白帆, 杨晓光, 刘志娟, 孙爽, 张镇涛, 王晓煜, 高继卿, 刘涛. 气候变化背景下播期对东北三省春玉米产量的影响[J]. 中国生态农业学报(中英文), 2020, 28(4): 480-491. DOI: 10.13930/j.cnki.cjea.190585
引用本文: 白帆, 杨晓光, 刘志娟, 孙爽, 张镇涛, 王晓煜, 高继卿, 刘涛. 气候变化背景下播期对东北三省春玉米产量的影响[J]. 中国生态农业学报(中英文), 2020, 28(4): 480-491. DOI: 10.13930/j.cnki.cjea.190585
BAI Fan, YANG Xiaoguang, LIU Zhijuan, SUN Shuang, ZHANG Zhentao, WANG Xiaoyu, GAO Jiqing, LIU Tao. Effects of sowing dates on grain yield of spring maize in the Three-Province of the Northeast China under climate change[J]. Chinese Journal of Eco-Agriculture, 2020, 28(4): 480-491. DOI: 10.13930/j.cnki.cjea.190585
Citation: BAI Fan, YANG Xiaoguang, LIU Zhijuan, SUN Shuang, ZHANG Zhentao, WANG Xiaoyu, GAO Jiqing, LIU Tao. Effects of sowing dates on grain yield of spring maize in the Three-Province of the Northeast China under climate change[J]. Chinese Journal of Eco-Agriculture, 2020, 28(4): 480-491. DOI: 10.13930/j.cnki.cjea.190585

气候变化背景下播期对东北三省春玉米产量的影响

Effects of sowing dates on grain yield of spring maize in the Three-Province of the Northeast China under climate change

  • 摘要: 为探究气候变化背景下东北三省(黑龙江省、吉林省和辽宁省)春玉米适宜播期的变化程度,本文以东北三省春玉米潜在种植区为研究区域,基于1981—2015年气象资料,1981—2012年农业气象观测站玉米生育期、产量资料以及土壤资料,分气侯区对农业生产系统模型(APSIM)进行调参和验证,建立适用于东北三省10个不同气候区的模型相关参数,在各气候区利用调参验证后的APSIM-Maize模型设置不同播期,模拟各年代不同播期下春玉米潜在产量和气候生产潜力,综合高产和稳产性指标,明确了不同区域各年代不同条件下适宜播期范围。研究结果表明,APSIM模型对于东北三省7个春玉米品种开花和成熟两个关键生育期以及产量模拟结果与实测结果具有较好的一致性,表明APSIM模型能够较好地模拟研究区域春玉米生育期和产量。充分灌溉条件下,研究区域内适宜播期范围从4月16日至5月19日,空间上呈纬向分布南早北迟的特征;20世纪90年代和21世纪00年代玉米适宜播期较20世纪80年代有提前趋势,其中20世纪90年代提前趋势更明显;第1、第3、第5、第7和第9气候区雨养条件下较充分灌溉条件下适宜播期有推迟趋势,推迟天数为3~6 d。雨养条件下各年代不同气候区理论上的适宜播期较目前生产中实际播期下的产量提高2.84%~9.96%。以上结果为进行未来气候变化对东北三省春玉米影响及其适宜播期等研究提供了技术支撑。

     

    Abstract: Northeast China is the most sensitive area to climate change, where is also the important region of maiza production in China. It has both theoretical and practical significance to explore suitable sowing date of spring maize in three provinces of Northeast China (Heilongjiang Province, Jilin Province and Liaoning Province) under climate change. Meteorological data from 1981 to 2015 and agro-meteorological observations, including maize phenology data, yield data, and soil data from 1981 to 2012, were used to construct an APSIM-Maize model. The data were collected from the potential cultivation zones of spring maize in the three provinces of the Northeast China. The model was calibrated and validated in different climatic zones across the study area and related parameters were established accordingly. The potential yields and climatic potential yields of spring maize during different decades were then determined by setting different sowing dates based on the validated APSIM model. Combined with the indices of yield level and yield stability, the suitable range of sowing dates was determined under different conditions during different decades in each climatic zone. The results showed that the simulated values, including the days from sowing date to flowering date and maturity date, and the yield, were in agreement with the observed values for the seven spring maize varieties in the study area. This indicated that the APSIM model accurately simulated the phenological development and yield information of spring maize in the study area. Under the condition of sufficient irrigation, the suitable sowing date in the study area ranged from April 16 to May 19. A latitudinal distribution was exhibited for the suitable sowing date with the date moving earlier from south to north. The suitable sowing date of maize in the 1990s and 2000s was earlier than that in the 1980s, and this advanced trend was more significant in the 1990s than in the 2000s. However, under rainfed conditions, the suitable sowing period in the first, third, fifth, seventh, and ninth climatic zones displayed a delayed trend, with the delay ranging from 3 days to 6 days. Compared with the yield simulated using the sowing date applied in current production, the yield simulated using the theoretical suitable sowing date increased by 2.84%-9.96% in different climatic zones during different decades under rainfed conditions. This research supports the use of the APSIM model in Northeast China for applications such as the selection of suitable sowing dates under future climate scenarios.

     

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