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1.1. WHAT DOES GIA ROOTS DO?
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We found no off-the-shelf solution available. As such, GiA Roots was born, first as a series of
Matlab scripts to accompany an imaging platform (Iyer-Pascuzzi et al., Plant Phys 2010) and now,
in its current version, as a stand-alone software.
In practice, GiA Roots presumes that you – the user – has access to images of root networks.
Perhaps these networks are from your own laboratory or that of your colleague. Perhaps these
networks were downloaded from an online database. Whatsoever the case, you would like to know
something about these root networks. For example, what is the average width of roots in the
network, or what is the volume in the network? At the heart of GiA Roots are algorithms that
transform the root systems in each image into a black and white image. Next, GiA Roots calculates
features of individual root systems (see Figure 1.3 for an example of what these algorithms actually
do). GiA Roots has become an essential tool in our collaborative work. We can now analyze
Figure 1.3: What GiA Roots does to each network: (i) transforms images into black and white
images; (ii) automatically extracts features of the networks.
thousands of images in a few hours, whereas hand-curated analysis can often require many hours
for an individual image.
However, in trying to develop software that would be useful for our colleagues in both academic
settings and in industry we were faced with two additional challenges: (i) GiA Roots must be
general enough to analyze root images taken in a variety of imaging conditions; (ii) GiA Roots
must be extensible so that advanced users could tell GiA Roots to extract features specific to their
application. The need for generality means that the user must help GiA Roots pre-process images
and decide which features to extract. We have tried to make these steps as intuitive as possible
(see Chapter 3). The need for extensibility will be addressed in the advanced sections.
So, in summary, GiA Roots can: