Indian Journal of Agricultural Research

  • Chief EditorT. Mohapatra

  • Print ISSN 0367-8245

  • Online ISSN 0976-058X

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Indian Journal of Agricultural Research, volume 55 issue 3 (june 2021) : 383-386

Prediction of Nematode Population Dynamics using Weather Variables in Leguminous Crops

Kamal Batra, Parul Gandhi
1Manav Rachna International Institute of Research and Studies, Faridabad-121 004, Haryana, India.
Cite article:- Batra Kamal, Gandhi Parul (2021). Prediction of Nematode Population Dynamics using Weather Variables in Leguminous Crops. Indian Journal of Agricultural Research. 55(3): 383-386. doi: 10.18805/IJARe.LR-4572.
Background: The soil nematodes can affect the crops in various ways. The plant-parasitic nematodes can lead to severe yield losses. The extent of crop yield loss depends on the susceptibility of the variety or host tolerance, population density of the nematode and various environmental variables. However, no tool is available for the prediction of nematode population buildup in soil therefore it has been difficult to issue advisories for timely management of these pathogens. Here we developed a method to accurately predict the nematode population buildup in soil for its timely management. 
Methods: Nematode population index of a plant-parasitic nematode Tylenchorynchus was taken from two crops i.e. mung bean and crotalaria. The model was developed considering various weather variables to predict the population of the Tylenchorynchus in the fields of mung bean and crotalaria. Weather parameters such as maximum and minimum temperature, relative humidity, wind speed and sunshine hours were considered for developing the model for Tylenchorynchus population prediction. Stepwise regression method was applied to predict the nematode population. 
Result: The regression analysis between estimated and observed values of Tylenchorynchus population gave the R2 value as 0.98 for mung bean and 0.87 for crotalaria. Well timed prediction can help the growers to apply the required management practices to make it beneficial economically. This method can be extended to predict the population buildup of other serious nematode pests of crops.
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