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中国农学通报

中国农学通报 ›› 2022, Vol. 38 ›› Issue (28): 13-20.doi: 10.11924/j.issn.1000-6850.casb2021-0991

• 农学·农业基础科学 • 上一篇    下一篇

黑龙江省2025年粮食产能优化分析

刘宝海1,2(), 李晓军3, 高世伟4, 吴立成1,2, 肖明纲1,2()   

  1. 1黑龙江省农业科学院生物技术研究所,哈尔滨 150028
    2黑龙江省作物与家畜分子育种重点实验室,哈尔滨 150028
    3黑龙江省发展规划研究所,哈尔滨 150030
    4黑龙江省农业科学院绥化分院,黑龙江绥化 152052
  • 收稿日期:2021-10-19 修回日期:2021-12-12 出版日期:2022-10-05 发布日期:2022-09-28
  • 通讯作者: 肖明纲
  • 作者简介:刘宝海,男,1978年出生,黑龙江绥化人,研究员,主要从事水稻遗传育种与栽培。通信地址：150028 黑龙江省哈尔滨市松北区创新三路800号,Tel：0451-51127851,E-mail： shslbh@163.com。
  • 基金资助:
    黑龙江省“百千万”工程生物育种重大科技专项“优质抗逆水稻新品种选育”(2020ZX16B01);黑龙江省农业科学院“农业科技创新跨越工程”专项“寒地水稻种质资源创制与应用”(HNK2019CX02);黑龙江省重点研发计划指导类项目(GZ20210161)

Optimization Analysis of Grain Production Capacity of Heilongjiang Province in 2025

LIU Baohai1,2(), LI Xiaojun3, GAO Shiwei4, WU Licheng1,2, XIAO Minggang1,2()   

  1. 1Biotechnology Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150028
    2Heilongjiang Laboratory of Crop and Live-stock Molecular Breeding, Harbin 150028
    3Heilongjiang Institute of Development Planning, Harbin 150030
    4Suihua Branch of Heilongjiang Academy of Agricultural Sciences, Suihua, Heilongjiang 152052
  • Received:2021-10-19 Revised:2021-12-12 Online:2022-10-05 Published:2022-09-28
  • Contact: XIAO Minggang

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摘要：

分析2011—2020年黑龙江省粮食产能变化,探究2025年粮食产能约束条件下各作物单产和种植面积优化的可能性,有助于黑龙江省粮食生产“压舱石”的生产规划布局。采用浮点数编码遗传算法(FGA)与熵权综合评价相结合的方法,使用统计年鉴及网络公开的历史数据,探寻2025年黑龙江省粮食产能极值条件下玉米、水稻、大豆作物品种种植优化方案。结果表明：仅调整单产的最佳优化方案,需要较2020年增产幅度依次是大豆5.01%、水稻5.00%、玉米3.69%;仅调整面积的最佳优化方案,需要较2020年增加幅度依次是玉米8.34%、水稻3.31%、大豆-0.04%;面积与单产协同调整的最佳优化方案,需要较2020年增加幅度依次是玉米面积7.97%、大豆单产5.01%、水稻面积3.31%、玉米单产2.29%、大豆面积-0.04%、水稻单产-3.67%。通过调整作物种植面积或单产或面积与单产协同的3种假设,均可获取实现粮食产能目标的动态优化方案。本研究可为黑龙江省粮食作物种植布局和安全生产提供科学支撑。

关键词: 优化分析, 粮食产能, FGA算法, 熵权评价, 黑龙江省

Abstract:

To analyze the change of grain production capacity in Heilongjiang during 2011-2020 and explore the possibility of optimizing the per unit area yield and planting area of crops under the constraints of grain production capacity in 2025 are conducive to the planning layout of grain production in Heilongjiang and the province’s role as ‘ballast stone’ of national food security. According to the statistical yearbook and historical data available on network, the planting optimization schemes of maize, rice and soybean varieties under the extremum condition of grain production capacity in Heilongjiang in 2025 were explored by using floating-point coding genetic algorithm (FGA) and entropy weight comprehensive evaluation method. The results showed that: for the optimized scheme by only adjusting the per unit area yield, the yield increase of soybean, rice and maize should be 5.01%, 5.00% and 3.69%, respectively, compared with those of 2020. For the optimized scheme by only adjusting the planting area, the planting area of maize, rice and soybean should be increased by 8.34%, 3.31% and -0.04%, respectively, compared with those of 2020. For the optimized scheme of coordinated adjustment of planting area and per unit area yield, the increase range should be maize planting area by 7.97%, soybean per unit area yield by 5.01%, rice planting area by 3.31%, maize per unit area yield by 2.29%, soybean planting area by -0.04%, and rice per unit area yield by -3.67% compared with those of 2020. Therefore, the dynamic optimized scheme to achieve the grain production capacity target could be obtained by adjusting planting area, or per unit area yield, or the coordination of planting area and per unit area yield. This study will provide scientific support for the planting layout and safe production of grain crops in Heilongjiang Province.

Key words: optimization analysis, grain production capacity, FGA algorithm, entropy weight evaluation, Heilongjiang Province

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