Use of Predator to Pest Ratio as a Decision Making Tool in Integrated Pest Management (IPM) in Cotton

Date Issued:2002-08-13

Abstract

Elsewhere in this proceedings I have stated that the cotton industry in Australia is undertaking a journey towards the adoption of a true IPM. The industry has come a long way from indiscriminate use of synthetic insecticides to realising the major role natural enemies of cotton pests particularly predatory insects play in cotton IPM. Many beneficial insects such as predatory beetles, bugs, lacewings, spiders and parasitoids have been recorded in cotton crops in Australia. However, the potential value of these beneficial insects have riot been fully exploited in cotton pest management. This is due to the lack of understanding of the efficacy of these beneficial insects, lack of techniques to maximise their abundance and effectiveness, and the continuous use of broad-spectrum insecticides on cotton crops against major pests. Cotton fields across Australia are strictly monoculture and can affect the activities of beneficial insects. In such agro-ecosystems, pest populations increase, minor pests become major pests and non-pests become pests. This is because the food, hosts, prey, and hibernating or overwintering sites of the natural enemies are reduced thus affecting biological control (Mensah, 1997, 1999). Natural enemies of cotton pests usually have different food requirements in the larval and adult stages to develop and survive through the season. In contrast, adult pests particularly Helicoverpa spp. can normally lay their eggs without any feeding, relying only on food reserves transferred from their larval stage. Helicoverpa spp. are highly migratory and can rapidly infest cotton crops and lay their eggs. Unless natural enemies are present and well established in high numbers before the pest arrive, they cannot respond rapidly enough to control these pests (Fit, 1989; Mensah, 1997, 1999). This paper focuses only on predatory insects and how to incorporate them in pest management decisions.

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