中国农业科学 ›› 2022, Vol. 55 ›› Issue (10): 1961-1970.doi: 10.3864/j.issn.0578-1752.2022.10.007

• 植物保护 • 上一篇    下一篇

玉米田桃蛀螟幼虫的空间分布型与抽样技术

李少华(),王云鹏,王荣成,尹萍,李向东(),郑方强()   

  1. 山东农业大学植物保护学院,山东泰安 271018
  • 收稿日期:2021-09-10 接受日期:2021-10-22 出版日期:2022-05-16 发布日期:2022-06-02
  • 通讯作者: 李向东,郑方强
  • 作者简介:李少华,E-mail: 18763822737@163.com
  • 基金资助:
    国家重点研发计划(2016YFD0300701);山东现代农业产业技术体系(SDAIT-02-10)

Spatial Distribution Pattern and Sampling Technique of Conogethes punctiferalis Larvae in Maize Fields

LI ShaoHua(),WANG YunPeng,WANG RongCheng,YIN Ping,LI XiangDong(),ZHENG FangQiang()   

  1. College of Plant Protection, Shandong Agricultural University, Taian 271018, Shandong
  • Received:2021-09-10 Accepted:2021-10-22 Online:2022-05-16 Published:2022-06-02
  • Contact: XiangDong LI,FangQiang ZHENG

摘要:

【目的】桃蛀螟(Conogethes punctiferalis)是重要的农业害虫,近年来在我国黄淮海玉米产区危害日益严重,已成为玉米安全生产的威胁之一。空间分布型是昆虫种群的重要生态属性,研究桃蛀螟幼虫在玉米田的空间分布型,明确其在玉米田的空间分布特征,为桃蛀螟的田间抽样计划制定、预测预报和有效防治提供科学依据。【方法】利用传统统计学(聚集度指标、Taylor幂法则和Iwao回归模型)和地统计学方法研究玉米田桃蛀螟幼虫种群的空间分布型。基于Iwao回归模型确定桃蛀螟幼虫的理论抽样数,通过序贯抽样技术得到不同允许误差(D=0.1、0.2、0.3)和经济阈值(m0=0.5、1、1.5、2头/株)下的最大理论抽样数。【结果】两种统计学方法的结果均表明桃蛀螟幼虫种群在玉米田的空间分布型属于聚集分布。聚集度指标分析表明桃蛀螟幼虫的分布型为聚集型;Taylor幂法则结果显示桃蛀螟幼虫种群为聚集分布,且聚集强度随种群密度的升高而增加;Iwao回归模型证明桃蛀螟幼虫的空间分布型属于聚集分布,且为一般的负二项分布。根据半方差函数模型参数,确定桃蛀螟幼虫种群的最优拟合模型为球型、指数型和线型,表明空间分布型为聚集型;通过Kriging插值法分析得到桃蛀螟幼虫种群的三维和二维空间分布图,其聚集中心主要分布在田块边缘。基于Iwao回归模型抽样技术明确了桃蛀螟幼虫在置信概率t=2,不同平均密度m=0.5、1、2、3、4、5、10、15时的理论抽样数。进行序贯抽样确定了最大理论抽样数,在t=2,D=0.1、0.2、0.3时,当m0=0.5头/株,最大理论抽样数分别为3 417、854和380株;当m0=1头/株,最大理论抽样数分别为1 717、429和191株;当m0=1.5头/株,最大理论抽样数分别为1 150、287和128株;当m0=2头/株,最大理论抽样数分别为867、217和96株。【结论】桃蛀螟幼虫种群的空间分布型为聚集分布中的负二项分布,聚集中心主要分布在田块边缘。基于序贯抽样确定的理论最大抽样数可用于指导玉米田桃蛀螟幼虫的监测和防治。

关键词: 桃蛀螟, 聚集度指标, 地统计学, 空间分布型, 抽样技术

Abstract:

【Objective】The yellow peach moth, Conogethes punctiferalis, as an agricultural insect pest, its damage to maize ears has become more and more serious in Huang-Huai-Hai maize-producing areas of China in recent years, threatening the safe production of maize and the food safety. The spatial distribution pattern is an important ecological attribute of insect population, the objective of this study is to research the spatial distribution pattern of C. punctiferalis larvae in maize fields, clarify the spatial distribution characteristics of the pest, and to provide scientific bases for formulating field sampling program of C. punctiferalis larvae in maize fields, forecasting and effective management of the insect pest on maize.【Method】The spatial distribution pattern of the population of C. punctiferalis larvae in maize fields was studied by traditional statistical method (aggregation indexes, Taylor’s power law and Iwao’s regression model) and geostatistical method. Based on the Iwao’s regression model, the theoretical sampling number of C. punctiferalis larvae in fields was determined, and the maximum theoretical sampling number with different admissible errors (D=0.1, 0.2, 0.3) and the putative economic thresholds (m0=0.5, 1, 1.5, 2 larvae per plant) was also determined by the sequential sampling.【Result】The results of the two kinds of statistical methods showed that the spatial distribution pattern of C. punctiferalis larvae belonged to aggregation distribution. The analysis of some aggregation indexes showed that spatial distribution pattern of C. punctiferalis larvae belonged to aggregation distribution. The results of Taylor’s power law showed that the spatial distribution pattern of C. punctiferalis larvae belonged to aggregation distribution, and the aggregation intensity increased with the population density. The Iwao’s regression model proved that the spatial distribution pattern of C. punctiferalis larvae belonged to negative binomial distribution in aggregation distributions. The parameters of semivariogram models indicated that the optimal fitting models of C. punctiferalis larvae were the spherical, exponential and linear models. The three-dimensional and two-dimensional maps from Kriging interpolations showed that the aggregation centers of C. punctiferalis larvae were located at the edges of the fields. Based on sampling technique from the Iwao’s regression model, the theoretical sampling number of C. punctiferalis larvae in maize fields was determined when the confidence probability t=2 and different mean densities m=0.5, 1, 2, 3, 4, 5, 10 and 15. The maximum theoretical sampling number was also determined by the sequential sampling. Assuming t=2, D=0.1, 0.2, 0.3, when m0=0.5 larva per plant, the maximum theoretical sampling numbers were 3 417, 854 and 380, respectively; when m0=1 larva per plant, the maximum theoretical sampling numbers were 1 717, 429 and 191, respectively; when m0=1.5 larvae per plant, the maximum theoretical sampling numbers were 1 150, 287 and 128, respectively; when m0=2 larvae per plant, the maximum theoretical sampling numbers were 867, 217 and 96, respectively.【Conclusion】The spatial distribution pattern of C. punctiferalis larvae belongs to the negative binomial distribution in aggregation distributions, and the aggregation centers were located at the edges of the fields. The maximum theoretical sampling number based on the sequential sampling in maize fields can be used for monitoring and management of C. punctiferalis larvae.

Key words: Conogethes punctiferalis, aggregation indices, geostatistics, spatial distribution pattern, sampling technique