MANAGEMENT AND CHARACTERIZATION OF CERCOSPORA SPP. ASSOCIATED WITH CORN By Nik Nurulhidayah Binti Nik Zainal Alam A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Plant Pathology – Master of Science 2023 ABSTRACT Cercospora spp. cause foliar disease and form leaf spots on the leaves of a wide variety plants. Symptoms on the leaves vary by host but the leaf spots often enlarge, coalesce, and cause early senescence. Gray leaf spot (GLS), caused by Cercospora spp. is a significant disease of corn in the United States. Currently, there are two known species of Cercospora that cause GLS of corn, C. zeae-maydis (previously Group I C. zeae-maydis) and C. zeina (previously Group II C. zeae-maydis). GLS of corn is the most destructive disease compared to other corn diseases in the United States and Ontario, Canada causing the greatest yield loss. Aside from cultivar resistance, fungicides are often used for disease management. Therefore, this thesis focuses on establishing fungicide sensitivity of Cercospora spp. of corn. In Chapter 1, I provide background and literature review of Cercospora spp. that are infecting corn and cultural practices used to mitigate losses to GLS. In my second chapter I validate fungicide movement in corn plants via several fungicide applications that contain flutriafol as active ingredient during planting and assess disease suppression by the fungicide. This is to show that this fungicide is effective in protecting the plants from planting until harvesting. Next, in Chapter 3 I conducted a multistate survey across 17 states within the United States and Ontario, Canada to identify Cercospora spp. associated with and pathogenic on corn, as well as conducted fungicide sensitivity testing on these isolates. This study established the fungicide sensitivity of flutriafol on corn plants. Finally, in Chapter 4 I present conclusions and impacts of the studies. Overall, the studies in this thesis provide information about a new fungicide that can be used to control GLS and Cercospora spp. that were infecting corn. Copyright by NIK NURULHIDAYAH BINTI NIK ZAINAL ALAM 2023 This thesis is dedicated to my beloved family. To my parents, who supported and encouraged me to pursue my Master’s study. To my husband and my newborn baby, for their unconditional love and support throughout this journey. Thank you for always believing in me. iv ACKNOWLEDGEMENTS First and foremost, I would like to express my deepest appreciation to my advisor, Dr. Martin I. Chilvers. Thank you for believing in me and for your continuous guidance throughout this process. Your unwavering support, patience, and wisdom have been instrumental in shaping the direction of my research and helping me navigate the challenges I encountered. I would like to thank my esteemed committee members: Dr. Timothy Miles and Dr. Jaime Willbur for their expertise, valuable insights, and advice during my Master’s study. Thank you Tim for introducing me to Marty, without you, I probably would not pursue my Master’s degree. I would like to acknowledge an awesome postdoctoral researcher, Dr. Safa Alzohairy for mentoring me during my undergraduate studies and preparing me for graduate school. She is not only a wonderful researcher but also a sister to me. Thank you for being a constant source of motivation and inspiration. I would also like to thank to all Chilvers lab members, past and present for their valuable advice and feedback during my study. A special thanks to Dr. Austin McCoy and Janette Jacobs for their guidance especially during the early Covid-19 phase. Thank you for your patience in guiding me during this difficult time. Finally, to my family, especially my husband who accompanies me in the United States while being far away from our home country, Malaysia. This achievement would not have been possible without your love, understanding, and sacrifices in welcoming our first newborn. I am forever grateful for your presence in my life. v TABLE OF CONTENTS CHAPTER 1: LITERATURE REVIEW ........................................................................................ 1 CHAPTER 2: FLUTRIAFOL MOVEMENT IN CORN VIA IN-FURROW FUNGICIDE APPLICATION .............................................................................................................................. 9 CHAPTER 3: IDENTIFICATION OF CERCOSPORA SPP. AND BASELINE FUNGICIDE SENSITIVITY TESTING OF FLUTRIAFOL ON CORN .......................................................... 32 CHAPTER 4: CONCLUSION AND IMPACTS ......................................................................... 68 REFERENCES ............................................................................................................................. 72 APPENDIX ................................................................................................................................... 81 vi CHAPTER 1: LITERATURE REVIEW 1 Corn (Zea mays L.) is widely grown in the United States for livestock feed and ethanol production. The United States is one of the primary corn producing countries with 32% (387 million metric tons) of world corn production (1.22 billion metric tons) in 2022 (United States Department of Agriculture, 2023). About 80% of the United States corn production is from the U.S. Corn Belt; Illinois, Indiana, Iowa, Kansas, Minnesota, Missouri, Nebraska, Ohio, Wisconsin, and South Dakota (United States Department of Agriculture, 2023). Over the last 30 years, corn yields have increased since 1993 to 2021 averaging 6,700 kg/ha to 11,600 kg/ha (NASS 2023). However, the average estimated yield loss due to disease from 2016 to 2019 was 35.9 million metric tons equivalent to $20.1 billion (Mueller et al. 2020). Corn production is severely impacted by plant diseases in the United States with foliar diseases such as gray leaf spot (GLS) (Cercospora zeae-maydis), northern corn leaf blight (Exserohilum turcicum), southern rust (Puccinia polysora) and tar spot (Phyllachora maydis) being the primary diseases that caused large yield loss in the northern United States and Ontario, Canada from 2012 to 2019 (Mueller et al. 2016; Mueller et al. 2020). GLS can cause more than 50% yield loss when plants are infected early in the season (Lipps 1998; Wegary et al. 2004). Although GLS was ranked as one of the top 10 diseases from 2012 to 2015, GLS was not the main destructive disease of corn that caused yield loss (Mueller et al. 2016). However, in recent years, GLS has been documented as one of the top two yield-limiting diseases, causing a mean of 6.7 metric tons yield loss annually in the United States and Ontario, Canada from 2016 to 2019 (Mueller et al. 2020). Apart from the United States, GLS has also been reported in Brazil, Canada, China, and South Africa (Brunelli et al. 2008; Dhami et al. 2015; Dunkle and Levy 2000; Ward et al. 1999; Zhu et al. 2007). 2 Cercospora spp. infecting corn Cercospora spp. are commonly known to cause foliar disease on diverse hosts including capsicum (Capsicum annuum), corn (Zea mays), soybean (Glycine max), sugar beet (Beta vulgaris), and many more (Groenewald et al. 2013). There are more than 3,000 described Cercospora species (Crous and Braun 2003, Pollack 1987). One of them is Cercospora zeae- maydis Tehon & E. Y. Daniels which was first discovered in Illinois in 1924 causing GLS on corn (Tehon and Daniels 1925). According to research conducted by Crous et al. (2006) in South Africa, there are two distinct species of Cercospora spp. that caused GLS on corn were identified namely C. zeae-maydis (previously Group I C. zeae-maydis) and C. zeina Crous & U. Braun (previously Group II C. zeae-maydis). These two Cercospora spp. are sister taxa that are genetically different and are morphologically similar, hence sequencing is needed to distinguish them (Crous et al. 2006; Dunkle and Levy 2000; Goodwin et al. 2001; Wang et al. 1998). C. zeae-maydis is predominantly found in the United States while C. zeina is prevalent in Southern Africa and has also been detected in the United States in Indiana, North Carolina, Virginia, Ohio, New York, and Pennsylvania (Crous et al. 2006; Dunkle and Levy 2000; Hsieh Lin-si 2011; Meisel et al. 2008; Okori et al. 2003; Swart et al. 2017; Wang et al. 1998). Morphology of Cercospora spp. causing GLS Cercospora spp. of GLS can be cultured on potato dextrose agar, green-corn-leaf decoction agar, senescent-corn-leaf decoction agar or V8 juice agar, however, colony growth was more consistent on V8 juice agar (Beckman and Payne 1983). Colony characteristics are typically slow-growing colonies, compact with gray to black color mycelium sometimes accompanied by cottony whitish to grayish mycelium on the top (Crous et al. 2006). The distinguishing morphology is the faster growth rate of C. zeae-maydis (8-12 mm per week) 3 compared to C. zeina (4-5 mm per week) and production of cercosporin by some C. zeae-maydis isolates, a toxin produced by most Cercospora spp. which is light pink-red pigmented color in culture (Brunelli et al. 2008; Crous et al. 2006; Dhami et al. 2015; Dunkle and Levy 2000; Goodwin et al. 2001). Although C. zeae-maydis can be distinguished from C. zeina in culture, it is challenging to differentiate them because not all C. zeae-maydis isolates produced cercosporin and they produce similar symptoms on corn plants (Brunelli et al. 2008; Dhami et al. 2015). The fungus produces conidiophores, originating from black stromata on the abaxial of the leaves usually arranged in a straight line following the leaf vein that can be viewed under dissecting microscope (Figure 1.1). Conidiophores are straight, unbranched, olivaceous, and ranged from 5 to 7.5 µm by 50 to 125 µm (Crous et al. 2006; Dunkle and Levy 2000). Conidia of C. zeae-maydis and C. zeina are hyaline, slightly curved, obclavate, and ranged from 6 to 10 µm wide and 56 to 86 µm long (Crous et al. 2006; Dunkle and Levy 2000; Wang et al. 1998). Although the conidia appear to be similar, C. zeae-maydis have longer conidiophores up until 180 µm while C. zeina have shorter conidiophores up until 100 µm (Crous et al. 2006). Figure 1.1. Conidiophores of Cercospora spp. with silvery and shiny conidia originating from black stromata on the abaxial of corn leaf after incubation for 48 hours at ambient room temperature (21°C ± 2°C) on water agar, metalaxyl and streptomycin (WMS) medium (20 g agar, 15 mg/L metalaxyl, and 300 mg/L streptomycin sulfate in 1 L of de-ionized water). 4 Disease cycle and symptoms of gray leaf spot on corn GLS increases in severity due to no or reduced tillage activity which contributes to accumulation of residue on the soil where C. zeae-maydis survives (Payne and Waldron 1983). In the spring, the pathogen produces conidia that can be dispersed to a young corn at V5 corn growth stage through wind and rain splash (Lipps 1998; Payne and Waldron 1983; Ward et al. 1999). The spores initially infect the lower leaves of corn. At high relative humidity, typically 95 to 100% and warm temperature (25 to 30°C), GLS lesions expand and sporulate rapidly (Paul and Munkvold 2005; Rupe et al. 1982). Symptoms typically appear two to four weeks after anthesis (from pollen shed to silk emergence) due to the long latent period of this pathogen, generally 9 to 21 days after infection (Beckman and Payne 1982; Ringer and Grybauskat 1995; Ward et al. 1999). Beckman and Payne (1982) suggested that growth stage is not significant for infection to occur, however high relative humidity plays a big role for disease appearance in the late season of the corn field due to the canopy closed when plant is at maturity. Symptoms of gray leaf spot on leaves initially appear as pinpoint lesions that are not easily distinguished from other foliar pathogens (Latterell and Rossi 1983). These lesions appear gray to tan in color, about 1-3 mm long that are rectangular to irregular in shape and surrounded by yellow haloes that are visible particularly when backlit (Latterell and Rossi 1983; Stromberg 2009; Ward et al. 1999). The small lesions then elongate to a distinct rectangular shape (5 to 70 mm long by 2 to 4 mm wide) of lesions that run parallel with the leaf veins (Figure 1.2) (Ward et al. 1999). Although it is uncommon, apart from the leaves, lesions can appear on the leaf sheath and corn husks (Crop Protection Network 2022; Latterell and Rossi 1983; Stromberg 2009). These mature lesions can further expand and coalesce resulting in extensive blighting and necrosis of the leaf tissue (Ward 1996; Ward et al. 1999). Under favorable conditions, the 5 secondary infection cycle begins with spore dispersal to neighboring corn plants (Ward et al. 1999). GLS can cause more than 50% yield loss when plants are infected early in the season (Lipps 1998). Figure 1.2. Symptoms of gray leaf spot on adaxial of the corn leaf showing gray to tan in color with irregular shape of immature lesions and mature lesions that have distinct rectangular shape that run parallel with the leaf veins submitted from Kansas, United States. Fungicides for Cercospora spp. management on corn To prevent yield losses caused by disease, foliar fungicides are commonly used in disease management of corn. Two main classes of fungicides, demethylation inhibitors (DMI; FRAC (Fungicide Resistance Action Committee) Code 3) and quinone outside inhibitors (QoI; FRAC Code 11) have been utilized to control GLS (Bradley and Ames 2010; Dhami et al. 2015; Ward et al. 1997). Recently, succinate dehydrogenase inhibitors (SDHI; FRAC Code 7) have also been tested for GLS control (Neves and Bradley 2019). According to FRAC (2018), DMI fungicides or sterol biosynthesis inhibitors (SBIs) Group 1 fungicides inhibit C14 demethylation within fungal sterol biosynthesis by binding to the C14 demethylase enzyme (erg11/cyp51), DMIs inhibit demethylation, leading to an accumulation of sterol precursors and a decrease in ergosterol production in fungi (Ziogas & Malandrakis, 2015). Ergosterol is important in fungi to manage membrane fluidity and permeability (Kwok and Loeffler 1993). According to FRAC 6 (2018), DMIs pose a medium risk in developing resistance while QoIs and SDHIs pose a high and medium-high risk respectively in developing resistance. The repeated use of high-risk fungicides can select for resistant individuals in the population and reduce the effectiveness of the fungicide within a few years of introduction (Brent and Hollomon, 2007). Using a medium risk fungicide, such as DMIs, provides less risk of resistance being selected in the community. Flutriafol a newer fungicide with unique characteristics Flutriafol is a DMI fungicide that belongs to FRAC Code 3. Flutriafol was initially used in 1981 in the United Kingdom, and in 2010, it received registration from the Environmental Protection Agency (EPA) for use on soybeans and apples in the United States. (Lewis et al., 2016). Subsequently, in 2012, flutriafol was approved to be used on corn (Minnesota Department of Agriculture 2012). Flutriafol is a systemic fungicide that is notable for its unique capability to be absorbed by plant tissues via the xylem and can translocate upwards to foliar tissues. As a result, it can be taken in by the roots and transported throughout the entire life cycle of a corn plant (Briggs et al. 1982). This characteristic makes it an invaluable resource for fungicides during planting. However, this fungicide possesses a long half-life and can potentially persist in the plant and the environment typically 1,587 days (about 4 and a half years) in a lab at 20°C and 1,177 days (about 3 years) in the field (Lewis et al. 2016). To ensure effective foliar disease management, research suggests applying fungicides during the tasseling (VT) or silking (R1) stages of corn growth (Wise and Mueller 2011; Wise 2019). This approach has been shown to result in lower disease severity and higher yields compared to vegetative stage applications, regardless of the fungicide class used, especially in high disease pressure fields (Adee and Duncan 2017; Faske and Emerson 2021; Telenko et al. 2020; Wise et al. 2019). However, this often requires expensive aerial fungicide applications 7 using planes or helicopters, which can cost up to $102.49/ha, compared to $88.77/ha for ground- based application (Wise et al. 2019). Therefore, it is crucial to find alternative methods to reduce costs, fuel, water, and labor resources. The active ingredient flutriafol is an effective fungicide to control GLS, northern corn leaf blight, and southern rust (Puccinia polysora) on corn using foliar applications ranging from 0.28 to 0.42 kg per hectare (Wise and Bradley 2017). Recent studies have shown that in-furrow fungicide applications using QoI fungicides (FRAC 11) such as fluxapyroxad and pyraclostrobin and SDHI fungicides (FRAC 7) fluopyram are effective in protecting corn and soybean plants from disease, and can reduce the need for aerial fungicide applications (Kandel et al. 2016; Potratz et al. 2020). Fungicide sensitivity monitoring A previous study by Bradley and Pederson (2011) reported baseline EC50 (concentration required to reduce growth by 50%) values of C. zeae-maydis for QoI fungicides namely azoxystrobin, pyraclostrobin, and trifloxystrobin with a mean of 0.018, 0.001, and 0.0023 µg/ml, respectively. For pydiflumetofen, an SDHI fungicide, a mean of 0.004 µg/ml for baseline EC50 values of C. zeae-maydis were reported (Neves and Bradley 2019). Although DMI fungicides are a common fungicide used to control GLS, no baseline studies have been conducted previously for corn-associated Cercospora spp. (Bradley and Ames 2010; Dhami et al. 2015; Ward et al. 1997). However, baseline studies of flutriafol on other Cercospora spp. infecting other crops have been established for C. beticola on sugarbeet and C. sojina and C. kikuchii on soybean (Karaoglanidis et al. 2000; Price 2013; Zhang et al. 2021). 8 CHAPTER 2: FLUTRIAFOL MOVEMENT IN CORN VIA IN-FURROW FUNGICIDE APPLICATION Authors who contributed to this study were: Nikzainalalam, N.1, Copeland, J.D.2, Byrne, A.M.1,2, and Chilvers, M.I.1 1 Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824 2 FMC Corporation, Dayton, OH 45458 9 Abstract Flutriafol, a demethylation inhibitor (DMI) fungicide, belongs to the Fungicide Resistance Action Committee (FRAC) Group 3. Field trials were conducted at Michigan State University Plant Pathology farm in Lansing, Michigan from 2019 to 2021 using four-row plots with a randomized complete block design. The study was conducted to investigate the systemic movement of flutriafol, the active ingredient in XywayTM Liquid Fertilizer Ready (20.9% a.i. flutriafol) and LucentoTM fungicide (15.55% a.i. bixafen and 26.47% a.i. flutriafol). All Xyway fungicide treatments were applied at planting at a rate of 1.06 kg per hectare. The Xyway in- furrow treatment was applied in three consecutive years; 2019, 2020, and 2021. The Xyway 2x2 treatment was also applied in 2020 and 2021 to compare different application methods. Additional fungicide treatments were applied including 0.35 kg per hectare Lucento fungicide at R1 (silking stage) in 2020 and Xyway 0x0 treatment at planting in 2021. A single non-treated plot was sampled to check for residual flutriafol for each year. Two plants per plot were randomly selected from each treatment each year for flutriafol using Gas Chromatography Mass Spectrometry. Flutriafol was found in every plant part tested including roots, stalks, and leaves for residual each year in all different fungicide treatments. Flutriafol concentration of Xyway in- furrow treatment was significantly higher from untreated check (P <.0001) for all years. Foliar disease of gray leaf spot (GLS) and northern corn leaf blight (NCLB) were also assessed in every fungicide treatment and area under disease progress curve (AUDPC) was calculated. The AUDPC of GLS in 2021 showed that all Xyway treatment including in-furrow, 2x2, and 0x0 were significantly lower from untreated control (P < 0.05) while NCLB was not significantly different. This study showed that in-furrow flutriafol fungicide treatments could potentially provide reduction in foliar disease severity of GLS throughout the growing season. 10 Introduction Foliar fungicide applications have been used to protect corn (Zea mays. L) grain yields since 1942 (Morton and Staub 2008), however, plant diseases continue to severely impact corn grain yields in the United States. Foliar diseases such as gray leaf spot (GLS) (Cercospora zeae- maydis Tehon & E. Y. Daniels) and northern corn leaf blight (NCLB) (Exserohilum turcicum (Pass) (Leonard and Suggs)) cause major yield losses annually in the United States and Ontario, Canada (Mueller et al. 2016; Mueller et al. 2020). In total, GLS caused losses of 41.3 million metric tons of yield from 2012 to 2019, ranking first as the most destructive disease from 2016 to 2018 while NCLB caused losses of 35.8 million metric tons of yield losses from 2012 to 2019, ranking first as the most destructive disease in 2014 and 2015 (Mueller et al. 2016; Mueller et al. 2020). Cercospora zeae-maydis is generally regarded as the causal agent of GLS on corn which was first found in Illinois in 1924 (Tehon and Daniels 1925). In recent research by Crous et al. (2006) in South Africa, it was found that there are two distinct species of Cercospora spp. that cause GLS on corn which are C. zeae-maydis (previously Group I C. zeae-maydis) and C. zeina (previously Group II C. zeae-maydis). These two Cercospora spp. are sister taxa that are genetically distinct (Crous et al. 2006; Dunkle and Levy 2000; Wang et al. 1998). Increased GLS severity is observed in no or reduced tillage fields that contributes to accumulation of C. zeae- maydis and more disease development residue on the soil (Negash 2013). GLS can cause more than 50% yield loss when plants are infected early in the season (Lipps 1998). At 100% relative humidity, GLS lesion expansion and sporulation are the highest between 25 to 30°C temperature (Paul and Munkvold 2005; Rupe et al. 1982). 11 Another disease of interest, NCLB also known as Turcicum leaf blight is caused by Exserohilum turcicum which was previously known as Helminthosporium turcicum. Apart from corn, E. turcicum can also infect sorghum (Sorghum bicolor), although genetic differentiation can be detected between E. turcicum of corn and sorghum (Bergquist & Masias 1974; Bhowmik and Prasada 1970; Bunker and Mathur 2006; Nieuwoudt et al. 2018; Ramathani et al. 2011). Depending on hybrid, disease development and crop yield losses associated with NCLB can reach up to 66% (Pataky et al. 1997; Perkins and Pedersen, 1987; De Rossi et al. 2022). To mitigate yield losses from disease, foliar fungicides are a widespread practice in disease management of corn. Flutriafol is a demethylation inhibitor (DMI) fungicide that belongs to Fungicide Resistance Action Committee (FRAC) Code 3. According to the FRAC (2018), DMI fungicides or sterol biosynthesis inhibitors (SBIs) Group 1 fungicides inhibit the C14 demethylation step within fungal sterol biosynthesis. When DMI fungicides bind to the C14 demethylase enzyme (erg11/cyp51), demethylation is inhibited, leading to an accumulation of sterol precursors and decreased ergosterol production by the fungi (Ziogas & Malandrakis, 2015). Sterols such as ergosterol are important in controlling membrane fluidity and permeability in fungi (Kwok and Loeffler 1993). DMI’s pose a medium risk in developing resistance compared to quinone outside inhibitor (QoI) and succinate dehydrogenase inhibitor (SDHI) fungicides that belong to FRAC 11 and FRAC 7, respectively, that pose a high risk in fungi developing resistance (FRAC, 2018). The repeated use of high-risk resistance fungicides can select for resistant individuals in the fungal population and reduce the effectiveness of the fungicide within a few years of introduction (Brent and Hollomon, 2007). Using a medium risk resistance fungicide, such as DMIs, provides longer period of use of the fungicide on the crop due to less risk of resistance being selected in the community. 12 Flutriafol was first introduced in 1981 in the United Kingdom (Lewis et al., 2016). In the United States of America, flutriafol was first registered in 2010 by the Environmental Protection Agency (EPA) on soybeans and apples, and later, in 2012, approved to be used on corn (Minnesota Department of Agriculture 2012). Flutriafol’s unique characteristics lie in its ability to target the xylem for absorption by plant tissues and translocation upwards to foliar tissues. Flutriafol’s systematicity (Figure 2.1) allows a fungicide applcation at planting to be taken up by roots and translocated into the entire corn plant throughout its productive life cycle (Briggs et al. 1982). This fungicide has a long half-life of 1,587 days (about 4 and a half years) in a lab at 20°C, and 1,177 days (about 3 years) in the field (Lewis et al. 2016), thus the fungicide does not break down quickly and can potentially persist longer in the plant and the environment. 13 Figure 2.1. Systemicity and persistence matrix, typical half-life in days taken from University of Hertfordshire Properties Database and translocation stream concentration factor (TSCF) as calculated using Briggs, Bromilow, and Evans equation Pesticide Science, 1982, Vol. 13 pages 495-504. The y-axis was plotted on a log scale to fit all data point. Flutriafol (XywayTM Liquid Fertilizer Ready (Xyway); FMC Corporation, Philadelphia, PA) received EPA registration in 2020 for application at planting for protection of corn against GLS, NCLB, southern leaf blight (Bipolaris maydis), common rust (Puccinia sorghi), head smut (Sphacelotheca reiliana), and common smut (Ustilago maydis) (Environmental Protection Agency 2020). Apart from fungicide application on corn, Xyway also was registered for cotton (Gossypium herbaceum), grain sorghum (Sorghum bicolor), sugar beet (Beta vulgaris), and wheat (Triticum) (Environmental Protection Agency 2020). Flutriafol is also the active 14 ingredient used in the LucentoTM fungicide (FMC Corporation, Dayton, OH) along with Bixafen (SDHI; FRAC 7) to be applied using a foliar application. According to Wise and Bradley (2012), the active ingredient flutriafol is an effective fungicide for control of GLS, NCLB, and southern rust (Puccinia polysora) on corn at a rate of 0.28 to 0.42 kg per hectare applied via foliar applications. Typically foliar fungicides are applied to corn during tasseling (VT) stage or silking (R1) stage for optimal foliar disease management (Wise and Mueller 2011; Wise 2019). Fungicides applied at VT stage or later showed lower disease severity and higher crop yield compared to vegetative stage application regardless of fungicide class if the field had high disease pressure (Adee and Duncan 2017; Faske and Emerson 2021; Telenko et al. 2020; Wise et al. 2019). However, applying fungicides at VT or R1 stage commonly requires the use of planes or helicopters for aerial fungicide applications due to the height of the corn at this growth stage. These application methods can cost an average of $102.49/ha for aerial application compared to $88.77/ha for a ground-based application (Wise et al. 2019). Thus, eliminating or reducing the need for a fungicide application during vegetative or reproductive stages would reduce cost, fuel, water, and labor resources. A recent study by Potratz et al. (2020) indicates that in-furrow fungicide application is effective in increasing corn and soybean yields using the QoI fungicides (FRAC11) fluxapyroxad and pyraclostrobin, along with other disease management strategies. In- furrow fungicide application also showed disease suppression on sudden death syndrome on soybean using fluopyram (SDHI; FRAC 7) (Kandel et al. 2016). Therefore, it is imperative to consider alternative methods to reduce costs, fuel, water, and labor resources while maintaining crop health. 15 In this study, we compared at planting and foliar fungicide applications at R1 with two flutriafol products; Xyway and Lucento. Several methods of fungicide application at planting are available including in-furrow where fungicide applies directly in the furrow with the seeds, fungicide applies in the soil 2 inches down and 2 inches away from the seed (2x2), and steady stream on the soil when the furrow has closed (0x0). The objectives of this study were to i) determine the movement of flutriafol in corn from an in-furrow application, ii) compare flutriafol uptake and movement of different fungicide application methods at planting including in-furrow, 2x2, and 0x0 applications, iii) compare plant uptake of foliar application of flutriafol to in-furrow application, iv) and assess disease suppression of GLS and NCLB across these application techniques. Trial Establishment Materials and Methods Field trials were planted in multiple growing seasons at the Michigan State University Plant Pathology Farm in Lansing, MI from 2019 to 2021 with approximate coordinates of 42.69 N, -84.49 W. In each year, trials were set up as a randomized complete block design, four row plots of 5.33 m long and 3.05 m wide, planted with 14,102 seeds/ha. The soil type in this field trial consisted of 18.5% Colwood loam and 81.5% Conover loam. The crop planted from the previous season was corn and the field was conventionally tilled. Three types of treatment using XywayTM (20.9% a.i.; FMC Corporation, Philadelphia, PA) were applied at planting using 1.11 L/ha (15.2 fl. oz. per acre) in-furrow, 2x2, or 0x0. The in-furrow treatment refers to the application of fungicide directly in the furrow with the seeds at planting. The 2x2 treatment consisted of the fungicide applied in the soil 2 inches down and 2 inches away on the right and left side from the corn seeds while treatment 0x0 consisted of the 16 fungicide being applied on the soil surface with a steady stream when the furrow has closed approximately 0 to ½ inches on the seed. Another treatment involved foliar spray application of LucentoTM (15.55% a.i. bixafen and 26.47% a.i. flutriafol; FMC Corporation, Philadelphia, PA) at R1 (silking stage). In 2019, only the in-furrow application was applied using 1.11 L/ha Xyway fungicide. In 2020, three treatments were conducted including 0.37 L/ha (5 fl. oz. per acre) of Lucento fungicide, 1.11 L/ha of Xyway application via in-furrow and 2x2 treatment at planting. In total, Xyway in-furrow applications were applied for a total volume of 44.81 L/ha while 2x2 applications at 93.54 L/ha. Foliar flutriafol application of Lucento was applied on 23-July 2020 with a CO2 backpack sprayer for a total volume of 140.31 L/ha at 40 psi using XR TeeJet 8001VS flat fan nozzles (TeeJet Technologies, Springfield, IL) with Induce (Non-ionic surfactant; Helena Chemical Company, Collierville, TN) at 0.25% v/v. In 2021, three treatments were conducted using 1.11 L/ha of Xyway application via in-furrow, 2x2, and 0x0 treatment at planting. Application of Xyway fungicide via in-furrow, 2x2, and 0x0 applications were applied for a total volume of 46.77 L/ha. The rate of fungicide applications was based on the label recommended rate by the manufacturer. At V5 (in 2019 and 2021) and V6 (in 2020) growth stage, GLS and NCLB inoculum consisting of infested corn kernels were broadcasted over each plot. Experiments received overhead irrigation frequently to assist in disease development throughout the season. Detailed summary of trial establishment including the inoculation date, inoculation rate, inoculation application growth stage, rating date, fungicide treatments, and application rate are documented in Table 2.1. 17 Table 2.1. Summary of trial establishment including the inoculation date, inoculation rate, inoculation application growth stage, rating date, fungicide treatments, and application rate. Inoculation Ratea Rating Date Year Hybrid Planting Date Inoculation Date - Stage GLS (kg) NCLB (kg) 2019 P9998AM 27-May 1 Jul - V5 0.57 0.45 2020 9-May 16 Jun - V6 0.42 0.53 DKC 52-61 6-Aug 18-Aug 2-Sep 2021 13-May 15 Jun - V5 0.85 0.85 4-Aug 23-Aug 9-Sep Third Rating Second Rating First Fungicide - Applicationb Rating 15-Aug 29-Aug 26-Sep Xyway LFR - in-furrow Xyway LFR - in-furrow 6-Aug 19-Aug 3-Sep Application Rate (L/ha) 1.11 1.11 1.11 0.37 1.11 1.11 1.11 Xyway LFR -2x2 Lucento - foliar at R1 Xyway LFR -in-furrow Xyway LFR - 2x2 Xyway LFR - 0x0 aInoculation rate in kg, disease abbreviated as followed: GLS = gray leaf spot, and NCLB = northern corn leaf blight bFungicide brand followed by method of applications 18 Flutriafol Quantification Corn plants were collected on 12-August 2019, 10-August 2020, and 19-August 2021 at R3 (kernel milk) stage in 2019 and 2021 and at R4 (kernel dough) stage in 2020. For flutriafol treated plots, four replicate plots in 2019 and 2021 and three replicate plots in 2020 were sampled. A single non-treated plot was also sampled each year. Two plants per treatment plot were randomly selected and dug with a shovel to ensure root mass was included in the samples for flutriafol detection. The roots were cleaned as needed to remove soil and debris. Root, stalk, and each leaf was paired from both plants and labelled as the ear leaf (E), E-1 (one leaf below ear leaf), E-2 (two leaves below ear leaf), E+1 (one leaf above ear leaf), E+2 (two leaves above ear leaf) and so on. All the samples were placed in a sample bag for storage in a freezer (-20°C) until ready to be analyzed. Residue sample analysis was performed at MSU Pesticide Analytical Laboratory, East Lansing, MI using Gas Chromatography Mass Spectrometry (GC-MS). GC-MS is an analytical technique that combines gas chromatography and mass spectrometry to identify the components in a mixture, quantify analytes, and detect any contamination in the substances. Samples for each plant parts were taken randomly and weighed to 25 g for residual analysis. Then, samples were mixed with 8 g magnesium sulfate to absorb water and 2 g sodium chloride to help the ionized compounds dissolve in water. A 150 mL High-performance liquid chromatography (HPLC)- grade dichloromethane was added until sample was submerged and stored in 4°C until samples were processed. The dichloromethane was removed from the solution by filtering the sample through 185 mm diameter filter paper containing 20 g sodium sulfate (EMD Chemicals Inc., Gibbstown, NJ) and the filtered solution were connected to a rotary evaporator (R-114 rotary evaporator, Büchi Labortechnik AG, Flawil, Switzerland) and rotated for three minutes. Then, 19 the remaining dry extract residue was dissolved by adding a total of 2 mL of HPLC-grade acetonitrile, and the flask was rotated for 3 minutes. To ensure there were no particulates in the samples, each sample was filtered through a 0.45 µm Acrodisc 13-mm syringe filter (Pall Corp., East Hills, NY). The filtered samples were quantified using an Agilent 7890A Gas Chromatograph (Agilent Technologies Inc., Santa Clara, CA) equipped with an Agilent 5973 Network Mass Selective Detector High-Performing 5%-phenyl-methylpolysiloxane (HP-5MSI), and a C18 reversed-phase column 30 by 0.25 mm bore with a 0.25 µm film column (Agilent Technologies Inc., Santa Clara, CA). The oven began at 70°C for one minute and then ramped at 20°C/min to 320°C for four minutes. Molecular ions for flutriafol were monitored at m/z 123.10, 164.00 and 219.10 (Da). The method level of quantification was 0.010 µg/mL of a.i., and level of detection was 0.003 µg/mL. The quantitation was performed against a standard curve and the recovery data was recorded as µg/mL for all samples namely stalk, root, ear leaf, leaf below ear leaves (E- 1 to E-7) and leaf above ear leaves (E+1 to E+8) depending on plants for each replicate every year. Disease Assessment and Yield Data Foliar diseases of GLS and NCLB were assessed visually. Apart from GLS and NCLB, southern rust in 2019 and tar spot in 2020 and 2021 were also observed at low levels but were not rated in our study. Foliar disease ratings of GLS and NCLB were evaluated three times each year by assessing two leaves per plant from 10 plants per plot in the center two rows (Table 2.1). On each rating date, the ear leaf and an additional leaf; either below or above the ear leaf were evaluated depending on the disease progression on the rating date. Disease severity (DS) was assessed visually by estimating the percentage of individual diseases on leaves. Disease 20 incidence (DI) was the percentage of plants with symptoms, rated as 0 (no disease) to 100 (death of plants) scale with 10% intervals. Disease index (DIX) that accounted for DS and DI was calculated for each disease: DIX = DI*(DS/100). DIX values were compared between each fungicide treatment each year. The center two rows of each 4-row plot were harvested on 24- October 2019, 20-October 2020, and 6-October 2021. Yields were calculated from total weight, test weight, and moisture values and adjusted to 15.5% moisture. Data Analyses All data analyses were conducted in R version 4.1.2 (R Core Team, 2021). Mean of plant parts including stalks, roots, and leaves were calculated from all replicates for each fungicide treatment each year using mean function from base R ‘stats’. The mean data were standardized by subtracting the untreated check values from respective years and plot as a horizontal bar chart for different treatments, years, and different plant parts (Table S.2.1, Figure 2.2). Data from flutriafol quantification were subjected to analysis of variance (ANOVA) using 'lm’ method and mean separation determined with least square means difference using ‘emmeans’ at α=0.05 (Russell, 2022). The ANOVA was performed separately each year due to different fungicide treatments application between years. Separate ANOVA was also conducted for Xyway in- furrow and Xyway 2x2 across all years. Fungicide treatments and year were treated as a fixed factor. DIX values for each rating date and each foliar disease ratings were subjected to ANOVA and mean separation similar to the flutriafol quantification data (Table S.2.2). The area under disease progress curve (AUDPC) was calculated to determine disease intensity over time on the corn field by dividing the DIX of the ear leaf by the total time in days duration of the epidemic from the first to last disease rating before calculating the mean AUDPC (Campbell and Madden, 21 1990). ANOVA and mean separation were also performed on mean AUDPC and yield data (Table 2.2). All graphs were visualized in R package ‘ggplot2’ (Wickham, 2016) and all code for data analyses is available publicly on https://github.com/triplenza/flutriafol-movement-in-corn. Flutriafol Quantification Results The quantification of flutriafol analyzed was reported as µg/mL for stalk, root, and leaf for each fungicide treatment each year (Table S.2.1). The untreated check in 2019 and 2020 showed below the level of detection for flutriafol concentration in all plant parts tested. However, the untreated control in 2021 showed 0 (no detection) in stalk, root, ear leaf, E-4, and E-5 and a range of 0.05 to 0.87 µg/mL of flutriafol was detected in E+1 to E+7 and E-1 to E-3. All plant parts tested with Xyway and Lucento fungicide treatments showed flutriafol concentrations ranging from 0.01 to 14.61 µg/mL (Figure 2.2). 22 Figure 2.2. Mean of different fungicide treatments on stalks, roots, and leaves with two replicates represented by each horizontal bar of flutriafol concentration (µg/mL) in (A) 2019, (B) 2020, and (C) 2021. Each color represents different fungicide treatments. 23 All residual sample analysis performed for flutriafol quantification was significantly higher from the untreated check for respective years (Table 2.2). Flutriafol quantification in 2020 for all fungicide applications was significantly different from the untreated control (P = 0.004), however, the mean comparisons indicated that fungicide treatments of Xyway in-furrow, Xyway 2x2, and Lucento were not significantly different from each other with a mean of 0.024, 0.044, and 0.045 µg/mL respectively. In 2021, flutriafol concentrations of all fungicide treatments were significantly different from the untreated control (P <.0001) with Xyway 0x0 treatment having the highest flutriafol concentration detected with a mean of 8.667 µg/mL followed by Xyway 2x2 at 3.122 µg/mL, Xyway in-furrow at 1.530 µg/mL, and untreated control at 0.187 µg/mL. Table 2.2. Residue sample analysis for flutriafol quantified using Gas Chromatography Mass Spectrometry (GC-MS). Flutriafol quantification (µg/mL)a 2019 2020 2021 a b 0 0.528 - - - <.0001 Fungicide Treatmentb UTC 0 IF 0.032 2x2 0.044 L 0.045 0x0 - p-valuec 0.004 aMean of flutriafol quantification reported in µg/mL bFungicide treatment abbreviations are as followed: UTC = Untreated control, IF = Xyway in- furrow, 2x2 = Xyway 2x2, 0x0 = Xyway 0x0, and L = Lucento. cMeans followed by the same letters within columns are not significantly different as determined by least square means comparison (α=0.05). 0.187 1.530 3.122 - 8.667 <.0001 a b b b a b c d Disease Assessment and Yield Data Diseases of GLS and NCLB were assessed on ear leaf and additional leaf either below or above the ear leaf on three rating dates each year (Table S.2.2). On the first rating of each year, symptoms were mostly below the ear leaf which is on the lower canopy. DIX of GLS on the untreated control varied by year, ranging from 0 (no disease) to 0.60. Greater DIX values of GLS were noted in the untreated control plots in 2019 followed by 2021 indicating higher disease 24 development of GLS in 2019. In 2020, the DIX values for all fungicide treatments did not significantly differ from the untreated control plots due to low disease of GLS was observed in this year compared to 2019 and 2021. In 2021, DIX values for fungicide treatments were significantly different from each fungicide treatment for four out of six ratings (P < 0.05) (Figure 2.3). Mean comparisons in this year indicated that Xyway in-furrow reduced GLS severity for every disease rating compared with Xyway 2x2 and Xyway 0x0 treatments with DIX ranging from 0 (no disease) to 0.05 µg/mL. All Xyway 2x2 and Xyway 0x0 treatments also reduced GLS compared to the control for every disease rating. Figure 2.3. Disease rating of gray leaf spot on three rating dates on 4-August, 23-August, and 9- September in 2021. Each color represents different leaf rating; 1 = first rating, 2 = second rating, 3 = third rating, E = ear leaf, E-2 = two leaves below ear leaf, E-1 = one leaf below ear leaf, and E+2 = two leaves above ear leaf. X-axis represents fungicide treatments abbreviated as followed: UTC = untreated control, IF = Xyway In-furrow, 2x2 = Xyway 2x2, and 0x0 = Xyway 0x0. AUDPC in 2019 was not calculated for both GLS and NCLB as no final rating was recorded on the ear leaf. The mean AUDPC in 2020 for GLS was not significant for all fungicide 25 treatments compared to the untreated control except for Lucento (P < 0.05) while in 2021, the mean AUDPC calculated showed that all Xyway treatments including in-furrow, 2x2, and 0x0 were significantly different from the untreated control (P < 0.05) (Table 2.3). However, the effect of fungicide treatment was not significantly different from each other for all years. The DIX values for NCLB were not statistically significant from the untreated control for all years for most ratings (Table S.2.2). Thus, the AUDPC of NCLB for all year is not statistically significant from the untreated control. For yield data, there is no significant difference between all fungicide treatments and untreated control in 2019 and 2020. However, in 2021, the untreated control has a higher yield compared to plots with fungicides treatment (Table 2.2). Table 2.3. Mean area under disease progress curve (AUDPC) of gray leaf spot (GLS) and northern corn leaf blight (NCLB) and yield adjusted to 15.5% moisture. AUDPCa GLS NLB Yield Year 2019 2020 2021 Fungicide Treatmentb Mean ± SEc UTC IF p-valued - - UTC IF 2x2 p-value UTC L p-value UTC IF 2x2 0x0 3.22 ± 1.98 3.23 ± 0.36 2.13 ± 1.60 NS 3.48 ± 2.10 0.53 ± 0.15 0.031 4.98 ± 4.32 0.72 ± 0.89 1.07 ± 1.13 1.34 ± 1.02 b a b a a a Mean ± SE - - 5.03 ± 7.04 2.85 ± 2.12 2.86 ± 4.95 NS 5.42 ± 8.40 0.09 ± 0.19 NS 8.26 ± 8.34 1.54 ± 3.08 3.20 ± 2.45 1.49 ± 2.01 26 Mean ± SE 217.04 ± 9.26 209.04 ± 24.4 NS 234.94 ± 57.9 243.74 ± 44.4 237.69 ± 88.1 NS 251.84 ± 24.6 268.23 ± 5.91 NS 291.82 ± 9.60 b 288.72 ± 11.0 ab 269.46 ± 13.1 a 268.59 ± 19.2 a Table 2.3. (cont'd) p-value 0.024 NS 0.0339 aAUDPC calculated for 2020 and 2021 only due to no third ratings were recorded in 2019. bFungicide treatment abbreviations are as followed: UTC = Untreated control, IF = Xyway in- furrow, 2x2 = Xyway 2x2, 0x0 = Xyway 0x0, and L = Lucento. cMeans followed by the same letters within columns are not significantly different as determined by least square means comparison (α=0.05). dp-value that is higher than 95% confidence interval (α=0.05) is abbreviated as NS = not significant. Discussion In this study, four fungicide treatments were applied at a field in Lansing, MI to quantify the flutriafol movement in corn plants and to assess the disease suppression of GLS and NCLB by fungicide application methods. All plant parts tested with various fungicide treatments in this study from 2019 to 2021 contained various flutriafol concentrations. The untreated control is mostly below the level of quantification due to no flutriafol being found in the plant parts. However, in 2021, flutriafol was detected in several leaves probably due to neighboring plots were sprayed with flutriafol and flutriafol building up in the soil from previous years fungicide application. Although Xyway fungicides were only applied at planting, flutriafol was detected in every root stalk, and leaf sample. This study showed the mobility of flutriafol in corn plants regardless of the method of application. The mobility of flutriafol and long half-life, typically 1,358 days (Lewis et al. 2016) might indicate that flutriafol has better disease control and protection against disease. Flutriafol application of Xyway in-furrow treatments were conducted from 2019 to 2021. In all years, flutriafol uptake of Xyway in-furrow treatments was significantly different from the untreated control in their respective years. The quantification of fungicide in corn has not been studied previously, hence there is no literature available to support this study. However, quantification of a systemic insecticides (azadirachtin) in trunk injections on Pear Psylla caused 27 by Cacopsylla pyricola showed a mean of 1.507 µg/mL while airblast insecticide application was below the level of detection similar to the untreated (Wheeler et al. 2020). This indicates that systemic fungicide that is applied as an airblast or foliar application had lower residual might be due to sun exposure degradation. However, in this study, the in-furrow fungicide application of Xyway is not labeled or recommended by the manufacturer of this fungicide. The field trial in 2020 compared fungicides applied at planting, Xyway in-furrow and Xyway 2x2, versus a foliar fungicide application of Lucento at the R1 growth stage. However, the three fungicide treatments showed no significant difference in flutriafol uptake by the plant indicating that using at planting regardless of application method could possibly reduce cost and labor because foliar fungicide application applied at later growth stage (VT to R1) is labor and cost extensive due to the need for aerial application (Mueller et al. 2013; Wise et al. 2019). In 2021, three methods of Xyway fungicide applications were compared at planting including in- furrow, 2x2, and 0x0. The results indicated that flutriafol applied as steady stream or 0x0 have higher flutriafol concentration followed by 2x2, and in-furrow. Fungicide treatments in 2021 exhibited higher flutriafol concentration in corn plants compared to 2019 and 2020. This might be due to high flutriafol residual build up in the soil in the following years due to the long half-life of flutriafol. Similarly, a study by Potter et al. (2001) demonstrated an increase in the residue of chlorothalonil in the soil after seven fungicide applications in one season. With year-to-year usage of flutriafol, the accumulation of chemical building up in the soil could potentially contaminate the environment. The long half-life of flutriafol is beneficial for the plants as it persists in the plant since the first application of fungicide and can potentially protect the plant all season long. Thus, the fungicide application of flutriafol must be applied according to the recommended manufacturer label. 28 Due to flutriafol showing higher residue analysis upon repeated use, one of the concerns is how long the fungicide will stay in the soil and corn kernels. A study by VanWoerkom et al. (2022) in 2014 and 2015 demonstrated that fenpropathrin residue exceeded European Union and India’s Default maximum residue level (MRL) which is 0.01 ppm but below MRL for the United States which is 5 ppm for washed tart cherry. Fenpropathrin typical half-life is 34 days while flutriafol half-life is 1,358 days which potentially indicate that flutriafol might persist in the corn kernels following harvest (Lewis et al. 2016). Thus, residue analysis should be conducted post- harvest to investigate whether the persistence level of flutriafol meets the international MRL; 9 ppm, 8ppm, and 0.03 ppm for forage corn, stover corn, and sweet kernels plus cobs with husk removed respectively (Environmental Protection Agency, 2020). Apart from that, different sampling segments of leaf could also play a role in flutriafol concentrations. A study by González Vázquez at al. (2022) proved that lower segments of turfgrass (Agrostis stolonifera) leaf have higher propiconazole concentrations regardless of temperature and time of fungicide application with a mean of 365 µg/mL compared to the upper leaf segments (mean = 0.18 µg/mL). The high flutriafol concentration observed in Xyway 0x0 fungicide treatment might be due to inconsistency of flutriafol quantification sampling segments of corn leaf each year. Thus, Xyway 0x0 fungicide treatment could not be concluded as a recommended fungicide application method at planting. Further studies should be conducted to study if there is a difference in flutriafol concentration in corn plants with the difference method of fungicide application at planting in different leaf segments of corn. Apart from flutriafol quantification, disease suppression of GLS and NCLB with various fungicide application methods was observed. Flutriafol applied as in-furrow effectively reduced DIX values of GLS compared to other fungicide treatments. In general, flutriafol reduced GLS 29 compared to the untreated control in this study. There was relatively moderate GLS disease pressure in 2019 and 2021, however in 2020, disease pressure was low explaining no significance found in fungicide treatments compared to the untreated control. Although in-furrow application has been documented as effective in managing foliar disease in other studies (Kandel et al. 2016; Potratz et al. 2020), this is the first report of flutriafol efficacy in managing GLS using in-furrow application treatment. A study by Ward et al. (1997c) reported that flutriafol had a lower mean AUDPC compared to the control, difenoconazole, propiconazole, and tebuconazole tested which was 8.1 and 10.4 in 1992-1993 and 1993-1994 seasons respectively. Their study also reported that flutriafol treatment had one of the lowest disease severities (5.8%), lower infection rate, and longer effective control in controlling GLS compared to the other fungicide treatments. The mean AUDPC for NCLB for all Xyway fungicide treatments is lower than the untreated control, however, it was not statistically different from the untreated check for all years. This study demonstrated that a flutriafol fungicide application, regardless of application method suppresses GLS in the corn field. Although in-furrow fungicide applications are not common to be used for corn production, in-furrow fungicides are a common practice to manage disease on cotton (Gossypium herbaceum), peanut (Arachis hypogaea), potato (Solanum tuberosum), soybean (Glycine max), and sugar beet (Beta vulgaris) (Kandel et al. 2016; Mueller et al. 2013). Apart from DMI fungicides, SDHI fungicides and Aromatic Hydrocarbon (AH) fungicides (FRAC Code 14) can also be applied via in-furrow application at planting (Mueller et al. 2013). Although Xyway fungicide applications showed disease suppression, the yield data was not significantly different compared to the untreated control in 2019 and 2020. In 2021, the 30 untreated control had a significant higher yield compared to the treated plots. This might be due to the difference in disease severity across the field, supported by Ward et al. 1997a that the yield response relies on application of fungicide during higher disease development. The findings from this study provide novel information on the fungicide flutriafol such as in-planta mobility and disease management efficacy in the field of this fungicide. It is important that flutriafol is used as an additional disease management in protecting corn from GLS. 31 CHAPTER 3: IDENTIFICATION OF CERCOSPORA SPP. AND BASELINE FUNGICIDE SENSITIVITY TESTING OF FLUTRIAFOL ON CORN Authors who contributed to this study were: Nik N. Nikzainalalam1, Drake J. Copeland2, Matthew S. Wiggins2, Darcy E.P. Telenko3, Kiersten A. Wise4, Austin G. McCoy1, Janette L. Jacobs1 and Martin I. Chilvers1 1 Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824 2 FMC Corporation, Dayton, OH 45458 3 Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907 4 Department of Plant Pathology, University of Kentucky, Lexington, KY 40546 32 Abstract Gray leaf spot (GLS) is a significant disease of corn. Currently, there are two known species of Cercospora that cause GLS of corn, C. zeae-maydis (previously Group I C. zeae-maydis) and C. zeina (previously Group II C. zeae-maydis). Aside from cultivar resistance, fungicides are often used for disease management. Recently, a new fungicide with the active ingredient, flutriafol received EPA registration; XywayTM Liquid Fertilizer Ready, a fungicide product that is applied at planting or post emergence for fungal disease management in corn, including suppression of GLS. In this study, 448 Cercospora spp. isolates were collected from infected corn leaf samples submitted from across the United States and Ontario, Canada. The Cercospora spp. were identified using multi-locus genotyping including internal transcribe spacer (ITS), elongation factor 1-α (EF1), calmodulin (CAL), histone H3 (HIS), and actin (ACT) gene. Based on the five loci, phylogenetic analyses were conducted, and six species were identified; C. cf. flagellaris (n = 77), C. kikuchii (n = 4), C. zeae-maydis (n = 361), Cercospora sp. M (n = 2), Cercospora sp. Q (n = 1), and Cercospora sp. T (n = 3). Cercospora spp. were artificially inoculated on corn and soybean to determine pathogenicity. Based on the pathogenicity test, C. cf. flagellaris, C. kikuchii, and Cercospora sp. Q were pathogens of soybean. Fungicide sensitivity of Cercospora spp. to flutriafol was assessed using a subset of 340 isolates collected in 2020 and 2021. To determine fungicide sensitivity, a poison plate method was used to determine the minimum inhibitory concentration (MIC) to inhibit the growth of Cercospora spp. completely on flutriafol- amended clarified V8 agar at 9 different concentrations. The EC50 was also calculated from the same trial by measuring relative growth as compared to the non-amended control. Cercospora zeae-maydis is sensitive to flutriafol with mean MIC values of 2.5 µg/mL and EC50 values 33 ranging from 0.016 to 1.020 µg/mL with a mean of 0.346 µg/mL. Findings will assist in monitoring the sensitivity of the flutriafol fungicide in Cercospora spp. populations. Introduction Plant diseases severely impact corn production in the United States. Foliar diseases such as gray leaf spot (GLS) (Cercospora zeae-maydis), northern corn leaf blight (NCLB) (Exserohilum turcicum), southern rust (Puccinia polysora) and tar spot (Phyllachora maydis) are the major diseases that caused large yield loss in the northern United States and Ontario, Canada from 2012 to 2019 (Mueller et al. 2016; Mueller et al. 2020). GLS can cause more than 50% yield loss when plants are infected early in the season (Lipps 1998; Wegary et al. 2004). Although GLS was ranked as one of the top 10 diseases from 2012 to 2015, GLS was not the main destructive disease of corn that caused yield loss (Mueller et al. 2016). However, in recent years, GLS has been documented as one of the top two yield-limiting diseases, causing a mean of 6,678,000 metric tons yield loss annually in the United States and Ontario, Canada from 2016 to 2019 (Mueller et al. 2020). Cercospora zeae-maydis is generally regarded as the causal fungal pathogen of GLS on corn and was first identified in Illinois in 1924 (Tehon and Daniels 1925). Recent research in South Africa by Crous et al. (2006) identified two distinct species of Cercospora spp. that caused GLS on corn; C. zeae-maydis (previously Group I C. zeae-maydis) and C. zeina (previously Group II C. zeae-maydis). These two Cercospora spp. are sister taxa that are genetically different (Crous et al. 2006; Dunkle and Levy 2000; Wang et al. 1998). Cercospora zeae-maydis is found most often in the United States while C. zeina is most common in Southern Africa (Crous et al. 2006; Dunkle and Levy 2000; Meisel et al. 2008; Okori et al. 2003). However, C. zeina has also been reported to be found in the United States in Indiana, North Carolina, Virginia, Ohio, New 34 York, and Pennsylvania (Hsieh Lin-si 2011; Okori et al. 2003; Swart et al. 2017; Wang et al. 1998). GLS increases in severity due to no-till or reduced tillage activity which contributes to the accumulation of infected corn residue on the soil and can serve as primary inoculum the following year. Disease severity of GLS can reach up to 84% in no-till practice compared to 73% maximum severity when conventional tillage was practiced (Negash 2013; Payne et al. 1987; Ward et al. 1997b). The yield for no-till continuous corn was reduced by 8% compared to plowing, a reduction from 10,895 to 10,020 kg/hectare of corn yield compared to corn-soybean rotation that increased yield (Lund et al. 1993). Corn and soybean rotation are a common practice in the United States to reduce pathogenic inoculum buildup and protect crop yields (Edwards et al. 1988; Lund et al. 1993; Porter et al. 1997). It is crucial to understand the species diversity of Cercospora spp. infecting corn to provide accurate disease management recommendations as different Cercospora spp. have different host ranges, some of which may cause disease on multiple rotation crops or have differing sensitivity to fungicidal compounds. To mitigate yield losses from disease, applying foliar fungicides is a widespread practice in disease management of corn. The main fungicide classes that have been used to control GLS are demethylation inhibitors (DMI; FRAC (Fungicide Resistance Action Committee) Code 3) and quinone outside inhibitors (QoI; FRAC Code 11) (Bradley and Ames 2010; Dhami et al. 2015; Ward et al. 1997b). Succinate dehydrogenase inhibitors (SDHI; FRAC Code 7) have only been recently tested for control of GLS (Neves and Bradley 2019). According to FRAC (2018), DMIs pose a medium risk in developing resistance while QoIs and SDHIs pose a high and medium-high risk respectively in developing resistance. The use of high-risk fungicides can reduce the effectiveness of the fungicide within a few years of introduction (Brent and Hollomon 35 2007). Using a medium risk fungicide, such as DMIs, provides longer periods of use of the fungicide on the crop due to less risk of resistance being selected in the community. DMI fungicides work by inhibiting the C-14 demethylase enzyme (erg11/cyp51) that is responsible for ergosterol production, which is important to control membrane fluidity and permeability of fungi (Ziogas and Malandrakis 2015; Kwok and Loeffler 1993). A new DMI fungicide, flutriafol (XywayTM Liquid Fertilizer Ready (Xyway); FMC Corporation, Philadelphia, PA) has received Environmental Protection Agency registration in 2020 for foliar disease protection of corn for GLS, NCLB, southern leaf blight (Bipolaris maydis), common rust (Puccinia sorghi), head smut (Sphacelotheca reiliana), and common smut (Ustilago maydis) (Environmental Protection Agency 2020). Baseline sensitivity of C. zeae-maydis to QoIs and SDHIs fungicides have been documented in Bradley and Pederson (2011) and Neves and Bradley (2019), however, no baseline sensitivity has been conducted on DMI fungicides. Thus, the objectives of this study were to i) identify Cercospora spp. that were present on corn leaves and causing GLS on corn in the United States and Ontario, Canada, ii) determine the fungicide sensitivity of the DMI fungicide, flutriafol in Cercospora spp. population using minimum inhibitory concentration (MIC), relative growth, and 50% effective concentration (EC50), and iii) compare MIC and EC50 values to evaluate fungicide sensitivity across identified Cercospora spp. Isolate Collection Materials and Methods Leaf samples with typical symptoms of GLS were collected from across the United States including Alabama, Delaware, Illinois, Indiana, Iowa, Kansas, Kentucky, Maryland, Michigan, Nebraska, New Jersey, New York, Ohio, Pennsylvania, Tennessee, Virginia, and Ontario, 36 Canada during the 2020 and 2021 growing seasons (Table S.3.1). Fresh leaves were dried and pressed for at least seven days to prevent mold and allow for long-term storage. Symptomatic corn leaves were cut into 5 by 5 cm pieces and surface sterilized with 5% bleach for 5 min and rinsed twice with sterile distilled water. The sterilized leaves were placed on water agar, metalaxyl and streptomycin (WMS) medium (20 g agar, 15 mg/L metalaxyl, and 300 mg/L streptomycin sulfate in 1 L of de-ionized water) for 24 – 48 hours at ambient room temperature (21°C ± 2°C) to encourage sporulation. Using a dissecting microscope at 4x magnification (Greenough Stereo Microscope Leica S6 E, Leica Microscopy, Wetzlar, Germany), conidia were collected using a sterilized needle-pin and spread with a sterile loop across a new WMS medium to obtain single spore colonies for 24 – 48 hours to allow for germination. Single conidium were transferred to V8 medium amended with chloramphenicol (1 g CaCO3, 163 mL V8 juice, 100 mg/L chloramphenicol, 14 g agar in 1 L de-ionized water) using a flame sterilized needle-pin. After 14 days of incubation at ambient room temperature (21°C ± 2°C), the colony morphology (Figure 3.1) was observed and determined to be putative Cercospora spp. Isolates were stored long-term in 5 mL scintillation vials containing sterile water at 4°C and in 2 mL cryogenic vials containing a 15% glycerol solution at -20°C. 37 Figure 3.1. Colonies of (A-B) faster-growing (60-80 mm diameter) and (C-D) slow-growing (10- 15 mm diameter) Cercospora spp. on V8 agar after 21 days of incubation at ambient room temperature (21°C ± 2°C). (A and C) Bottom-view and (B and D) top-view of Cercospora spp. 38 DNA Extraction, Amplification, and Sequencing Genomic DNA was extracted from fungal mycelia harvested from a 14 day-old culture grown on V8 agar using the FastDNATM Spin Kit (MP Biomedicals, Santa Ana, CA) according to the manufacturer’s manual. Extracted DNA concentrations were standardized to 50 ng/µL and used for polymerase chain reaction (PCR) amplification. Based on the morphology of the mycelial growth (Figure 3.1), slow-growing isolates were initially determined to be C. zeae- maydis complex and only the Internal Transcribed Spacer (ITS) region or calmodulin (CAL) locus were amplified to distinguish between C. zeae-maydis and C. zeina (Groenewald et al. 2013). The primer pair ITS1 and ITS4 (White et al., 1990) were used to amplify part of the ITS nrDNA including the 5.8S region. To identify other putative Cercospora spp. morphologies that were faster-growing, four other loci in addition to ITS were sequenced to obtain additional information because no single locus was able to identify to the species level in Cercospora spp. (Groenewald et al. 2013). Part of the elongation factor 1-α gene (EF1) was amplified with primer set EF1-728F and EF1-986R (Carbone & Kohn 1999), part of CAL gene using primers CAL- 228F and CAL-737R (Carbone & Kohn 1999) or CAL2Rd (Groenewald et al. 2013), part of histone H3 gene (HIS) using primer set CylH3F and CylH3R (Crous et al. 2004), and part of actin gene (ACT) using primer set ACT-512F and ACT-783R (Carbone & Kohn 1999). Details of the primer sets of all five loci are provided in Table 3. 39 Table 3.1. Details of primers used in this study. See Groenewald et al. (2013) for additional information on primers. Name Sequence (5' - 3') Orientation %GC Tm (°C) Reference Actin (ACT) ACT-512F ATG TGC AAG GCC GGT TTC GC ACT-783R TAC GAG TCC TTC TGG CCC AT Forward Reverse 60.0 55.0 51.4 47.6 Carbone & Kohn (1999) Carbone & Kohn (1999) Calmodulin (CAL) CAL-228F GAG TTC AAG GAG GCC TTC TCC C CAL-737R CAT CTT TCT GGC CAT CAT GG CAL2Rd Forward Reverse TGR TCN GCC TCD CGG ATC ATC TC Reverse 59.1 50.0 58.0 49.2 Carbone & Kohn (1999) 43.4 Carbone & Kohn (1999) 47.5 - 50.8 - 54.9 Groenewald et al. (2013) Histone H3 (HIS) CYLH3F AGG TCC ACT GGT GGC AAG CYLH3R AGC TGG ATG TCC TTG GAC TG Forward Reverse 61.1 55.0 47.6 46.6 Crous et al.(2004) Crous et al.(2004) Internal Transcribed Spacer (ITS) ITS 1 ITS 4 Forward TCC GTA GGT GAA CCT GCG G TCC TCC GCT TAT TGA TAT GC GGA Reverse 63.2 45 49.5 41.6 White et al. (1990) White et al. (1990) Translation Elongation Factor 1-α (EF1) EF1-728F CAT CGA GAA GTT CGA GAA GG EF1-986R TAC TTG AAG GAA CCC TTA CC Forward Reverse 50.0 45.0 42.2 40.9 Carbone & Kohn (1999) Carbone & Kohn (1999) 40 PCR for ITS, EF1, CAL, HIS, and ACT were conducted in a total volume of 25 µL containing 50 ng genomic DNA, 1x PCR Buffer (Invitrogen Corp., Carlsbad, CA), 1.5 mM MgCl2 (Invitrogen Corp.), 0.2 mM dNTPs, 0.2 µM of forward and reverse primer (Sigma Aldrich, St. Louis, MO), 5 ng Bovine Serum Albumin (New England BioLabs Inc., Ipswich, MA), and 1 Unit Taq DNA Polymerase (Invitrogen Corp.). PCR conditions for ITS, EF1, HIS, and ACT comprised an initial denaturation step at 94°C for 3 min; followed by 35 cycles of denaturation at 94°C for 45 s, annealing at 55°C for 45 s, and elongation at 72°C for 1 min, and a final elongation step at 72°C for 7 min. PCR conditions for CAL differed from other primers which comprised an initial denaturation step at 94°C for 3 min; followed by 35 cycles of denaturation at 94°C for 30 s, annealing at 60°C for 30 s, and elongation at 72°C for 1 min, and a final elongation step at 72°C for 4 min. PCR amplification was performed using MiniAmp™ Thermal Cycler (Applied Biosystems™, Foster City, CA). The size of amplicons was determined using 1 Kb Plus DNA Ladder (Invitrogen Corp.). The amplified PCR products were purified using ExoSAP-IT™ (Applied Biosystems™, Foster City, CA) to remove excess primers and nucleotides before Sanger sequencing. The purified PCR products were submitted to Psomagen Inc. (Rockville, MD) or the Michigan State University Genomics Core (East Lansing, MI) for sequencing. Phylogenetic Analyses The sequences were trimmed and assembled using CodonCode Aligner v4.2.7 (CodonCode Corp., Dedham, MA). The trimmed sequences were approximately 500, 310, 320, 400, and 230 bp for ITS, EF, CAL, HIS, and ACT, respectively. The consensus sequence FASTA file for the ITS region and CAL gene of the slow-growing Cercospora spp. isolates were input into the Basic Local Alignment Search Tool (BLAST) to find homologous sequences 41 deposited into the NCBI nucleotide database limited to type material to identify the organism associated with the nucleotide sequence. Individual phylogenetic trees for the ITS region and CAL gene were constructed to identify the slow-growing putative Cercospora spp. isolates. Twenty-two and 34 sequences of slow-growing isolates from 2020 and 2021, respectively, were selected to represent the slow-growing isolates based on their alignment. In addition, 20 Cercospora spp. reference sequences were included (Table S.3.2) from Groenewald et al. (2013) that are closely related to C. zeae-maydis including C. cf. flagellaris, C. coniogrammes, C. kikuchii, C. senecionis-walkeri, C. sojina, C. sp. A, C. zeina, and Septoria provencialis as an outgroup. Individual loci of the sequences generated from this study were deposited into the NCBI’s GenBank nucleotide database (Table S.3.1). Faster-growing Cercospora spp. isolates raw FASTA files for each locus were edited using Molecular Evolutionary Genetics Analysis (MEGA) v.11.0.13 (Tamura et al. 2021) and manual adjustments were made visually where necessary. An additional 117 Cercospora spp. reference sequences including 109 DNA sequences from Groenewald et al. (2013) and 8 DNA sequences from Bakhshi et al. (2015) were aligned using Multiple Sequence Comparison by Log-Expectation (MUSCLE) in MEGA. The detailed information for the reference isolates used in this study including GenBank accession numbers, culture accession numbers, species, and host of the species are provided in Table S.3.2. The sequence of Septoria provencialis (isolate CPC 12226) was used as an outgroup based on phylogenetic analyses in Groenewald et al. (2013). The concatenated sequences from five loci were generated manually for each isolate and best model selection was calculated using Maximum Likelihood with 95% partial deletion in MEGA v.11.0.13 (Tamura et al. 2021). 42 DNA model selection with the lowest Bayesian information criterion (BIC) and Akaike information criterion (AIC) was implemented using MEGA v.11.0.13 (Tamura et al. 2021). Based on the lowest BIC and AIC determined by MEGA for faster-growing isolates, Hasegawa- Kishino-Yano (HKY) + I + G with inverse gamma-distributed rates were chosen as the best DNA model selection. Multi-locus phylogenetic trees were constructed using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion. The resulting phylogenetic tree with low statistical values less than 50% was condensed and 50% majority-rule consensus tree was selected (Nei and Kumar, 2000). An individual trees for each locus; ITS, EF1, CAL, HIS, and ACT were also constructed using the same parameter and model for consistency. For the slow-growing isolates, a single locus of ITS or CAL was used to construct a phylogenetic tree due to these loci being informative in determining C. zeae-maydis or C. zeina (Groenewald et al. 2013). Kimura-2 parameter + G with gamma-distributed rates was selected based on the best DNA model selection determined by the lowest BIC and AIC. Similar to multi-locus phylogenetic tree, all other parameters were kept constant. Koch’s Postulates Artificial Inoculation of Corn and Soybean Plants Seeds of the C. zeae-maydis susceptible corn hybrid ‘B73’ and soybean variety ‘Sloan’ were planted and cultivated in the greenhouse at 22°C ± 2°C under a 14 h photoperiod. A pathogenicity test was conducted using two isolates each of C. cf. flagellaris, C. kikuchii, Cercospora sp. M, Cercospora sp. T, one isolate of Cercospora sp. Q, one isolate of C. zeae- maydis as a positive control and sterile water as negative control (Table 3.2). Isolates from long- term storage were grown on V8 medium prepared as mentioned above for at least 14 days to induce sporulation. Conidial suspensions from all isolates were prepared on the day of inoculation by flooding the culture with 10 mL sterile distilled water, scrapping off with a sterile 43 glass rod, and filtered through sterile double layered cheesecloth to filter out the mycelia. The conidial suspensions were enumerated using a hemocytometer and adjusted to 1 x 105 conidia/mL. Tween 20 (0.01%) was added to the conidial suspensions to aid inoculation of conidia on corn and soybean leaves. Table 3.2. Cercospora spp. isolates used in artificial inoculation of corn and soybean. Sample Number 1 2 3 4 5 6 7 8 9 10 11 Isolate Name Speciesa GLS_20_6 C. cf. flagellaris GLS_21_168 C. cf. flagellaris GLS_21_238A C. kikuchii GLS_21_254 C. kikuchii Czm_21_154 Cercospora sp. Q Czm_21_134 Cercospora sp. T GLS_21_256A Cercospora sp. T GLS_21_256B Cercospora sp. T GLS_21_256 Cercospora sp. M GLS_21_261B Cercospora sp. M Czm_20_77 C. zeae-maydis Year Collected 2020 2021 2021 2021 2021 2021 2021 2021 2021 2021 2020 Sample Locationb IN IN VA PA VA VA VA VA VA VA MD aSpecies as determined by multilocus phylogenetic tree in this study from Figure 3.3. C. zeae- maydis served as positive control. bLocations: IN = Indiana, MD = Maryland, PA = Pennsylvania, and VA = Virginia. When corn plants reached V3 (three visible collar leaves) growth stage and soybean reached V2 (second trifoliate) growth stage, 21 days after planting, 1 x 105 conidia/mL suspension of each isolate including the C. zeae-maydis as positive control were sprayed on three replicates of the whole plant of each crop type until run-off. For negative control plants, leaves were similarly sprayed with sterile distilled water to the point of run-off. Inoculated plants were bagged for 48 hours to maintain leaf wetness. Afterwards, the inoculated plants were transferred to a misting chamber in the greenhouse and misted over night for 3 seconds every 4 minutes between 10 PM and 10 AM to allow lesions to sporulate faster (Beckman and Payne 1983). Plants were observed daily and after 14 days post inoculation, plants were checked for typical 44 symptoms of GLS on corn as described by Latterell and Rossi (1983) and Cercospora leaf blight (CLB) on soybean as described by Walters (1980). Observed lesions were reisolated using the same method previously described above, compared morphologically and sequenced using CAL and ACT primer sets described in Table 3.1 to confirm pathogenicity and the completion of Koch’s postulates. Fungicide Sensitivity Testing Out of 448 isolates, subsets of 340 isolates were tested for fungicide sensitivity against flutriafol. All isolates were obtained from commercial fields and field research plots with various fungicide history applications in 2020 and 2021. Isolates were chosen based on geographical location and species, representing the sampling performed in 17 states in the United States and Ontario, Canada mentioned in Isolates Collection in the Method section. In total, 253 isolates of C. zeae-maydis, 77 isolates of C. cf. flagellaris, four isolates of C. kikuchii, three isolates of Cercospora sp. T, two isolates of Cercospora sp. M and one isolate of Cercospora sp. Q were tested. Isolates were removed from long-term storage and placed on V8 medium as prepared above. The plates were incubated for 7 to 10 days at ambient room temperature (21°C ± 2°C) before using them for fungicide sensitivity testing. The technical-grade formulation of flutriafol fungicide (20.9% a.i.; Xyway LFR, FMC Corporation, Philadelphia, PA) was used to prepare a stock solution of 100,000 µg/ml in acetone. Serial dilutions in acetone were prepared to a final concentration of 0.01, 0.1, 0.5, 1, 2.5, 5, 10, and 20 µg/ml in the assay plates. Clarified V8 agar was prepared similarly as V8 medium mentioned above by centrifuging the solution at 3,000 x g for 10 minutes to remove solids from solution and decanting off the clarified V8 juice. Clarified V8 medium was cooled down to 50°C before amended with a serially diluted flutriafol. A 45 control plate was also included in each trial by amending the plate with 0.1% acetone (equal to the amount of solvent in the fungicide concentration). Methods for all fungicide sensitivity testing were adapted with some adjustment as below from Proffer et al. (2006). Mycelial plugs of 1 mm were cut using an autoclaved 2 mL glass Pasteur pipette tip to ensure a uniform mycelial plug size. The mycelial plugs were transferred mycelia side down to the flutriafol-amended medium in 100 mm x 15 mm Petri plates. Due to slow growth of C. zeae-maydis, a single plate was used to test 10 isolates at a time to each flutriafol concentration with two replicates. For all other Cercospora spp., four isolates were tested on a single plate due to faster growth rates of the fungi. After 14 days of incubation at ambient room temperature (21°C ± 2°C) alternating dark and light (Latterell and Rossi 1983), the plates were examined for colony growth and the minimum inhibitory concentration (MIC) of the fungicide required to completely inhibit growth of both replicates was estimated. In addition, the mycelial growth was also measured after 14 days of inoculation in two perpendicular directions using a digital caliper (Absolute Digimatic Caliper, model CD-6” AX, Mitutoyo Corp., Sakado 1-Chome, Japan). Relative growth was calculated on the same day as MIC values recorded. Relative growth was calculated by dividing the average radial growth on the amended media by the average growth on the control non-amended for each concentration and isolate. EC50 values, the effective concentration to reduce growth by 50%, were calculated by averaging the colony diameter between two replicates and subtracting 1 mm of mycelial plugs to obtain the average colony area. The trial was separated into 8 runs with 40 to 48 isolates tested for each trial. To ensure reproducibility of this experiment, a total of 46 isolates were chosen randomly and retested using the same procedure as mentioned above. 46 Data Analyses All data analyses were conducted in R v 4.1.2 (R Core Team, 2021). The R code for model selection was adapted from Breunig (2021). The R package ‘drc’ was used to select the best-fitting nonlinear dose-response curve model (Ritz et al. 2015). The tested nonlinear models include the three-parameter log-logistic model (LL.3), the four-parameter log-logistic model (LL.4), the four-parameter Weibull models (W2.4), and the Brain-Cousens hormesis models (BC.4) (Noel et al. 2018; Wang et al. 2017). Briefly, LL.3 was chosen to calculate dose response curve and EC50 value as it best fit the greatest population of the assay which was determined from the lowest AIC value. For the reproducibility dataset, Wilcoxon signed-rank test was used to check if samples differ significantly between the original dataset and reproducibility dataset. The MIC, absolute mean EC50 value, and percent relative growth at 0.5 and 1 µg/ml were plotted and visualized using ‘ggplot2’ package (Wickham, 2016). Data for mean EC50 estimation based on species were subjected to ANOVA (analysis of variance) using 'lm’ method and mean separation determined with least square means difference using ‘emmeans’ (Russell, 2022) at α=0.05. All code for data analyses can be found publicly on https://github.com/triplenza/identification-of-cercospora-and-fungicide-assay. Identification of species isolated from corn Results In 2020, 154 isolates were collected from leaf lesions on corn, and an additional 294 isolates were collected in 2021. In total, 448 isolates were recovered from 17 states across the United States including Alabama, Delaware, Illinois, Indiana, Iowa, Kansas, Kentucky, Maryland, Michigan, Nebraska, New Jersey, New York, Ohio, Pennsylvania, Tennessee, Virginia, and Ontario, Canada (Figure 3.2, Table S.3.1). Species were identified using ITS or 47 CAL gene loci as described in Table 3.1 for slow-growing isolates and using multi-locus phylogenetic analyses for faster-growing isolates. The slow-growing isolates were determined to be C. zeae-maydis with 99% and 91% bootstrap support for 2020 and 2021 isolates respectively (Figure S.3.1, Figure S.3.2). C. zeae-maydis were abundant in corn samples, representing 80.6% of total isolates with 361 isolates. Figure 3.2. Map of isolates recovered across the United States and Canada in this study. A total of 448 isolates across recovering six species with color depicting different species from 17 states were recovered from this study. Number under the individual pie chart indicates the total number of isolates found each state. For Cercospora spp. other than C. zeae-maydis, a multi-locus phylogenetic tree was constructed. The concatenated alignment contained 204 taxa including the outgroup taxon of Septoria provencialis (isolate CPC 12226) with 434, 237, 287, 354, and 205 bp used in the ITS, 48 EF1, CAL, HIS, and ACT, respectively. The phylogenetic tree for individual locus; ITS, EF1, CAL, HIS, and ACT were also shown in Figure S.3.3, S.3.4, S.3.5, S.3.6, and S.3.7 respectively. The concatenated sequences of all five loci were 1509 bp long including alignment gaps. Based on the phylogenetic tree, five species were found in addition to C. zeae-maydis including; C. cf. flagellaris, C. kikuchii, Cercospora sp. M, Cercospora sp. Q, and Cercospora sp. T (Figure 3.3). The resulting phylogenetic tree showed that 77 isolates nested within the C. cf. flagellaris clade of the reference isolates with 80% bootstrap support. C. cf. flagellaris isolates were found in 12 out of 17 states which included Delaware, Illinois, Indiana, Iowa, Maryland, Michigan, Nebraska, New Jersey, Ohio, Pennsylvania, Tennessee, and Virginia representing 17.2% of total isolates. Additional Cercospora spp. were found at a low level, including C. kikuchii (n=4), Cercospora sp. M (n=2), Cercospora sp. Q (n=1), and Cercospora sp. T (n=3). The majority of these isolates were recovered in Virginia except for two isolates of C. kikuchii that was recovered in Maryland and Pennsylvania. 49 Figure 3.3. Multilocus phylogenetic tree constructed using Hasegawa-Kishino-Yano (HKY) + I + G with inverse gamma-distributed rates DNA model of Cercospora spp. on corn from concatenated alignment of ITS, EF1, CAL, HIS, and ACT. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated with MEGA v.11.0.13. Number for each branch indicates bootstrap support and bootstrap values lower than 50% were condensed. Isolates collected and sequenced in this study are highlighted and bold in red. C. cf. flagellaris branch were condensed for viewing purpose. The tree was rooted to Septoria provencialis (isolate CBS 113265). 50 Figure 3.3. (cont’d) 51 Figure 3.3. (cont’d) 52 Figure 3.3. (cont’d) 53 Koch’s Postulates Artificial Inoculation of Corn and Soybean Plants Typical symptoms of GLS were observed for the positive control of C. zeae-maydis on corn plants after 12 to 14 days post inoculation (Figure 3.4 (A)). The negative control of water remained free of symptoms. No symptoms were observed on soybean plants sprayed with C. zeae-maydis isolates. C. cf. flagellaris, C. kikuchii, Cercospora sp. M, Cercospora sp. Q, and Cercospora sp. T did not cause any symptoms on corn. However, on soybean plants, typical symptoms of CLB were observed on plants sprayed with C. cf. flagellaris, C. kikuchii and Cercospora sp. Q which resulted in a speck lesion on trifoliate leaves 12 days post inoculation (Figure 3.4 (B-D)). Conidia were reisolated from the leaf lesions as mentioned above and were verified by sequencing CAL and ACT genes confirming the completion of Koch’s postulates (data not shown) as these two loci could distinguish all six isolates presented in our study (Bakhshi et al. 2015; Groenewald et al. 2013). Purple seed stain symptoms were not observed in this study because observations were taken prior to reproductive growth stages of soybean when seeds begin to develop (R2). 54 Figure 3.4. Leaves inoculated with 1x105 conidia/mL of (A) C. zeae-maydis on corn, (B-D) C. cf. flagellaris, C. kikuchii, and Cercospora sp. Q on soybean 14 days after inoculation in the greenhouse. 55 Fungicide Sensitivity Testing The Cercospora spp. fungicide sensitivity assay on flutriafol was conducted determining MIC estimation, percent relative growth, and absolute mean EC50 estimation. Using Wilcoxon signed-rank test to compare between actual datasets and reproducibility replicates, the two datasets were not statistically significant demonstrating reproducibility of this assay. Based on the MIC estimation, all C. zeae-maydis isolates had a low MIC value which fell in the range between 1 to 10 µg/mL with a mean of 2.5 µg/mL representing 149 out of 253 isolates, while all other Cercospora spp. were at 20 or >20 µg/mL (Figure 3.5). A MIC value >20 µg/mL indicates that these isolates were not inhibited at the highest concentration tested. The actual MIC value for 78 isolates of Cercospora spp. could not be determined due to the value exceeding the highest concentration tested at 20 µg/mL. 56 Figure 3.5. Minimum Inhibitory Concentration (MIC), flutriafol concentration (µg/mL) required to completely inhibit colony growth based on six species of Cercospora (N=340). Flutriafol concentration (µg/mL) >20 indicates that the isolate was not inhibited at the highest concentration tested. Bar color represents Cercospora species. Based on the lowest AIC values, the LL.3 model was chosen as the best fitting model for 50% of the isolates, the remaining isolates 24%, 20%, and 5% of the isolates best fitted with BC.4, W2.4, and LL.4 model respectively. However, for parsimonious results, the LL.3 model was used consistently to calculate percent relative growth and EC50 values estimation. From the 340 isolates of Cercospora spp., average percent relative growth for each species was calculated separately using LL.3 model. Based on the average growth curve results (Figure 3.6), the dose response curve was most informative at 0.5, 1, and 2.5 µg/mL of flutriafol concentration with greatest separation between the curves for C. zeae-maydis compared to other Cercospora spp. 57 The average relative growth showed that C. zeae-maydis had a 50% growth at approximately in between 0.1 and 0.5 µg/mL while the remaining Cercospora spp. ranging from 1 to 10 µg/mL. Thus, 0.5 and 1 µg/mL were used for informative dose response as visualized in Figure 3.7. Hormetic effect was observed at 0.5 µg/ml flutriafol concentration where isolates on amended- medium grew 0.2x faster than non-amended medium (Figure 3.7). Comparisons between species for relative growth in response to flutriafol at 0.5 ug/mL were conducted using ANOVA where it showed species as an informative factor in affecting relative growth. Cercospora zeae-maydis was significantly sensitive (P < 0.0001) to flutriafol compared to C. cf. flagellaris, Cercospora sp. M, and Cercospora sp. T, while C. kikuchii is significantly less sensitive (P < 0.0001) to flutriafol compared to C. zeae-maydis. Figure 3.6. Average growth curve of Cercospora spp. relative to the control plates using LL. 3 (three-parameter log-logistic) model response curve. Each line represents a different species of Cercospora (N=340). 58 Figure 3.7. Distribution of mean relative growth of Cercospora spp. at 0.5 and 1 µg/mL relative to the control plates using LL. 3 (three-parameter log-logistic) model response curve. Each color represents a different species of Cercospora (N=340). The absolute mean EC50 estimates were determined using a mycelial growth assay amended with flutriafol fungicides (Table 3.3). The EC50 values for C. zeae-maydis ranged between 0.016 to 1.020 µg/mL, with the mean and median values of 0.346 and 0.322 µg/mL respectively. The EC50 values for C. cf. flagellaris ranged from 0.165 to 4.210 µg/mL and the mean and median values were 1.220 and 0.952 µg/mL respectively. C. kikuchii had significantly greater EC50 values compared to all species ranging between 1.26 to 13.9 µg/mL and the mean and median values were 7.14 and 6.72 µg/mL respectively. All Cercospora spp. had EC50 values lower than 5 µg/mL except for C. kikuchii (Figure 3.8). 59 Table 3.3. Mean EC50 estimates of six species of Cercospora isolated from corn on flutriafol based on LL. 3 (three-parameter log-logistic) model. Number of isolates tested Number of isolates collected 77 4 361 2 1 3 Species C. cf. flagellaris C. kikuchii C. zeae-maydis Cercospora sp. M Cercospora sp. Q Cercospora sp. T aMeans followed by same letter are not significantly different as determined by least square means comparison (α=0.05). EC₅₀ ± SEa 1.25 ± 0.10 7.14 ± 2.60 0.35 ± 0.01 2.48 ± 0.11 1.81 2.24 ± 0.68 Percent of isolates tested 100% 100% 70% 100% 100% 100% 77 4 253 2 1 3 b d a c bc c Figure 3.8. Absolute mean EC50 estimation (µg/mL) calculated using (three-parameter log- logistic) LL.3 model of six Cercospora spp. represented by different colors (N=340). 60 Discussion The collection of 448 Cercospora spp. isolates from across the United States and Ontario, Canada in 2020 and 2021 allowed us to investigate the species diversity of Cercospora colonizing corn. According to Lipps 1998, GLS is a major concern since 1960 in the eastern United States and since then have cause a major risk in Illinois, Indiana, Iowa, Kentucky, Missouri, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia, and West Virginia. However, GLS already become a major concern in all corn producing states (Mueller et al. 2015; Mueller et al. 2020). C. zeae-maydis and C. zeina are the known causal agents of GLS on corn as described by Crous et al. (2006). However, in our study, only C. zeae- maydis was found in abundance across the United States and Ontario, Canada. No C. zeina was isolated, although we also sampled from the eastern United States where C. zeina was found previously (Hsieh Lin-si 2011; Swart et al. 2017; Wang et al. 1998). This provides evidence that C. zeae-maydis is the more common pathogen causing GLS in the United States and Ontario, Canada. This finding is supported by other literature where C. zeae-maydis is mostly found in the United States while C. zeina is the causal agent of GLS in the southern Africa (Crous et al. 2006; Dunkle and Levy 2000; Meisel et al. 2009). However, Okori et al. (2003) also found C. zeina in 5 out of 9 isolates sampled from Indiana, New York, North Carolina, Ohio, and Virginia. According to Crous et al. (2006), C. zeina can be identified by its slower growth rate in culture measuring 10 – 15 mm in diameter of three weeks of growth compared to C. zeae-maydis (15 – 25 mm). Due to the slower growth rate of this species, it might be possible that C. zeina was overlooked during isolation process. Thus, C. zeina may be found in the United States if extensive sampling were conducted in the area where C. zeina was previously reported. 61 Although no C. zeina was found, other Cercospora spp. (C. cf. flagellaris, C. kikuchii, Cercospora sp. Q, and Cercospora sp. M) were recovered (Figure 3.3, Table 3.4) which are reported to be pathogenic to soybean causing CLB and purple seed stain (Albu et al. 2016; Guillin et al. 2017; Jones 1959; Sautua et al. 2020a). The presence of C. cf. flagellaris was foreseeable since this species has a broad host range, infecting soybean (Glycine max L.) (Albu et al. 2016), hemp (Cannabis sativa) (Marin et al. 2020), table beet (Beta vulgaris) (Vaghefi et al. 2017; 2018), okra in China (Abelmoschus esculentus) (Chai et al. 2021) and melon (Cucumis melo L.) in Korea (Park et al. 2020). Cercospora cf. flagellaris was found in 12 out of 17 states, indicating a widespread dispersal of this species across the country. Cercospora sp. M was also reported in Thailand on banana (Musa sp.) (Groenewald et al. 2013), while Cercospora sp. T was only reported in Iran on coreopsis (Coreopsis sp.) (Bakhshi et al. 2015). Cercospora sp. M and Cercospora sp. T have never been reported in the United States prior to this study. Summary of host-fungus reported in this study and other literature were documented in Table 3.4. In this study, the presence of Cercospora sp. M, Cercospora sp. Q and Cercospora sp. T on corn were found in Virginia at different sites suggesting that these species may be found widely in Virginia in the future with extensive sampling. The presence of variety Cercospora spp. at Virginia possibly due to difference crop practice, although the reason remains unclear. This is the first report of C. cf. flagellaris, C. kikuchii, Cercospora sp. M, Cercospora sp. Q, and Cercospora sp. T associated with corn in the United States. 62 Table 3.4. Documented hosts of Cercospora spp. recovered in this study. Species C. cf. flagellaris Host Glycine maxL. Cannabis sativa Common Namesa Soybean Hemp Reference Albu et al. 2016 Marin et al. 2020 Vaghefi et al. 2017; 2018 Chai et al. 2021 Park et al. 2020 (This study) Johnson & Jones 1962 Jones 1959 (This study) Tehon and Daniels 1925 Groenewald et al. 2013 Table beet Beta vulgaris Abelmoschus esculentus Okra (China) Cucumis melo L. Zea mays L. Cyamopsis tetragonoloba Cluster beans Glycine maxL. Zea mays L. Melon (Korea) Corn Soybean Corn Zea mays L. Musa sp. Glycine maxL. Zea mays L. Humulus lupulus Glycine maxL. Zea mays L. Coreopsis sp. Zea mays L. Corn Banana (Thailand) Soybean (Argentina) Sautua et al. 2020a (This study) Corn Hop (Brazil) Pereira et al. 2022 Soybean (Argentina) Guillin et al. 2017 Corn Calliopsis (Iran) Corn (This study) Bakhshi et al. 2015 (This study) C. kikuchii C. zeae-maydis C. sp. M C. sp. Q C. sp. T aHost reported other than in the United States is in bracket. The artificial inoculation of Cercospora isolates on corn (Table 3.2) in this study showed that these species were not pathogenic on corn except C. zeae-maydis. The presence of these isolates on corn during initial fungal isolation showed that these pathogens may be present due to common practice of soybean-corn rotation to increase crop yield (Edwards et al. 1988; Lund et al. 1993; Porter et al. 1997). This showed that other Cercospora spp. in this study except C. zeae- maydis may colonize but not infect corn. By completing Koch’s postulates, C. zeae-maydis was verified to be as the primary causal agent of GLS and other Cercospora spp. were not pathogenic to corn. However, this might be due to the shortcomings of the Koch’s postulates conducted. This is due to artificial inoculation of Cercospora spp. in the greenhouse being challenging as a 63 result of the long latent period of this genus (Meisel et al. 2009; Sautua et al. 2020a; Sautua et al. 2020b) especially C. zeae-maydis where symptoms can be observed visually after 9 to 19 days with high relative humidity (Beckman and Payne 1982; Ringer and Grybauskat 1995). Future studies should be conducted to identify the Cercospora spp. distribution that can colonize or infect corn across the United States by varying the optimal humidity and temperature for Cercospora spp. to develop. The pathogenicity test in this study included soybean to serve as a positive check. This is because C. cf. flagellaris, C. kikuchii, Cercospora sp. Q, and Cercospora sp. M have been reported in the literature to infect soybean causing CLB and purple seed stain (Albu et al. 2016; Guillin et al. 2017; Jones 1959; Sautua et al. 2020a; Soares et al. 2015). Other Cercospora spp. were also reported to cause CLB and purple seed stain including C. cf. nicotianae and C. cf. sigesbeckiae (Albu et al. 2016; Sautua et al. 2020b). In this study, C. cf. flagellaris, C. kikuchii, and Cercospora sp. Q were found to infect soybean which is supported by previous studies (Albu et al. 2016; Guillin et al. 2017; Jones 1959). However, plants inoculated with Cercospora sp. M did not show symptoms of CLB in this study. This contrasts with Sautua et al. (2020a) where the study reported Cercospora sp. M as one of the causal agents of CLB, although it is weakly supported with bootstrap value less than 50%. The shortcoming of this study is the scarcity of other Cercospora spp. isolates which were found in the United States. Cercospora sp. M and Cercospora sp. T were not shown to colonize or infect on either corn or soybean in this study. Another main objective of this study was to determine the flutriafol sensitivity of Cercospora spp. isolated from corn. All methods showed that C. zeae-maydis was sensitive to flutriafol. Using the MIC estimation, C. zeae-maydis and the other Cercospora spp. had different MIC values likely due to the other Cercospora spp. being less sensitive compared to C. zeae- 64 maydis to flutriafol. MIC estimation is usually used to determine a quantitative measure of mycelial growth response for slow growing fungi such as Blumeriella jaapii and Rhynchosporium secalis (Kendall et al. 1993; Outwater et al. 2019; Proffer et al. 2006; Proffer et al, 2013). Thus, MIC method is more suitable for fungicide sensitivity testing on slower-growing fungi such as C. zeae-maydis. More concentration of fungicide is needed to be tested on faster- growing fungi if MIC method is chosen to test for fungicide sensitivity. The average percent relative growth indicates that at 10 µg/mL, there is no growth for C. zeae-maydis similar to the MIC recorded which showed this species being sensitive to flutriafol. The average percent relative growth in Figure 3.6 is informative at 0.5 and 1 µg/mL as it had the greatest variation in values for all Cercospora spp. tested. Thus, this concentration can be used for discriminatory doses to determine EC50 estimations. Discriminatory dose for screening can be helpful to screen a huge collection of isolate as it is less labor intensive. Average percent relative growth is also important to differentiate growth versus no growth at a certain concentration. The low EC50 values for C. zeae-maydis showed that this species was sensitive towards flutriafol. This indicates that flutriafol can be used to manage GLS on corn. Similar to Zhang et al. 2021, EC50 values for C. sojina collected from 2007 to 2012 exposed to flutriafol ranged from 0.106 to 0.643 µg/mL and no shift was detected compared to their baseline study prior to 2001. In another study, all Cercospora spp. isolates tested in Argentina were sensitive to DMI fungicides including difenoconazole, prothioconazole, epoxiconazole, tebuconazole, and cyproconazole (Sautua et al. 2020a). However, monitoring fungicide sensitivity of flutriafol over time in C. zeae-maydis populations should be conducted to monitor for sensitivity shifts. Future studies should also be performed to evaluate cross-resistance across DMI fungicides on GLS (Ward et al. 1997a). 65 In Figure 3.7, hormetic effect was observed at lower concentration of flutriafol where amended medium grown isolates grew faster than on non-amended medium. Five isolates exhibited hormesis at 0.5 µg/mL flutriafol concentration which indicated an EC50 above 0.5 µg/mL. Hormesis was also reported in Fusarium virguliforme tested against fluopyram at 0.5 and 1 µg/mL of fungicide concentration (Wang et al. 2017). The hormetic effect in the lower concentration of fungicide indicates an increased disease severity by pathogens in the field (Garzon et al. 2011; Pradhan et al. 2017). Additional studies should be conducted in the greenhouse or in the field to compare the efficacy of flutriafol on isolates that demonstrate hormesis and isolates that do not show hormesis. In this study, EC50 estimation was significantly higher than C. zeae-maydis for C. kikuchii on flutriafol indicating less sensitive isolate. Difference in sensitivity for C. kikuchii were potentially due to this species had been exposed to flutriafol. Price et al. (2013) also suggested a possible shift in flutriafol sensitivity and other DMI fungicides for C. kikuchii isolates due to reduced sensitivity observed from 2011 and 2012 isolates compared to their baseline study in 2000, with EC50 values ranging between 0.009 to 0.906 µg/ml and 0.130 to 5.480 µg/ml respectively. Resistance was also detected in 2011 to 2013 to QoI and MBC fungicides for C. kikuchii isolates (Price et al. 2013). These studies suggest that C. kikuchii might have shifted in sensitivity to flutriafol compared to the study conducted by Price et al. 2013. Reduction in flutriafol sensitivity over time may indicate resistance development in C. kikuchii populations is possible in the future. Aside from in vitro studies, fungicide sensitivity in field trials should also be conducted to compare the efficacy of flutriafol between in vitro and in vivo. The findings from this study will allow for a better understanding of Cercospora spp. diversity on corn for effective disease 66 management such as rotation with non-host crops and application of fungicides to control disease. Although, this study has resulted in additional questions such as the role of corn in C. cf. flagellaris epidemiology and infection of subsequent soybean crops. This study also explores the effectiveness of flutriafol in disease management of GLS on corn and allows for future monitoring of shifts in fungicide sensitivity of Cercospora spp. over time. 67 CHAPTER 4: CONCLUSIONS AND IMPACTS 68 Conclusions Gray leaf spot (GLS) continues to be a significant foliar disease of corn in the United States and occurring worldwide. GLS is caused by two Cercospora spp. namely C. zeae-maydis and C. zeina, however, population composition of Cercospora spp. causing GLS is not known in the United States and Ontario, Canada. Therefore, the research in this thesis focused on a geographically broad sampling of Cercospora spp. to identify species infecting corn and establishing baseline sensitivity of flutriafol of Cercospora spp. on corn throughout the United States and Ontario, Canada. The morphology of different Cercospora spp. from corn can be hard to distinguish from each other. Sequencing on internal transcribe spacer (ITS) including 5.8S nrDNA alone is inadequate to distinguish certain species of Cercospora. Thus, multi-locus genotyping namely ITS, elongation factor 1-α (EF1), calmodulin (CAL), histone H3 (HIS), and actin (ACT) genes was performed to discriminate Cercospora spp. present on corn. Based on these five loci, six species were identified: C. cf. flagellaris (n=77), C. kikuchii (n=4), C. zeae-maydis (n=361), Cercospora sp. M (n=2), Cercospora sp. Q (n=1) and Cercospora sp. T (n=3). Although C. zeina was one of the Cercospora species previously reported to cause GLS in the U.S., no C. zeina was isolated in this study. Pathogenicity assays were conducted for all six species and only C. zeae- maydis was observed to cause disease on corn while on soybean, C. cf. flagellaris, C. kikuchii, and Cercospora sp. Q resulted in Cercospora leaf blight symptoms. Chemical management is a common management practice in controlling foliar diseases of corn such as GLS. However, the repeated and widespread use of fungicides with moderate to high-risk for resistance development can select for resistant individuals in the population and can potentially reduce the effectiveness of the fungicide within a few years of introduction. A new 69 demethylation inhibitor (DMI) fungicide, flutriafol (Xyway Liquid Fertilizer Ready; FMC Corporation, Philadelphia, PA) has received Environmental Protection Agency registration in 2020 for foliar disease protection of corn for GLS. Flutriafol was tested for its mobility in corn plants and found in every plant part tested including stalks, roots, and leaves. This fungicide has a long half-life, 1,358 days, thus does not break down quickly and can potentially persist longer in the plant and the environment. Baseline sensitivity of flutriafol was also conducted on the Cercospora spp. isolated from corn in the United States and Ontario, Canada. The EC50 values for C. zeae-maydis ranged between 0.016 to 1.020 µg/mL, with the mean and median values of 0.346 and 0.322 µg/mL respectively. All Cercospora spp. had EC50 values lower than 5 µg/mL except for C. kikuchii (< 13.9 µg/mL) which showed that Cercospora spp. were sensitive to flutriafol. The EC50 values of baseline flutriafol fungicide for Cercospora spp. associated with corn falls below 13.9 µg/mL while the flutriafol residual detected on corn plants were below 14.6 µg/mL which indicated that flutriafol is a potential fungicide to control growth of Cercospora spp. associated with corn. In conclusion, these works provide a list of Cercospora spp. that can be recovered from and causing disease on corn in the United States and Ontario, Canada. In addition, this thesis also provides novel information on the fungicide flutriafol such as in-planta mobility and disease management efficacy in the field of this fungicide. This data will be useful for chemical management of Cercospora spp. associated with corn. Broader Impacts The studies presented in this thesis have an impact on the detection of Cercospora spp. associated with corn and flutriafol efficacy in the United States and Ontario, Canada. This is important for plant disease management and plant breeding of corn in the United States and 70 Ontario, Canada. In chapter 2, flutriafol mobility and control of disease in corn was validated in the field at Lansing, Michigan. Chapter 3 involved detection of Cercospora spp. recovered from typical GLS symptoms on corn, evaluation of pathogenicity of the recovered Cercospora spp. on corn and soybean plants, and establishment of flutriafol baseline sensitivities for Cercospora spp. associated with corn. Of the six Cercospora spp. recovered from corn, we found that only C. zeae-maydis was able to cause GLS symptoms on corn. However, this project has resulted in additional questions such as the role of corn in C. cf. flagellaris, C. kikuchii, and Cercospora sp. Q epidemiology and infection of subsequent soybean crops. 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Mean of flutriafol quantification on corn for all plant parts each year APPENDIX 2019 2020 2021 UTC IF UTC IF 2x2 L UTC IF 2x2 0x0 Year Fungicide Treatmenta Stalkb Root E+8 E+7 E+6 E+5 E+4 E+3 E+2 E+1 E E-1 E-2 E-3 E-4 E-5 E-6 E-7 Meanc ND ND - - ND ND ND ND ND ND ND ND ND ND ND ND ND ND - 0.078 0.467 - - 0.290 0.331 0.178 0.482 0.396 1.481 1.081 1.213 0.792 0.272 0.498 0.267 0.246 0.381 0.528 - - ND 0.012 0.015 0.010 ND 0.027 0.010 0.013 ND 0.166 ND 0.064 0.201 0.155 ND 0.042 0.047 0.155 ND 0.010 0.083 0.034 ND 0.014 0.025 0.038 ND 0.017 0.042 0.039 ND 0.016 0.019 0.100 ND 0.011 0.049 0.022 ND 0.029 0.021 0.028 ND 0.034 0.029 0.028 ND 0.022 0.039 0.025 ND 0.026 0.019 0.017 ND 0.024 0.018 0.010 ND 0.012 0.056 0.028 ND 0.016 0.035 0.024 - - - - - ND ND - 1.747 0.433 5.762 3.773 0.604 5.589 - - - 0.100 4.649 5.897 9.945 0.058 1.840 5.203 4.541 0.053 1.109 2.746 4.901 0.090 1.752 3.642 12.502 0.868 0.256 4.476 6.078 0.258 1.409 3.809 8.673 0.096 0.784 4.716 9.036 0.000 0.980 3.934 5.127 0.199 0.991 2.027 9.144 0.209 0.337 1.935 12.716 0.130 0.423 2.000 14.607 1.139 3.067 9.549 ND 1.758 2.346 11.834 ND - - - - - - - - 0.032 0.044 0.045 0.187 1.53 3.122 8.667 aFungicide treatment abbreviation is as followed: UTC = Untreated check, IF = Xyway in- furrow, 2x2 = Xyway 2x2, 0x0 = Xyway 0x0, and L = Lucento. bFlutriafol quantification on plant parts relative to the ear leaf: E = ear leaf, E-1 = one leaf below ear leaf, E+1 = one leaf above ear leaf, - = no quantification, ND = below level of detection (0.003 µg/mL) cMean for each fungicide treatments each year 81 Table S.2.2. Disease severity index (DIX) values of gray leaf spot (GLS) and northern corn leaf blight (NCLB) on three trial dates recorded in Table 2.1 at ear leaf and another additional leaf on each date for different fungicide treatments on corn crop from 2019 to 2021 growing season. Disease GLS Fungicide Treatmenta First Rating Second Rating Third Rating Year 2019 2020 2021 UTC IF p-valued UTC IF 2x2 p-value UTC L p-value UTC IF 2x2 0x0 p-value Meanb E-2c 0.53 0.08 0.0152 b a Mean E 0.15 0.05 0.0498 b a Mean E-2 0.60 0.28 0.0407 b a Mean E 0.15 0.10 NS E-3 0.13 0.03 0.23 NS 0.27 0.71 NS E-2 0.13 0.02 0.02 0.04 0.0430 b a a ab E 0.00 0.00 0.00 NS 0.01 0.00 NS E 0.01 0.00 0.00 0.00 NS E-2 0.17 0.16 0.12 NS 0.28 0.11 NS E-1 0.19 0.03 0.06 0.04 0.0184 82 Mean E+2 0.33 0.18 NS E+2 0.08 0.17 0.16 NS 0.14 0.02 NS E 0.08 0.02 0.04 NS 0.05 0.01 NS b a ab a E 0.09 0.02 0.01 0.02 0.0285 E+2 0.15 b 0.13 a 0.22 a ab 0.14 NS Mean E - - E 0.33 0.38 0.20 NS b a 0.37 0.05 0.0224 E 0.38 0.05 0.12 0.12 0.0315 b a ab ab Table S.2.2 (cont’d) NLB Disease 2019 2020 2021 UTC IF p-value UTC IF 2x2 p-value UTC L p-value UTC IF 2x2 0x0 p-value E-2 0.30 0.00 0.0104 b a E-3 0.07 0.00 0.08 NS 0.09 0.03 NS E-2 0.00 0.03 0.03 0.03 NS E 0.08 0.00 NS E 0.00 0.00 0.00 NS 0.00 0.00 NS E 0.00 0.00 0.00 0.00 NS E-2 0.73 0.03 NS E-2 0.04 0.07 0.10 NS 0.75 0.00 NS E-1 0.15 0.05 0.04 0.05 NS E 0.25 0.03 NS E 0.05 0.00 0.01 NS 0.08 0.00 NS E 0.19 0.05 0.01 0.00 NS E+2 1.08 0.95 NS E+2 0.05 0.04 0.03 NS 0.43 0.03 NS E+2 0.19 0.24 0.38 0.67 NS E - - E 0.55 0.38 0.35 NS 0.59 0.01 NS E 0.58 0.08 0.35 0.18 0.0461 b a ab ab aFungicide treatment abbreviations are as followed: UTC = Untreated check, IF = Xyway in-furrow, 2x2 = Xyway 2x2, 0x0 = Xyway 0x0, and L = Lucento. bMean of DIX was calculated as followed: disease incidence multiply by (disease severity/100). Means followed by the same letters within columns are not significantly different as determined by least square means comparison (α=0.05). cFoliar disease ratings are abbreviated as followed: E = ear leaf, E-1 = one leaf below ear leaf, E-2 = two leaves below ear leaf, E-3 = three leaves below ear leaf, E+2 = two leaves above ear leaf, and - = not rated dp-value that is higher than 95% confidence interval (α=0.05) is abbreviated as NS = not significant 83 Table S.3.1. Isolates information of Cercospora spp. from corn in 2020 and 2021 collected in this study. Species C. cf. flagellaris Isolates Name Year Statea GLS_20_6 GLS_20_7 GLS_20_8 GLS_20_11A GLS_20_11B GLS_20_13A GLS_20_13B GLS_20_14 GLS_20_18 GLS_20_20A GLS_20_20B GLS_20_31 GLS_20_32 GLS_20_37A GLS_20_37B GLS_20_38 GLS_20_40A GLS_20_40B GLS_20_44A GLS_20_44B GLS_20_46 GLS_20_62A GLS_20_62B GLS_20_63 GLS_20_64 GLS_20_69 GLS_20_70 GLS_20_72 GLS_20_75 GLS_20_79 GLS_20_81 GLS_20_82 GLS_20_83 GLS_20_89 GLS_20_91 GLS_20_93A GLS_20_93B GLS_20_94A GLS_20_94B IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 IN 2020 2020 IN 2020 NE 2020 NE 2020 IL 2020 MI 2020 OH 2020 OH 2020 MD 2020 IA 2020 TN 2020 TN 2020 IL 2020 TN 2020 TN 2020 TN 2020 NE 2020 NE 2020 MD 2020 MD GenBank Accession Numbersb ITS EF1 ACT CAL HIS OQ732025 OQ774028 OQ773856 OQ773662 OQ773942 OQ732026 OQ774029 OQ773857 OQ773663 OQ773943 OQ732027 OQ774030 OQ773858 OQ773664 OQ773944 OQ732028 OQ774031 OQ773859 OQ773665 OQ773945 OQ732029 OQ774032 OQ773860 OQ773666 OQ773946 OQ732030 OQ774033 OQ773861 OQ773667 OQ773947 OQ732031 OQ774034 OQ773862 OQ773668 OQ773948 OQ732032 OQ774035 OQ773863 OQ773669 OQ773949 OQ732033 OQ774036 OQ773864 OQ773670 OQ773950 OQ732034 OQ774037 OQ773865 OQ773671 OQ773951 OQ732035 OQ774038 OQ773866 OQ773672 OQ773952 OQ732036 OQ774039 OQ773867 OQ773673 OQ773953 OQ732037 OQ774040 OQ773868 OQ773674 OQ773954 OQ732038 OQ774041 OQ773869 OQ773675 OQ773955 OQ732039 OQ774042 OQ773870 OQ773676 OQ773956 OQ732040 OQ774043 OQ773871 OQ773677 OQ773957 OQ732041 OQ774044 OQ773872 OQ773678 OQ773958 OQ732042 OQ774045 OQ773873 OQ773679 OQ773959 OQ732043 OQ774046 OQ773874 OQ773680 OQ773960 OQ732044 OQ774047 OQ773875 OQ773681 OQ773961 OQ732045 OQ774048 OQ773876 OQ773682 OQ773962 OQ732046 OQ774049 OQ773877 OQ773683 OQ773963 OQ732047 OQ774050 OQ773878 OQ773684 OQ773964 OQ732048 OQ774051 OQ773879 OQ773685 OQ773965 OQ732049 OQ774052 OQ773880 OQ773686 OQ773966 OQ732050 OQ774053 OQ773881 OQ773687 OQ732051 OQ774054 OQ773882 OQ773688 OQ773967 OQ732052 OQ774055 OQ773883 OQ773689 OQ773968 OQ732053 OQ774056 OQ773884 OQ773690 OQ773969 OQ732054 OQ774057 OQ773885 OQ773691 OQ773970 OQ732055 OQ774058 OQ773886 OQ773692 OQ773971 OQ732056 OQ774059 OQ773887 OQ773693 OQ773972 OQ732057 OQ774060 OQ773888 OQ773694 OQ773973 OQ732058 OQ774061 OQ773889 OQ773695 OQ773974 OQ732059 OQ774062 OQ773890 OQ773696 OQ773975 OQ732060 OQ774063 OQ773891 OQ773697 OQ773976 OQ732061 OQ774064 OQ773892 OQ773698 OQ773977 OQ732062 OQ774065 OQ773893 OQ773699 OQ773978 OQ732063 OQ774066 OQ773894 OQ773700 OQ773979 - 84 Table S.3.1. (cont'd) 2020 MD GLS_20_95A 2020 MD GLS_20_95B 2020 MD GLS_20_95C 2020 MD GLS_20_98A 2020 MD GLS_20_98B 2020 MD GLS_20_100 2020 NE GLS_20_102 IL GLS_20_109 2020 IN GLS_21_157A 2021 IN GLS_21_157B 2021 IN 2021 GLS_21_162 IN GLS_21_163 2021 IN GLS_21_164A 2021 IN GLS_21_164B 2021 IN 2021 GLS_21_165 IN 2021 GLS_21_168 IN 2021 GLS_21_177 IN 2021 GLS_21_180 IN 2021 GLS_21_200 2021 GLS_21_214 IN IN 2021 GLS_21_218 GLS_21_231A 2021 VA GLS_21_231B 2021 VA GLS_21_231C 2021 VA GLS_21_233A 2021 VA GLS_21_233B 2021 VA GLS_21_238 2021 VA GLS_21_238A 2021 VA GLS_21_238B 2021 VA GLS_21_244A 2021 MD GLS_21_244B 2021 MD GLS_21_245A 2021 MD GLS_21_245B 2021 MD GLS_21_254 2021 PA GLS_21_261A 2021 VA GLS_21_270A 2021 DE GLS_21_270B 2021 DE GLS_21_271A 2021 DE GLS_21_271B 2021 DE GLS_21_271C 2021 DE GLS_21_271D 2021 DE 2021 NE GLS_21_275 GLS_21_256 2021 VA GLS_21_261B 2021 VA OQ732064 OQ774067 OQ773895 OQ773701 OQ773980 OQ732065 OQ774068 OQ773896 OQ773702 OQ773981 OQ732066 OQ774069 OQ773897 OQ773703 OQ773982 OQ732067 OQ774070 OQ773898 OQ773704 OQ773983 OQ732068 OQ774071 OQ773899 OQ773705 OQ773984 OQ732069 OQ774072 OQ773900 OQ773706 OQ773985 OQ732070 OQ774073 OQ773901 OQ773707 OQ773986 OQ732071 OQ774074 OQ773902 OQ773708 OQ773987 OQ732072 OQ774077 OQ773905 OQ773711 OQ773990 OQ732073 OQ774078 OQ773906 OQ773712 OQ773991 OQ732074 OQ774079 OQ773907 OQ773713 OQ773992 OQ732075 OQ774080 OQ773908 OQ773714 OQ773993 OQ732076 OQ774081 OQ773909 OQ773715 OQ773994 OQ732077 OQ774082 OQ773910 OQ773716 OQ773995 OQ732078 OQ774083 OQ773911 OQ773717 OQ773996 OQ732079 OQ774084 OQ773718 OQ773997 - OQ732080 OQ774085 OQ773912 OQ773719 OQ773998 OQ732081 OQ774086 OQ773913 OQ773720 OQ773999 OQ732082 OQ774087 OQ773914 OQ773721 OQ774000 OQ732083 OQ774088 OQ773915 OQ773722 OQ774001 OQ732084 OQ774089 OQ773916 OQ773723 OQ774002 OQ732085 OQ774090 OQ773917 OQ773724 OQ774003 OQ732086 OQ774091 OQ773918 OQ773725 OQ774004 OQ732087 OQ774092 OQ773919 OQ773726 OQ774005 OQ732088 OQ774093 OQ773920 OQ773727 OQ774006 OQ732089 OQ774094 OQ773921 OQ773728 OQ774007 OQ732090 OQ774095 OQ773922 OQ773729 OQ774008 OQ732091 OQ774096 OQ773923 OQ773730 OQ774009 OQ732092 OQ774097 OQ773924 OQ773731 OQ774010 OQ732093 OQ774098 OQ773925 OQ773732 OQ774011 OQ732094 OQ774099 OQ773926 OQ773733 OQ774012 OQ732095 OQ774100 OQ773927 OQ773734 OQ774013 OQ732096 OQ774101 OQ773928 OQ773735 OQ774014 OQ732097 OQ774102 OQ773929 OQ773736 OQ774015 OQ732101 OQ774106 OQ773933 OQ773740 OQ774019 OQ732103 OQ774108 OQ773935 OQ773742 OQ774021 OQ732104 OQ774109 OQ773936 OQ773743 OQ774022 OQ732105 OQ774110 OQ773937 OQ773744 OQ774023 OQ732106 OQ774111 OQ773938 OQ773745 OQ774024 OQ732107 OQ774112 OQ773939 OQ773746 OQ774025 OQ732108 OQ774113 OQ773940 OQ773747 OQ774026 OQ732109 OQ774114 OQ773941 OQ773748 OQ774027 OQ732098 OQ774103 OQ773930 OQ773737 OQ774016 OQ732102 OQ774107 OQ773934 OQ773741 OQ774020 85 C. sp. M Table S.3.1. (cont'd) C. sp. Q C. sp. T C. zeae- maydis 2021 VA Czm_21_154 Czm_21_134 2021 VA GLS_21_256A 2021 VA GLS_21_256B 2021 VA IN Czm_20_1 IN Czm_20_2 IN Czm_20_3 IN Czm_20_4 IN Czm_20_5 IN Czm_20_6 IN Czm_20_7 IN Czm_20_8 IN Czm_20_9 IN Czm_20_10 IN Czm_20_11 IN Czm_20_12 IN Czm_20_13 IN Czm_20_14 IN Czm_20_15 IN Czm_20_16 IN Czm_20_17 IN Czm_20_18 IN Czm_20_19 IN Czm_20_20 IN Czm_20_21 IN Czm_20_22 IN Czm_20_23 IN Czm_20_24 IN Czm_20_25 IN Czm_20_26 IN Czm_20_27 IN Czm_20_28 IN Czm_20_29 IN Czm_20_30 IN Czm_20_31 IN Czm_20_32 IN Czm_20_33 IN Czm_20_34 IN Czm_20_35 IN Czm_20_36 IN Czm_20_37 IN Czm_20_38 IN Czm_20_39 IN Czm_20_40 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 OQ732073 OQ774076 OQ773904 OQ773710 OQ773989 OQ732072 OQ774075 OQ773903 OQ773709 OQ773988 OQ732099 OQ774104 OQ773931 OQ773738 OQ774017 OQ732100 OQ774105 OQ773932 OQ773739 OQ774018 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - OQ773749 OQ773750 OQ773751 OQ773752 OQ773753 OQ773754 OQ773755 OQ773756 OQ773757 OQ773758 OQ773759 OQ773760 OQ773761 OQ773762 OQ773763 OQ773764 OQ773765 OQ773766 OQ773767 OQ773768 OQ773769 OQ773770 OQ773771 OQ773772 OQ773773 OQ773774 OQ773775 OQ773776 OQ773777 OQ773778 OQ773779 OQ773780 OQ773781 OQ773782 OQ773783 OQ773784 OQ773785 OQ773786 OQ773787 OQ773788 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 86 Table S.3.1. (cont'd) Czm_20_41 Czm_20_42 Czm_20_43 Czm_20_44 Czm_20_45 Czm_20_46 Czm_20_47 Czm_20_48 Czm_20_49 Czm_20_50 Czm_20_51 Czm_20_52 Czm_20_53 Czm_20_54 Czm_20_55 Czm_20_56 Czm_20_57 Czm_20_58 Czm_20_59 Czm_20_60 Czm_20_61 Czm_20_62 Czm_20_63 Czm_20_64 Czm_20_65 Czm_20_66 Czm_20_67 Czm_20_68 Czm_20_69 Czm_20_70 Czm_20_71 Czm_20_72 Czm_20_73 Czm_20_74 Czm_20_75 Czm_20_76 Czm_20_77 Czm_20_78 Czm_20_79 Czm_20_80 Czm_20_81 Czm_20_82 Czm_20_83 Czm_20_84 IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 MD 2020 MD 2020 MD 2020 MD 2020 MD 2020 MD 2020 MD 2020 MD 2020 MD 2020 MD 2020 PA 2020 PA 2020 PA - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 87 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - OQ773789 OQ773790 OQ773791 OQ773792 OQ773793 OQ773794 OQ773795 OQ773796 OQ773797 OQ773798 OQ773799 OQ773800 OQ773801 OQ773802 OQ773803 OQ773804 OQ773805 OQ773806 OQ773807 OQ773808 OQ773809 OQ773810 OQ773811 OQ773812 OQ773813 OQ773814 OQ773815 OQ773816 OQ773817 OQ773818 OQ773819 OQ773820 OQ773821 OQ773822 OQ773823 OQ773824 OQ773825 OQ773826 OQ773827 OQ773828 OQ773829 OQ773830 OQ773831 OQ773832 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table S.3.1. (cont'd) Czm_20_85 Czm_20_86 Czm_20_87 Czm_20_88 Czm_20_89 Czm_20_90 Czm_20_91 Czm_20_92 Czm_20_93 Czm_20_94 Czm_20_95 Czm_20_96 Czm_20_97 Czm_20_98 Czm_20_99 Czm_20_100 Czm_20_101 Czm_20_102 Czm_20_103 Czm_20_104 Czm_20_105 Czm_20_106 Czm_20_107 Czm_21_1 Czm_21_2 Czm_21_3 Czm_21_4 Czm_21_5 Czm_21_6 Czm_21_7 Czm_21_8 Czm_21_9 Czm_21_10 Czm_21_11 Czm_21_12 Czm_21_13 Czm_21_14 Czm_21_15 Czm_21_16 Czm_21_17 Czm_21_18 Czm_21_19 Czm_21_20 Czm_21_21 2020 NE 2020 OH IL 2020 2020 OH 2020 MI 2020 MD IA 2020 2020 PA 2020 PA 2020 MD IA 2020 2020 IL 2020 MI 2020 MI 2020 MI 2020 OH 2020 OH 2020 AL IL 2020 2020 IL 2020 MI 2020 OH 2020 TN IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 2021 IL 2021 KY IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 2021 IL 2021 MI 2021 MI 2021 MI 2021 MI - - - - - - - - - - - - - - - - - - - - - - - OQ732112 OQ732113 OQ732114 OQ732115 OQ732116 OQ732117 OQ732118 OQ732119 OQ732120 OQ732121 OQ732122 OQ732123 OQ732124 OQ732125 OQ732126 OQ732127 OQ732128 OQ732129 OQ732130 OQ732131 OQ732132 88 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - OQ773833 OQ773834 OQ773835 OQ773836 OQ773837 OQ773838 OQ773839 OQ773840 OQ773841 OQ773842 OQ773843 OQ773844 OQ773845 OQ773846 OQ773847 OQ773848 OQ773849 OQ773850 OQ773851 OQ773852 OQ773853 OQ773854 OQ773855 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table S.3.1. (cont'd) Czm_21_22 Czm_21_23 Czm_21_24 Czm_21_25 Czm_21_26 Czm_21_27 Czm_21_28 Czm_21_29 Czm_21_30 Czm_21_31 Czm_21_32 Czm_21_33 Czm_21_34 Czm_21_35 Czm_21_36 Czm_21_37 Czm_21_38 Czm_21_39 Czm_21_40 Czm_21_41 Czm_21_42 Czm_21_43 Czm_21_44 Czm_21_45 Czm_21_46 Czm_21_47 Czm_21_48 Czm_21_49 Czm_21_50 Czm_21_51 Czm_21_52 Czm_21_53 Czm_21_54 Czm_21_55 Czm_21_56 Czm_21_57 Czm_21_58 Czm_21_59 Czm_21_60 Czm_21_61 Czm_21_62 Czm_21_63 Czm_21_64 Czm_21_65 2021 MI 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS IL 2021 IL 2021 IL 2021 2021 IL 2021 MI 2021 MI 2021 MI 2021 MI 2021 NY 2021 PA 2021 PA 2021 KS 2021 MI 2021 KS 2021 MI 2021 MI 2021 MI 2021 MI 2021 MI 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 KS 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA OQ732133 OQ732134 OQ732135 OQ732136 OQ732137 OQ732138 OQ732139 OQ732140 OQ732141 OQ732142 OQ732143 OQ732144 OQ732145 OQ732146 OQ732147 OQ732148 OQ732149 OQ732150 OQ732151 OQ732152 OQ732153 OQ732154 OQ732155 OQ732156 OQ732157 OQ732158 OQ732159 OQ732160 OQ732161 OQ732162 OQ732163 OQ732164 OQ732165 OQ732166 OQ732167 OQ732168 OQ732169 OQ732170 OQ732171 OQ732172 OQ732173 OQ732174 OQ732175 OQ732176 89 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table S.3.1. (cont'd) Czm_21_66 Czm_21_67 Czm_21_68 Czm_21_69 Czm_21_70 Czm_21_71 Czm_21_72 Czm_21_73 Czm_21_74 Czm_21_75 Czm_21_76 Czm_21_77 Czm_21_78 Czm_21_79 Czm_21_80 Czm_21_81 Czm_21_82 Czm_21_83 Czm_21_84 Czm_21_85 Czm_21_86 Czm_21_87 Czm_21_88 Czm_21_89 Czm_21_90 Czm_21_91 Czm_21_92 Czm_21_93 Czm_21_94 Czm_21_95 Czm_21_96 Czm_21_97 Czm_21_98 Czm_21_99 Czm_21_100 Czm_21_101 Czm_21_102 Czm_21_103 Czm_21_104 Czm_21_105 Czm_21_106 Czm_21_107 Czm_21_108 Czm_21_109 2021 PA 2021 PA 2021 PA 2021 NY 2021 NY 2021 NY 2021 NY 2021 NY 2021 NY 2021 KS 2021 KS 2021 KS IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 IL 2021 2021 IL 2021 KY IN 2021 2021 PA IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 OQ732177 OQ732178 OQ732179 OQ732180 OQ732181 OQ732182 OQ732183 OQ732184 OQ732185 OQ732186 OQ732187 OQ732188 OQ732189 OQ732190 OQ732191 OQ732192 OQ732193 OQ732194 OQ732195 OQ732196 OQ732197 OQ732198 OQ732199 OQ732200 OQ732201 OQ732202 OQ732203 OQ732204 OQ732205 OQ732206 OQ732207 OQ732208 OQ732209 OQ732210 OQ732211 OQ732212 OQ732213 OQ732214 OQ732215 OQ732216 OQ732217 OQ732218 OQ732219 OQ732220 90 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table S.3.1. (cont'd) Czm_21_110 Czm_21_111 Czm_21_112 Czm_21_113 Czm_21_114 Czm_21_115 Czm_21_116 Czm_21_117 Czm_21_118 Czm_21_119 Czm_21_120 Czm_21_121 Czm_21_122 Czm_21_123 Czm_21_124 Czm_21_125 Czm_21_126 Czm_21_127 Czm_21_128 Czm_21_129 Czm_21_130 Czm_21_131 Czm_21_132 Czm_21_133 Czm_21_135 Czm_21_136 Czm_21_137 Czm_21_138 Czm_21_139 Czm_21_140 Czm_21_141 Czm_21_142 Czm_21_143 Czm_21_144 Czm_21_145 Czm_21_146 Czm_21_147 Czm_21_148 Czm_21_149 Czm_21_150 Czm_21_151 Czm_21_152 Czm_21_153 Czm_21_155 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 IN 2021 2021 IN 2021 NY 2021 NY 2021 NY 2021 NJ 2021 NJ 2021 NJ 2021 VA 2021 MD 2021 PA 2021 PA 2021 NJ 2021 PA 2021 PA 2021 PA 2021 MD 2021 NJ 2021 PA 2021 MD 2021 PA 2021 PA 2021 PA 2021 PA 2021 MD 2021 MD 2021 VA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 MD OQ732221 OQ732222 OQ732223 OQ732224 OQ732225 OQ732226 OQ732227 OQ732228 OQ732229 OQ732230 OQ732231 OQ732232 OQ732233 OQ732234 OQ732235 OQ732236 OQ732237 OQ732238 OQ732239 OQ732240 OQ732241 OQ732242 OQ732243 OQ732244 OQ732245 OQ732246 OQ732247 OQ732248 OQ732249 OQ732250 OQ732251 OQ732252 OQ732253 OQ732254 OQ732255 OQ732256 OQ732257 OQ732258 OQ732259 OQ732260 OQ732261 OQ732262 OQ732263 OQ732264 91 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table S.3.1. (cont'd) Czm_21_156 Czm_21_157 Czm_21_158 Czm_21_159 Czm_21_160 Czm_21_161 Czm_21_162 Czm_21_163 Czm_21_164 Czm_21_165 Czm_21_166 Czm_21_167 Czm_21_168 Czm_21_169 Czm_21_170 Czm_21_171 Czm_21_172 Czm_21_173 Czm_21_174 Czm_21_175 Czm_21_176 Czm_21_177 Czm_21_178 Czm_21_179 Czm_21_180 Czm_21_181 Czm_21_182 Czm_21_183 Czm_21_184 Czm_21_185 Czm_21_186 Czm_21_187 Czm_21_188 Czm_21_189 Czm_21_190 Czm_21_191 Czm_21_192 Czm_21_193 Czm_21_194 Czm_21_195 Czm_21_196 Czm_21_197 Czm_21_198 Czm_21_199 2021 PA 2021 PA 2021 PA 2021 PA 2021 MD 2021 PA 2021 MD 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 PA 2021 MD 2021 PA 2021 VA 2021 VA 2021 DE 2021 NY 2021 NY 2021 NY 2021 PA 2021 PA 2021 PA 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE OQ732265 OQ732266 OQ732267 OQ732268 OQ732269 OQ732270 OQ732271 OQ732272 OQ732273 OQ732274 OQ732275 OQ732276 OQ732277 OQ732278 OQ732279 OQ732280 OQ732281 OQ732282 OQ732283 OQ732284 OQ732285 OQ732286 OQ732287 OQ732288 OQ732289 OQ732290 OQ732291 OQ732292 OQ732293 OQ732294 OQ732295 OQ732296 OQ732297 OQ732298 OQ732299 OQ732300 OQ732301 OQ732302 OQ732303 OQ732304 OQ732305 OQ732306 OQ732307 OQ732308 92 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table S.3.1. (cont'd) Czm_21_200 Czm_21_201 Czm_21_202 Czm_21_203 Czm_21_204 Czm_21_205 Czm_21_206 Czm_21_207 Czm_21_208 Czm_21_209 Czm_21_210 Czm_21_211 Czm_21_212 Czm_21_213 Czm_21_214 Czm_21_215 Czm_21_216 Czm_21_217 Czm_21_218 Czm_21_219 Czm_21_220 Czm_21_221 Czm_21_222 Czm_21_223 Czm_21_224 Czm_21_225 Czm_21_226 Czm_21_227 Czm_21_228 Czm_21_229 Czm_21_230 Czm_21_231 Czm_21_232 Czm_21_233 Czm_21_234 Czm_21_235 Czm_21_236 Czm_21_237 Czm_21_238 Czm_21_239 Czm_21_240 Czm_21_241 Czm_21_242 Czm_21_243 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE 2021 NE IA 2021 IA 2021 IA 2021 IA 2021 IA 2021 IA 2021 IA 2021 IA 2021 2021 IA 2021 NJ 2021 NJ 2021 NJ 2021 NY 2021 NY 2021 NY 2021 NY 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 VA 2021 DE 2021 DE 2021 DE 2021 DE 2021 NY 2021 NY OQ732309 OQ732310 OQ732311 OQ732312 OQ732313 OQ732314 OQ732315 OQ732316 OQ732317 OQ732318 OQ732319 OQ732320 OQ732321 OQ732322 OQ732323 OQ732324 OQ732325 OQ732326 OQ732327 OQ732328 OQ732329 OQ732330 OQ732331 OQ732332 OQ732333 OQ732334 OQ732335 OQ732336 OQ732337 OQ732338 OQ732339 OQ732340 OQ732341 OQ732342 OQ732343 OQ732344 OQ732345 OQ732346 OQ732347 OQ732348 OQ732349 OQ732350 OQ732351 OQ732352 93 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table S.3.1. (cont'd) Czm_21_244 Czm_21_245 Czm_21_246 Czm_21_247 Czm_21_248 Czm_21_249 Czm_21_250 Czm_21_251 Czm_21_252 Czm_21_253 2021 NY 2021 KY 2021 KY 2021 KY 2021 KY 2021 KY 2021 ON 2021 ON 2021 ON 2021 ON OQ732353 OQ732354 OQ732355 OQ732356 OQ732357 OQ732358 OQ732359 OQ732360 OQ732361 OQ732362 Czm_21_254 2021 ON OQ732363 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - aSamples collected in: AL = Alabama, DE = Delaware, IL = Illinois, IN = Indiana, IA = Iowa, KS = Kansas, KY = Kentucky, MD = Maryland, MI = Michigan, NE = Nebraska, NJ = New Jersey, NY = New York, OH = Ohio, PA = Pennsylvania, TN = Tennessee,VA = Virginia, and ON = Ontario, Canada. bITS = internal transcribed spacer including 5.8S nrDNA, EF1 = elongation factor 1-α, CAL = calmodulin, HIS = histone H3, ACT = actin, - = samples not sequenced 94 Table S.3.2. Reference sequences of Cercospora spp. from Bakhshi et al. (2015) and Groenewald et al. (2013) for multi-locus phylogenetic analyses. Speciesa Culture accession numberb Host name GenBank accession numbersc Cercospora achyranthis CPC 10091 CPC 11774 (ex-TYPE) Cercospora agavicola Cercospora alchemillicola CPC 5259 (ex-TYPE) Cercospora cf. alchemillicola Cercospora althaeina Cercospora apii CPC 5127 CPC 5117 (ex-TYPE) CBS 110816 CBS 11556 (ex-TYPE) CBS 553.71 CBS 10267 (ex-TYPE) CBS 116458 CPC 10811 CPC 5056 CBS 11557 (ex-TYPE) CPC 18813 MUCC 569 CPC 11598 CPC 14585 CBS 153.55 CPC 15871 CPC 4409 CBS 118712 MUCC 574 Cercospora apiicola Cercospora armoraciae Cercospora beticola Cercospora cf. brunkii Cercospora campi-silii Cercospora canescens complex Cercospora capsici Cercospora celosiae CPC 10660 Cercospora chenopodii CPC 14237 Cercospora cf. chenopodii CPC 10304 (ex-TYPE) ITS JX143524 EF1 JX143278 CAL JX142786 HIS JX142540 ACT JX143032 AY647237 AY966897 AY966899 AY966900 AY966898 JX143033 JX142787 JX143525 JX143279 JX142541 JX143281 JX143284 JX142543 JX142546 JX143035 JX142789 JX143527 JX143530 JX143038 JX142792 AY156919 DQ233346 DQ233398 DQ233424 DQ233372 AY840519 AY840486 AY840417 AY840384 AY840450 DQ233320 DQ233344 DQ233396 DQ233422 DQ233370 AY840536 AY840503 AY840434 AY840401 AY840467 AY840537 AY840504 AY840435 AY840402 AY840468 JX143049 JX142803 JX143541 JX143549 JX143057 JX142811 AY840527 AY840494 AY840425 AY840392 AY840458 JX143064 JX142818 JX143556 JX143066 JX142820 JX143558 JX143067 JX142821 JX143559 JX143069 JX142823 JX143561 JX143310 JX143312 JX143313 JX143315 JX142572 JX142574 JX142575 JX142577 JX142557 JX142565 JX143295 JX143303 JX143318 JX143321 JX143072 JX142826 JX143564 JX143567 JX143075 JX142829 AY260068 DQ835087 DQ835106 DQ835133 DQ835106 JX142584 JX143076 GU214653 JX143079 JX142833 JX143569 JX142580 JX142583 JX143322 JX143325 JX142830 JX142587 JX143570 JX143326 JX142834 JX142588 JX143080 JX143571 JX143327 JX142835 JX142589 JX143081 JX143572 JX143328 JX142836 JX142590 JX143082 Achyranthes japonica Agave tequilana var. azul Alchemilla mollis Gaura lindheimeri Althaea rosea Moluccella laevis Apium graveolens Plumbago europaea Apiumsp. Apium graveolens Armoracia rusticana Erysimum cuspidatum Beta vulgaris Beta vulgaris Beta vulgaris Geranium thunbergii Impatiens noli-tangere Phaseolus lunatus - Citrus maxima - Capsicum annuum Celosia argentea var. cristata Chenopodium cf. album Chenopodium ficifolium 95 Table S.3.2. (cont’d) Cercospora chinensis Cercospora cf. citrulina CPC 15763 CPC 10831 CPC 12682 MUCC 584 Cercospora coniogrammes CBS 17017 (ex-TYPE) Cercospora convolvulicola CBS 136126 (ex-TYPE) Cercospora conyzae- canadensis CBS 135978 (ex-TYPE) Chenopodiumsp. Polygonatum humile Musa sp. Psophocarpus tetragonolobus Coniogramme japonica var. gracilis JX143575 JX143578 EU514222 JX143331 JX143334 JX143335 JX142839 JX142842 JX142843 JX142593 JX142596 JX142597 JX143085 JX143088 JX143089 JX143581 JX143339 JX142847 JX142601 JX143093 JX143583 JX143341 JX142849 JX142603 JX143095 Convolvulus arvensis KJ886441 KJ886280 KJ885797 KJ886119 KJ885958 Conyza canadensis KJ886445 KJ886284 KJ885962 KJ885801 KJ885962 Cercospora corchori Cercospora cf. coreopsidis CPC 10122 Cercospora cylindracea Cercospora delaireae MUCC 585 (ex-TYPE) Cercospora dispori Cercospora cf. erysimi Cercospora euphorbiae- sieboldianae Cercospora fagopyri Cercospora cf. flagellaris CBS 138580 (ex-TYPE) CPC 10455 CPC 10628 CPC 10773 CPC 5361 CBS 113306 (ex-TYPE) CPC 14541 (ex-TYPE) MUCC 866 CBS 113127 CBS 132648 CPC 1052 CPC 4411 CPC 5441 Corchorus olitorius Coreopsis lanceolata Lactuca serriola Delairea odorata Delairea odorata Disporum viridescens Erysimum mutabile Euphorbia sieboldiana Fagopyrum esculentum Hibiscus syriacus Eichhornia crassipes Amaranthus patulus Populus deltoides Citrus sp. Amaranthus sp. JX143342 JX143344 JX142604 JX142606 JX143096 JX142850 JX143584 JX143586 JX143098 JX142852 KJ886449 KJ886288 KJ885805 KJ886127 KJ885966 JX143099 JX142853 JX143587 JX143101 JX142855 JX143589 JX143103 JX142857 JX143591 JX143104 JX142858 JX143592 JX143345 JX143347 JX143349 JX143350 JX142607 JX142609 JX142611 JX142612 JX143592 JX143350 JX142858 JX142612 JX143104 JX142612 JX142619 JX143350 JX143357 JX143104 JX142858 JX143592 JX143599 JX143111 JX142865 DQ835075 AF146147 DQ835148 DQ835175 DQ835121 JX143114 JX142868 JX143602 JX143609 JX143122 JX142876 AY260071 DQ835098 DQ835145 DQ835172 DQ835118 JX143124 JX142878 JX143611 JX143360 JX143368 JX142622 JX142630 JX142632 JX143370 Cercospora cf. helianthicola Cercospora cf. ipomoeae Cercospora iranica Cercospora kikuchii MUCC 716 CPC 10833 MUCC 442 CBS 136124 (ex-TYPE) CPC 5068 Helianthus tuberosus Ipomoea nil Ipomoea aquatica Vicia faba Glycine soja 96 JX143374 JX143376 JX143377 JX143615 JX142882 JX143128 JX143617 JX142884 JX143130 JX143131 JX142885 JX143618 KJ886513 KJ886352 KJ885869 KJ886191 KJ886030 DQ835070 DQ835088 DQ835134 DQ835161 DQ835107 JX142636 JX142638 JX142639 Table S.3.2. (cont’d) Cercospora lactucae- sativae CBS 132633 CBS 135.28 MUCC 590 CPC 10728 Glycine max Glycine soja Glycine soja Ixeris chinensis subsp. strigosa JX143378 JX143619 JX143132 JX142887 DQ835071 DQ835089 DQ835135 DQ835162 DQ835108 JX143133 JX142887 JX143620 JX142641 JX143379 JX142640 JX143621 JX143380 JX142888 JX142642 JX143134 Cercospora cf. malloti Cercospora mercurialis Cercospora cf. modiolae Cercospora cf. nicotianae Cercospora olivascens Cercospora cf. physalidis Cercospora pileicola Cercospora polygonacea Cercospora pseudochenopodii Cercospora punctiformis Cercospora cf. resedae Cercospora cf. richardiicola Cercospora ricinella Cercospora rodmanii Cercospora rumicis Cercospora senecionis- walkeri Cercospora cf. sigesbeckiae MUCC 570 Lactuta sativa JX143623 JX143382 JX142890 JX142644 JX143136 MUCC 787 CBS 549.71 CBS 550.71 (ex-TYPE) CPC 5115 CBS 131.32 CBS 132632 CBS 570.69 CPC 5085 (ex-TYPE) CBS 765.79 CPC 11369 CPC 11318 Mallotus japonicus Mercurialis annua Mercurialis perennis Modiola caroliniana Nicotiana tabacum Glycine max Nicotiana tabacum Aristolochia clematidis Solanum tuberosum Pilea pumila Persicaria longiseta CBS 136022 (ex-TYPE) CPC 14606 CBS 118793 Chenopodium sp. Cynanachum wilfordii Reseda odorata CPC 14680 MUCC 128 CPC 10734 CBS 113124 CBS 113128 CPC 5439 Ajuga multiflora Tagetes erecta Ricinus communis Eichhornia crassipes Eichhornia crassipes Rumex sanguineus JX143385 JX143386 JX143387 JX143389 JX142647 JX142648 JX142649 JX142651 JX143139 JX142893 JX143626 JX143140 JX142894 JX143627 JX143141 JX142895 JX143628 JX143630 JX143143 JX142897 DQ835073 DQ835099 DQ835146 DQ835173 DQ835119 JX143631 JX143144 JX142898 DQ835074 DQ835100 DQ835147 DQ835174 DQ835120 JX143145 JX142899 JX143632 JX143146 JX142900 JX143633 JX143149 JX142903 JX143636 JX143150 JX142904 JX143637 JX142653 JX142654 JX142657 JX142658 JX143391 JX143392 JX143395 JX143396 JX143390 JX142652 KJ886516 KJ886355 KJ885872 KJ886194 KJ886033 JX143151 JX142905 JX143638 JX143152 JX142906 JX143639 JX142659 JX142660 JX143397 JX143398 JX143399 JX143400 JX143405 JX143153 JX142907 JX143640 JX143154 JX142908 JX143641 JX143646 JX143159 JX142913 DQ835077 AF146137 DQ835150 DQ835177 DQ835123 DQ835080 AF146139 DQ835153 DQ835180 DQ835126 JX143161 JX142915 JX143648 JX142661 JX142662 JX142667 JX143407 JX142669 CBS 132636 Senecio walkeri JX143649 JX143408 JX142916 JX142670 JX143162 CPC 10117 MUCC 849 Persicaria orientalis Dioscorea tokoro JX143653 JX143658 JX143412 JX143417 JX142920 JX142925 JX142674 JX142679 JX143166 JX143171 97 Table S.3.2. (cont’d) Cercospora sojina Cercospora solani Cercospora sorghicola Cercospora sp. A Cercospora sp. B Cercospora sp. C Cercospora sp. D Cercospora sp. E Cercospora sp. F Cercospora sp. G Cercospora sp. H Cercospora sp. I Cercospora sp. J Cercospora sp. K Cercospora sp. L Cercospora sp. M Cercospora sp. N Cercospora sp. O Cercospora sp. P Cercospora sp. Q Cercospora sp. S Cercospora sp. T Cercospora vignigena Cercospora violae Cercozpora zeae-maydis Cercospora zebrina CBS 132018 CBS 132615 (ex-TYPE) CBS 136038 CBS 136448(ex-TYPE) CBS 132631 CBS 132602 CBS 132629 CBS 132630 CBS 132628 CBS 132618 CBS 115518 CBS 115205 CBS 114815 MUCC 541 CBS 132603 CBS 115477 CBS 132596 CBS 132619 CBS 132635 CBS 116365 (ex-TYPE) CBS 132679 CBS 132599 CBS 136125 CPC 10812 (ex-TYPE) MUCC 579 CPC 5079 (ex-TYPE) CBS 117757 (ex-TYPE) CBS 132668 CBS 132678 CBS 112893 CBS 129.39 CPC 5437 Glycine soja Glycine soja Solanum nigrum Sorghum halepense Chenopodium sp. Ipomoea purpurea - - Unidentified wild plant Zea mays Bidens frondosa Dichondra repens Deutzia purpurascens Antirrhinum majus Ipomoea coccinea Crepis capillaris Acacia mangium Musa sp. Musa sp. Acacia mangium Phaseolus vulgaris Crepidiastrum denticulatum Coreopsis sp. Vigna unguiculata Vigna unguiculata Viola tricolor Zea mays Zea mays Zea mays Trifolium pratense Trifolium subterraneum Lotus pedunculatus 98 JX142680 JX142681 JX143418 JX143419 JX142697 JX142698 JX142699 JX142700 JX142701 JX143435 JX143436 JX143437 JX143438 JX143439 GU214655 JX142926 JX143172 JX143173 JX142927 JX143659 KJ886523 KJ886362 KJ885879 KJ886201 KJ886040 KJ886525 KJ886364 KJ885881 KJ886203 KJ886042 JX143189 JX142943 JX143675 JX143190 JX142944 JX143676 JX143191 JX142945 JX143677 JX143192 JX142946 JX143678 JX143193 JX142947 JX143679 DQ185071 DQ185083 DQ185107 DQ185119 DQ185095 JX143195 JX142949 JX143681 JX143197 JX142951 JX143683 JX143199 JX142953 JX143685 JX143209 JX142963 JX143695 JX143210 JX142964 JX143696 JX143213 JX142967 JX143699 JX143700 AY752175 AY752234 AY752265 AY752203 JX143214 JX142968 EU514224 JX143215 JX142969 JX143701 AY752141 AY752176 AY752235 AY752266 AY752204 JX143239 JX142993 JX143726 JX143441 JX143443 JX143445 JX143455 JX143456 JX143459 JX142703 JX142705 JX142707 JX142717 JX142718 JX142721 JX143460 JX143461 JX142722 JX142723 JX142747 JX143485 JX142754 JX143492 JX143493 JX143495 JX143496 JX143733 JX143246 JX143000 KJ886541 KJ886380 KJ885897 KJ886219 KJ886058 JX143247 JX143001 JX143734 JX143249 JX143003 JX143736 JX143737 JX143250 JX143004 DQ185074 DQ185086 DQ185110 DQ185122 DQ185098 JX143255 JX143009 JX143742 JX143256 JX143010 JX143743 JX142768 JX143260 AY260078 JX142755 JX142757 JX142758 JX143501 JX143502 JX143506 JX142763 JX142764 JX143014 JX143750 JX143754 JX143512 JX143516 JX143020 JX143024 JX142774 JX142778 JX143266 JX143270 Table S.3.2. (cont’d) Cercospora zeina Cercospora cf. zinniae CPC 11995 (ex-TYPE) CPC 11998 CPC 15075 MUCC 572 CBS 118910 Zea mays Zea mays - Zinnia elegans Eucalyptus sp. DQ185081 DQ185093 DQ185105 DQ185117 DQ185129 DQ185082 DQ185094 DQ185106 DQ185118 DQ185130 JX143273 JX143027 JX143757 JX143275 JX143029 JX143759 JX143276 JX143030 DQ303096 JX142781 JX142783 JX142784 JX143519 JX143521 JX143522 Septoria provencialis aSpecies highlighted in bold were taken from Bakhshi et al. (2015), all other species were from Groenewald et al. (2013) bCBS: CBS-KNAW Fungal Biodiversity Centre, Utrecht, The Netherlands; CPC: Culture collection of Pedro Crous, housed at CBS; MUCC: Culture Collection, Laboratory of Plant Pathology, Mie University, Tsu, Mie Prefecture, Japan cITS: internal transcribed spacer including 5.8S nrDNA; EF1: elongation factor 1-α; CAL: calmodulin; HIS: histone H3; ACT: actin 99 Figure S.3.1. Phylogenetic tree constructed using Kimura-2 parameter + G with gamma- distributed rates DNA model of Cercospora spp. on corn from calmodulin gene. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated in MEGA v.11.0.13. Number indicates bootstrap support for each branches and bootstrap values lower than 50% were condensed. Isolates collected in 2020 and sequenced in this study are highlighted and bold in red. The tree was rooted to Septoria provencialis (isolate CBS 113265). 100 Figure S.3.1. (cont’d) 101 Figure S.3.2. Phylogenetic tree constructed using Kimura-2 parameter + G with gamma- distributed rates DNA model of Cercospora spp. on corn from internal transcribed spacer including 5.8S nrDNA. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated in MEGA v.11.0.13. Number indicates bootstrap support for each branches and bootstrap values lower than 50% were condensed. Isolates collected in 2021 and sequenced in this study are highlighted and bold in red. The tree was rooted to Septoria provencialis (isolate CBS 113265). 102 Figure S.3.2. (cont’d) 103 Figure S.3.3. Phylogenetic tree constructed using Hasegawa-Kishino-Yano (HKY) + I + G with inverse gamma-distributed rates DNA model of Cercospora spp. on corn from internal transcribed spacer including 5.8S nrDNA. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated in MEGA v.11.0.13. Number indicates bootstrap support for each branches and bootstrap values lower than 50% were condensed. Isolates collected and sequenced in this study are highlighted and bold in red. The tree was rooted to Septoria provencialis (isolate CBS 113265). 104 Figure S.3.3. (cont’d) 105 Figure S.3.3. (cont’d) 106 Figure S.3.3. (cont’d) 107 Figure S.3.4. Phylogenetic tree constructed using Hasegawa-Kishino-Yano (HKY) + I + G with inverse gamma-distributed rates DNA model of Cercospora spp. on corn translation elongation factor 1-α gene. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated in MEGA v.11.0.13. Number indicates bootstrap support for each branches and bootstrap values lower than 50% were condensed. Isolates collected and sequenced in this study are highlighted and bold in red. The tree was rooted to Septoria provencialis (isolate CBS 113265). 108 Figure S.3.4. (cont’d) 109 Figure S.3.4. (cont’d) 110 Figure S.3.4. (cont’d) 111 Figure S.3.4. (cont’d) 112 Figure S.3.5. Phylogenetic tree constructed using Hasegawa-Kishino-Yano (HKY) + I + G with inverse gamma-distributed rates DNA model of Cercospora spp. on corn calmodulin gene. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated in MEGA v.11.0.13. Number indicates bootstrap support for each branches and bootstrap values lower than 50% were condensed. Isolates collected and sequenced in this study are highlighted and bold in red. C. cf. flagellaris branch were condensed for viewing purpose. The tree was rooted to Septoria provencialis (isolate CBS 113265). 113 Figure S.3.5. (cont’d) 114 Figure S.3.5. (cont’d) 115 Figure S.3.6. Phylogenetic tree constructed using Hasegawa-Kishino-Yano (HKY) + I + G with inverse gamma-distributed rates DNA model of Cercospora spp. on corn histone H3 gene. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated in MEGA v.11.0.13. Number indicates bootstrap support for each branches and bootstrap values lower than 50% were condensed. Isolates collected and sequenced in this study are highlighted and bold in red. The tree was rooted to Septoria provencialis (isolate CBS 113265). 116 Figure S.3.6. (cont’d) 117 Figure S.3.6. (cont’d) 118 Figure S.3.6. (cont’d) 119 Figure S.3.7. Phylogenetic tree constructed using Hasegawa-Kishino-Yano (HKY) + I + G with inverse gamma-distributed rates DNA model of Cercospora spp. on corn actin gene. Consensus phylogram (50% majority rule) using Maximum Likelihood with 1000 bootstrap replications and 95% partial deletion generated in MEGA v.11.0.13. Number indicates bootstrap support for each branches and bootstrap values lower than 50% were condensed. Isolates collected and sequenced in this study are highlighted and bold in red. The tree was rooted to Septoria provencialis (isolate CBS 113265). 120 Figure S.3.7. (cont’d) 121 Figure S.3.7. (cont’d) 122 Figure S.3.7. (cont’d) 123