In November 2004, a 29-question survey was mailed to Delaware soybean growers to determine grower perceptions of glyphosate-resistant (GR) horseweed and if glyphosate applications, GR soybean usage, and management practices had been altered in lieu of the presence of resistance. A total of 213 valid responses were received. Ninety-eight percent of respondents reported planting GR soybean at some point in the last 5 yr, with 90% reporting having planted GR soybean 3 or more years. The presence of GR horseweed on-farm was reported by 38% of the respondents and 95% of those growers with GR horseweed on-farm reported implementing one or more changes in GR soybean management. The most frequent change (66% of growers) due to resistant horseweed was the application of another herbicide with a different mode of action before planting. Forty-eight percent of growers with resistance on-farm reported a $5 to $17/ha increase to manage for GR horseweed, with 28% reporting a greater than $17/ha increase. Regardless of experience with GR horseweed, approximately 80% responded that it was worthwhile to incur additional costs now to preserve glyphosate for future use. Soybean grower reliance on glyphosate has not decreased in light of GR horseweed in Delaware. Misconceptions of timing for the selection of GR horseweed biotypes and the future availability of new herbicides with different modes of action exist within the farming community.

Certified Crop Advisors of Arkansas and members of the Arkansas Crop Consultants Association were surveyed in Fall 2006 through direct mail to assess current weed management practices and needs in rice from both a research and educational perspective. Consultants reported scouting 228.2 of the possible 567 thousand hectares (40%) of rice grown in Arkansas. Pre-emergence herbicides most often recommended were clomazone (93%) and quinclorac (40%). Propanil (55%) and quinclorac (47%) were the two most commonly recommended postemergence herbicides. Thirty-two percent of the consultants often recommend three or more herbicide applications per field. An average of 37% of the fields were believed to have “serious” or “very serious” weed infestations, and fields were scouted for weeds on average 11 times per growing season. Ninety-two percent of the consultants had “moderate” to “high” concerns with herbicide-resistant weeds. The perceived average additional expense associated with managing a resistant weed in rice was $65.60/ha. Propanil-resistant and quinclorac-resistant barnyardgrass were believed to be infesting 24 and 7% of the scouted rice hectares, respectively. Barnyardgrass was the most problematic weed of rice followed by red rice. Northern jointvetch and smartweeds were the two most problematic broadleaf weeds. The number one research need was improved broadleaf weed control. Respondents indicated that research and educational efforts should continue to focus on herbicide performance and development of economical weed control programs.

Jointed goatgrass is a prominent weed infesting winter wheat in the western United States. Individual control tactics often are ineffective and inconsistent, but management systems comprised of several tactics designed to disrupt population dynamics of jointed goatgrass can reduce infestation levels in winter wheat. Tactics are planned to favor decline of seedbank density, reduce seedling emergence in winter wheat, and minimize seed production of plants established in winter wheat. We describe a visual guide that will help producers plan management systems for jointed goatgrass with a diversity of cultural tactics. The guide organizes cultural tactics by decision times of producers during the winter wheat production cycle. Scientists are effectively managing jointed goatgrass in a diversity of production systems by integrating cultural tactics across decision times.

Although many of us fondly associate parsnips with a rustic, home-cooked meal, there is also a wild variety that is increasingly causing problems as a weed in North America. The cultivated variety is a subspecies of Pastinaca sativa (Pastinaca sativa ssp. sativa) and contains lower amounts of the problematic furanocoumarins than the wild version. Wild parsnip (Pastinaca sativa L. PAVSA) is an introduced facultative biennial from Eurasia. It has spread throughout the United States and southern Canada and is now colonizing old fields, railroad embankments, roadsides, and waste areas. Wild parsnip contains furanocoumarins, which deter herbivores from eating its foliage. These compounds can also cause phytophotodermatitis in humans and livestock, a condition that results in patches of redness and blisters on the skin when they come into contact with the sap or ingest parts of the plant in the presence of sunlight. Few people, including medical professionals, recognize the plant or associate it with the burns it causes. Recently, wild parsnip has received increasing attention as expanding populations have resulted in more frequent human and livestock contact with the plant. This article reviews important aspects of the etymology, distribution, history, biology, and management of wild parsnip. A key objective of this review is to raise awareness of the potential health problems caused by wild parsnip and to stimulate research that will lead to effective management of this increasingly problematic species.

Advances in statistical software allow statistical methods for nonlinear regression analysis of dose-response curves to be carried out conveniently by non-statisticians. One such statistical software is the program R with the drc extension package. The drc package can: (1) simultaneously fit multiple dose-response curves; (2) compare curve parameters for significant differences; (3) calculate any point along the curve at the response level of interest, commonly known as an effective dose (e.g., ED30, ED50, ED90), and determine its significance; and (4) generate graphs for publications or presentations. We believe that the drc package has advantages that include: the ability to relatively simply and quickly compare multiple curves and select ED-levels easily along the curve with relevant statistics; the package is free of charge and does not require licensing fees, and the size of the package is only 70 MB. Therefore, our objectives are to: (1) provide a review of a few common issues in dose-response-curve fitting, and (2) facilitate the use of up-to-date statistical techniques for analysis of dose-response curves with this software. The methods described can be utilized to evaluate chemical and non-chemical weed control options. Benefits to the practitioners and academics are also presented.