Impact of foliar fungicide timing and fungicide class on corn yield response in the United States and Ontario, Canada

Kiersten A. Wise, University of Kentucky; Damon L. Smith, University of Wisconsin-Madison; Anna Freije, Purdue University; Daren S. Mueller, Iowa State University; Yuba R. Kandel, Iowa State University; Tom W. Allen, Mississippi State University; Carl A. Bradley, University of Kentucky; Emmanuel Byamukama, South Dakota State University; Martin I. Chilvers, Michigan State University; Travis Faske, University of Arkansas; Andrew Friskop, North Dakota State University; Clayton Hollier, LSU AgCenter; Tamra A. Jackson-Ziems, University of Nebraska-Lincoln; Heather Kelly, University of Tennessee; Bob Kemerait, University of Georgia; Paul "Trey" Price, III, LSU AgCenter; Alison Robertson, Iowa State University; and Albert U. Tenuta, Ontario Ministry of Agriculture, Food, and Rural Affairs

Introduction

Foliar fungicides can be applied to corn at multiple growth stages, ranging from early vegetative growth stages to mid-reproductive stages. The ease of application and possible positive physiological responses have led to interest in early vegetative stage applications. However, most university research has indicated that fungicide applications applied during the tasseling (VT) to silking (R1) growth stages result in the greatest yield response, and consequently the largest economic gain (Paul et al., 2011; Wise and Mueller, 2011). Fungicide class may be an additional factor impacting yield response. Fungicide products that combine two or more fungicide classes have expanded in recent years. Our research aimed to compare the yield response of fungicide application timing using products with one or two fungicide classes and calculate the likelihood of breaking even or getting a positive return on investment (ROI) from a fungicide application.

The Research

Researchers from 13 states and Ontario, Canada (Table 1) conducted trials using a uniform protocol from 2014 - 2015. Foliar fungicide application timings included fungicides applied at the V6, VT, or V6 + VT (two-pass program) corn growth stages. Products were evaluated using label recommended rates on a disease-susceptible hybrid at each location. Active ingredients and rates are listed in Table 2. Each location included at least three of the fungicide treatments included on the uniform protocol and a non-fungicide treated control. Foliar disease severity was assessed as percent severity of each disease present on the ear leaf at the late dough-early dent growth stages (R4-R5). Analysis was conducted on the 436 data points from locations with disease severity data. Grain yield was collected, calculated, and standardized to 15.5 percent moisture prior to analysis. Yield response due to fungicide treatment was calculated by subtracting the yield of each fungicide treated plot from the yield of the non-fungicide treated plot. Data were then subjected to a meta-analysis to investigate the influence of fungicide class, foliar disease level, and application timing on corn yield response.

Table 1. Locations of uniform foliar fungicide trials in the United States and Ontario, Canada.

Table 2. Fungicides used in uniform foliar fungicide trials in the United States and Ontario, Canada.

¹Treatment active ingredients: Priaxor = pyraclostrobin + fluxapyroxad; Quadris = azoxystrobin; Stratego YLD = prothioconazole + trifloxystrobin; Aproach = picoxystrobin; Fortix = fluoxastrobin + flutriafol; Headline AMP = metconazole + pyraclostrobin; Quilt Xcel = azoxystrobin + propiconazole; Aproach Prima = picoxystrobin + cyproconazole; Tilt = propiconazole

²QoI = quinone outside inhibiting fungicide class; SDHI = succinate dehydrogenase inhibiting fungicide class; DMI = demethylation inhibiting fungicide class

³V6 = six leaf collar growth stage; VT = tasseling growth stage

Application timing impact on yield

Application timing significantly affected yield response with over 68 percent of the 436 comparisons resulting in a positive yield response. Furthermore, VT and V6 + VT applications of DMI + QoI products resulted in nearly three times greater yield response than the V6 timing alone. This is similar to previous university research, where VT applications were more likely to result in significant yield increases compared to V6 applications (Adee and Duncan, 2017; Byrne et al., 2015; Faske, 2017; Harbour and Jackson-Ziems, 2016). This result has been attributed to the fact that foliar fungicides applied at VT are more likely to protect against yield-limiting foliar diseases that typically initiate and increase during the reproductive stages in corn in the U.S. and Canada. In the U.S. and Canada, foliar diseases are rarely present at damaging levels at the V6 corn growth stage. Fungicide applications that occur at the VT corn growth stage protect the ear leaf and leaves above the ear leaf from foliar disease, and consequently are more likely to result in a greater yield response.

Fungicide class impact on yield

Fungicide class also affected yield response, with fungicides in the DMI + QoI class resulting in a greater yield response than solo QoI fungicides (Table 3). Treatments of products with a single DMI or SDHI + QoI fungicide classes did not result in substantial yield responses, and therefore data are not shown. The yield response for trials with low disease severity (less than 5% foliar disease) and high disease severity (greater than 5% foliar disease) was similar.

Table 3. Effect of fungicide timing and fungicide class on yield response of hybrid corn.

¹Mean yield response is the yield difference between the fungicide-treated and non-treated control. Percent yield increase is calculated based on meta-analysis values of the mean yield response.

Economic Analysis

Information regarding the cost of each fungicide program was solicited from retailers and industry representatives in states where trials were conducted. Fungicide product prices, application costs, and corn prices were used to calculate probability of a break-even return on investment (ROI) for each fungicide class and application timing. Across the U.S. and Ontario, Canada, ground application fees ranged from $3.00 to $8.50 per acre, while aerial application fees ranged from $6.50 to $12.00 per acre. Median fungicide product costs + application costs by application timing are presented in Table 4. Economic analysis focused on calculating ROI for QoI and DMI + QoI fungicides only.

For all application timings and fungicide classes, the probability of breaking-even on a fungicide investment increased when corn prices increased (Figures 1-4). Fungicide class and application timing also influenced ROI. Applications of both QoI and DMI + QoI fungicide classes at VT resulted in a higher likelihood of ROI than applications of any fungicide at V6. No fungicide class applied at V6 exceeded a 30 percent probability of breaking even at current corn prices. DMI + QoI fungicides applied at VT resulted in a higher probability of breaking even (exceeding 50%) at 2019 corn pricing, whereas QoI fungicides at VT only reach a 50 percent likelihood of breaking even if corn prices were over $5.00/bu.

Table 4. Application costs used for economic analysis.

Conclusion

A single fungicide application of a DMI + QoI fungicide at VT resulted in a similar yield response as a two-pass (V6 + VT) fungicide program when compared to the non-treated control. As a result, the greatest likelihood of a positive return on investment across the U.S. and Canadian corn production belt is to apply a DMI + QoI fungicide once at the VT corn growth stage.

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References

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This research was based on the following manuscript

Wise, K.A., Smith, D., Freije, A., Mueller, D.S., Kandel, Y., Allen, T.W., Bradley, C.A., Byamukama, E., Chilvers, M., Faske, T., Friskop, A., Hollier, C., Jackson-Ziems, T.A., Kelly, H., Kemerait, R., Price III, P., Robertson, A., and Tenuta, A. 2019. Meta-analysis of yield response of foliar fungicide-treated hybrid corn in the United States and Ontario, Canada. PLoS ONE 14(6): e0217510. Article / Google Scholar

Acknowledgments

Authors

Kiersten A. Wise, University of Kentucky; Damon L. Smith, University of Wisconsin-Madison; Anna Freije, Purdue University; Daren S. Mueller, Iowa State University; Yuba R. Kandel, Iowa State University; Tom W. Allen, Mississippi State University; Carl A. Bradley, University of Kentucky; Emmanuel Byamukama, South Dakota State University; Martin I. Chilvers, Michigan State University; Travis Faske, University of Arkansas; Andrew Friskop, North Dakota State University; Clayton Hollier, LSU AgCenter; Tamra A. Jackson-Ziems, University of Nebraska-Lincoln; Heather Kelly, University of Tennessee; Bob Kemerait, University of Georgia; Paul Price, III, LSU AgCenter; Alison Robertson, Iowa State University; and Albert U. Tenuta, Ontario Ministry of Agriculture, Food, and Rural Affairs

Reviewers

Alyssa Koehler, University of Delaware; and Edward Sikora, Auburn University.

The authors wish to acknowledge the Grain Farmers of Ontario for support, which obtained funding through the Ontario Farm Innovation Program (OFIP), a component of Growing Forward.

Assistance with field trials came from N. Anderson and J. Ravellette in Indiana; A. M. Byrne, W. Widdicombe, and L. Williams in Michigan; S. Chapman and B. Mueller in Wisconsin; K. Ames, B. Mansfield, J. Pike, T. Seifert, and G. Steckel in Illinois; Dr. James Harbour, Bradley Tharnish, and the staff of the UNL-South Central Agricultural Laboratory in Nebraska; many technicians and student workers in Louisiana; and M. Emerson in Lonoke, Arkansas.