Spatial Distribution of Eggs of Alabama argillacea Hübner and Heliothis virescens Fabricius (Lepidoptera: Noctuidae) on Bt and non-BtCotton

• Autor(a) principal: RODRIGUES,TATIANA R.
• Data de Publicação: 2015
• Outros Autores: FERNANDES,MARCOS G., DEGRANDE,PAULO E., MOTA,THIAGO A.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Anais da Academia Brasileira de Ciências (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652015000502243
• topic: Cotton leafworm; Gossypium hirsutum; Tobacco Budworm; GMO

ABSTRACT Among the options to control Alabama argillacea (Hübner, 1818) and Heliothis virescens (Fabricius, 1781) on cotton, insecticide spraying and biological control have been extensively used. The GM'Bt' cotton has been introduced as an extremely viable alternative, but it is yet not known how transgenic plants affect populations of organisms that are interrelated in an agroecosystem. For this reason, it is important to know how the spatial arrangement of pests and beneficial insect are affected, which may call for changes in the methods used for sampling these species. This study was conducted with the goal to investigate the pattern of spatial distribution of eggs of A. argillacea and H. virescens in DeltaOpalTM (non-Bt) and DP90BTMBt cotton cultivars. Data were collected during the agricultural year 2006/2007 in two areas of 5,000 m2, located in in the district of Nova América, Caarapó municipality. In each sampling area, comprising 100 plots of 50 m2, 15 evaluations were performed on two plants per plot. The sampling consisted in counting the eggs. The aggregation index (variance/mean ratio, Morisita index and exponent k of the negative binomial distribution) and chi-square fit of the observed and expected values to the theoretical frequency distribution (Poisson, Binomial and Negative Binomial Positive), showed that in both cultivars, the eggs of these species are distributed according to the aggregate distribution model, fitting the pattern of negative binomial distribution.