Biotech Updates

Weed Risk Assessment System (WRA) Assesses Potential Invasiveness of Bioenergy Crop Species

January 28, 2011
(complete access to journal article may require paid subscription) http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V22-50X9S7F-
6&_user=10&_coverDate=01/31/2011&_rdoc=1&_fmt=high&_orig=search&_origin=search
&_sort=d&_docanchor=&view=c&_searchStrId=1621129812&_rerunOrigin=google&_acct=
C000050221&_version=1&_urlVersion=0&_userid=10&md5=20d1b4fcd93d42399176bb6
140039551&searchtype=a

Researchers from the University of Florida (United States) report the use of the Australian Weed Risk Assessment (WRA) system to evaluate the potential invasiveness of certain taxa of biofuel crops in Florida and the United States. "Potential invasiveness" is a not-so-often-mentioned criterion in the selection of bioenergy crops for cultivation and biofuel production. The more commonly mentioned biofuel-crop-cultivation criteria are: (1) high productivity, (2) low input requirements, and (3) wide habitat breadth. Invasion potential is said to be an issue of concern "because of the substantial economic and ecological impacts of plant species that become invasive in new habitats". Thus, it has been recommended that the selection of biofuel crops to be planted in a certain area must include an assessment of potential risk that the species might become invasive. The Australian WRA has been reported to identify invaders 90% of the time, while for non-invaders, 70% of the time. Using this system to test certain bioenergy crop species for cultivation in Florida, the following were found to have a high probability of invasiveness: Jatropha curcas, Eucalyptus grandis, Leucaena leucocephala, Ricinus communis. On the other hand, Miscanthus giganteus, Saccharum officinarum, and a sweet variety of Sorghum bicolor was found to have a low probability for invasiveness. The full paper is published in the journal, Biomass and Bioenergy (URL above)

Related information on Australian Weed Risk Assessment (WRA) System: http://plants.ifas.ufl.edu/assessment/pdfs/predictive_tool.pdf