浙江农业科学 ›› 2024, Vol. 65 ›› Issue (10): 2443-2446.DOI: 10.16178/j.issn.0528-9017.20230938

• 观赏园艺 • 上一篇    下一篇

基于灰色关联分析法的7种耐盐绿化树种综合评价

黄婷(), 左忠*(), 范金鑫   

  1. 宁夏农林科学院 林业与草地生态研究所,宁夏 银川 750002
  • 收稿日期:2023-09-18 出版日期:2024-10-11 发布日期:2024-10-25
  • 通讯作者: 左忠(1976—),男,宁夏盐池人,研究员,主要从事沙生植物开发利用与荒漠化防治技术监测研究,E-mail:nxzuozhong@163.com
  • 作者简介:黄婷(1992—),女,宁夏中宁人,硕士,主要从事荒漠化防治技术监测研究,E-mail:1182934403@qq.com
  • 基金资助:
    2021年度中央财政林业科技推广示范项目(〔2021〕ZY03号);2022年度中央财政林业科技推广示范项目(〔2022〕ZY09号);宁夏回族自治区人才专项“宁夏回族自治区第六批科技创新领军人才项目”(2020GKLR0100);宁夏退耕还林工程效益监测项目(250000005)

Comprehensive evaluation of 7 salt tolerant greening tree species based on grey correlation analysis method

HUANG Ting(), ZUO Zhong*(), FAN Jinxin   

  1. Institute of Forestry and Grassland Ecology, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan 750002, Ningxia
  • Received:2023-09-18 Online:2024-10-11 Published:2024-10-25

摘要:

对平罗县2021年度同期种植的7种耐盐绿化树种的9个指标进行了灰色关联度分析,通过等权关联度和加权关联度排序位次,对绿化树种优劣进行综合评价。结果表明,不同绿化树种的等权关联度和加权关联度的排序基本一致,9901旱柳、馒头柳、白蜡位列前三名,综合评价较高,适合在本地区种植。垂柳关联度排序在最后,综合评价较低,适宜性相对较差。

关键词: 灰色关联度, 耐盐绿化树种, 指标, 综合评价, 平罗县

Abstract:

A grey correlation analysis was conducted on 9 indicators of 7 salt tolerant greening tree species planted in Pingluo County during the same period in 2021. The advantages and disadvantages of greening tree species were comprehensively evaluated by ranking them by equal weight correlation degree and weighted correlation degree. The results showed that the order of the equal weight correlation degree and the weighted correlation degree of different greening tree species was basically the same, and Salix matsudana Koidz cv. 9901, Salix matsudana var. matsudana f. umbraculifera Rehd., and Fraxinus chinensis Roxb, ranked in the top three. The comprehensive evaluation was high, and it was suitable for planting in this region. The ranking of the correlation degree of Salix babylonica was in the end, with a low comprehensive evaluation and relatively poor suitability.

Key words: grey correlation degree, salt tolerant greening tree species, indicators, comprehensive evaluation, Pingluo County

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