Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Biometrical Letters

The Journal of Polish Biometric Society

2 Issues per year

Open Access
Online
ISSN
1896-3811
See all formats and pricing
More options …

On determination of ETL – a distributional approach

Satyabrata Pal
  • Corresponding author
  • Former Dean, Post Graduate Studies and Professor of Agricultural Statistics, Bidhan Chandra Krishi Viswavidyalaya, Faculty of Agriculture, Mohanpur, Nadia, West Bengal, 741252, India
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Arunava Ghosh
  • Corresponding author
  • Uttar Banga Krishi Viswavidyalaya, Department of Agricultural Statistics, Pundibari, Coochbehar, West Bengal, 736165, India
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Tapamay Dhar
  • Corresponding author
  • Uttar Banga Krishi Viswavidyalaya, Regional Research Sub Station, Malda, West Bengal, 732203, India Uttar Banga Krishi Viswavidyalaya, Regional Research Sub Station, Malda, West Bengal, 732203, India
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2013-12-10 | DOI: https://doi.org/10.2478/bile-2013-0021

Summary

Economic threshold level (ETL) is an important component in pest management and control. Usually, it is determined by the grower/technologist utilizing his experience on a crop; however, for cereals the values of these indices are available. Knowledge of ETL helps reduce crop loss (and ensure less pesticide application), and as a consequence, profit is increased. Also substantial knowledge is required on the dynamics of the pest population, in order to determine the density at which the economic injury level (EIL) may be prevented (Weersink et al. 1991). This paper is devoted to the development of an analytical method (probabilistic) for determination of ETL, which is defined as the density at which control measures should be determined to prevent an increasing pest population from reaching the economic injury level. A method to model the dynamics of the pest population is also proposed. The above method is demonstrated on a real life data set on pest (whitefly) incidence on betelvine, obtained from an experiment designed for that purpose.

Keywords: Economic Threshold Level (ETL); Nonparametric and semi-parametric models; Occurrence Probability; Kolmogorov-Smirnov (K-S) Test

  • Eubank R. (1988): Spline Smoothing and Nonparametric Regression. Marcel Dekker, New York.Google Scholar

  • Afzal M., Yasin M., Sherawat S.M. (2002): Evaluation and Demonstration of Economic Threshold Level (ETL) for Chemical Control of Rice Stem Borers Scirpophagaincertulus Wlk. And S.innotata Wl. International Journal of Agriculture and Biology 3: 323-325.Google Scholar

  • Simonoff J. (1995): Smoothing Methods of Statistics. Springer. New York.Google Scholar

  • Thisted R.A. (1988): Elements of Statistical Computing. Chapman and Hall, New York.Google Scholar

  • Weersink A., Deen W., Weaver S. (1991): Defining and Measuring Economic Threshold Levels. Canadian Journal of Agricultural Economics 39(4): 619-625.CrossrefGoogle Scholar

About the article

Published Online: 2013-12-10

Published in Print: 2013-12-01


Citation Information: Biometrical Letters, Volume 50, Issue 2, Pages 107–116, ISSN (Print) 1896-3811, DOI: https://doi.org/10.2478/bile-2013-0021.

Export Citation

This content is open access.

Comments (0)

Please log in or register to comment.
Log in