Date of Award
Doctor of Philosophy (PhD)
Plant and Environmental Science
Peanut is an important food crop grown in the southeastern region of the United States. Diseases are the most yield-limiting component in peanut production with one of the most important being late leaf spot (LLS), caused by Nothopassalora personata (Np). The disease initially appears in the lower canopy as dark brown to black lesions and conidiophores bearing conidia are produced on the abaxial side of the lesion. Np is passively dispersed primarily by wind and rain events. Spore traps were used to detect and quantify conidia captured up to 70 m from an inoculum source and to further assess the relationship between weather patterns and spread of propagules.
Fungicide resistance is a major concern with Np as loss of efficacy to active ingredients in the quinone outside inhibitor, demethylation inhibitor, and succinate-dehydrogenase inhibitor (SDHI) classes has been reported. Isolates from grower fields and university research plots were evaluated in detached leaf assays for sensitivity across fifteen fungicide treatments including a non-treated control. The majority of isolates exhibited reduced efficacy to several active ingredients and probable cross-resistance to SDHI fungicides, pydiflumetofen and benzovindiflupyr plus azoxystrobin and pydiflumetofen and penthiopyrad. Based on these results, an integrated management approach is strongly suggested for preventing and suppressing LLS epidemics.
Np overwinters on residues and increasing the rate of decomposition could potentially reduce the amount of inoculum for the subsequent growing season. The application of nitrogen treatments, alone or in combination with adjuvants, to residues increases decomposition. In a two-year study, nitrogen treatments, urea ammonium nitrate (UAN), UAN plus microbial stubble digestor, and UAN plus Bond Max adjuvant were evaluated at fall and spring application timings. There were not consistent differences between nitrogen treatments and the nontreated control.
The first step for any management program should be an accurate diagnosis to prevent loss of resources trying to treat the wrong problem. Image analysis and logistic regression were used to develop seven accurate diagnostic models using a dataset of ≥ 4,000 images to classify foliar symptoms of paraquat injury, healthy, hopperburn, tomato spotted wilt, LLS, provost injury, and surfactant injury.
Becton, Hope, "Epidemiological Approaches for Practical Solutions to Pertinent Peanut Problems" (2023). All Dissertations. 3353.
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