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Abstract

Consumers’ valuation of food products derived from Genetically Modified Organisms (GMOs) have played a pivotal and often constraining role in the development of biotechnology advances in agriculture. As a result, agricultural companies have started exploring new biotechnologies that do not require the genetic modification of crops. One of these emerging biotechnologies is a non-GMO RNA interference (RNAi) liquid application that could be used to control specific insect pests. When ingested by a targeted sub-species of an insect during production, RNAi blocks the expression of a vital gene, which in turn kills it. RNAi is non-toxic to humans and kills only targeted sub-species of insects, which differs from most conventional pesticides. For example, RNAi could selectively eliminate a specific sub-species of caterpillar pest, while not harming a monarch butterfly caterpillar. In contrast, conventional pesticides often kill insects indiscriminately and vary in human toxicity levels. Since agricultural producers and researchers have faced opposition to GMOs, this may be an alternative to controlling commonly encountered insects; however, consumers’ valuation of traditional GM compared to RNAi derived foods has not been evaluated in the scientific literature. Thus, we conducted a Willingness-To-Pay (WTP) survey in the USA, Canada, Australia, France, and Belgium to analyze whether consumers need a premium or discount for: (1) a hypothetical GMO rice using the Bacillus thuringiensis (Bt) gene for insect control; and (2) a hypothetical non-GMO rice using RNAi for insect control. Since there is currently no commercially-available GMO rice, measuring consumers’ valuation of rice produced by alternative biotechnologies provides vital information for crop breeders and policy makers. The results suggest that consumers require a discount for RNAi and Bt rice compared to a conventionally produced rice, but the discount required for the non-GMO RNAi rice was 30-40 percent less than that needed to purchase GMO Bt rice (p < 0.01).

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