Sequential sampling model for monitoring of Rhopalosiphum maidis (Fitch) (Hemiptera: Aphididae) in broomcorn fields of Miyaneh region, Iran

The present research was carried out for determining spatial distribution type and developing sequential sampling models for precise estimating of corn leaf aphid, Rhopalosiphum maidis (Fitch) population in broomcorn, sorghum vulgare var. technicum, fields of Miyaneh region, Iran. To investigate spatial distribution pattern, population was sampled every 3 days on 50 broomcorn tillers to calculate variance and mean number of aphids at each sampling date. Taylor’s power law was more suitable and so its parameters was used to develop sequential sampling models using Green (1970) method at precision levels of D = 0.1 and D = 0.25. Results revealed high number of corn leaf aphid in broomcorn field with an aggregated dispersion pattern. Mean aphid population at different sampling dates varied from 5.22 to 109.10 aphids per stem. Estimates of spatial distribution parameters were used to develop sequential sampling models and sampling stop lines using Green (1970) method at precision levels of D = 0.1 and D = 0.25. Comparison of sampling models showed that sample size required for estimating aphid density significantly increased by decreasing precision level from 0.25 to 0.1. So, sequential sampling model at 0.10 precision level was time - consuming and it was not suitable for estimating corn leaf aphid population. However, sequential sampling model at 0.25 precision level reduced sample size required for monitoring R. maidis population in comparison to the fixed sample size method. In conclusion, sequential sampling model at 0.25 precision level could reduce sampling time and so, it recommended for estimating population in IPM programs of the pest in broomcorn fields of Miyaneh region.