Efficacy of fungicides for management of blueberry rust, Appling County, Georgia, 2016

摘要

Fungicides were evaluated for control of blueberry rust in a replicated trial within a single row of mature (10-yr-old) highbush blueberries (cv. Rebel) in a commercial field near Baxley, GA. Of particular interest were the relative levels of controlamong the four demethylation inhibitor (DMI) fungicides and one premix containing a DMI fungicide. Treatments were assigned using a randomized complete block design consisting of with five single-bush replicates per treatment; adjacent buffer rows and asingle bush on either side of treatments were left unsprayed to prevent spray drift. It should be noted that a significant proportion of blueberry bushes at this site were also affected by blueberry leaf scorch but care was taken to avoid inclusion of severely affected bushes in experimental blocks. Treatments were applied until run-off with approximately 0.5 gal applied per five bushes (equivalent to 100 gal water/A) using a CO2 backpack sprayer fitted with a cone nozzle at 40 psi. Treatments includedan untreated control, Abound (azoxystrobin), Pristine (pyraclostrobin + boscalid), Indar (fenbuconazole), Orbit (propiconazole), Proline (prothioconazole), Quash (metconazole), Aprovia (benzovindiflupyr), Quilt Xcel (azoxystrobin + propiconazole), and asplit schedule application of Abound until harvest followed by Bravo (chlorothalonil) until trial termination. Application dates were 4 Apr, 18 Apr, 2 May (last spray prior to harvest), 16 May, 30 May, and 13 Jun. On each of four assessment dates (30 Mar, 21 Apr, 2 Jun, 15 Jun), 50 leaves per bush were destructively sampled and assessed for blueberry rust with severity calculated as % affected leaf area and incidence as the proportion of infected leaves. The area under the disease progress curve (AUDPC)was calculated using the formula AUDPC = 2~]f=i[{(Xi + ^(i+i))/2) x (t(i+1) - t;)], where Yj= disease severity or incidence at tt and t(i+1) - tt = the number or days between disease assessments. PROC GLIMMIX (Generalized Linear Mixed Model) within thestatistical software SAS 9.4 was used to analyze the data.