Prediction of Whitefly Population and Infestation Based on Multitrophic Analysis between Competitor Pest, Plant Traits and Natural Enemy

Abstract

Interaction among arthropods (insect-acarine) was investigated at all trophic levels in agro-ecosystem and affects the population dynamic and diversification of arthropod pests and intensity of natural enemy (parasitism) as well as stimulates the plant chemical defence. In the present study of two cropping periods, nutrient concentration and early infestation of plant-sucking pests are known to trigger different degrees of interactions (plant's parameters) which potentially alert abundance and diversity of the insect pests. Clearer interaction and magnitude of impact could be assessed (multivariate analysis of variance (MANOVA) and redundancy analysis (RDA)) and observed between arthropods (insect-acarine) community and plants' parameters from the strongest to the lowest effects. The two factors could have affected the community of insect-pests with various degrees of pressure effect and interaction that occurred naturally, thus leading to the predictable abundance of insect-acarine populations under eggplant leaves in response to plant physical characteristics (e.g., size of leaves, number of leaves and plant height) and biochemical constituents (flavonoid, phenolic, peroxidase and β-1,3-glucanase). Based on multivariate analyses of multitrophic interaction, MANOVA and RDA have the potential to elucidate the complex interaction among plant performance, abundance of pests and activity chemical defence compounds. Both analyses interpreted similar interactions of measured parameters in different ways. Whitefly population in this study was predictable by aphids, thrips and total phenolic contents in eggplant. Eggplant has capable defence systems against insect-acarine pests after stimulation (pre-infestation). In relation to IPM strategy, early stages of plant growth are known as susceptible periods for pests attack but the plant becomes more tolerant during the fruiting stage.