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Carrot (Daucus carotavar.sativus) cultivars with common root shape, appearance, and end-use are grouped and commercialized in market classes. The shape of the carrot storage root is the result of growth and development, which is highly influenced by genotype; however, the extent to which planting density affects root shape traits and its interaction with genotype remains unexplored. To observe the effects of market class and density on carrot root shape characteristics, five cultivars classified in five different market classes, including Imperator, Nantes, Danvers, Chantenay, and Ball, were each grown at five planting densities ranging from 0.5 million to 4.5 million plants/ha. A generalized complete block design with a two-way factorial treatment arrangement of the two factors, density and genotype, was used in three environments. Roots were phenotyped using a digital imaging pipeline and scored for root size (length, maximum width) and compound root shape traits including traits derived from the principal component analysis of root contour profiles like root fill and tip and shoulder curvature. The results suggest that planting density had minimal impact on the shape of carrot roots, and the expected shape for each market class was maintained regardless of planting density; however, the analysis was constrained by the presence of interactions among genotype, density, and environment, which influence the contribution of main effects to shape. For the Nantes, Danvers, Chantenay, and Imperator market classes, planting density influenced the size of the carrot root, with size decreasing by up to 50% in length and width at high planting densities. We found high estimates of broad-sense heritability for traits that determine the shape of the carrot root, such as root fill and length-to-width ratio, which capture size-independent variation of the storage root. Although environmental signals play a role, our results suggested that the shape of the carrot root is primarily determined by genotype, and that planting density generally does not have a significant effect on its shape.
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A Digital Image-Based Phenotyping Platform for Analyzing Root Shape Attributes in Carrot
Root shape in carrot (Daucus carota subsp. sativus), which ranges from long and tapered to short and blunt, has been used for at least several centuries to classify carrot cultivars. The subjectivity involved in determining market class hinders the establishment of metric-based standards and is ill-suited to dissecting the genetic basis of such quantitative phenotypes. Advances in digital image acquisition and analysis has enabled new methods for quantifying sizes of plant structures and shapes, but in order to dissect the genetic control of the shape features that define market class in carrot, a tool is required that quantifies the specific shape features used by humans in distinguishing between classes. This study reports the construction and demonstration of the first such platform, which facilitates rapid phenotyping of traits that are measurable by hand, such as length and width, as well as principal component analysis (PCA) of the root contour and its curvature. This latter approach is of particular interest, as it enabled the detection of a novel and significant quantitative trait, defined here as root fill, which accounts for 85% of the variation in root shape. Curvature analysis was demonstrated to be an effective method for precise measurement of the broadness of the carrot shoulder, and degree of tip fill; the first principal component of the respective curvature profiles captured 87% and 84% of the total variance. This platform’s performance was validated in two experimental panels. First, a diverse, global collection of germplasm was used to assess its capacity to identify market classes through clustering analysis. Second, a diallel mating design between inbred breeding lines of differing market classes was used to estimate the heritability of the key phenotypes that define market class, which revealed significant variation in the narrow-sense heritability of size and shape traits, ranging from 0.14 for total root size, to 0.84 for aspect ratio. These results demonstrate the value of high-throughput digital phenotyping in characterizing the genetic control of complex quantitative phenotypes.
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- Award ID(s):
- 2048425
- PAR ID:
- 10315266
- Date Published:
- Journal Name:
- Frontiers in plant science
- Volume:
- 12
- ISSN:
- 1664-462X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fpls.2021.690031
