GIS based pest-weather model to predict the incidence of Girdle beetle (Oberiopsis brevis) in Soybean crop

Authors

  • RAM MANOHAR PATEL ICAR-Indian Institute of Soybean Research, Indore (M.P.), India
  • A. N. SHARMA ICAR-Indian Institute of Soybean Research, Indore (M.P.), India
  • PURUSHOTTAM SHARMA ICAR-Indian Institute of Soybean Research, Indore (M.P.), India

DOI:

https://doi.org/10.54386/jam.v23i2.65

Keywords:

Girdle beetle, soybean, weather variables, forewarning, validation, GIS

Abstract

Girdle beetle (Oberiopsis brevis) is an important insect of soybean that can cause up to 42.2% yield loss in severe infestation during flowering stage. The infestation of girdle beetle is prevailed by congenial environmental conditions, which leads girdle beetle to be the severe pest of soybean. The present study assesses the relevant weather variables that can cause the peak infestation. Crop Pest Surveillance and Advisory Project (CROPSAP) survey data of girdle beetle incidence were analyzed with weather variables using correlation and regression techniques. The girdle beetle infestation had significantly positive correlation with relative humidity of current and 2nd lag week (RH0, RH-2); and with rainfall of 2nd lag week (RF-2) but significantly negative correlation with maximum temperature of 1st lag week (TMax-1). The multiple regression technique was used to develop the forewarning models for three zones (Vidarbha, Madhya Maharashtra and Marathwada zones) and overall Maharashtra, the developed models could explain 80.30%, 94.62%, 73.56% and 79.56% variation in girdle beetle infestation, respectively. The congenial conditions for the peak infestation of girdle beetle on soybean have been worked out and validated, which were TMax0, RH0, RF0, RH-1, RF-1, TMax-2, and RF-2 ranged between 28.6-31.6 ºC, 85.2- 91.8 %, 31.8-119.2 mm, 86.3-92.6 %, 38.1-76.4 mm, 27.7-30.8ºC, and 23.3-60.7 mm, respectively. The insect forewarning would be useful in devising the integrated management strategies for protecting the crop from insect in the incidence region.

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Published

01-06-2021

How to Cite

RAM MANOHAR PATEL, A. N. SHARMA, & PURUSHOTTAM SHARMA. (2021). GIS based pest-weather model to predict the incidence of Girdle beetle (Oberiopsis brevis) in Soybean crop. Journal of Agrometeorology, 23(2), 183–188. https://doi.org/10.54386/jam.v23i2.65

Issue

Vol. 23 No. 2 (2021): June

Section

Research Paper

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