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Nevin Manimala Statistics

Cultivar-specific fixed-precision sequential sampling plans for monitoring Oligonychus afrasiaticus (Acari: Tetranychidae) in date palm orchards of southwestern Iran

J Econ Entomol. 2026 Aug 14:toag252. doi: 10.1093/jee/toag252. Online ahead of print.

ABSTRACT

The Old World date mite, Oligonychus afrasiaticus (McGregor) (Acari: Tetranychidae), is one of the most economically important pests of date palm (Phoenix dactylifera L.) throughout the Middle East and North Africa. Reliable estimation of mite density is essential for integrated pest management (IPM), but the aggregated spatial distribution of this species reduces the efficiency of conventional fixed-sample-size sampling. This study developed and validated cultivar-specific fixed-precision sequential sampling plans for O. afrasiaticus on the commercially important date palm cultivars Sayer and Barhi using field data collected from commercial orchards in southwestern Iran during 2020 and 2021. Taylor’s power law adequately described the variance-mean relationship for both cultivars (R² > 0.93), with aggregation parameters significantly greater than unity (b = 1.380 for Sayer and 1.460 for Barhi), confirming aggregated distributions. Green’s fixed-precision sequential sampling model was used to construct stop lines at precision levels of D = 0.25, 0.15, and 0.10. Required sample size decreased with increasing mite density and increased as higher precision was required. Validation using the Resampling for Validation of Sampling Plans (RVSP) procedure with 1,000 iterations and 10 independent datasets showed excellent agreement between target and achieved precision. Mean achieved precision ranged from 0.101 to 0.251 for Sayer and from 0.099 to 0.249 for Barhi, with deviations from target precision below 0.01 for all sampling plans. The proposed sequential sampling plans provide statistically robust and operationally efficient tools for estimating O. afrasiaticus populations and improving pest monitoring and decision-making in date palm IPM programs.

PMID:42600049 | DOI:10.1093/jee/toag252

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