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.
Sarah J. Pethybridge, Niloofar Vaghefi, and Julie R. Kikkert
Jason B. Scott, David H. Gent, Frank S. Hay, and Sarah J. Pethybridge
Flower number is the primary determinant of yield in pyrethrum (Tanacetum cineariifolium). Traditional estimates of flower numbers use physical harvesting of flowers, which is time consuming, destructive, and complicated. The precision of flower number estimates may be highly influenced by spatial heterogeneity of plant density and vigor. Here, we examined the potential for digital image analysis to enable rapid, nondestructive assessment of flower number. This technique involved removal of pixels with color profiles not typical of the disc florets of pyrethrum. Particle counting was then performed using defined size and shape parameters to estimate flower numbers. Estimates of flower number based on image analyses were correlated with physical harvests of flowers, with estimates representing about an average of 32% of total flower numbers present within a sampling unit. This relationship was consistent across all observed flower densities. Covariate analysis indicated that occurrences of crop lodging and over mature flower canopies had significant, detrimental effects on system predictions. Pyrethrum flowers were spatially aggregated within fields with the degree of aggregation greatest at the lowest flower densities. Based on modeled flower distributions, eight quadrats (0.49-m2 sampling unit) were sufficient to achieve a cv of 0.1 in a 600-m2 plot area in all but the lowest flower densities. The utility of this approach for biomass assessment in pyrethrum and other Compositae is discussed.