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中国农学通报

中国农学通报 ›› 2012, Vol. 28 ›› Issue (15): 180-184.doi: 10.11924/j.issn.1000-6850.2012-0237

所属专题： 水稻

• 植物保护 农药 • 上一篇    下一篇

灰飞虱在水稻田空间分布格局及抽样技术研究

赵敏 王华弟 杨廉伟 李荣 吴传伟 张国忠 王道泽   

  • 收稿日期:2012-01-31 修回日期:2012-03-13 出版日期:2012-05-25 发布日期:2012-05-25
  • 基金资助:

    浙江省科技厅重大科技攻关项目“玉米油菜重大病害监测预警与持续控制技术研究与推广”

The Spatial Distribution Pattern and Sampling Technique of the Small Brown Planthopper, Laodelphax striatellus, in Paddy Field

  • Received:2012-01-31 Revised:2012-03-13 Online:2012-05-25 Published:2012-05-25

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摘要：

为了提高对灰飞虱在稻田的监测预报与持续控制水平，应用聚集度指标法、Iwao法和Taylor幂法则，研究了浙西北水稻田灰飞虱的空间分布格局和抽样技术。结果表明，灰飞虱在水稻田呈聚集分布为主，聚集强度随虫口密度增加而增强。其聚集原因经Blackith种群聚集均数(λ)测定，当成虫、成若虫平均虫口密度分别在1.3978头/丛、1.4883头/丛以下时，λ<2，聚集是由周边环境、移栽期、生育期等某种环境因素所引起的；当成虫、成若虫平均虫口密度分别在1.3978头/丛、1.4883头/丛以上时，λ≥2。而若虫：λ均≥2。其聚集因素是由灰飞虱自身特性与环境因子共同作用所引起。以此为基础，提出了理论抽样数和序贯抽样模型：n=(1.96)2/D2(1.35595/m+0.41366)和T(n)= 5n±4.13778 。研究结果为稻田灰飞虱的准确抽样调查和有效防治提供了科学依据。

关键词: 贮藏, 贮藏

Abstract:

The spatial distribution pattern and sampling technique of the small brown planthopper, Laodelphax striatellus, in paddy field in the Northwestern of Zhejiang province were studied by the methods of the aggregated indices method, Iwao method and Taylor power law method, in order to improve the monitoring, prediction and the sustained control level for this pest in paddy field. All of three methods shown that the distribution pattern of L. striatellus is the assemble distribution type, and the aggregation intensity increased with density of population. It was tested by Blackith’s population aggregation mean number (λ) method, when average population density (m) of adult and adult+nymph was less than 1.3978 and 1.4883 insect/tuft, respectively, their aggregation was caused by some environmental factors, such as surrounding environment, transplanting period, growth period and etc; when m≥1.3978 and 1.4883 insect/tuft, respectively, all λ≥2. The gathering was caused by the interaction of their biological characteristics and environment factor. Based on this distribution pattern, the model for determining the optimum theoretical sampling number and the optimum sequential sampling were proposed. The model were as follows: n=(1.96)2/D2(1.35595/m+0.41366) and T(n)=5n±4.13778 . These results provided scientific basis for sampling investigating precisely and controlling effectively the field populations of L. striatellus.