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Journal: Vegetos- An International Journal of Plant Research

Article DOI :10.5958/2229-4473.2016.00081.1
Year :2016, Volume : 29, Issue :3
First page : (138) Last page : (145)
Print ISSN : 0970-4078. Online ISSN : 2229-4473.


Appraisal of Thrips Population Dynamics in Mango using Weather Based Indices

Gundappa*, Adak T, Shukla PK

ICAR-Central Institute for Subtropical Horticulture, Rehmankhera, Lucknow, Uttar Pradesh, India

*Corresponding author: Gundappa, ICAR-Central Institute for Subtropical Horticulture, Rehmankhera, Lucknow-226101, Uttar Pradesh, India, Tel: +91–522 284 1022, E-mail:

The aim of this investigation was to assess the dynamics of mango thrips population across 20 mango orchards based on thermal indices under subtropical Lucknow condition during 2013 and 2014. Wide variations in thrips populations were observed across different critical crop phenological stages and seasons. The thrips population was observed between 13th SMW to 24th SMW during 2013 cropping season, whereas it was found from 15th SMW to 28th SMW in the subsequent year. The mean thrips population across standard weeks was highest (6.18 ±0.14) during 15th SMW followed by 3.13 ± 0.15 in 16th and 1.87 ± 0.06 in 17th SMW during 2013, whereas in the next year (2014), the highest values were 4.67 ± 0.09 followed by 4.19 ± 0.10 and 4.07 ± 0.15 in 16th, 17th and 18th SMW respectively. Step wise regression analysis revealed that maximum temperature, minimum temperature, maximum relative humidity, minimum relative humidity, sunshine hours and evaporation could explained 55 per cent variations in thrips population. Different thermal indices viz., growing degree days (GDD), heliothermal units (HTU), photothermal units (PTU), were cumulated up to peak population density and a positive and significant correlation was revealed. The best fit polynomial regression analysis indicated that thrips population could be predicted up to 95 per cent using these thermal indices. Thus, it was concluded that use of all these robust indices may be useful in assessing the pest-weather dynamics of mango growing region and serve as a basis for real time pest management advisory.