This article focuses on the issue of plant phenotyping and the challenge to link that to processes at the molecular level. To bridge those two, non-invasive approaches and evaluation tools are developed, complemented by e-infrastructure for quantitative analysis of structure and function of plants. The article closes by introducing the content of this special issue on Plant Phenotyping.

Breeding for drought tolerance in grain crops requires different traits with different types of drought. Phenotyping of large numbers of genotypes, both in the field and in controlled environments, is needed to identify novel traits that can be effectively incorporated into breeding programs. Appropriate combinations of such traits will lift the yield of crops towards their water-limited potential in different environments.

Increased leaf elevation angle (hyponasty) and leaf elongation in Arabidopsis are caused by different environmental stimuli such as shading by surrounding vegetation. Here we report on a phenotyping approach based on laser scanning to measure the diurnal pattern of these two growth responses. High-throughput monitoring of individual plants can be achieved non-invasively during several days under different light conditions with high temporal resolution.

A new image analysis method is developed to facilitate the breeding of better varieties. Using 8 cameras, a 3D picture of a plant is reconstructed which is used to automatically measure features of greenhouse plants, correlating well with manual measurements. This method can automate phenotyping of plants, which is considered a major bottleneck in the progress of plant breeding.

Interpretable classification methods optimised for massive datasets are a prerequisite for phenotyping with hyperspectral imaging sensors. The proposed technique, simplex volume maximisation, is optimised for these conditions and was able to detect drought stress faster than established vegetation indices. This method has the potential to lead to intuitive data exploration and easier visualisation of temporal and spatial stress dynamics.

Quantitative root phenotyping in soil is challenging. We introduce a new automated phenotyping system (GROWSCREEN-Rhizo) for imaging simultaneously roots and shoots in 2D for plants grown in soil-filled rhizotrons. To validate this method, we studied a diverse set of monocots and dicots species to compare manually scored and imaging derived parameters. We found that the portion of the root system captured during imaging time-series can be used to estimate whole-root parameters.

Drought is a major limitation to crop yields worldwide. Devices able to automatically simulate droughts and measure plant responses in order to identify tolerant varieties are currently expensive. We have developed a platform that was able to detect differences in drought tolerance among soybean varieties, which is simpler and has a lower construction cost than previously existing devices, thus, being suitable for low-budget researchers, companies and for use in the developing world.

This study presents a semi-automatic system designed to monitor micro-plots of wheat cultivars in field conditions. The measurements are interpreted for crop architecture and biochemical content characterisation and their frequency allows a good description of their dynamics along the growth cycle. This work demonstrates the ability of this system to acquire high throughput phenotyping pertinent data for wheat cultivar characterisation.

One important challenge towards the development of sustainable agricultural systems is the development of cultivars that show high yield associated with an efficient use of natural resources. This is particularly important for phosphorus in view of the limited availability of its reserves. This work investigated the relationship between genes related to root morphology and yield performance under low P conditions, seeking to elucidate the molecular and physiological basis of maize P efficiency with a focus on root morphology traits. Our results should be conducive for establishing early selection strategies for P efficiency in maize, which should eventually help plant breeders to generate cultivars with improved performance under low P conditions.

A chlorophyll fluorescence protocol was standardised and used for mass screening of 1274 wheat cultivars under heat stress. The screening was repeated three times with increasing selection pressure to identify the contrasting set of cultivars with increased genetic determination of the genotype variation. Chlorophyll fluorescence parameters were evaluated for their ability to detect genetic differences between wheat cultivars. The results are important for further studies to understand the genetic nature of heat stress tolerance.