Vol. 11, Special Issue 9 (2022)

Author(s):
Kumari Pragya, SB Das and Sumit Kakade

Abstract:
Maize also known as queen of cereals is having its utility because of its rich nutritive value along with its wide usability in industries. A recent study mentioned that 61% of global maize consumption is in the form of feed, whereas 17 and 22% is being utilized as food and in various industries, respectively. The increasing cropping area under maize, provides conditions conducive for flourishing of the insect pest population. One of the recently emerging and most damaging pest of maize is fall army worm (FAW). FAW is considered as an invasive species with great migration capabilities, however, it is an established fact that the entry and establishment of any invasive pest is majorly driven by favourable climatic conditions prevailing in the area. Present study aims to provide some regression models for prediction of FAW in maize in maize in 1-2 weeks in advance. The findings of present study revealed that preceding one week maximum temperature, wind speed and evaporation exhibited significant positive correlation with the FAW population and the prediction equation computed is Ŷ= - 10.54 + 0.03 X₁ + 0.56 X₂ + 0.24 X₃ - 0.14 X₄ - 0.02 X₅ - 0.75 X₆ - 0.01 X₇ + 0.46 X₈ + 0.79 X₉ - 0.05 X₁₀ (R²=0.9265). Whereas, for preceding two week wind speed exhibited significant positive correlation with the FAW population and the prediction model is Ŷ= 6.37 + 0.00 X₁ + 0.00 X₂ + 0.24 X₃ - 0.05 X₄ – 0.11 X₅ – 1.10 X₆ - 0.01 X₇ + 0.66 X₈ + 0.66 X₉ + 0.46 X₁₀ (R² = 0.9047).