Yu, HL; Li, YH; Wu, KM
Journal of Integrative Plant Biology. 2011 July. 53(7):520–538
Link to full text (journal may charge for access)
PMID: 21564541 DOI: 10.1111/j.1744-7909.2011.01047.x ISSN: 1672-9072
The application of recombinant DNA technology has resulted in many insect-resistant varieties by genetic engineering (GE). Crops expressing Cry toxins derived from Bacillus thuringiensis (Bt) have been planted worldwide, and are an effective tool for pest control. However, one ecological concern regarding the potential effects of insect-resistant GE plants on non-target organisms (NTOs) has been continually debated. In the present study, we briefly summarize the data regarding the development and commercial use of transgenic Bt varieties, elaborate on the procedure and methods for assessing the non-target effects of insect-resistant GE plants, and synthetically analyze the related research results, mostly those published between 2005 and 2010. A mass of laboratory and field studies have shown that the currently available Bt crops have no direct detrimental effects on NTOs due to their narrow spectrum of activity, and Bt crops are increasing the abundance of some beneficial insects and improving the natural control of specific pests. The use of Bt crops, such as Bt maize and Bt cotton, results in significant reductions of insecticide application and clear benefits on the environment and farmer health. Consequently, Bt crops can be a useful component of integrated pest management systems to protect the crop from targeted pests.
Yu, HL, YH Li, KM Wu. "Risk assessment and ecological effects of transgenic Bacillus thuringiensis crops on non-target organisms." Journal of Integrative Plant Biology 53.7 (2011): 520–538. Web. 2 Jul. 2020.
Yu, HL., Li, YH., & Wu, KM. (2011). Risk assessment and ecological effects of transgenic Bacillus thuringiensis crops on non-target organisms. Journal of Integrative Plant Biology, 53(7), 520–538. doi:10.1111/j.1744-7909.2011.01047.x
Please verify citations before use, citations are automatically generated based on information stored within the GENERA database and therefore may or may not be correct.