1Faculty of Agriculture, Department of Plant Protection, Igdir University Igdır-76000, Turkey
2Faculty of Economics and Administrative Sciences, Department of Business Administration, Igdir, Turkey
3Centre of Advanced Studies in Vaccinology and Biotechnology, University of Balochistan, Quetta, Pakistan
ABSTRACT
The current study was conducted to develop a new approach for revealing egg-laying behaviour of alfalfa weevil, Hypera postica (Gyllenhal) (Coleoptera: Curculionidae)laying in alfalfa fields at late fall. Totally, the infected 675 alfalfa plants were evaluated with the objective to predict height of eggs laid by the alfalfa weevil at the plant stem from plant height, number of eggs per cluster, number of egg clusters at the plant stem, and location as potential predictors. In the prediction of height of eggs, CHAID (Chi-square Automatic Interaction Detection) and MARS (Multivariate Adaptive Regression Splines) algorithms were implemented for describing egg laying behaviour of the alfalfa weevil and giving an idea on minimizing loss of the fields, in practice. In conclusion, a new scale developed by CHAID indicated that height of eggs was found higher as the plant height increased from Node 1 (plant height < 23 cm) to Node 10 (plant height > 74 cm), and in MARS, number of egg cluster and plant height affected height of eggs (P<0.05), which may help to describe egg laying behaviour of alfalfa weevil, H. postica.
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