Population prediction model of citrus psylla, Diaphorina citri Kuwayama on Kinnow Mandarin using weather data in Punjab, India

Authors

  • SANDEEP SINGH Department of Fruit Science, Punjab Agricultural University, Ludhiana- 141004, Punjab, India
  • RAJWINDER KAUR SANDHU Department of Fruit Science, Punjab Agricultural University, Ludhiana- 141004, Punjab, India
  • S. S. SANDHU Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana- 141004, Punjab, India
  • K. K. GILL Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana- 141004, Punjab, India
  • MASRAT SIRAJ Department of Entomology, Punjab Agricultural University, Ludhiana- 141004, Punjab, India
  • P. VENKATA RAMI REDDY Division of Crop Protection, ICAR-Indian Institute of Horticultural Research, Bengaluru- 560089, Karnataka, India
  • PRAKASH PATIL Project Coordinator Cell, ICAR-AICRP on Fruits, ICAR-Indian Institute of Horticultural Research, Bengaluru- 560089, Karnataka, India

DOI:

https://doi.org/10.54386/jam.v26i2.2444

Keywords:

Diaphorina citri, Correlation, Temperature-humidity index (THI), Prediction model, Psylla population, Kinnow Mandarin

Abstract

Field experiments were carried out to study the population dynamics of citrus psylla, Diaphorina citri Kuwayama on Kinnow Mandarin for twelve years (2007-08 to 2019-20) in relation to different weather parameters and to develop population prediction model. Adult psyllids were observed throughout the year but the population was very low during November-January. Two population peaks were observed during March and September. Highest mean population (80.8 nymphs/25 twigs) was observed during second fortnight of September which varied in different years. Psyllid population showed significant and positive correlation with maximum and minimum temperature, vapour pressure, wind speed, sunshine hours, rainfall and negative correlation with relative humidity and number of rainy days. A weather-based model was developed to predict psylla population seven days in advance. The validation of the model carried out using various indices viz, root mean square error, coefficient of determination, Nash-Sctuliffe efficiency and mean bias error suggested that, the model predicted the population of citrus psylla quite satisfactorily. Thus, the developed model can be used satisfactorily for weather-based prediction of citrus psylla in Punjab, seven days in advance.

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Published

01-06-2024

How to Cite

SINGH, S., SANDHU, R. K., SANDHU, S. S., GILL, K. K., SIRAJ, M., REDDY, P. V. R., & PATIL, P. (2024). Population prediction model of citrus psylla, Diaphorina citri Kuwayama on Kinnow Mandarin using weather data in Punjab, India: . Journal of Agrometeorology, 26(2), 243–248. https://doi.org/10.54386/jam.v26i2.2444

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