Accurate inference of shoot biomass from high-throughput images of cereal plants

Plant biomass is an important factor in the study of functional plant biology and growth analysis, and it is the basis for the calculation of net primary production and growth rate [1-4]. Depending on the available budget, accuracy required, structure and composition of the vegetation, and also different disciplines of plant biology, there are several techniques to measure plant biomass [5]. In the study of biomass of an individual plant, shoot dry weight is one of the acceptable measures. This method is typically used to estimate a plant's yield, but it is also an accurate measure of plant biomass.The conventional means of determining shoot dry weight (SDW) is the measurement of oven-dried samples. In this method, tissue is harvested and dried, and then shoot dry weight is measured at the end of the experiment. To investigate the biomass of a large number of plants, this method is very time consuming and labor intensive. Also, since this method is destructive, it is impossible to take several measurements on the same plant at different time points. Therefore, an imaging method has been proposed to infer plant biomass accurately as a non-destructive and fast alternative. The Plant Accelerator [6] and the High Resolution Plant Phenotyping Centre [7] in Australia, the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) in Germany [8], the Institute of Biological, Environmental and Rural Sciences (IBERS) in the UK [9], and PHENOPSIS system being built by the National Institute for Agricultural Research (INRA) in Montpellier, France [10], have established or are planning to establish advanced plant phenotyping facilities that each provide the capability of hundreds to thousands of plants to be automatically imaged from standard positions and then analyzed via image analysis programs every day.Digital image analysis has been an important tool in biological research and also has been applied to satellite images, aerial photographs and macroscopic and microsc