Measuring fruit morphology and color traits of vegetable and fruit crops in an objective and reproducible way is important for detailed phenotypic analyses of these traits. Tomato Analyzer (TA) is a software program that measures 37 attributes related to two-dimensional shape in a semi-automatic and reproducible manner 1,2 . Many of these attributes, such as angles at the distal and proximal ends of the fruit and areas of indentation, are difficult to quantify manually. The attributes are organized in ten categories within the software: Basic Measurement, Fruit Shape Index, Blockiness, Homogeneity, Proximal Fruit End Shape, Distal Fruit End Shape, Asymmetry, Internal Eccentricity, Latitudinal Section and Morphometrics. The last category requires neither prior knowledge nor predetermined notions of the shape attributes, so morphometric analysis offers an unbiased option that may be better adapted to high-throughput analyses than attribute analysis. TA also offers the Color Test application that was designed to collect color measurements from scanned images and allow scanning devices to be calibrated using color standards 3 .TA provides several options to export and analyze shape attribute, morphometric, and color data. The data may be exported to an excel file in batch mode (more than 100 images at one time) or exported as individual images. The user can choose between output that displays the average for each attribute for the objects in each image (including standard deviation), or an output that displays the attribute values for each object on the image. TA has been a valuable and effective tool for indentifying and confirming tomato fruit shape Quantitative Trait Loci (QTL), as well as performing in-depth analyses of the effect of key fruit shape genes on plant morphology. Also, TA can be used to objectively classify fruit into various shape categories. Lastly, fruit shape and color traits in other plant species as well as other plant organs such as leaves and seeds can be evaluated with TA. Video LinkThe video component of this article can be found at http://www.jove.com/video/1856/ ProtocolTomato Analyzer (TA) software is designed to recognize objects of a certain size and image resolution, measured in dots (pixels) per inch (dpi). The software automatically determines the boundaries of fruit in a scanned image. The object boundary is determined through contour tracing, which results in a list of adjacent points describing the border of an object in an image. All fruit shape measurements are calculated based on the boundaries. The color test module "Tomato Analyzer Color Test" is designed to quantify the color parameters inside the boundaries recognized by the software. The color measurements are based on the RGB color space: R (red), G (green), and B (Blue). The average RGB values for each pixel is taken by Color test module and then translated to the CIELAB color space which uses L*, a*, b* to describe color in a way that approximates human visual perception. The Color test module calculates Hu...

Variation in fruit morphology is a prevalent characteristic among cultivated tomato. The genetic and developmental mechanisms underlying similarities and differences in shape between the fruit of two elongated tomato varieties were investigated. Fruit from two F2 populations constructed from either Solanum lycopersicum cv. Howard German or cv. Banana Legs crossed with S. pimpinellifolium accession LA1589, and one BC1 population constructed with S. lycopersicum Howard German as the recurrent parent, were analysed for shape by using a new software program Tomato Analyzer. Quantitative trait loci (QTLs) controlling 15 individual shape attributes were mapped by both single and multitrait composite interval mapping in each population. In addition, principal components analysis and canonical discriminant analysis were conducted on these shape attributes to determine the greatest sources of variation among and between the populations. Individual principal components and canonical variates were subjected to QTL analysis to map regions of the genome influencing fruit shape in the cultivars. Common and unique regions, as well as previously known and novel QTLs, underlying fruit morphology in tomato were identified. Four major loci were found to control multiple fruit shape traits, principal components, and canonical variates in the populations. In addition, QTLs associated with the principal components better revealed regions of the genome that varied among populations than did the QTL associated with canonical variates. The QTL identified can be compared across additional populations of tomato and other fruit-bearing crop species.

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The level of reducing sugars and asparagine in raw potatoes is critical for potato breeders and the food industry for production of commonly consumed food products including potato chips and French fries. Our objective was to evaluate the use of a portable infrared instrument for the rapid quantitation of major sugars and amino acids in raw potato tubers using single-bounce attenuated total reflectance (ATR) and dial path accessories as an alternative to time-consuming chromatographic techniques. Samples representing a total of 84 experimental and commercial potato varieties harvested in two consecutive growing seasons (2012 and 2013) were used in this study. Samples had wide ranges of sugars determined by HPLC-RID (non-detectable (ND)-7.7 mg glucose, ND-9.4 mg fructose and 0.4-5.4 mg sucrose per 1 g fresh weight), and asparagine and glutamine levels determined by GC-FID (0.7-2.9 mg and 0.3-1.7 mg per 1 g fresh weight). Infrared spectra collected from 64 varieties were used to create partial least squares regression (PLSR) calibration models that predicted the sugar and amino acid levels in an independent set of 16 validation potato varieties. Excellent linear correlations between infrared predicted and reference values were obtained. PLSR models had a high correlation coefficient of prediction (rPred >0.95) and residual predictive deviation (RPD) values ranging between 3.1 and 5.5. Overall, the results indicated that the models could be used to simultaneously predict sugars, free asparagine and glutamine levels in the raw tubers, significantly benefiting potato breeding, certain aspects of crop management, crop production and research.

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