مدل نمونه‌برداری دنباله‌ای برای پایش شته برگ ذرت Rhopalosiphum maidis (Fitch) در مزارع سورگوم جارویی منطقه میانه

محورهای موضوعی : بوم شناسی گیاهان زراعی

حبیب اله خدابنده ¹ (گروه گیاه‌پزشکی، واحد میانه، دانشگاه آزاد اسلامی، میانه، ایران)
شهرام شاهرخی خانقاه ² (مؤسسة تحقیقات گیاه‌پزشکی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران)

تاریخ دریافت : 1397/03/13 تاریخ پذیرش : 1397/08/06 تاریخ انتشار : 1397/08/01

کلید واژه:  تخمین جمعیت,  توزیع‌فضایی,  ردیابی,  شته برگ ذرت,  مدیریت تلفیقی آفات,

چکیده مقاله :

این پژوهش به منظور تعیین نوع توزیع فضایی و ارایه مدل نمونه برداری دنباله ای برای تخمین دقیق تراکم جمعیت شته برگ ذرت (Fitch) Rhopalosiphum maidisدر مزارع سورگوم جارویی منطقه میانه انجام شد. برای نمونه برداری از جمعیت شته، هر سه روز یک بار تعداد 50 ساقه سورگوم جارویی مورد بازدید قرار گرفت و میانگین و واریانس جمعیت در هر تاریخ نمونه برداری برای تخمین پارامتر های توزیع فضایی مورد استفاده قرار گرفت. در ادامه با توجه به مناسب بودن قانون نمایی تیلور، از پارامتر های این روش برای تهیه مدل های نمونه برداری دنباله ای به روش گرین (1970) در دو سطح دقت 10 و 25% استفاده شد. شته برگ ذرت فراوانی قابل توجهی در مزارع سورگوم جارویی منطقه میانه داشت و توزیع فضایی آن در مزرعه به صورت تجمعی بود. میانگین جمعیت شته در تاریخ های مختلف نمونه برداری از 5 تا 109 عدد در هر ساقه متغیر بود. مقایسه مدل های نمونه برداری تهیه شده نشان داد که با کاهش سطح دقت از 25 به 10%، اندازه نمونه مورد نیاز برای تخمین جمعیت شته در مدل نمونه برداری دنباله ای به طور قابل توجهی افزایش یافت. بنابراین، مدل نمونه برداری دنباله ای در سطح دقت 10% بسیار وقت گیر بوده و برای تخمین تراکم جمعیت شته مناسب نبود. با این وجود، مدل نمونه برداری دنباله ای در سطح دقت 25% در مقایسه با اندازه نمونه ثابت، باعث کاهش اندازه نمونه لازم برای پایش جمعیت شته شد. در مجموع، استفاده از مدل نمونه برداری دنباله ای در سطح دقت 25% می تواند زماننمونه برداری را نسبت به روش اندازه نمونه ثابت کاهش داده و برای تخمین جمعیت این آفت در برنامه مدیریت تلفیقی آن در مزارع سورگوم جارویی میانه قابل توصیه می باشد.

چکیده انگلیسی:

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.

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