Drought is one of the most important environmental stresses in the agriculture and many efforts have been made to improve crop productivity under water limiting conditions. While natural selection has favoured mechanisms for adaptation and survival, breeding activity has directed selection towards increasing the economic yield of cultivated species.
Unfortunately, precise phenotyping under reliable conditions represents the most limiting factor for the progress of genomic studies on drought tolerance. In recognition of this need to develop quantitative, reproducible, and automated system for analyzing large numbers of plants, a high-throughput plant phenotyping platform (LemnaTec-Scanalyzer 3D system) was placed at the Metapontum Agrobios s.r.l. (Matera, IT).
In this work we present the progress on the morphological characterization of a core set of wild and cultivated wheat accessions (Triticum turdigum ssp.) carried out during the vegetative stage for their response to drought stress.
For this purpose we established a glasshouse experiment with the factorial combination of 25 genotypes, 2 different conditions of water supply and the measurements were taken twice a week for about 1,5 month. After water stress treatment digital biomass and leaf water status, determined by image analysis in the spectrum of the near infrared (NIR), both decreased in average by 60 %.
In general, the earliest parameter reacting to stress was the photosynthetic activity, measured indirectly by estimating the leaf fluorescence. The growth of stressed plants was reduced compared to the control plants, before any other visible sign of stress could be detected.
The genotypes showed phenotypic differences both under well watered and under drought conditions. With daily non-invasive imaging of plant growth it is now possible to quantify growth related parameters, detect stress symptoms and their timing as well as estimate the recovery of growth after drought stress.
The short-term goal is to combine detailed genotypic information with deep and robust phenotypic data for detection of the genetic basis of the traits evaluated.