In-Field and Soil-Related Factors that Affect the Presence and Prediction of Glyphosate-Resistant Horseweed (Conyza canadensis) Populations Collected from Indiana Soybean Fields

Abstract

Glyphosate-resistant (GR) crops have been rapidly adopted in the United States and the evolution of GR weeds throughout the world has also been on the rise. With experience, weed scientists and crop advisers develop “intuition” on the basis of field history and current in-field conditions for predicting whether escaped weed biotypes may be herbicide resistant. However, there are no previous reports on the association of in-field crop management factors with the prediction of herbicide resistance. By using in-field survey data, we tested the accuracy of predicting glyphosate resistance in late-season horseweed escapes. We hypothesized that glyphosate resistance in late-season horseweed populations found in soybean fields could be predicted using in-field knowledge of crop residues and the appearance and distribution of weeds in the field. Field survey data were collected to determine the distribution and frequency of GR horseweed populations in Indiana soybean fields during September and October of 2003, 2004, and 2005. After the in-field survey, soil properties for sampled field locations were also collected from the U.S. Department of Agriculture Natural Resources Conservation Service Web Soil Survey. GR horseweed predictions used in-field presence of crop residues and the appearance, abundance, and distribution of weeds in the field. The significance of independent data factors were determined by chi-square statistics. The interactions and relative significance of multiple factors were modeled using classification and regression tree analysis. Our results indicated that the most important factor for predicting GR populations was the identification of an altered plant phenotype after injury from POST glyphosate. This was followed by crop rotation, field distribution, and the presence of other escaped weed species in the field in a model with a classification rate of 0.68.

Herbicide‐resistant weed management: focus on glyphosate

“…The authors suggest that fitness costs may partially contribute to the relatively low frequency of glyphosate resistance alleles in the absence of selection, which is a plausible explanation. However, other studies have found minor or no fitness costs of glyphosate resistance 47–50…”

“…In Indiana, GR C. canadensis was associated with a lack of crop rotation diversity—i.e. soybean monoculture—and no‐tillage systems 47. The light C. canadensis seeds can disperse readily by wind or convective air currents, documented at distances of over 500 km 77, 78…”

“…sulfentrazone) before planting corn or soybean, in sequence with glyphosate applied POST, were often the most cost effective at reducing season‐long C. canadensis densities and maximising crop yield 47, 83. After 4 years, GR C. canadensis control was better in a soybean–corn rotation than in continuous soybean 47. In a survey of Delaware soybean growers with GR C .…”

Why have no new herbicide modes of action appeared in recent years?

“…The most resistant weed biotypes have other mechanisms of resistance based on gene amplification15, 16 or sequestration of glyphosate in the vacuole 17, 18. Weeds with these two mechanisms of action have been highly problematic in some places where GR crops have been grown continuously for several years, such as GR cotton in the southeastern United States19 and GR soybeans in the mid‐southern and mid‐western United States 5, 20…”

Respray Requests on Custom-Applied, Glyphosate-Resistant Soybeans in Illinois: How Many and Why

“…Although direct-mail surveys and interviews have made clear the general beliefs that underlie weed control decisions, still unknown are the specific criteria that perhaps ultimately determine whether control is implemented or withheld because surveys and interviews can occur much later in the season, and therefore, they may fail to incorporate the actual conditions seen by farmers during deliberation. Such disconnections between settings of commercial crop production and scientific inquiry have long been recognized (Thompson and Thompson 1990;Wuest et al 1999), and have recently been accounted for with paired surveys of weed communities and management practices on cooperator farms (Davis et al 2009;Luschei et al 2009). …”