Corn foliar fungicide trials were done at six locations in Iowa in 2022: ISU Northwest Research and Demonstration Farm (NWRF), Sutherland; Northeast Research and Demonstration Farm (NERF), Nashua; Northern Research and Demonstration Farm (NRF), Kanawha; Southwest Research and Demonstration Farm (SWRF), Lewis; Southeast Research and Demonstration Farm (SERF), Crawfordsville; and the Ag Engineering and Agronomy Farm (AEA) near Boone.
The goal of these trials was to help farmers determine best practices for foliar fungicides in corn production. Our objectives are to 1) assess the effect of fungicide application timing on foliar disease, 2) evaluate the yield response of hybrid corn to foliar fungicides and 3) discern differences between fungicide products.
Products used and application timings tested
Seven products, applied at growth stage V12, eight products applied at R1, and two products applied at planting, V6 and/or R1 were evaluated (Table 1). No surfactant was included in applications made at V12. A randomized complete block design with six replications was used at each site. Each plot was four rows wide (30-in. row spacing) and ranged from 30 to 73 ft long depending on the farm. All plots were bordered by two rows on each side. Disease severity on the ear leaf on five plants in the middle two rows of each plot was assessed in the check plots at NERF and SERF at silking (R1), and in all plots at R5 at all locations (last week of August). All four rows of each plot were harvested using a plot combine. All data were subjected to analysis of variance and means were compared at the 0.1 significance level using Fisher’s protected least significant difference (LSD) test.
Effect of product and timing on foliar disease
Tar spot and gray leaf spot (GLS) were observed at NERF and SERF at R1. At NERF, one tar spot stroma on one of 60 ear leaves assessed was observed. At SERF, one tar spot stroma on each of three of the 60 leaves assessed was observed. No GLS was observed on the ear leaves at either location. No disease notes were taken at R1 at the other 4 locations.
Insignificant disease was observed at AEA, NRF, NWRF and SWRF at R5. At NERF and SERF, GLS, tar spot, and northern corn leaf blight (<NCLB) was observed at NERF and SERF only (Table 1). NCLB severity at both locations was <1% in the non-sprayed check.
At NERF, tar spot and GLS severity averaged 1.3% and 1.2%, respectively in the non-sprayed check. In general, all foliar applications of fungicides at V12 or R1 reduced both diseases (P<0.1). Products applied at planting or at V6 had little effect on tar spot and GLS.
More severe tar spot and GLS was observed at R5 at SERF compared to NERF. Tar spot and GLS severity in the non-sprayed check averaged 23.2% and 3.2%, respectively. All products reduced disease severity, but differences were observed among time of application and products. In general, applications made at R1 reduced tar spot severity more than applications made at V1. In contrast, applications made at V12 reduced GLS better than applications made at R1.
Effect of product and timing on yield
Yields of the non-sprayed check ranged from 178.6 bu/ac at SWRF to 250.5 bu/ac at NRF (Table 2). We detected no effect of a fungicide application on yield at any location (P>0.1).
Data from NERF and SERF are consistent with data from the Midwest that a single well-timed application of a fungicide can effectively reduce tar spot (and GLS) severity and protect corn yield. Moreover, data from NWRF, NRF, SWRF and AEA trials are consistent with previous work that indicates corn yields are rarely greater following a fungicide application in the absence of disease.
For a list of fungicides effective against tar spot, GLS, NCLB, and other diseases on corn, the publication “Fungicide efficacy for corn diseases” is available from the Crop Protection Network. This publication is updated annually by corn pathologists across the U.S. and Ontario, Canada.
Thank you to the farm managers and staff at each location who managed the trial and applied the fungicides. Thanks to Jyotsna Acharya for analysis of the data.