Late and early leaf spot, respectively caused by Nothopassalora personata and Passalora arachidicola, are damaging diseases of peanut (Arachis hypogaea) capable of defoliating canopies and reducing yield. Although one of these diseases may be more predominant in a given area, both are important on a global scale. To assist informed management decisions and quantify relationships between end-of-season defoliation and yield loss, meta-analyses were conducted over 140 datasets meeting established criteria. Slopes of proportion yield loss with increasing defoliation were estimated separately for Virginia and runner market type cultivars. Yield loss for Virginia types was described by an exponential function over the range of defoliation levels, with a loss increase of 1.2 to 2.2% relative to current loss levels per additional percent defoliation. Results for runner market type cultivars showed yield loss to linearly increase 2.2 to 2.8% per 10% increase in defoliation for levels up to approximately 95% defoliation, after which the rate of yield loss was exponential. Defoliation thresholds to prevent economic yield loss for Virginia and runner types were estimated at 40 and 50%, respectively. Although numerous factors remain important in mitigating overall yield losses, the integration of these findings should aid recommendations about digging under varying defoliation intensities and peanut maturities to assist in minimizing yield losses.

Brassica carinataor Ethiopian mustard, a non‐edible oilseed brassica, is a low carbon, purpose‐grown, and none‐to‐low indirect land‐use change bioenergy feedstock for the production of drop‐in sustainable aviation fuel, biodiesel, renewable diesel, and a suite of value‐added coproducts. Carinata oil converted to drop‐in fuel using an American Society for Testing and Materials approved Catalytic Hydrothermolysis process has been successfully tested in commercial and military aviation. Carinata meal, the residue after oil extraction, is a high‐protein feed supplement for livestock, poultry, and swine, and can also yield specialty products. The Southeast Partnership for Advanced Renewables from Carinata (SPARC) is a public–private partnership formed with a twofold mission: (1) Removing physical, environmental, social, and economic constraints that prevent regional intensification of carinata production as a low‐carbon feedstock for renewable fuel and coproducts and (2) demonstrating enhanced value across the entire value chain by mitigating risk to farmers and other stakeholders. The partnership's goal is to energize the US bioeconomy through sustainable agriculture and thus contribute to energy security and economic diversification. SPARC relies on a combination of cutting‐edge multidisciplinary research and active industry engagement to facilitate adoption of the crop. This involves informing stakeholders along the entire supply chain, from producers to end‐users, policymakers, influencers, and the public, about the opportunities and best practices related to carinata. This article provides context and background concerning carinata commercialization as a winter cash crop in the Southeast US for renewable fuels and bioproducts. The advances made to date in the areas of feedstock development, fuel and coproduct development, meal valorization, supply chain logistics, and stakeholder engagement are outlined.

Cotton leafroll dwarf disease (CLRDD) caused by the Cotton leafroll dwarf virus (CLRDV), is an emerging disease of cotton (Gossypium hirsutum L.) in the United States. It was previously reported in...

Epidemics of sugarcane orange rust (caused by Puccinia kuehnii) in Florida are largely influenced by prevailing weather conditions. In this study, we attempted to model the relationship between weather conditions and rust epidemics as a first step toward development of a decision aid for disease management. For this purpose, rust severity data were collected from 2014 through 2016 at the Everglades Research and Education Center, Belle Glade, Florida, by recording percentage of rust-affected area of the top visible dewlap leaf every 2 weeks from three orange rust susceptible cultivars. Hourly weather data for 10- to 40-day periods prior to each orange rust assessment were evaluated as potential predictors of rust severity under field conditions. Correlation and stepwise regression analyses resulted in the identification of nighttime (8 PM to 8 AM) accumulation of hours with average temperature 20 to 22°C as a key predictor explaining orange rust severity. The five best regression models for a 30-day period prior to disease assessment explained 65.3 to 76.2% of variation of orange rust severity. Prediction accuracy of these models was tested using a case control approach with disease observations collected in 2017 and 2018. Based on receiver operator characteristic curve analysis of these two seasons of test data, a single-variable model with the nighttime temperature predictor mentioned above gave the highest prediction accuracy of disease severity. These models have potential for use in quantitative risk assessment of sugarcane rust epidemics.