Modeling of tomato fruits into nine shape categories using elliptic fourier shape modeling and Bayesian classification of contour morphometric data

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Classification and characterization of the shape of plant organs are important tools for plant biologists, breeders and growers. Here we use boundary measurements, i.e. contour morphometric data, of scanned tomato fruits in conjunction with elliptic Fourier shape modeling and Bayesian classification techniques to find the optimum number of shape categories. Our findings show that there are nine computationally and visually distinct tomato shape categories: ellipsoid, flat, heart, long, long rectangular, rectangular, round, obovoid, and oxheart. Analyses of fruits from a diverse set of tomato accessions demonstrate that some varieties carry fruits that conform to predominantly one shape category while others carry fruits that conform to multiple shape categories. In particular the categories oxheart and long rectangular feature fruit that tend to equivalently fit several categories of shape, while the flat and obovoid categories contain fruit that consistently conform exclusively to a single category. The findings show that elliptic Fourier shape modeling and Bayesian classification provide an excellent tool for further in depth analyses of fruit shape variation that may occur across varieties and/or result from growth under different environmental conditions.


classification, contour morphometric analysis, fruit shape, modelling, tomato, uniformity

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