Fixed precision Sequential Sampling of Aphids on Wheat fields in Ahvaz

Document Type : Research Article



Introduction: Aphids are secondary pests in cereal fields but sometimes they outbreak and cause considerable damage to wheat and barley. Integrated pest management is one of the most important strategy in insect ecology and estimating population can be used to employ the strategy. Sampling of population is the most basic outdoor activities in ecology and as time goes need to fast and reliable sampling methods be felt more. Dispersion can be quantified by the comparison of observed frequency distribution data (based on a common sample unit) with mathematical models used to describe possible spatial distributions. Knowledge about dispersion pattern of an organism is required for understanding population biology, resource exploitation and dynamics of biological control agents. Moreover determination the dispersion pattern of a species is essential for developing an effective pest management program. . The degree of aggregation can be expressed by several indices of dispersion. Taylor's power law and Iwao's patchiness regression are two main models that also depend on the relationship between the sample mean and the variance of insect numbers per sampling unit. The slope of the regression model is used as an index of aggregation. Usually, sampling of insects is from the estimatation of some population parameter for research purposes or to make a pest control decision. However, the often large, fixed sample size necessary for research may be inappropriate where frequent and rapid monitoring is required to make a control decision. In such cases the sequential sampling method may be a better alternative as it characteristically has a variable sample number and can serve to classify a population in relation to a treatment level rather than provide actual estimates of population density. Designing sampling plans based on these indicators has been reported to reduce sampling effort, cost and minimize variation of sampling precision. As there were no any information about the spatial distribution and sequential sampling program of cereal aphids in Khuzestan province, this study was undertaken to determine dispersion pattern of cereal aphids in order to develop a suitable sampling plan for these pests.
Material and Methods: In order to assess the distribution pattern and density of aphid species on wheat the mixed population of aphids was sampled during 2012-2013 at three pesticide-free wheat fields (two wheat fields in Ahvaz and one in Mollasani) in Khuzestan province, southwestern of Iran. Each field was sampled twice a week throughout the growing season from initiation of tillering to grain ripening stage. Each sample included 25 plant, which were chosen randomly and the number of aphids was counted. Tillers were collected by traveling an X-shaped procedure. Spatial distribution of different developmental stages of wheat aphids were described by calculating dispersion indices (Taylor’s and Iwao’s indices of dispersion). A sequential sampling plan was also developed using the fixed precision method of Green for estimating the density of adults, Nymphs and total population.
Result and Discussion: Analysis of spatial distribution pattern using Taylor’s power law and Iwao’s regression model showed that Taylor's power law provides a better description of the aphids spatial distribution and based on this model dispersion pattern of wheat aphids population was aggregated for nymph and the total of life stage, but was random for adult life stage. Green’s fixed precision sequential sampling plan at precision levels of 0.25 and 0.10 was designed for estimating the density of the adult, nymph and total population. The results showed that the required sample size increased dramatically with increasing levels of precision, and generally ranged from 1 to 34 and 8 to 210 tillers at the precision levels of 0.25 and 0.10 respectively, and the optimum sample size for the estimation of mean aphid density decreased approximately between 44% - 83%.


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