浙江农业学报 ›› 2019, Vol. 31 ›› Issue (4): 600-606.DOI: 10.3969/j.issn.1004-1524.2019.04.12

• 植物保护 • 上一篇    下一篇

设施番茄昆虫群落组成及时间动态的聚类分析

邢鲲, 曹俊宇, 赵飞*   

  1. 农业有害生物综合治理山西省重点实验室,山西省农业科学院 植物保护研究所,山西 太原 030031
  • 收稿日期:2018-09-06 出版日期:2019-04-25 发布日期:2019-04-19
  • 通讯作者: *赵飞,E-mail: zhaofei12@126.com
  • 作者简介:邢鲲(1980-),男,山西太原人,博士,副研究员,主要从事昆虫生态及害虫综合治理。E-mail:xingkun1215@126.com
  • 基金资助:
    山西省重点研发计划重点项目(201603D21110-2)

Fuzzy clustering analysis and structure of insect community in protected tomato

XING Kun, CAO Junyu, ZHAO Fei*   

  1. Shanxi Key Laboratory of Integrated Pest Management in Agriculture, Institute of Plant Protection, Shanxi Academy of Agricultural Sciences, Taiyuan 030031, China
  • Received:2018-09-06 Online:2019-04-25 Published:2019-04-19

摘要: 在设施番茄栽培环境下,采取5点取样法调查黄板诱集的昆虫的种类和数量。利用群落特征指数对昆虫各群落的基本特征进行分析,并应用系统聚类方法对昆虫各群落特征的时间动态进行聚类分析。结果表明,设施番茄诱集昆虫隶属7个目16个科。其中粉虱科Aleyrodidae为优势害虫;在天敌昆虫中蚜小蜂科Aphelinidae为优势种。设施番茄的害虫防治可以分为2段,其中番茄生长初期应充分发挥天敌昆虫的生物防治作用,但是番茄生长中后期,随着害虫数量的剧增,昆虫群落极为不稳定,此时应以化学防治措施为主。

关键词: 设施番茄, 昆虫群落, 时间动态, 系统聚类

Abstract: In the protected tomato field, the five points sampling method was used to record the species and quantities of insects trapped on yellow templates. The basic characteristics of the insect community were analyzed using basic features of the community characteristics index, and temporal dynamics of the insect community characteristics were clustered using hierarchical clustering methods. The study indicated that the insects were collected by tomato in greenhouse belonged to 16 families, 7 orders. Aleyrodidae was the highest in pests and Aphelinidae was the dominant species in natural enemies. The results showed that the control period of main pests might be divided into two phases. In the early stage of tomato growth, biological control of natural enemies should be given. However, in the middle and later stage of tomato growth, insect community was extremely unstable with the increase of pests, so the chemical control should be adopted.

Key words: protected tomato, insect community, temporal dynamics, hierarchical cluster

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