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BINOMIAL COUNT ANALYSIS BASED ON THE SPATIAL DISTRIBUTION AND POPULATION DENSITY ESTIMATION OF COTTON APHIDS 1)
Author(s) -
Zhang Guangmei,
Shen Zuorui,
Zhao Zhonghua
Publication year - 1998
Publication title -
insect science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.991
H-Index - 45
eISSN - 1744-7917
pISSN - 1672-9609
DOI - 10.1111/j.1744-7917.1998.tb00299.x
Subject(s) - aphid , aphididae , statistics , negative binomial distribution , sampling (signal processing) , aphis gossypii , biology , economic threshold , population , mathematics , binomial (polynomial) , pest analysis , agronomy , botany , homoptera , demography , poisson distribution , physics , optics , detector , sociology
Abstract Based on field population sampling of Aphis gossypii on cotton seedlings in Quzhou Experiment Station of China Agricultural University in Hebei Province in 1991, we obtained a data set consisting of 24 estimates of mean aphid density ( m , number of aphids per plant), variance (s 2 ) and the proportion of plants (P T ) with no more than T aphids (T=0, 1, 2,…, 8, 10, 15, 20, respectively and defined as tally threshold). Taylor's power law fitted the data well (r 2 = 0. 958). The resulting slope (1. 515) was significantly greater than 1, indicating that the spatial distribution of this aphid was in aggregated pattern. An empirical relationship between m and Pr was developed for each T value using the parameters from the linear regression In( m )= a +bln[‐ ln( P T )}]. The importance of the T values in reduction of sampling errors and their application to binomial sampling plans are discussed. Small T values, particularly aphid‐free plant (T = 0, conventional binomial sample), could lead to spurious estimates of m from P T . A value of T from 10 to 15 was recommended to develop binomial sampling plans for the aphids on cotton seedlings because of the relatively small sampling errors.