Horticultural Characteristics and Susceptibility of Table Beet Cultivars to Cercospora Leaf Spot in New York

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  • 1 1Cornell University, School of Integrative Plant Science, Section of Plant Pathology and Plant-Microbe Biology, Geneva, NY 14456
  • 2 2Cornell Cooperative Extension, Canandaigua, NY 14424

Table beet (Beta vulgaris ssp. vulgaris) production in New York is increasing for direct sale, use in value-added products, or processing. One of the most important diseases affecting table beet is cercospora leaf spot (CLS) caused by the fungus Cercospora beticola. CLS causes lesions on leaves that coalesce and leads to premature defoliation. The presence of CLS may cause buyer rejection at fresh markets. Defoliation from CLS may also result in crop loss because of the inability to harvest with top-pulling machinery. The susceptibility of popular table beet cultivars (Boldor, Detroit, Falcon, Merlin, Rhonda, Ruby Queen, and Touchstone Gold) to CLS was tested using C. beticola isolates representative of the New York population. Two trials were conducted by inoculating 6-week-old plants in the misting chamber. A small-plot replicated field trial was also conducted to examine horticultural characteristics of the cultivars. In the misting chamber trials, disease progress measured by the area under the disease progress stairs (AUDPS) was not significantly different between the red cultivars, Detroit and Ruby Queen, and was significantly higher in ‘Boldor’ than the other yellow cultivar Touchstone Gold. In the field trial, the number of CLS lesions per leaf at the final disease assessment and AUDPS were significantly lower in cultivar Ruby Queen than others and not significantly different between the yellow cultivars. The dry weight of roots was not significantly different among cultivars at first harvest (77 days after planting). At 112 days after planting, the dry weight of roots was significantly higher in cultivar Detroit than Rhonda and Boldor. Leaf blade length and the length:width ratio were cultivar-dependent, which may facilitate selection for specific fresh markets. Significant associations between canopy reflectance in the near infrared (IR) (830 nm), dry weight of foliage, and number of CLS lesions per leaf suggested that this technique may have utility for remote assessment of these variables in table beet research. Implications of these findings for the management of CLS in table beet are discussed.

Abstract

Table beet (Beta vulgaris ssp. vulgaris) production in New York is increasing for direct sale, use in value-added products, or processing. One of the most important diseases affecting table beet is cercospora leaf spot (CLS) caused by the fungus Cercospora beticola. CLS causes lesions on leaves that coalesce and leads to premature defoliation. The presence of CLS may cause buyer rejection at fresh markets. Defoliation from CLS may also result in crop loss because of the inability to harvest with top-pulling machinery. The susceptibility of popular table beet cultivars (Boldor, Detroit, Falcon, Merlin, Rhonda, Ruby Queen, and Touchstone Gold) to CLS was tested using C. beticola isolates representative of the New York population. Two trials were conducted by inoculating 6-week-old plants in the misting chamber. A small-plot replicated field trial was also conducted to examine horticultural characteristics of the cultivars. In the misting chamber trials, disease progress measured by the area under the disease progress stairs (AUDPS) was not significantly different between the red cultivars, Detroit and Ruby Queen, and was significantly higher in ‘Boldor’ than the other yellow cultivar Touchstone Gold. In the field trial, the number of CLS lesions per leaf at the final disease assessment and AUDPS were significantly lower in cultivar Ruby Queen than others and not significantly different between the yellow cultivars. The dry weight of roots was not significantly different among cultivars at first harvest (77 days after planting). At 112 days after planting, the dry weight of roots was significantly higher in cultivar Detroit than Rhonda and Boldor. Leaf blade length and the length:width ratio were cultivar-dependent, which may facilitate selection for specific fresh markets. Significant associations between canopy reflectance in the near infrared (IR) (830 nm), dry weight of foliage, and number of CLS lesions per leaf suggested that this technique may have utility for remote assessment of these variables in table beet research. Implications of these findings for the management of CLS in table beet are discussed.

The New York table beet industry currently supplies ≈30,000 tons annually and is the second largest producer for the processing and fresh markets in the United States (U.S. Department of Agriculture, 2014). In New York, table beets are produced for the fresh market in diverse systems ranging from small, diversified farms to broad-acre fields. Production across the northeastern United States is increasing as a result of the resurgence in popularity driven by demand for table beet in value-added products (i.e., juices) because of the enhanced perception of the health benefits of consumption (Clifford et al., 2015).

For the fresh market, table beets may be sold with foliage intact or separated from roots. Profitability in table beet production is, therefore, a direct function of the number of marketable units (roots, foliage, or both) per length of row and the uniformity of root sizes for sale into specific markets (Hipp, 1977; Kikkert et al., 2010; Warne, 1948, 1953). For example, higher in-row plant densities increase the proportion of plants with smaller root diameters in globe-shaped cultivars but are inversely correlated with total root yield (Benjamin, 1987; Benjamin et al., 1985; Tyler et al., 1982). Similarly, agronomic characteristics such as row width, in-row populations, and harvest date also have a significant impact on disease incidence but adjustments often lead to economic detriments to growers (Kikkert et al., 2010).

The quality of foliage and roots are major determinants of profitability, with the presence of disease leading to consumer rejection at fresh markets. Diseases that deleteriously affect table beet production include root decay (Abawi et al., 1986; Shah and Stivers-Young, 2004) and foliar diseases (Franc, 2010). Maintenance of healthy leaves is critical to facilitate mechanized harvest, which is conducted in broad-acre fields by top-pulling machinery that removes the roots from the ground and separates the tops, which are left in the field. The use of top-pulling machinery reduces the need for mineral or other inorganic foreign contaminants to be separated at the factory, which is often problematic with conventional digger harvesters (J.L. Johnson, personal communication). In New York, CLS caused by the fungus Cercospora beticola is the most important foliar disease affecting table beet production. Symptoms begin as small gray spots on the leaves that coalesce and cause defoliation (Franc, 2010). For the fresh market, the presence of CLS lesions on leaves may lead to rejection. The disease is also important in sugar beet (Beta vulgaris ssp. vulgaris) and C. beticola isolates are known to infect either host (Jacobsen and Franc, 2009; Ruppel, 1986).

Cercospora beticola produces conidiospores that are dispersed short distances by wind, rain, or both (Franc, 2010). However, the mechanisms by which the fungus is dispersed between fields remain elusive as the sexual form of C. beticola has not been identified. Cercospora beticola populations from table beet fields in New York have an equal distribution of the two mating type alleles and high genotypic diversity (Vaghefi et al., 2016, 2017a, 2017b) consistent with observations suggestive of the presence of cryptic sex in populations on sugar beet (Bolton et al., 2012; Groenewald et al., 2006, 2008).

The fungus may overwinter on plant debris as pseudostromata and in soil which may initiate epidemics by splash dispersal of inoculum to leaves (Franc, 2010; Khan et al., 2008), and in sugar beet, soilborne inoculum has been shown to remain viable for up to 22 months in North Dakota (Khan et al., 2008) and 3 years in Israel (Solel, 1970). Studies in New York have demonstrated that C. beticola populations on table beet and swiss chard (B. vulgaris ssp. vulgaris) are sympatric suggesting either of these hosts may serve as inoculum for each other when in close proximity (Vaghefi et al., 2017b). The role of infected weeds as alternative hosts for initiating epidemics in sugar beet fields has also been suggested (McKay and Pool, 1918; Vestal, 1933).

In conventional table beet production, CLS is controlled by prophylactic fungicide application (Pethybridge et al., 2016). However, a high frequency of C. beticola isolates that are resistant to fungicides threatens the durability of disease management strategies. For example, 40% of the C. beticola population in New York was reported as resistant to the quinone outside inhibitor fungicide, azoxystrobin (Vaghefi et al., 2016). In the CLS-sugar beet pathosystem, reports of resistance to multiple fungicide modes of action restrict tactical control options for growers (e.g., Georgopoulos and Dovas, 1973; Giannopolitis, 1978; Kirk et al., 2012; Ruppel, 1975; Weiland and Halloin, 2001). A significant variation in CLS susceptibility between sugar beet cultivars has been identified enabling the use of resistant cultivars as a sentinel part of the integrated disease management strategy (Skaracis and Biancardi, 2000; Smith and Martin, 1978; Smith and Ruppel, 1974). To date, there has been less emphasis on CLS susceptibility in table beet breeding in comparison with desirable horticultural characteristics for the fresh market such as root shape and size, and color (Goldman and Navazio, 2003). In addition to disease response, the processing table beet industry has strict market preferences on root sizes and preservation quality standards translating to limited potential to use less susceptible cultivars (Kikkert et al., 2010).

The objective of this study was to evaluate the susceptibility of popular table beet cultivars to local (New York) C. beticola populations and horticultural characteristics of interest to fresh market growers. A secondary objective was to investigate the potential of near IR canopy reflectance to remotely assess table beet health. This information is vital for the implementation of durable disease management strategies for CLS in table beet in New York.

Materials and methods

Misting chamber trials.

Two trials were conducted in a misting chamber facility to assess the susceptibility of seven locally popular table beet cultivars [‘Boldor’, ‘Detroit’, ‘Falcon’, ‘Merlin’, ‘Rhonda’, ‘Ruby Queen’, and ‘Touchstone Gold’ (Table 1)] to infection by C. beticola. The experimental design of each trial was a completely randomized block including 10 plants of each cultivar inoculated with a C. beticola isolate representative of the dominant clade present in New York [Tb14–085 (Vaghefi et al., 2016)]. All cultivars were grown from seed in the greenhouse, and inoculations were conducted on 6-week-old plants with 7–10 true leaves. Conidial inoculum was prepared according to the protocol of Secor and Rivera (2012) with minor modifications. In brief, 10 mL of sterile distilled water was added to 2-week-old cultures of Tb14–085 on potato dextrose agar (PDA; Hardy Diagnostics, Santa Maria, CA). Mycelia were gently scraped from the plate with a sterile spatula and 500 µL of the suspension was transferred and spread over petri plates containing clarified V8 (CV8) agar [10% (v/v) clarified V8 juice (Campbell’s Soup Co., Camden, NJ), 0.5% (w/v) calcium carbonate (CaCO3), 2% agar]. These plates were left to dry for 1 h under sterile conditions and incubated at room temperature and exposed to a 12-h white fluorescent light photoperiod for 6 d to induce sporulation (Calpouzos and Stallknecht, 1965). To prepare the conidial inoculum, 5 mL of sterile distilled water was added to each of the CV8 plates. Conidia were dislodged by gentle scraping with a sterile spatula, and the suspension was passed through two layers of sterile cheesecloth and vortexed for 10 s. Conidial concentrations were quantified using a hemocytometer and adjusted to a final concentration of 104 spores/mL and 0.01% (v/v) polysorbate 20 (Tween-20; Bio-Rad, Hercules, CA).

Table 1.

Characteristics of the popular table beet cultivars in New York included in this study for quantifying susceptibility to cercospora leaf spot and variation in horticultural characteristics.

Table 1.

Ten plants were placed in individual transparent plastic bags in centrally controlled misting chambers (New York State Agricultural Experiment Station, Geneva, NY) with a 14-h photoperiod at 25 ± 4 °C. Each plant received ≈12 mL of inoculum using a hand sprayer. The bags were closed for 48 h to increase relative humidity for infection. Ten plants of each cultivar were noninoculated controls and placed in individual plastic bags and received an equal volume of sterile distilled water + 0.01% (v/v) polysorbate 20. The misting apparatus was operated for 2–3 h daily delivering a fine mist of water at 25 °C resulting in 90% to 100% relative humidity. The entire trial was conducted twice.

Disease severity was assessed by counting the number of CLS lesions on each plant and calculating the average number per leaf. Disease assessments were conducted at 6, 10, 13, and 17 d after inoculation (DAI) and used to interpolate epidemic progress as the AUDPS (Simko and Piepho, 2012). The effect of cultivars on the average number of CLS lesions per leaf at 17 DAI and AUDPS was quantified using generalized linear modeling in Genstat (version 17.1; VSN International, Hemel Hempstead, UK). Results of the two trials were analyzed separately as exploratory data analysis identified significant differences in the means between the datasets from each trial using the Anderson–Darling goodness-of-fit test (Anderson and Darling, 1954), and nonhomogeneous variances using the Fisher F-test (Markowski and Markowski, 1990). Significant differences between cultivars within trials were separated using least significant differences (P = 0.05).

Field trial.

A small-plot, replicated trial was conducted to further assess CLS susceptibility and evaluate horticultural characteristics between the table beet cultivars at Geneva, NY, in 2016. The experimental design was a completely randomized block with five replications of each cultivar (Table 1). The crop was planted on 22 June with a Monosem vacuum planter at a rate of 17 seeds/ft with 30 inches between rows (Monosem, Edwardsville, KS). Before planting, 10N–4.4P–8.3K fertilizer (Phelps Supply, Phelps, NY) at 300 lb/acre was broadcast and incorporated with shallow tillage using a tractor-mounted coulter mulcher. Additional 10N–4.4P–8.3K fertilizer at 350 lb/acre was banded at planting and 1.5 pt/acre of s-metolachlor herbicide (Dual Magnum®; Syngenta Corp., Greensboro, NC) was applied the day after planting (DAP). The entire trial area also received supplementary nitrogen (22% as urea, 50 lb/acre) in a side-dressed application 28 DAP. Irrigation was applied using overhead sprinklers as required for optimal plant growth. In-season weed management was conducted by hand and mechanical cultivation between rows. Each plot was 20 ft long and two rows wide. Plots within rows were separated by 4 ft of bare ground. Plots between rows were separated by two rows planted to the processing industry-standard cultivar Ruby Queen.

The entire trial area was inoculated with a mycelial suspension containing eight C. beticola isolates representative of the New York population (Tb14-047, Tb14-070, Tb14-081, Tb14-113, Tb14-116, Tb14-118, Tb14-146, and Tb14-154; Vaghefi et al., 2016). Individual liquid cultures of each isolate were established by transferring mycelia into CV8 broth [10% (v/v) clarified V8 juice, 0.5% (w/v) CaCO3]. After 14 d, the mycelia of each isolate was collected and filtered through two layers of cheesecloth. The mycelia were then dispersed in sterile distilled water in a blender (Waring Commercial, Torrington, CT) at low speed for 30 s and again filtered through sterile cheesecloth. The number of mycelial fragments per milliliter of suspension was counted using a hemocytometer, and the concentration was adjusted to about 106 fragments/mL. The inoculum was diluted 10 times with sterile distilled water before applying to plants in the field, including 0.01% (v/v) polysorbate 20, with a backpack sprayer at a volume of 28 gal/acre. To estimate the colony-forming units (cfu) in the inoculum, 1 mL of the mycelial suspension was serially diluted (10–10−6) in sterile distilled water, and 100 µL was spread on CV8 plates. Three replicate plates were used for each concentration and incubated at room temperature exposed to a 12-h photoperiod of white light. After 3 d, the number of colonies was counted on each plate and quantified. The first inoculation was conducted on 9 Aug. (48 DAP) with 3.6 × 103 CFU/mL, followed by 1.6 × 104 CFU/mL on 17 Aug. (56 DAP). The second inoculation was conducted to ensure disease development following dry conditions after the first inoculation.

Disease assessment.

Plant density (number of plants/foot) and CLS severity were assessed before the first inoculation [8 Aug. (47 DAP)] and at regular intervals [24 Aug. (63 DAP), 28 Aug. (67 DAP), 31 Aug. (70 DAP), 5 Sept. (75 DAP), 9 Sept. (79 DAP), and 23 Sept. (93 DAP)] until harvest. Plant density was assessed by counting the number of plants in two, 3.2-ft lengths beginning at an arbitrarily located position within each row of the plots. An individual leaf was defined as the sampling unit for assessment of CLS severity. CLS lesions were counted on each of the 10 arbitrarily selected leaves of similar age from different plants within each of the two rows (n = 20 plants/plot). The temporal disease progress was then depicted within each plot by calculating AUDPS based on the average number of CLS lesions per leaf (Simko and Piepho, 2012).

Canopy reflectance.

A hand-held, multispectral radiometer (MSR5; CropScan, Rochester, MN) equipped with five narrow wavelength band sensors (485, 560, 660, 830, and 1650 nm) was used to measure spectral reflectance from the plots. Canopy reflectance was measured the day before the first inoculation, and then postinoculation on 24 Aug. (63 DAP), 5 Sept. (75 DAP), 9 Sept. (79 DAP), 23 Sept. (93 DAP), and 11 Oct. (regrowth after defoliation; 111 DAP). The radiometer was positioned 6.6 ft above the soil and a spirit level mounted to the support pole was used to ensure it was positioned at the appropriate angle and height. The support pole was placed 5 and 15 ft from the end of each plot in the middle of the rows. Canopy reflectance was therefore measured from an area that was 3.2 ft in diameter. Percentage reflectance readings were obtained between 1200 and 1400 hr. Reflectance was calculated as a percentage of the voltage for the reflected radiation divided by the voltage for the incident radiation of each corresponding wavelength. Two readings were obtained for each plot, which were averaged.

Yield and other horticultural characteristics.

Plants were removed by hand from 3.2-ft row lengths on 7 Sept. (77 DAP) and 12 Oct. (112 DAP). The second harvest was conducted following defoliation to quantify cultivar differences in regrowth ability. In-ground storage into late autumn is often used to facilitate processing schedules and by fresh market growers to extend product sales. At each harvest, the total number of plants removed per unit row length was counted, and tops were removed from the roots and weighed separately following washing. Fresh and dry weights of the foliage and roots were recorded. The dry weight of the foliage was calculated by placing ≈20% of the sample at 149 °F for 48 h. The dry weight of the roots was calculated after the subsample was left to dry in the same conditions for 120 h. At the first harvest (77 DAP), 30 leaves were randomly selected from each plot for measuring blade length and width (at the midpoint) with a ruler, and the average length to width ratio was calculated. The shoulder diameter of 20 randomly selected roots from each plot was measured using digital calipers. The number of immature roots (less than 0.5 inch in diameter) in the subsample was also recorded.

Data analysis.

The effect of cultivar on the number of CLS lesions per leaf, temporal disease progress (AUDPS), canopy reflectance at 830 nm, and yield components (dry weight of foliage and roots at each of the two harvests, and average leaf and root dimensions at 77 DAP) were assessed using generalized linear models. The 830 nm wavelength was selected as canopy reflectance within the near IR region has been demonstrated as a good predictor of plant health (Nilsson, 1995). Means were separated with Fisher’s protected least significant difference test (P = 0.05). Pearson’s correlation coefficient was used to analyze the associations between the number of CLS lesions per leaf, AUDPS, canopy reflectance at 830 nm, and the dry weight of foliage. All analyses were conducted within the statistical software, Genstat (version 17.1).

Results and discussion

Significant differences in CLS susceptibility and desirable horticultural characteristics between table beet cultivars grown in New York were found. In the misting chamber trials, the average number of CLS lesions per leaf across cultivars at 17 DAI was 13.1 and 19.9 in trials 1 and 2, respectively, and a significant cultivar × trial interaction was identified (Table 2). No CLS lesions were observed in any of the noninoculated control plants in either trial. In both trials, AUDPS in cultivar Touchstone Gold was significantly lower than in the other yellow cultivar, Boldor. In trial 1, the number of CLS lesions per leaf in cultivar Merlin was significantly lower than the other cultivars with the exception of ‘Rhonda’ and ‘Detroit’. In trial 2, the cultivars were of similar susceptibility with the exception of ‘Touchstone Gold’, which was not significantly different from ‘Rhonda’, ‘Falcon’, and ‘Detroit’. When evaluating epidemic progress, the interaction between trials was also significant as AUDPS average values were 63% higher in the second trial compared with the first (Table 2). In trial 1, AUDPS in cultivars Rhonda and Merlin was not significantly different between each other but reduced by 48.5% and 33.9%, respectively, compared with ‘Boldor’. Moreover, AUDPS in cultivar Rhonda was not significantly different from ‘Touchstone Gold’. AUDPS was not significantly different between the red cultivars, Detroit, Falcon, and Ruby Queen. In trial 2, AUDPS was similar across cultivars with no significant differences between ‘Detroit’, ‘Merlin’, ‘Rhonda’, and ‘Ruby Queen’ (Table 2).

Table 2.

The effect of table beet cultivar on severity of cercospora leaf spot (CLS) following inoculation with Cercospora beticola isolate Tb14-085 in two trials conducted in the misting chamber.

Table 2.

In the field trial, the number of CLS lesions per leaf at the final assessment was significantly lower in cultivar Ruby Queen than other cultivars, and not significantly different between ‘Detroit’, ‘Falcon’, ‘Rhonda’, and ‘Merlin’ (Table 3). For example, the number of CLS lesions in cultivar Ruby Queen was 43.3% lower compared with ‘Falcon’. The number of lesions was not significantly different between either of the yellow cultivars, Boldor and Touchstone Gold (Figs. 1 and 2). Disease progress was also significantly lower in ‘Ruby Queen’ than other cultivars and 41.6% lower in ‘Ruby Queen’ than ‘Rhonda’. Moreover, AUDPS in ‘Rhonda’ was significantly higher than the other red cultivars. For example, AUDPS in cultivar Rhonda was higher by 23.7%, 13.9%, 34.7%, and 71.4% compared with ‘Detroit’, ‘Falcon’, ‘Merlin’, and ‘Ruby Queen’, respectively. AUDPS between the yellow cultivars was not significantly different but was on average 21.5% lower than in ‘Rhonda’ (Table 3).

Table 3.

Table beet cultivar susceptibility to cercospora leaf spot (CLS) and effect of cultivar on the fresh and dry weight of foliage and average leaf dimensions tested in a small-plot, replicated trial conducted at Geneva, NY in 2016.

Table 3.
Fig. 1.
Fig. 1.

Temporal progression of cercospora leaf spot (CLS) epidemics according to the cultivar in a replicated field trial conducted at Geneva, NY, in 2016. (A) Yellow cultivars (Touchstone Gold and Boldor) compared with processing cultivar standard (Ruby Queen); (B) Ruby Queen compared with other red cultivars, Detroit, Rhonda, Falcon, and Merlin; error bars = SE.

Citation: HortTechnology hortte 27, 4; 10.21273/HORTTECH03743-17

Fig. 2.
Fig. 2.

Cercospora leaf spot (CLS) symptoms in table beet cultivars [(A) Boldor, (B) Rhonda, (C) Detroit, (D) Falcon, (E) Ruby Queen, (F) Touchstone Gold] following inoculation with Cercospora beticola isolates representative of the population in New York.

Citation: HortTechnology hortte 27, 4; 10.21273/HORTTECH03743-17

Cultivar differences in CLS susceptibility when comparing the number of CLS lesions per leaf and AUDPS may reflect variation in disease progression on a leaf scale, which has also been suggested in sugar beet (Skaracis and Biancardi, 2000). For example, in cultivar Ruby Queen lesions remained small and discrete, but in ‘Touchstone Gold’ and ‘Boldor’, lesions expanded and coalesced leading to increased disease severity. Averaged over 30 leaves, lesion size was also significantly (P = 0.01) greater in ‘Rhonda’ and ‘Falcon’ (mean = 3.6 cm, SD = 0.6 cm) than in ‘Ruby Queen’ (mean = 1.1 cm, SD = 0.3 cm). Minor variation in cultivar susceptibility rankings between trials in the misting chamber and field may be attributed to a range of factors. Temperature and relative humidity in the misting chamber trials were highly conducive to infection and disease development, whereas in the field, environmental conditions varied and included sporadic irrigation to promote disease spread. In all trials, plants were inoculated at similar leaf stages (42–48 DAP). The inoculum used for the misting chamber trials consisted of a single representative isolate, whereas the field trial inoculum consisted of a mixture of isolates (Vaghefi et al., 2016). Variation in virulence between C. beticola isolates infecting sugar beet has been reported (Ruppel, 1972; Solel and Wahl, 1971). No information is available on variation in virulence between isolates on table beet in New York but may be substantial considering the high genotypic diversity within populations (Bolton et al., 2012; Groenewald et al., 2008; Moretti et al., 2004; Vaghefi et al., 2016, 2017a, 2017b).

Preliminary information on CLS susceptibility in table beet cultivars grown in New York indicated that ‘Touchstone Gold’ and the red cultivar Bull’s Blood were more resistant than ‘Early Wonder Tall Top’. This study relied upon naturally occurring inoculum and used disease severity to estimate disease progress rather than the number of lesions per leaf (Lange et al., 2015). By contrast, under high disease pressure resulting from homogeneously applied inoculum with isolates representative of the genetic diversity of the New York population in the current study, the susceptibility of the yellow cultivars was similar to the selected red with the exception of ‘Ruby Queen’. ‘Ruby Queen’ is the predominant cultivar used by the processing table beet industry in New York (J.L. Johnson, personal communication). Reduced susceptibility of ‘Touchstone Gold’ to CLS compared with ‘Detroit’ and ‘Ruby Queen’ has been reported in previous studies in Florida where the epidemic resulted from natural inoculum from an adjacent field and had generally low disease severity [≤20.3% (Raid et al., 2013a, 2013b)].

A significant negative association was described between canopy reflectance at 830 nm and AUDPS (r = −0.36, P = 0.017) and the number of CLS lesions per leaf at the final disease assessment (r = −0.65, P < 0.001). Conversely, there was a significant, positive linear relationship between canopy reflectance at 830 nm and the dry weight of foliage (r = 0.56, P < 0.001). The utility of canopy reflectance in the near IR as an alternative to quantifying CLS severity has also been tested in sugar beet (Steddom et al., 2005). In the CLS-sugar beet study, canopy near IR reflectance was measured using a device (MSR16, CropScan) similar to the MRS5. In sugar beet, this method improved the precision of CLS severity estimation (Steddom et al., 2005) compared with the use of the industry-standard Kleinwanzleber Saatzucht diagrammatic scale on a plot basis (Kleinwanzleber Saatzucht Ag. Einbeck, 1970). In table beet, CLS severity has been assessed by counting lesions on multiple leaves to obtain an average on a plot scale (Abawi et al., 2005). The significant association between canopy reflectance at 830 nm and the dry weight of foliage also suggests this technique may be a reliable and rapid method for remote estimation of biomass and plant health in table beet research. The relationships between growth and yield and amount of intercepted radiation has been well documented (e.g., Nilsson, 1995) and used for plant health assessment in many agricultural crops (e.g., Kobayashi et al., 2001; Nutter, 1989; Pethybridge et al., 2008).

The significant cultivar differences in the number of CLS lesions per leaf did not translate to significant differences in the fresh and dry weights of foliage at 77 DAP (Table 3). Significant differences between cultivars in fresh and dry weights of foliage at 112 DAP were reflective of cultivar differences based on AUDPS. For example, the dry weight of foliage in cultivar Rhonda was 27.4% lower than in ‘Ruby Queen’, and was not significantly different to ‘Detroit’. The dry weight of foliage at 112 DAP was not significantly different between the yellow cultivars (Touchstone Gold and Boldor), Falcon and Merlin (Table 3). Significant cultivar variation in the dry weight of foliage at 112 DAP was not reflective of differences in CLS susceptibility. Foliar biomass in fall was significantly higher in ‘Detroit’ than ‘Rhonda’ and ‘Boldor’. Similarly, root biomass was significantly higher at 112 DAP in ‘Detroit’ and ‘Ruby Queen’ than ‘Rhonda’ and ‘Boldor’. This suggests the former two cultivars may be more suitable for in-ground storage because of less deterioration (reduced biomass) to facilitate processing schedules and extend fresh product sales. The cultivars also differed significantly in leaf blade length and shape. For example, the leaf blade of ‘Rhonda’ was 26.1% shorter than ‘Detroit’ and did not significantly differ between the yellow cultivars nor ‘Merlin’ and ‘Ruby Queen’. No significant differences were detected between cultivars in leaf width. Therefore, the significant differences between cultivars in leaf length led to effects on the length to width ratio (Table 3). This information may be important for fresh market growers considering the attractiveness of foliage for intact or separate sale in cultivar selection.

No significant differences were found among cultivars in the number of beets per unit row length at either harvest date. This is not surprising as CLS is not known to affect plant stand but was quantified as a potential covariate affecting foliar disease severity and horticultural characteristics. No significant differences were found among cultivars (Table 4). Root shoulder diameter and dry weight were not significantly different between cultivars at 77 DAP. However, differences were detected at 112 DAP in root dry weight which were significantly higher in cultivar Detroit, than ‘Rhonda’ and ‘Boldor’. The dry weight of roots was not significantly different among ‘Boldor’, ‘Rhonda’, and ‘Touchstone Gold’. The average dry weight of roots at 112 DAP across cultivars was 47.5% lower than at first harvest (Table 4).

Table 4.

The effect of table beet cultivar on the number of roots per row length, dry weight of roots, the percentage of immature roots (< 0.5 inch shoulder diameter), and root shoulder diameter following inoculation with Cercospora beticola in a small-plot, replicated trial conducted at Geneva, NY, in 2016.

Table 4.

Conclusions

Popular table beet cultivars in New York included in this study were similarly susceptible to CLS when inoculated with local C. beticola isolates with the exception of the less susceptible ‘Ruby Queen’. Significant positive associations between canopy reflectance at 830 nm and foliar biomass, and inversely the number of CLS lesions per leaf indicated this technique may have utility for remote estimation of these variables in table beet research. Significant cultivar differences were detected in foliar and root biomass upon in-ground storage to 112 DAP. Moreover, significant differences in leaf length and the length:width ratio may be informative for the selection of cultivars for fresh market sales in New York.

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Literature cited

  • Abawi, G.S., Crosier, D.C., Cobb, A.C. & Becker, R.F. 1986 Root rot of table beets in New York State. New York’s Food Life Sci. Bul. No. 115

  • Abawi, G.S., Ludwig, J.W. & Gugino, B.K. 2005 Evaluation of fungicides for the control of pocket rot and leaf spot of table beet, 2004 Plant Dis. Mgt. Rpt. 60 V146

    • Search Google Scholar
    • Export Citation
  • Anderson, T.W. & Darling, D.A. 1954 A test of goodness-of-fit J. Amer. Stat. Assn. 49 765 769

  • Benjamin, L.R. 1987 The relative importance of cluster size, sowing depth, time of seedling emergence, and between-plant spacing on variation in plant size in red beet (Beta vulgaris L.) crops J. Agr. Sci. Cambridge 108 221 230

    • Search Google Scholar
    • Export Citation
  • Benjamin, L.R., Sutherland, R.A. & Senior, D. 1985 The influence of sowing rate and row spacing on the plant density and yield of red beet J. Agr. Sci. Cambridge 104 615 624

    • Search Google Scholar
    • Export Citation
  • Bolton, M.D., Secor, G.A., Rivera, V., Weiland, J.J., Rudolph, K., Birla, K., Rengifo, J. & Campbell, L.G. 2012 Evaluation of the potential for sexual reproduction in field populations of Cercospora beticola from USA Fungal Biol. 116 511 521

    • Search Google Scholar
    • Export Citation
  • Calpouzos, L. & Stallknecht, G.F. 1965 Sporulation of Cercospora beticola affected by an interaction between light and temperature Phytopathology 55 1370 1371

    • Search Google Scholar
    • Export Citation
  • Clifford, T., Howatson, G., West, D.J. & Stevenson, E.J. 2015 The potential benefits of red beetroot supplementation in health and disease Nutrients 7 2801 2822

    • Search Google Scholar
    • Export Citation
  • Franc, G.D. 2010 Ecology and epidemiology of Cercospora beticola, p. 7–19. In: R.T. Lartey, J.J. Weiland, L. Panella, P.W. Crous, and C.E. Windels (eds.). Cercospora leaf spot of sugar beet and related species. APS Press, St. Paul, MN

  • Georgopoulos, S.G. & Dovas, C. 1973 Occurrence of Cercospora beticola strains resistant to benzimidazole fungicides in N. Greece Plant Dis. Rptr. 57 321 324

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    • Export Citation
  • Giannopolitis, C.N. 1978 Occurrence of strains of Cercospora beticola resistant to triphenyltin fungicides in Greece Plant Dis. Rptr. 62 205 208

    • Search Google Scholar
    • Export Citation
  • Goldman, I.L. & Navazio, J.P. 2003 History and breeding of table beet in the United States Plant Breed. Rev. 22 357 388

  • Groenewald, M., Groenewald, J.Z., Harrington, T.C., Abeln, E.C.A. & Crous, P.W. 2006 Mating type gene analysis in apparently asexual Cercospora species is suggestive of cryptic sex Fungal Genet. Biol. 43 813 825

    • Search Google Scholar
    • Export Citation
  • Groenewald, M., Linde, C.C., Groenewald, J.Z. & Crous, P.W. 2008 Indirect evidence for sexual reproduction in Cercospora beticola populations from sugar beet Plant Pathol. 57 25 32

    • Search Google Scholar
    • Export Citation
  • Hipp, B.W. 1977 Influence of nitrogen and growing season on yield and size distribution of table beets J. Amer. Soc. Hort. Sci. 102 598 601

  • Jacobsen, B.J. & Franc, G.D. 2009 Cercospora leaf spot, p. 7–10. In: R.M. Harveson, L.E. Hanson, and G.L. Hein (eds.). Compendium of beet diseases and pests. 2nd ed. APS Press, St. Paul, MN

  • Khan, J., del Rio, L.E., Nelson, R., Rivera-Varas, V., Secor, G.A. & Khan, M.F.R. 2008 Survival, dispersal and primary infection site for Cercospora beticola in sugar beet Plant Dis. 92 741 745

    • Search Google Scholar
    • Export Citation
  • Kirk, W.W., Hanson, L.E., Franc, G.D., Stump, W.L., Gachango, E., Clark, G. & Stewart, J. 2012 First report of strobilurin resistance in Cercospora beticola in sugar beet (Beta vulgaris) in Michigan and Nebraska, USA New Dis. Rptr. 26 3

    • Search Google Scholar
    • Export Citation
  • Kikkert, J.R., Reiners, S. & Gugino, B.K. 2010 Row width, population density, and harvest date effects on marketable yield of table beet HortTechnology 20 560 567

    • Search Google Scholar
    • Export Citation
  • Kleinwanzleber Saatzucht Ag. Einbeck 1970 Cercospora. Kleinwanzleber Saatzucht Ag. Einbeck Rabbethge and Giesecke, Einbeck, Germany

  • Kobayashi, T.E., Kanda, K., Kitada, K., Ishiguro, K. & Torigoe, Y. 2001 Detection of rice panicle blast with multispectral radiometer and the potential of using airborne multispectral scanners Phytopathology 91 316 323

    • Search Google Scholar
    • Export Citation
  • Lange, H.W., Smart, C.D. & Seaman, A.J. 2015 Evaluation of biopesticides allowed for organic production on cercospora leaf spot of beet, 2014 Plant Dis. Mgt. Rptr. 9 V007

    • Search Google Scholar
    • Export Citation
  • McKay, M.B. & Pool, V.W. 1918 Field studies of Cercospora beticola Phytopathology 8 119 136

  • Markowski, C.A. & Markowski, E.P. 1990 Conditions for the effectiveness of a preliminary test of variance Amer. Stat. 44 322 326

  • Moretti, M., Saracchi, M. & Farina, G. 2004 Morphological, physiological and genetic diversity within a small population of Cercospora beticola Sacc Ann. Microbiol. 54 129 150

    • Search Google Scholar
    • Export Citation
  • Nilsson, H.E. 1995 Remote sensing and image analysis in plant pathology Annu. Rev. Phytopathol. 15 489 527

  • Nutter, F.W. Jr 1989 Detection and measurement of plant disease gradients in peanut with a multispectral radiometer Phytopathology 79 958 963

  • Pethybridge, S.J., Hay, F., Esker, P., Groom, T., Wilson, C. & Nutter, F.W. Jr 2008 Visual and radiometric assessments for yield losses caused by ray blight in pyrethrum Crop Sci. 48 343 352

    • Search Google Scholar
    • Export Citation
  • Pethybridge, S.J., Vaghefi, N. & Kikkert, J.R. 2016 Efficacy of fungicides for the control of cercospora leaf spot in processing table beet, 2015 Plant Dis. Mgt. Rpt. 10 V003

    • Search Google Scholar
    • Export Citation
  • Raid, R., Hartman, D. & Raid, S. 2013a Evaluation of table beet varieties for resistance to cercospora leaf spot Plant Dis. Mgt. Rpt. 7 V080

  • Raid, R., Hartman, D. & Raid, S. 2013b Evaluation of table beet varieties for resistance to cercospora leaf spot, Spring 2013 Plant Dis. Mgt. Rpt. 7 V145

    • Search Google Scholar
    • Export Citation
  • Ruppel, E.G. 1972 Variation among isolates of Cercospora beticola from sugar beet Phytopathology 62 134 136

  • Ruppel, E.G. 1975 Biology of benomyl-tolerant strains of Cercospora beticola from sugar beet Phytopathology 65 785 789

  • Ruppel, E.G. 1986 Cercospora leaf spot, p. 8–9. In: E.D. Whitney and J.E. Duffus (eds.). Compendium of beet diseases and insects. APS Press, St. Paul, MN

  • Secor, G.A. & Rivera, V.V. 2012 Fungicide resistance assays for fungal plant pathogens, p. 385–392. In: M.D. Bolton, and B.P.H.J. Thomma (eds.). Plant fungal pathogens: Methods and protocols. Humana Press, New York, NY

  • Shah, D.A. & Stivers-Young, L. 2004 Factors associated with decay in table beets identified by a statistical analysis of grower and processor records HortTechnology 14 25 29

    • Search Google Scholar
    • Export Citation
  • Simko, I. & Piepho, H.-P. 2012 The area under the disease progress stairs: Calculation, advantage, and application Phytopathology 102 381 389

  • Skaracis, G.N. & Biancardi, E. 2000 Breeding for cercospora resistance in sugar beet, p. 177–195. In: M.J.C. Asher, B. Holtschulte, M. Richard Molard, F. Rosso, G. Steinruecken, and R. Beckers (eds.). Cercospora beticola Sacc. Biology, agronomic influence and control measures in sugar beet. Adv. Sugar Beet Res. Vol. 2. IIRB, Brussels, Belgium

  • Smith, G.A. & Ruppel, E.G. 1974 Heritability of resistance to cercospora leaf spot in sugarbeet Crop Sci. 14 113 115

  • Smith, G.A. & Martin, S.S. 1978 Differential response of sugar beet cultivars to cercospora leaf spot disease Crop Sci. 18 39 42

  • Solel, Z. 1970 Survival of Cercospora beticola, the causal agent of sugar beet leaf spot, in Israel Trans. Br. Mycol. Soc. 54 504 506

  • Solel, Z. & Wahl, I. 1971 Pathogenic specialization of Cercospora beticola Phytopathology 61 1081 1083

  • Steddom, K., Bredehoeft, M.W., Khan, M. & Rush, C.M. 2005 Comparison of visual and multispectral radiometric disease evaluations of cercospora leaf spot of sugar beet Plant Dis. 89 153 158

    • Search Google Scholar
    • Export Citation
  • Tyler, F.T., Adas, L. & Benjamin, L.R. 1982 Spacing red for beet for high returns Grower 97 25 19 23

  • U.S. Department of Agriculture 2014 Agricultural statistics for 2012. 12 Feb. 2017. <http://www.nass.usda.gov/Quick-stats/>

  • Vaghefi, N., Hay, F.S. & Pethybridge, S.J. 2016 Genotypic diversity and resistance to azoxystrobin of Cercospora beticola on processing table beet in New York Plant Dis. 100 1466 1473

    • Search Google Scholar
    • Export Citation
  • Vaghefi, N., Kikkert, J.R., Bolton, M.D., Hanson, L.E., Secor, G.A. & Pethybridge, S.J. 2017a De novo assembly of Cercospora beticola for microsatellite development and validation Fungal Ecol. 26 125 134

    • Search Google Scholar
    • Export Citation
  • Vaghefi, N., Nelson, S.C., Kikkert, J.R. & Pethybridge, S.J. 2017b Genetic structure of Cercospora beticola populations on Beta vulgaris in New York and Hawaii Scientific Rpt. 7 1726

    • Search Google Scholar
    • Export Citation
  • Vestal, E.F. 1933 Pathogenicity, host response and control of Cercospora leaf-spot of sugar beets. Iowa State College Agr. Mechanic Arts, Agr. Expt. Sta., Res. Bul. No. 168

  • Warne, L.G.G. 1948 Spacing experiments on vegetables IV. The yield of globe beet grown at twelve spacings and two manurial levels in Cheshire J. Hort. Sci. 26 296 303

    • Search Google Scholar
    • Export Citation
  • Warne, L.G.G. 1953 Effects of close spacing on the growth of garden beet Nature 172 506

  • Weiland, J. & Halloin, J. 2001 Benzimidazole resistance in Cercospora beticola samples from sugar beet fields in Michigan, USA Can. J. Plant Pathol. 23 78 82

    • Search Google Scholar
    • Export Citation

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Contributor Notes

Funding was provided by the United States Department of Agriculture, National Institute of Food and Agriculture Hatch project NYG-625424, managed by the New York State Agricultural Experiment Station. Table beet seed was donated by Sakata Seeds America Inc., and Bejo Seeds.

We thank Carol Bowden, Elizabeth Maloney, and David Strickland for technical assistance.

Corresponding author. E-mail: sjp277@cornell.edu.

  • View in gallery

    Temporal progression of cercospora leaf spot (CLS) epidemics according to the cultivar in a replicated field trial conducted at Geneva, NY, in 2016. (A) Yellow cultivars (Touchstone Gold and Boldor) compared with processing cultivar standard (Ruby Queen); (B) Ruby Queen compared with other red cultivars, Detroit, Rhonda, Falcon, and Merlin; error bars = SE.

  • View in gallery

    Cercospora leaf spot (CLS) symptoms in table beet cultivars [(A) Boldor, (B) Rhonda, (C) Detroit, (D) Falcon, (E) Ruby Queen, (F) Touchstone Gold] following inoculation with Cercospora beticola isolates representative of the population in New York.

  • Abawi, G.S., Crosier, D.C., Cobb, A.C. & Becker, R.F. 1986 Root rot of table beets in New York State. New York’s Food Life Sci. Bul. No. 115

  • Abawi, G.S., Ludwig, J.W. & Gugino, B.K. 2005 Evaluation of fungicides for the control of pocket rot and leaf spot of table beet, 2004 Plant Dis. Mgt. Rpt. 60 V146

    • Search Google Scholar
    • Export Citation
  • Anderson, T.W. & Darling, D.A. 1954 A test of goodness-of-fit J. Amer. Stat. Assn. 49 765 769

  • Benjamin, L.R. 1987 The relative importance of cluster size, sowing depth, time of seedling emergence, and between-plant spacing on variation in plant size in red beet (Beta vulgaris L.) crops J. Agr. Sci. Cambridge 108 221 230

    • Search Google Scholar
    • Export Citation
  • Benjamin, L.R., Sutherland, R.A. & Senior, D. 1985 The influence of sowing rate and row spacing on the plant density and yield of red beet J. Agr. Sci. Cambridge 104 615 624

    • Search Google Scholar
    • Export Citation
  • Bolton, M.D., Secor, G.A., Rivera, V., Weiland, J.J., Rudolph, K., Birla, K., Rengifo, J. & Campbell, L.G. 2012 Evaluation of the potential for sexual reproduction in field populations of Cercospora beticola from USA Fungal Biol. 116 511 521

    • Search Google Scholar
    • Export Citation
  • Calpouzos, L. & Stallknecht, G.F. 1965 Sporulation of Cercospora beticola affected by an interaction between light and temperature Phytopathology 55 1370 1371

    • Search Google Scholar
    • Export Citation
  • Clifford, T., Howatson, G., West, D.J. & Stevenson, E.J. 2015 The potential benefits of red beetroot supplementation in health and disease Nutrients 7 2801 2822

    • Search Google Scholar
    • Export Citation
  • Franc, G.D. 2010 Ecology and epidemiology of Cercospora beticola, p. 7–19. In: R.T. Lartey, J.J. Weiland, L. Panella, P.W. Crous, and C.E. Windels (eds.). Cercospora leaf spot of sugar beet and related species. APS Press, St. Paul, MN

  • Georgopoulos, S.G. & Dovas, C. 1973 Occurrence of Cercospora beticola strains resistant to benzimidazole fungicides in N. Greece Plant Dis. Rptr. 57 321 324

    • Search Google Scholar
    • Export Citation
  • Giannopolitis, C.N. 1978 Occurrence of strains of Cercospora beticola resistant to triphenyltin fungicides in Greece Plant Dis. Rptr. 62 205 208

    • Search Google Scholar
    • Export Citation
  • Goldman, I.L. & Navazio, J.P. 2003 History and breeding of table beet in the United States Plant Breed. Rev. 22 357 388

  • Groenewald, M., Groenewald, J.Z., Harrington, T.C., Abeln, E.C.A. & Crous, P.W. 2006 Mating type gene analysis in apparently asexual Cercospora species is suggestive of cryptic sex Fungal Genet. Biol. 43 813 825

    • Search Google Scholar
    • Export Citation
  • Groenewald, M., Linde, C.C., Groenewald, J.Z. & Crous, P.W. 2008 Indirect evidence for sexual reproduction in Cercospora beticola populations from sugar beet Plant Pathol. 57 25 32

    • Search Google Scholar
    • Export Citation
  • Hipp, B.W. 1977 Influence of nitrogen and growing season on yield and size distribution of table beets J. Amer. Soc. Hort. Sci. 102 598 601

  • Jacobsen, B.J. & Franc, G.D. 2009 Cercospora leaf spot, p. 7–10. In: R.M. Harveson, L.E. Hanson, and G.L. Hein (eds.). Compendium of beet diseases and pests. 2nd ed. APS Press, St. Paul, MN

  • Khan, J., del Rio, L.E., Nelson, R., Rivera-Varas, V., Secor, G.A. & Khan, M.F.R. 2008 Survival, dispersal and primary infection site for Cercospora beticola in sugar beet Plant Dis. 92 741 745

    • Search Google Scholar
    • Export Citation
  • Kirk, W.W., Hanson, L.E., Franc, G.D., Stump, W.L., Gachango, E., Clark, G. & Stewart, J. 2012 First report of strobilurin resistance in Cercospora beticola in sugar beet (Beta vulgaris) in Michigan and Nebraska, USA New Dis. Rptr. 26 3

    • Search Google Scholar
    • Export Citation
  • Kikkert, J.R., Reiners, S. & Gugino, B.K. 2010 Row width, population density, and harvest date effects on marketable yield of table beet HortTechnology 20 560 567

    • Search Google Scholar
    • Export Citation
  • Kleinwanzleber Saatzucht Ag. Einbeck 1970 Cercospora. Kleinwanzleber Saatzucht Ag. Einbeck Rabbethge and Giesecke, Einbeck, Germany

  • Kobayashi, T.E., Kanda, K., Kitada, K., Ishiguro, K. & Torigoe, Y. 2001 Detection of rice panicle blast with multispectral radiometer and the potential of using airborne multispectral scanners Phytopathology 91 316 323

    • Search Google Scholar
    • Export Citation
  • Lange, H.W., Smart, C.D. & Seaman, A.J. 2015 Evaluation of biopesticides allowed for organic production on cercospora leaf spot of beet, 2014 Plant Dis. Mgt. Rptr. 9 V007

    • Search Google Scholar
    • Export Citation
  • McKay, M.B. & Pool, V.W. 1918 Field studies of Cercospora beticola Phytopathology 8 119 136

  • Markowski, C.A. & Markowski, E.P. 1990 Conditions for the effectiveness of a preliminary test of variance Amer. Stat. 44 322 326

  • Moretti, M., Saracchi, M. & Farina, G. 2004 Morphological, physiological and genetic diversity within a small population of Cercospora beticola Sacc Ann. Microbiol. 54 129 150

    • Search Google Scholar
    • Export Citation
  • Nilsson, H.E. 1995 Remote sensing and image analysis in plant pathology Annu. Rev. Phytopathol. 15 489 527

  • Nutter, F.W. Jr 1989 Detection and measurement of plant disease gradients in peanut with a multispectral radiometer Phytopathology 79 958 963

  • Pethybridge, S.J., Hay, F., Esker, P., Groom, T., Wilson, C. & Nutter, F.W. Jr 2008 Visual and radiometric assessments for yield losses caused by ray blight in pyrethrum Crop Sci. 48 343 352

    • Search Google Scholar
    • Export Citation
  • Pethybridge, S.J., Vaghefi, N. & Kikkert, J.R. 2016 Efficacy of fungicides for the control of cercospora leaf spot in processing table beet, 2015 Plant Dis. Mgt. Rpt. 10 V003

    • Search Google Scholar
    • Export Citation
  • Raid, R., Hartman, D. & Raid, S. 2013a Evaluation of table beet varieties for resistance to cercospora leaf spot Plant Dis. Mgt. Rpt. 7 V080

  • Raid, R., Hartman, D. & Raid, S. 2013b Evaluation of table beet varieties for resistance to cercospora leaf spot, Spring 2013 Plant Dis. Mgt. Rpt. 7 V145

    • Search Google Scholar
    • Export Citation
  • Ruppel, E.G. 1972 Variation among isolates of Cercospora beticola from sugar beet Phytopathology 62 134 136

  • Ruppel, E.G. 1975 Biology of benomyl-tolerant strains of Cercospora beticola from sugar beet Phytopathology 65 785 789

  • Ruppel, E.G. 1986 Cercospora leaf spot, p. 8–9. In: E.D. Whitney and J.E. Duffus (eds.). Compendium of beet diseases and insects. APS Press, St. Paul, MN

  • Secor, G.A. & Rivera, V.V. 2012 Fungicide resistance assays for fungal plant pathogens, p. 385–392. In: M.D. Bolton, and B.P.H.J. Thomma (eds.). Plant fungal pathogens: Methods and protocols. Humana Press, New York, NY

  • Shah, D.A. & Stivers-Young, L. 2004 Factors associated with decay in table beets identified by a statistical analysis of grower and processor records HortTechnology 14 25 29

    • Search Google Scholar
    • Export Citation
  • Simko, I. & Piepho, H.-P. 2012 The area under the disease progress stairs: Calculation, advantage, and application Phytopathology 102 381 389

  • Skaracis, G.N. & Biancardi, E. 2000 Breeding for cercospora resistance in sugar beet, p. 177–195. In: M.J.C. Asher, B. Holtschulte, M. Richard Molard, F. Rosso, G. Steinruecken, and R. Beckers (eds.). Cercospora beticola Sacc. Biology, agronomic influence and control measures in sugar beet. Adv. Sugar Beet Res. Vol. 2. IIRB, Brussels, Belgium

  • Smith, G.A. & Ruppel, E.G. 1974 Heritability of resistance to cercospora leaf spot in sugarbeet Crop Sci. 14 113 115

  • Smith, G.A. & Martin, S.S. 1978 Differential response of sugar beet cultivars to cercospora leaf spot disease Crop Sci. 18 39 42

  • Solel, Z. 1970 Survival of Cercospora beticola, the causal agent of sugar beet leaf spot, in Israel Trans. Br. Mycol. Soc. 54 504 506

  • Solel, Z. & Wahl, I. 1971 Pathogenic specialization of Cercospora beticola Phytopathology 61 1081 1083

  • Steddom, K., Bredehoeft, M.W., Khan, M. & Rush, C.M. 2005 Comparison of visual and multispectral radiometric disease evaluations of cercospora leaf spot of sugar beet Plant Dis. 89 153 158

    • Search Google Scholar
    • Export Citation
  • Tyler, F.T., Adas, L. & Benjamin, L.R. 1982 Spacing red for beet for high returns Grower 97 25 19 23

  • U.S. Department of Agriculture 2014 Agricultural statistics for 2012. 12 Feb. 2017. <http://www.nass.usda.gov/Quick-stats/>

  • Vaghefi, N., Hay, F.S. & Pethybridge, S.J. 2016 Genotypic diversity and resistance to azoxystrobin of Cercospora beticola on processing table beet in New York Plant Dis. 100 1466 1473

    • Search Google Scholar
    • Export Citation
  • Vaghefi, N., Kikkert, J.R., Bolton, M.D., Hanson, L.E., Secor, G.A. & Pethybridge, S.J. 2017a De novo assembly of Cercospora beticola for microsatellite development and validation Fungal Ecol. 26 125 134

    • Search Google Scholar
    • Export Citation
  • Vaghefi, N., Nelson, S.C., Kikkert, J.R. & Pethybridge, S.J. 2017b Genetic structure of Cercospora beticola populations on Beta vulgaris in New York and Hawaii Scientific Rpt. 7 1726

    • Search Google Scholar
    • Export Citation
  • Vestal, E.F. 1933 Pathogenicity, host response and control of Cercospora leaf-spot of sugar beets. Iowa State College Agr. Mechanic Arts, Agr. Expt. Sta., Res. Bul. No. 168

  • Warne, L.G.G. 1948 Spacing experiments on vegetables IV. The yield of globe beet grown at twelve spacings and two manurial levels in Cheshire J. Hort. Sci. 26 296 303

    • Search Google Scholar
    • Export Citation
  • Warne, L.G.G. 1953 Effects of close spacing on the growth of garden beet Nature 172 506

  • Weiland, J. & Halloin, J. 2001 Benzimidazole resistance in Cercospora beticola samples from sugar beet fields in Michigan, USA Can. J. Plant Pathol. 23 78 82

    • Search Google Scholar
    • Export Citation
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