Potential Distribution Of The Pest At Different Plant Stages

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the reduction in time and a number of samples translates directly to the costs (Ahuja et al., 2015).
Expected Outcomes

objective Expected project research outcome
Data collection and spatial distribution - Intensities of the pest on lower, middle and upper leaves of the plant at different plant stages in three provinces for two seasons/ years.
- The spatial distribution of the pest in the field at different plant stages.
Sample unit The most efficient sample unit for the pest at different plant stages.
Fixed sampling requirements Sample sizes required for fixed precision at precision levels of 0.1 and 0.25; according to many studies, these numbers will be high, and because of the time required to count the pest on leaves, binomial sequential
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Three sequential binomial sampling plans with different action thresholds using the presence/absence of the pest at different plant stages; if the cumulative number of infested leaves is less than the lower decision threshold line, then sampling can be stopped and no control is required. If the cumulative number of infested leaves is above the upper decision threshold line, then control action is required. If the cumulative number of infested plants falls between the lower and upper lines, additional plants need to be sampled.

Dissemination -One workshop in each province. 100 farmers/ producers have been expected to participate in each workshop.
- Phone app for the binomial sampling plans, which can help to make a decision to determine when to intervene.
- 1000 reports.
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These two regression techniques have been widely used to measure dispersion and develop sampling protocols (Davis, 1994).
Describing the sample unit for the pest: To identify the sampling unit of the pest which infests the leaves on the crop, each plant will be divided into three parts (sub-samples; lower, middle and upper leaves) based on plant growth stages. To investigate the relationship between aphid counts on plant parts and whole plants, data for each species will be normalized using the log (10) transformation. Linear regressions will then utilized to describe the precision of each relationship (SAS Institute Inc., 2002).
Fixed sampling requirements: The sample sizes required for fixed precision levels of 0.1 and 0.25 will be calculated by using TPL parameters a and b to compare with binomial sequential sampling plans’ sample

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