=Paper=
{{Paper
|id=None
|storemode=property
|title= New Features and Many Improvements to Analyze Morphology and Color of Digitalized Plant Organs Are Available in Tomato Analyzer 3.0
|pdfUrl=https://ceur-ws.org/Vol-710/paper42.pdf
|volume=Vol-710
|dblpUrl=https://dblp.org/rec/conf/maics/RodriguezFKSNTJ11
}}
== New Features and Many Improvements to Analyze Morphology and Color of Digitalized Plant Organs Are Available in Tomato Analyzer 3.0==
https://ceur-ws.org/Vol-710/paper42.pdf
New Features and Many Improvements to Analyze
Morphology and Color of Digitalized Plant Organs Are
Available in Tomato Analyzer 3.0
Gustavo Rodriguez, David Francis, and Esther van der Knaap
Department of Horticulture and Crop Science, The Ohio State University/ Ohio Agricultural Research and
Development Center, Wooster, Ohio 44691
AND
Jaymie Strecker, Itai Njanji, Josh Thomas, and Atticus Jack
Department of Mathematics and Computer Science, The College of Wooster, Wooster,
Ohio 44691
from the detected boundaries in each object is able to
obtain more than 35 morphological attributes. The pixels
Abstract
inside the boundaries recognized by the software are used
Tomato Analyzer measures morphological and color
to translate color data from the RGB system into the
attributes via image analysis in an objective, high-
throughput, and semiautomatic manner. This software L*a*b* universal color space which is able to approximate
allows for reproducible quantification of phenotypic data human visual perception (Darrigues et al, 2008). Moreover,
that previously were done by hand or visual analysis. The TA combines controlled vocabulary consistent with terms
new version has improved the accuracy of all present in trait ontology databases and mathematical
measurements and reduced the need to make time- descriptors for each shape and color attribute. Even though
consuming manual adjustments. In this paper new the application was specifically developed to analyze
morphological and color attributes available in Tomato tomato fruit, this software can be applied to analyze fruit of
Analyzer 3.0 as well as how the color test module was other species and other plant organs such as seeds, flowers,
made more user-friendly are described.
and leaves.
This paper describes how morphological and color analysis
Introduction of plant organs can be precisely done using Tomato
Analyzer. Lastly, some possible applications of Color Test
The species in the plant kingdom are characterized by a in Tomato Analyzer 3.0 are discussed.
great diversity in color, shapes and size displayed in
organs such as leaves, flowers, and fruits. Even within a
particular species the individuals also can be distinguished 1. Morphological Analysis of Plant Organs Using
by the morphology and color displayed in those organs. Tomato Analyzer
Biologists trying to understand the genetic and molecular
basis for this variation need to measure morphological and Tomato Analyzer can do a high-throughput analysis of
color attributes in an objective and reproducible way. Most morphological traits in images obtained from plant organs.
of this type of phenotypic analysis consists of time- Moreover, the data obtained are unbiased compared to
consuming manual measurements or subjective visual those manually measured by different researchers or using
scoring of characteristics that reduce the success of different instruments. This impartiality allows the
identifying genomic regions or physiological causes reproducibility of the experiments as well as the
underlying this variation. compilation and analysis of data obtained from
Tomato Analyzer (TA) is a software program designed to experiments conducted in several environments and years.
collect objective data from digital images obtained from To date, most of the morphological classifications in plants
plant organs (Brewer et al, 2006). Many of these data are were made based on eyeball observations. Instead,
nearly impossible to quantify manually, such as angles at attributes of TA can be used to objectively classify plant
the distal and proximal ends of the organs or the variation organs into various morphological categories.
for color in their surfaces. Briefly, the software recognizes Tomato Analyzer 2.0 has been a valuable and effective tool
the objects (fruits, leaves or seed) in digitalized images and to indentify and confirm genomic regions that control
tomato fruit shape as well as performing in-depth analyses
of the effect of key fruit shape genes on plant morphology.
It was possible due to color of tomato fruits are contrasting
enough with a black background used in the scanned
images. However, the software was unable to detect other
darker fruits or leaves.
1.1 Workflow for Morphological Analysis
Scan plant organs against a black background to Width Mid-height (W_mid) – The width measured at ½
eliminate shadows. of the fruit’s height.
Open the image in TA, select the attributes to Maximum Width (W) – The maximum horizontal
distance of the fruit.
measure, tell TA to analyze the image. Height Mid-width (H_mid) – The height measured at ½
TA separates objects from background. It does this by of the fruit’s width.
looking at a histogram of luminance for the image and Maximum Height (H) – The maximum vertical distance
finding the separation point (area of low histogram of the fruit.
Curved Height (CH) – The height measured along a
values) between the foreground (lighter colors) and curved line through the fruit (passing through the midpoints
the background (darker colors). It then finds of opposing pairs of points on either side of the distal and
contiguous areas of foreground pixels (the objects) proximal points).
and calculates the boundaries around them.
Resulting data appears in a spreadsheet panel in TA
(screenshot) and can be exported as .csv file.
Some measurements can be manually adjusted.
1.2 New Features and Attributes for Morphological
Analysis in Tomato Analyzer 3.0 Fruit Shape Index External I (H / W) – The ratio of the
Maximum Height to Maximum Width.
Fruit Shape Index External II (H_mid / W_mid) – The
ratio of Height Mid-width to Width Mid-height
1.2.1 Reading TIFF images Curved Fruit Shape Index (CH / CW) – The ratio of
Curved Height to the width of the fruit at mid-curved-height,
The previous version of Tomato Analyzer read only JPEG as measured perpendicular to the curved height line.
(.jpg) files but this new version can open both JPEG (.jpg)
Figure 1. Basic measurement attributes of Tomato
and TIFF (.tif) files. TIFF files are recommended because
Analyzer 3.0 and fruit shape index ratios based on this
they preserve the image as it was originally scanned. JPEG
basic measurements.
images alter some of the colors in the image, reducing the
accuracy of object boundary detection and color analysis.
For example, this new feature has improved the boundary
1.2.3 Increased number of morphometric points
detection in dark green leaves and cucumber fruits. This
improves the accuracy of all measurements and reduces
To measure shape without selecting individual attributes,
the need to make time-consuming manual adjustments.
TA offers a morphometric or geometric analysis of each
object. This function finds points along the boundary of
each tomato slice in the loaded image. Statistical tools such
1.2.2 Length, width and fruit shape index attributes in
as Principal Component Analyses can be used to analyze
curved fruits.
the points in the exported data and it has been used to
identifying tomato genome regions that control fruit
One of the most important features to analyze fruit shape
morphology (Gonzalo et al, 2009). The distal and proximal
in tomato is the fruit shape index (defined as the ratio
ends are used as landmark points for every object (Figure
between the width and the height of the fruits). When the
2). The number of points measured along the boundary is
tomato fruit or other type of fruits as cucumber is curved,
defined by the user and ranges from 4 to 200 in this new
the values for this index do not represent the actual value,
version of TA. The first morphometric point (1x, 1y) is
they are underestimated. A new measurement, named
always the proximal end point. The origin (0,0) of the
curved height, was added in the new version of Tomato
coordinate system is located in the upper left corner of the
Analyzer (Figure 1). This attribute allows an accurate
rectangle defined by the Maximum Width and the
estimation of the length on curved fruits as well as is
Maximum Height.
possible to be measured a new fruit shape index attribute.
shown in the real time on the screen shot of the software
(Figure 3). In the previous version, the results only could
be visualized in .csv files after the analysis was done.
Figure 2. The morphometric points are a fixed number of
points along the perimeter.
2. Color Analysis of Plant Organs Using Tomato
Analyzer
Figure 3. Screenshot of the Tomato Analyzer Test Color
Color is an important quality attribute in horticultural and Module. This new version shows the color results in real
floricultural crops defined by particular genes. However, time (right-down window).
color changes in plant organs also are indicators of biotic
or abiotic stresses. The genetic bases for color attributes as
well as factors affecting plant health would be better 2.2.2. A More User-friendly Test Color Module
understood if computer-based analysis of digital images is calibration
applied instead of their subjective characterization. The
Color Test module in Tomato Analyzer (TACT) is able of The user should chose a color checker with a black or very
collecting and analyzing color parameters in an efficient, dark background based on the broad range of colors
accurate and high-throughput manner from scanned observed in the object of interest (Figure 4). Color checkers
images that contain plant organs. However, the scanner can be purchased custom made or standard.
needs to be calibrated if the user intends to translate RGB
values to L*, a* and b* parameters. This is because
scanners may change in accuracy and how they capture the
color scheme over time. Moreover, scanners differ in how
well they capture color information.
2.1 Workflow for Color Analysis
Scan a color checker. Open the image in TA and
perform a color calibration.
Scan objects and open the image in TA, as you would
for morphological analysis.
Select the color attributes to measure, and tell TA to
perform color analysis.
Resulting data appears in the spreadsheet panel, as in
morphological analysis.
2.2 New Features and Attributes for Color Analysis in
Tomato Analyzer 3.0
Figure 4. Standard color checker from X-rite (Grand
Rapids, MI) and actual L*, a*, b* values for each tile of the
2.2.1 Color Attributes Visualized in real time
color checker are shown in the table.
The most important improvement related to the color test
After the color checker was scanned should be opened and
module in this new version of TA is that the results are
analyzed in TA. The software recognizes each tile as an
object. Then, the user needs to enter the actual L*,a*,b* 2.3. Possible Applications Color Test Module of Tomato
values for each tile in the color checker, as provided by the Analyzer 3.0
manufacturer (Figure 4). TA uses the actual and observed
L*, a*, and b* values to calculate the linear regression. The Color Test module in Tomato Analyzer 3.0 is able to
After that, the color module is calibrated. define the average for several color attributes inside the
boundaries of a plant organ as well as the proportion of six
different user-defined color parameters. This new feature
2.2.3 Three Methods to Analyze Color with Tomato can be useful to study pattern of color variation in some
Analyzer 3.0 plant organ such as petals or leaves. In the plants, soil
nutritional deficiencies, pesticides toxicities and even the
Average color values. The values displayed are: severity of pathogen attacks affect the color pattern on
Average Red, Average Green, Average Blue, Average some plant organ. For example, it has been demonstrated
Luminosity, Average L* Value, Average a* Value, that the estimation of severity in a specific corn disease is
Average b* Value, Average Hue, Average Chroma. highly affected by the rater experience when they directly
These average values are calculated taking account all estimate percentage of diseased leaf area and even more
pixel within the object. when they use a 0 to 9 ordinal rate scale (Poland and
Nelson 2011). With TACT you can define a color range for
L*, hue, chroma distributions. These measurements the diseased portion and calculate the percentage of the leaf
provide histogram data for L*, hue, and chroma. The having that color. Thus, different researchers will get
data appear in the tabs called L* Distributions, Hue exactly the same results because they won’t be interpreting
Distributions, and Chroma Distributions, respectively. the colors or the ratings differently. Therefore, Tomato
Each column shows the fraction of the object whose Analyzer software would become in a powerful tool for
color falls within a certain range. For example, if the this type of studies.
L[40..50) column in L* Distributions has the value
0.3, then 30% of the fruit has L* between 40
(inclusive) and 50 (exclusive). Acknowledgments
Set custom color parameters. Based on the L*, hue, This project was funded by the National Science
chroma distributions, the user can define custom Foundation DBI 0227541 to Esther van der Knaap
ranges of L*, hue, chroma, or a combination of the
three. The User-Defined Color Ranges dialog appears
as shown in Figure 5. The user can define up to 6 References
combinations of color ranges. In the example in
Figure 5, Parameter 1 includes all colors where the Brewer M.T.; Lang L.; Fujimura K.; Dujmovic N.; Gray,
hue is between 30 (inclusive) and 45 (exclusive); L* S.; and van der Knaap E. 2006. Development of a
and chroma may be anything. Parameter 2 includes all controlled vocabulary and software application to analyze
colors where the L* is between 0 and 30 and the hue is fruit shape variation in tomato and other plant species.
between 0 and 90; the chroma may be anything. The Plant Physiology 141 (1): 15-25.
data will appear in the data window tab called Custom
Color Parameters. Darrigues A.; Hall J.; van der Knaap E.; and Francis D.M.
2008. Tomato analyzer-color test: A new tool for efficient
digital phenotyping. Journal of the American Society for
Horticultural Science 133 (4): 579-586.
Gonzalo M.J.; Brewer M.T.; Anderson C.; Sullivan D.;
Gray S.; and van der Knaap E. 2009. Tomato fruit shape
analysis using morphometric and morphology attributes
implemented in tomato analyzer software program. Journal
of the American Society for Horticultural Science 134 (1):
77-87.
Poland J.A. and Nelson R.J. 2011. In the Eye of the
Beholder: The Effect of Rater Variability and Different
Rating Scales on QTL Mapping. Phytopathology 101 (2):
290-298.
Figure 5. Set Custom Color parameters dialog box