资源科学 ›› 2019, Vol. 41 ›› Issue (10): 1935-1948.doi: 10.18402/resci.2019.10.15

• 土地资源 • 上一篇    下一篇

河南省夏玉米产量空间分布特征及其影响因素

巫振富1,赵彦锋2,程道全3,陈杰2()   

  1. 1. 郑州大学公共管理学院,郑州 450001
    2. 郑州大学农学院,郑州 450001
    3. 河南省土壤肥料站,郑州 450002
  • 收稿日期:2019-03-22 修回日期:2019-06-11 出版日期:2019-10-25 发布日期:2019-10-25
  • 通讯作者: 陈杰
  • 作者简介:巫振富,男,广西八步人,博士生,从事土地资源可持续利用研究。E-mail: wfjt1988@163.com
  • 基金资助:
    国家自然科学基金项目(40971128)

Key factors affecting the spatial variation of summer maize yield in Henan Province, China

WU Zhenfu1,ZHAO Yanfeng2,CHENG Daoquan3,CHEN Jie2()   

  1. 1. School of Public Administration, Zhengzhou University, Zhengzhou 450001, China
    2. School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China
    3. Station of Soil and Fertilizer Extension Service, Henan Province, Zhengzhou 450002, China
  • Received:2019-03-22 Revised:2019-06-11 Online:2019-10-25 Published:2019-10-25
  • Contact: CHEN Jie

摘要:

科学评价各种影响因素在作物产量空间分异中的作用,对因地制宜进行粮食生产功能区划定、种植结构选择、中低产田改造、高标准粮田建设等农业生产实践具有重要意义。本文以河南省为研究区,收集整理2008—2010年各县田间肥料试验数据、耕地地力评价资料和夏玉米生长季气象数据,利用Boruta算法和随机森林模型定量评价施肥、土壤、气候、品种和灌排等5个组别共计17个因素对夏玉米产量空间分异的影响。结果显示:河南省夏玉米高产区主要分布在豫北黄淮海平原区,中产区主要分布在豫东平原区和南阳盆地,低产区分布在豫西、豫南和南阳盆地外围的丘陵山地。产量年际波动较小的区域主要集中分布于中产区。17个因素对夏玉米产量空间分异均有重要影响。施肥,尤其是配方施肥,虽然可以有效提高作物产量,但是并不能改变作物产量的空间分布格局。上述结果表明,作物产量空间分布格局主要受气候、土壤和立地条件等区域性因素的综合制约,有效保护高产稳产的优质耕地资源、通过消除土壤障碍因素和改善耕地立地条件提高耕地基础地力是保障可持续粮食安全的重要途径。

关键词: 夏玉米, 产量, 空间分异, Boruta算法, 随机森林, 土壤, 气候, 河南省

Abstract:

Assessing the contribution of various factors to the spatial variation of crop yield is of vital importance in promoting agricultural practice according to local conditions, such as delimiting functional regions of grain production, optimizing cropping system, improving medium and low yield fields, and developing high-standard grain fields. This study was carried out in Henan Province, China, by using the field fertilization experiment data at the county level from 2008 to 2010, cultivated land productivity evaluation data, and meteorological data in summer maize growing season. Employing the Boruta algorithm and random forest model, contributions of five factor categories (including 17 factors) namely fertilization, soil, climate, cultivar, and irrigation and drainage, to the spatial variation of summer maize yield were quantitatively assessed. It was demonstrated that the high-yield areas of summer maize were mainly distributed in the Huang- Huai- Hai Plain (HHHP) in the north, and the medium-yield fields were concentrically located in the HHHP in the east and in Nanyang Basin, while the low-yield parcels were scattered in the mountainous and hilly areas in the west, the south, and the periphery of Nanyang Basin. The fields with less inter-annual fluctuation of yield were mainly found in medium-yield areas. All the 17 factors played an important role in the spatial variation of summer maize yield. Fertilization, particularly formulated fertilization, effectively increased crop yield, however, it was not work on changing the spatial distribution pattern of crop yield. This led to the conclusion that the spatial distribution pattern of crop yield is dominated by regional factors such as climate, soil and site conditions. Thus, for sustainable food security, it is necessary to protect high quality cultivated land resources with high and stable yield, and to improve cultivated land productivity by eliminating soil obstacle factors and improving the site.

Key words: summer maize, yield, spatial variation, Boruta algorithm, random forest, soil, climate, Henan Province