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Non-preference for oviposition and damage intensity on soybean genotypes by Bemisia tabaci
Marida Santi Yudha Ika Bayu and Apri Sulistyo

Indonesian Legumes and Tuber Crops Research Institute


Abstract

Bemisia tabaci is one of the economically important pests of many cultivated plant. This pest also plays as a virus vector that causes high yield losses. The objective of this study was to determine non-preference for oviposition in soybean genotypes to B. tabaci and the damage intensity caused by this pest. The experiment was conducted in Indonesian Legumes and Tuber Crops Research Institute in 2018. 24 soybean genotypes were evaluated in screen house with three replicates in which infested naturally by B. tabaci. The result showed that egg and nimph populations were found on low, middle, and upper leaves. Generally, the highest population was found on middle leaves that ranged from 5-89 individuals/ trifoliate, followed by lower leaves (5-30 individuals/trifoliate) and upper leaves (0-19 individuals/trifoliate). Totally, the population of B. tabaci ranged form 12-125 individuals/plant. The highest population was found on genotype G100H/9305//IAC100-271///Grob-36-2 (125 individuals) and the lowest population was found on Kaba/IAC100//Brg 63///Grob-392-1 (12 individuals). Moreover, the leaf damage intensity caused by B. tabaci ranged from 8.6-38.3%. The highest damage intensity was found on G100H/9305//IAC100-271///Agro-803-1. However, the lowest damage intensity was found on G100H/9305//IAC100-271///Grob-42-3. Therefor, Kaba/IAC100//Brg 63///Grob-392-1 indicated as genotype that showed non-preference for oviposition based on egg and nymph populations and categorized as moderately resistant against B. tabaci based on leaf damage intensity. Whitefly attack characterized by the presence of black sooty mold on leaf surface.

Keywords: B. tabaci; damage intensity; non-preference; resistance mechanism.

Topic: Sustainable Agriculture and Agricultural Engineering

Link: https://ifory.id/abstract/X6qf2AhnLFej

Conference: International Conference on Innovation and Technology (ICIT 2019)

Plain Format | Corresponding Author (Marida Santi Yudha Ika Bayu)

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