Langfang > Baoding > Cangzhou > Handan > Xingtai > Hengshui. Then that for maize was Xingtai > Handan > Baoding > Cangzhou > Hengshui > Langfang. 3) Based on the 14-year maximum accumulative NDVI, the maximum production gap (the difference of potential productivity and actual productivity) for both wheat and maize occurred in Cangzhou. In the low-to-medium yield farmlands in the Lowland Plains of Hebei, yield-increasing potential was 3.90 × 108 kg for winter wheat and 9.62 × 108 kg for maize. The total yield-increasing potential of both wheat and maize (13.52 × 108 kg) was approximately 1/5 of the theoretical production gap of the two crops. In general, yield gap and production gap were both lower for winter wheat than for summer maize. Thus maize was the most important crop in terms of increasing future grain production in the study area. The method used in this study was applicable to various other crops at different scales, whose results were useful for decision-making and management policies.

     

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