Agrobiodiversity: Effect of Drought Stress on the Eco-physiology and Morphology of Wheat

Osmotic adjustment (OA) and cellular compatible solute accumulation are widely recognized to have a role in plant adaptation to dehydration mainly through turgor maintenance and the protection of specific cellular functions by defined solutes. At the same time, there has been an ongoing trickle of skepticism in the literature about the role of OA in supporting crop yield under drought stress. Contrarian reviews argued that OA did not sustain turgor or that it served mainly for plant survival rather than productivity. This critical review examined 26 published studies where OA was compared with yield under drought stress in variable genotypes of 12 crops, namely, barley, wheat, maize, sorghum, chickpea, pea, pigeon pea, soybean, canola, mustard, castor bean and sunflower. Over all crops a positive and significant association between OA and yield under drought stress were found in 24 out of 26 cases. Considering that it is generally difficult to find a singular plant trait responsible for yield advantage of numerous crops under different drought stress conditions, this evidence is no less than remarkable as proof that OA sustains crop yield under drought stress. Show more

We present in this paper a novel, semiautomated image-analysis software to streamline the quantitative analysis of root growth and architecture of complex root systems. The software combines a vectorial representation of root objects with a powerful tracing algorithm that accommodates a wide range of image sources and quality. The root system is treated as a collection of roots (possibly connected) that are individually represented as parsimonious sets of connected segments. Pixel coordinates and gray level are therefore turned into intuitive biological attributes such as segment diameter and orientation as well as distance to any other segment or topological position. As a consequence, user interaction and data analysis directly operate on biological entities (roots) and are not hampered by the spatially discrete, pixel-based nature of the original image. The software supports a sampling-based analysis of root system images, in which detailed information is collected on a limited number of roots selected by the user according to specific research requirements. The use of the software is illustrated with a time-lapse analysis of cluster root formation in lupin (Lupinus albus) and an architectural analysis of the maize (Zea mays) root system. The software, SmartRoot, is an operating system-independent freeware based on ImageJ and relies on cross-platform standards for communication with data-analysis software. Show more