The domestication and improvement of fruit-bearing crops resulted in a large diversity of fruit form. To facilitate consistent terminology pertaining to shape, a controlled vocabulary focusing specifically on fruit shape traits was developed. Mathematical equations were established for the attributes so that objective, quantitative measurements of fruit shape could be conducted. The controlled vocabulary and equations were integrated into a newly developed software application, Tomato Analyzer, which conducts semiautomatic phenotypic measurements. To demonstrate the utility of Tomato Analyzer in the detection of shape variation, fruit from two F 2 populations of tomato (Solanum spp.) were analyzed. Principal components analysis was used to identify the traits that best described shape variation within as well as between the two populations. The three principal components were analyzed as traits, and several significant quantitative trait loci (QTL) were identified in both populations. The usefulness and flexibility of the software was further demonstrated by analyzing the distal fruit end angle of fruit at various user-defined settings. Results of the QTL analyses indicated that significance levels of detected QTL were greatly improved by selecting the setting that maximized phenotypic variation in a given population. Tomato Analyzer was also applied to conduct phenotypic analyses of fruit from several other species, demonstrating that many of the algorithms developed for tomato could be readily applied to other plants. The controlled vocabulary, algorithms, and software application presented herein will provide plant scientists with novel tools to consistently, accurately, and efficiently describe twodimensional fruit shapes.

Reliable analysis of plant traits depends on the accuracy of scoring the phenotype. We report here on the efficacy of two methods in the detection of quantitative trait loci (QTL) controlling fruit morphology in three segregating tomato (Solanum spp.) F2 populations using the software program, Tomato Analyzer. The first method uses fruit morphology attributes such as fruit shape index, blockiness, pear shape, indentation area, and angles of the fruit along the boundary. The second method uses morphometric points to quantify shape. The morphometric data were subjected to principle components analysis (PCA). QTL that control the fruit morphology attributes and the morphometric PCA were identified that revealed that the methods were comparable in that they resulted in nearly identical loci. Novel attributes were added to Tomato Analyzer that improved versatility of the program in measuring additional morphological features of fruit. We demonstrated that these novel attributes permitted identification of QTL controlling the traits.

Measuring plant characteristics via image analysis has the potential to increase the objectivity of phenotypic evaluations, provides data amenable to quantitative analysis, and is compatible with databases that aim to combine phenotypic and genotypic data. We describe a new tool, which is implemented in the Tomato Analyzer (TA) software application, called Color Test (TACT). This tool allows for accurate quantification of color and color uniformity, and allows scanning devices to be calibrated using color standards. To test the accuracy and precision of TACT, we measured internal fruit color of tomato (Solanum lycopersicum L.) with a colorimeter and from scanned images. We show high correlations (r > 0.96) and linearity of L*, a*, and b* values obtained with TACT and the colorimeter. We estimated genotypic variances associated with color parameters and show that the proportion of total phenotypic variance attributed to genotype for color and color uniformity measured with TACT was significantly higher than estimates obtained from the colorimeter. Genotypic variance nearly doubled for all color and color uniformity traits when collecting data with TACT. This digital phenotyping technique can also be applied to the characterization of color in other fruit and vegetable crops.

No abstract