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油菜病毒病田间分布型及抽样技术研究
引用本文:钱浚,高智谋,陈森,项兆鹏.油菜病毒病田间分布型及抽样技术研究[J].中国油料作物学报,1991(2).
作者姓名:钱浚  高智谋  陈森  项兆鹏
作者单位:安徽农学院植保系 (钱浚,高智谋),安徽省徽州地区农科所 (陈森),安徽省徽州地区农科所(项兆鹏)
摘    要:本文采用概率频次拟合法和种群扩散指数法测定了油菜病毒病(TpMV、YMV和CMV)在油菜幼苗期、越冬期及盛花期的田间分布型。结果表明:病株田间分布在幼苗期和越冬期符合奈曼分布和负二项分布,在盛花期仅符合奈曼分布;病级分布在越冬期和盛花期均为聚集分布。比较几种抽样方法,以棋盘式取样效果最佳。在置信概率为95%,抽样误差不超过5%的条件下,理论抽样数为70—384株。田间调查时可取样200株,其精确度在93%以上。

关 键 词:油菜  病毒病  分布型  抽样技术

PRELIMINARY STUDY ON DISTRIBUTION PATTERN OF RAPE VIRUS DISEASE IN FIELD AND ITS SAMPLING TECHNIQUE
Qian Jun Gao Zhimou.PRELIMINARY STUDY ON DISTRIBUTION PATTERN OF RAPE VIRUS DISEASE IN FIELD AND ITS SAMPLING TECHNIQUE[J].Chinese Journal of Oil Crop Sciences,1991(2).
Authors:Qian Jun Gao Zhimou
Abstract:The spacial distribution patterns of rape virus disease(TpMV,YMV,CMV and TMV)in seedling stage,overwintering period and flowering phase were studied respectively in this paper.The results indicated that the spacial distribution pattern of diseased plants in seedling stage and overwintering period accorded with Neyman distribution and negative binomial distribution,but the pattern in the flowering phase corresponded only to Neyman distribution.The distribution patterns of diseased plants seriousness in overwintering period and flowering stage were of aggregation distribution.The comparison of various sampling methods showed the sampling error rate of five-point sampling was highest,and the chessboard-form sampling was lowest.In order to increase the degree of accuracy,therefore,the former should be not applied and the latter or other multiple-point sampling should be emploied in the disease investigation in field.When the believable probability was 95% and the sampling error rate was below 5 %,the theoretial sampling number of plant should be 70-384.To consider two factors of the sampling accuracy degree and the affording of the investigation in field,a saitable number of 200 plants might be applied for investigation of disease in field.Statistical examination showed that the degree of accuracy could be above 93%.
Keywords:Rape  Virus disease  Distribution pattern  Sampling technique
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