Spatially-Optimized Sequential Sampling Plan for Cabbage AphidsBrevicoryne brassicaeL. (Hemiptera: Aphididae) in Canola Fields

Abstract

The cabbage aphid is a significant pest worldwide in brassica crops, including canola. This pest has shown considerable ability to develop resistance to insecticides, so these should only be applied on a "when and where needed" basis. Thus, optimized sampling plans to accurately assess cabbage aphid densities are critically important to determine the potential need for pesticide applications. In this study, we developed a spatially optimized binomial sequential sampling plan for cabbage aphids in canola fields. Based on five sampled canola fields, sampling plans were developed using 0.1, 0.2, and 0.3 proportions of plants infested as action thresholds. Average sample numbers required to make a decision ranged from 10 to 25 plants. Decreasing acceptable error from 10 to 5% was not considered practically feasible, as it substantially increased the number of samples required to reach a decision. We determined the relationship between the proportions of canola plants infested and cabbage aphid densities per plant, and proposed a spatially optimized sequential sampling plan for cabbage aphids in canola fields, in which spatial features (i.e., edge effects) and optimization of sampling effort (i.e., sequential sampling) are combined. Two forms of stratification were performed to reduce spatial variability caused by edge effects and large field sizes. Spatially optimized sampling, starting at the edge of fields, reduced spatial variability and therefore increased the accuracy of infested plant density estimates. The proposed spatially optimized sampling plan may be used to spatially target insecticide applications, resulting in cost savings, insecticide resistance mitigation, conservation of natural enemies, and reduced environmental impact.

Field evaluation of synthetic and neem-derived alternative insecticides in developing action thresholds against cauliflower pests

“…While straightforward strategies of applying insecticides at pre-determined times may be preferred, over integration of multiple control methods, by growers due to their operational simplicity and perceived effectivity 42 , such approaches are likely to fail in the absence of action threshold guidelines 43 . Action threshold based guidelines have been developed for cruciferous pests 44 but thresholds can vary according to pest species (e.g. due to differing consumption rates) 41,45 and may also differ regionally 46 .…”

Edge-biased distributions of insects. A review

“…For example, increased performance (less sampling needed) of such a spatially targeted sampling approach was demonstrated for the wheat stem sawfly ). In addition, Severtson et al (2016) described a spatially optimized sequential sampling plan for cabbage aphids in canola fields. In their study, canola fields were divided into two types of sampling grids: inner grids and edge grids.…”

“…Their sampling results showed that 9 out of 20 edge grids displayed infestation level above threshold while only 2 out of 20 inner grids showed infestation level above threshold. Taking the proposed edge effect distribution of aphids into account, Severtson et al (2016) conducted stratified sampling analysis and managed to reduce spatial variability as well as to increase accuracy of infestation level. Nonetheless, we also acknowledge that edge effect distribution of insects in many agricultural systems can be highly seasonal and temporally dependent (Corbett and Rosenheim 1996;Winder et al 1999;Holland et al 1999;Wilson and Morton 1993).…”

Economic injury levels and sequential sampling plans forFrankliniella schultzeiin watermelon crops

“…This results in a variable number of samples in sequential sampling plans . Therefore, in sequential sampling plans, the number of evaluated samples, the time and the cost of sampling may be lower than those in conventional plans . Nevertheless, the use of a certain sequential sampling plan in any given crop must be validated.…”