Abstract
BackgroundIn the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time by means of image acquisition techniques. During such screening different images of each plant are recorded and must be analysed by applying sophisticated image analysis algorithms.ResultsThis paper presents an image analysis pipeline (HTPheno) for high-throughput plant phenotyping. HTPheno is implemented as a plugin for ImageJ, an open source image processing software. It provides the possibility to analyse colour images of plants which are taken in two different views (top view and side view) during a screening. Within the analysis different phenotypical parameters for each plant such as height, width and projected shoot area of the plants are calculated for the duration of the screening. HTPheno is applied to analyse two barley cultivars.ConclusionsHTPheno, an open source image analysis pipeline, supplies a flexible and adaptable ImageJ plugin which can be used for automated image analysis in high-throughput plant phenotyping and therefore to derive new biological insights, such as determination of fitness.
Highlights
In the last few years high-throughput analysis methods have become state-of-the-art in the life sciences
High-throughput analysis methods are commonly used in molecular biology
We describe the ImageJ [5] plugin HTPheno, which is a freely available open source pipeline to handle image data from plants
Summary
Analysing images from high-throughput screening experiments is time consuming and computationally demanding. Measuring 8 plants at 6 different time points in side view and top view manually means to measure parameters from 96 images. All images were analysed by HTPheno to obtain phenotypic parameters such as width, height and projected shoot area. The growth rate over a period of time measured at 15 time points is illustrated by average values of all plants per cultivar and condition and the standard deviation (see Figure 5C). Investigating the images it was observed that Morex plants develop differently whereas Barke plants develop more Both cultivars have a smaller average projected shoot area under drought stress conditions. The image analysis shows that the phenotypic parameter projected shoot area can be used to describe morphological differences between the two barley cultivars Barke and Morex as well as differences in growth under different conditions
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