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中国农学通报

中国农学通报 ›› 2021, Vol. 37 ›› Issue (10): 150-157.doi: 10.11924/j.issn.1000-6850.casb2020-0292

所属专题： 现代农业发展与乡村振兴

• 乡村振兴 • 上一篇    下一篇

贫困山区粮食单产变化贡献因素分解与测算——以云南为例

毛昭庆(), 王雪娇, 陈良正, 鄢文光, 李隆伟   

  1. 云南农业科学院农业经济与信息研究所,昆明 650205
  • 收稿日期:2020-07-27 修回日期:2020-12-02 出版日期:2021-04-05 发布日期:2021-04-12
  • 通讯作者: 李隆伟
  • 作者简介:毛昭庆,女,1990年出生,湖北潜江人,助理研究员,硕士,研究方向：农业产业经济。通信地址：650200 云南省昆明市盘龙区北京路2238号云南省农业科学院农业经济与信息研究所,E-mail： 809499657@qq.com。
  • 基金资助:
    云南省应用基础研究计划重点项目“云南高原特色农业产业经济及政策研究”(2016FA027);云南省科技人才培养计划“云南省农科院高原特色农业产业经济研究省级创新团队”(2018HC018);云南省首批重点培育新型智库“云南农业发展智库”;云南省粮食局招标项目“云南省发展粮食产业经济问题研究”;云南省统计局招标课题“云南省农业发展质量及效益研究”(0848-1841ZC207060/Q)

Decomposition and Calculation of Contribution Factors of Grain Yield Change in Poverty-stricken Mountainous Areas: Taking Yunnan as an Example

Mao Zhaoqing(), Wang Xuejiao, Chen Liangzheng, Yan Wenguang, Li Longwei   

  1. Agricultural Economy and Information Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650205
  • Received:2020-07-27 Revised:2020-12-02 Online:2021-04-05 Published:2021-04-12
  • Contact: Li Longwei

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摘要：

明确粮食单产变化的贡献因素,为保障贫困山区粮食安全提供应对策略。以云南为例,根据1989—2018年的粮食生产数据,利用RLI模型,构建粮食单产变化的因素分解模型,从作物和区域2个角度对云南粮食单产变化的贡献因素进行分解测算。结果显示,云南粮食单产呈明显上升趋势,且单产变化的稳定性有所增强。云南粮食增产的首要贡献因素是粮食作物单产水平的提升,平均贡献率达82.21%,但结构效应的作用也不容小觑。从作物角度看,玉米和薯类的综合效应最大,贡献率达134.89%。从区域角度看,保山市、昭通市、西双版纳州、文山州、临沧市和德宏州发挥主导作用。贫困山区省份的各级政府在巩固脱贫攻坚成果时,要妥善处理产业扶贫经济作物与粮食作物的关系,优化贫困山区粮食生产优势区域的产业结构,加大贫困山区粮食新品种和新技术的研发投入,加快完善贫困山区粮食技术推广体系,增强贫困山区粮食储备与应急机制。

关键词: 云南, RLI模型, 粮食, 单产, 因素分解

Abstract:

The contribution factors of the change of grain yield per unit area are clarified to provide coping strategies for food security in poor mountainous areas. Taking Yunnan Province as an example, based on the grain production data from 1989 to 2018, using the RLI model, this paper constructs a factor decomposition model for the change of grain yield per unit area, and calculates the contribution factors of grain yield change in Yunnan Province from the perspectives of crops and regions. The results show that: the grain yield per unit area in Yunnan presents an obvious upward trend, and the stability of the change is enhanced. The primary contribution factor of grain yield increase in Yunnan is the improvement of grain yield per unit area, with an average contribution rate of 82.21%, but the role of structural effect should not be underestimated. From the perspective of crops, corn and potato have the greatest combined effect, with the contribution rate of 134.89%. From the regional perspective, Baoshan, Zhaotong, Xishuangbanna, Wenshan, Lincang and Dehong play a leading role. When consolidating the achievements of poverty alleviation, governments at all levels in poverty-stricken mountainous areas should properly handle the relationship between industrial poverty alleviation cash crops and food crops, optimize the industrial structure of advantageous areas for grain production, increase research and development investment in new varieties and technologies of grain, accelerate the improvement of grain technology extension system, and strengthen the grain reserve and emergency mechanism in poor mountainous areas.

Key words: Yunnan, refined laspeyres index model, grain, yield per unit, factor decomposition

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