Browsing by Author "VanGessel, Mark"
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Item Common ragweed (Ambrosia artemisiifolia L.) accessions in the Mid-Atlantic region resistant to ALS-, PPO-, and EPSPS-inhibiting herbicides(Weed Technology, 2024-03-08) D’Amico Jr. , Frank; Besanҫon, Thierry; Koehler, Alyssa; Shergill, Lovreet; Ziegler, Melissa; VanGessel, MarkCommon ragweed is a troublesome weed in many crops. Farmers and crop advisors in the coastal Mid-Atlantic region have reported inadequate control of common ragweed in soybean fields with glyphosate and other herbicide modes of action. To determine whether herbicide resistance was one of the causes of poor herbicide performance, 29 accessions from four states (Delaware, Maryland, New Jersey, and Virginia) where common ragweed plants survived herbicide applications and produced viable seeds were used for greenhouse screening. Common ragweed seedlings from those accessions were treated with multiple rates of cloransulam, fomesafen, or glyphosate, applied individually postemergence (POST). All accessions except one demonstrated resistance to at least one of the herbicides applied at twice the effective rate (2×), 17 accessions were two-way resistant (to glyphosate and cloransulam, or to glyphosate and fomesafen), and three-way resistance was present in eight accessions collected from three different states. Based on the POST study, five accessions were treated preemergence (PRE) with herbicides that inhibit acetolactate synthase (ALS), and two accessions were treated with herbicides that inhibit protoporphyrinogen oxidase (PPO). All accessions treated PRE with the ALS inhibitors chlorimuron or cloransulam demonstrated resistance at the 2× rates. Both accessions treated PRE with the PPO inhibitor sulfentrazone had survivors at the 2× rate. When the same accessions were treated PRE with fomesafen, one had survivors at the 2× rate, and one had survivors at the 1× rate. Results from these tests confirmed common ragweed with three-way resistance to POST herbicides is widespread in the region. In addition, this is the first confirmation that common ragweed accessions in the region are also resistant to ALS- or PPO-inhibiting herbicides when applied PRE.Item Early-season biomass and weather enable robust cereal rye cover crop biomass predictions(Agricultural & Environmental Letters, 2024-02-13) Huddell, Alexandra; Needelman, Brian; Law, Eugene P.; Ackroyd, Victoria J.; Bagavathiannan, Muthukumar V.; Bradley, Kevin; Davis, Adam S.; Evans, Jeffery A.; Everman, Wesley Jay; Flessner, Michael; Jordan, Nicholas; Schwartz-Lazaro, Lauren M.; Leon, Ramon G.; Lindquist, John; Norsworthy, Jason K.; Shergill, Lovreet S.; VanGessel, Mark; Mirsky, Steven B.Farmers need accurate estimates of winter cover crop biomass to make informed decisions on termination timing or to estimate potential release of nitrogen from cover crop residues to subsequent cash crops. Utilizing data from an extensive experiment across 11 states from 2016 to 2020, this study explores the most reliable predictors for determining cereal rye cover crop biomass at the time of termination. Our findings demonstrate a strong relationship between early-season and late-season cover crop biomass. Employing a random forest model, we predicted late-season cereal rye biomass with a margin of error of approximately 1,000 kg ha−1 based on early-season biomass, growing degree days, cereal rye planting and termination dates, photosynthetically active radiation, precipitation, and site coordinates as predictors. Our results suggest that similar modeling approaches could be combined with remotely sensed early-season biomass estimations to improve the accuracy of predicting winter cover crop biomass at termination for decision support tools. Core Ideas - Cereal rye winter cover crop biomass modeled on data from 35 site-years. - We found a strong relationship between early and late-season biomass. - Random forest model with early-season biomass and weather data performed well. - Similar approach could improve decision support tools for cover crop management. Graphical Abstract available at: https://doi.org/10.1002/ael2.20121 Effect size estimates from the generalized linear mixed effects model prediction late-season cereal rye cover crop biomass. All covariates were standardized, and significant relationships are indicated by *p < 0.05, **p < 0.01, and ***p < 0.001. Abbreviations CGDD cumulative growing degree days GLMM generalized linear mixed effects model PAR photosynthetically active radiation