کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6296045 | 1617410 | 2016 | 4 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Shannon information theory a useful tool for detecting significant abiotic factors influencing the population dynamics of Helicoverpa armigera (Hübner) on cotton crop
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
بوم شناسی، تکامل، رفتار و سامانه شناسی
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چکیده انگلیسی
Helicoverpa armigera is a major pest on cotton (Gossypium spp.) and India ranks second in world production of cotton. This pest is highly adapted to different environments and abundance of this pest is due to both abiotic factors and hosts. In this study, the data mining technique based on Shannon information theory has been used for finding the significant factors that affect H. armigera incidence. This has been discussed in detail. The crop stage of cotton, season and abiotic factors like maximum temperature, minimum temperature, morning relative humidity, evening relative humidity, rainfall, number of rainy days in a week, have been considered for the analysis. The results of Shannon information theory showed that among all the factors, crop stage played a major role followed by number of rainy days in a week and relative humidity for the pest incidence and agreed well with correlation analysis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Modelling - Volume 337, 10 October 2016, Pages 25-28
Journal: Ecological Modelling - Volume 337, 10 October 2016, Pages 25-28
نویسندگان
M. Pratheepa, Abraham Verghese, H. Bheemanna,