Wheat yields globally will depend increasingly on good management to conserve rainfall and new varieties that use water efficiently for grain production. Here we propose an approach for developing new varieties to make better use of deep stored water. We focus on water-limited wheat production in the summer-dominant rainfall regions of India and Australia, but the approach is generally applicable to other environments and root-based constraints. Use of stored deep water is valuable because it is more predictable than variable in-season rainfall and can be measured prior to sowing. Further, this moisture is converted into grain with twice the efficiently of in-season rainfall since it is taken up later in crop growth during the grain-filling period when the roots reach deeper layers. We propose that wheat varieties with a deeper root system, a redistribution of branch root density from the surface to depth, and with greater radial hydraulic conductivity at depth would have higher yields in rainfed systems where crops rely on deep water for grain fill. Developing selection systems for mature root system traits is challenging as there are limited high-throughput phenotyping methods for roots in the field, and there is a risk that traits selected in the lab on young plants will not translate into mature root system traits in the field. We give an example of a breeding programme that combines laboratory and field phenotyping with proof of concept evaluation of the trait at the beginning of the selection programme. This would greatly enhance confidence in a high-throughput laboratory or field screen, and avoid investment in screens without yield value. This approach requires careful selection of field sites and years that allow expression of deep roots and increased yield. It also requires careful selection and crossing of germplasm to allow comparison of root expression among genotypes that are similar for other traits, especially flowering time and disease and toxicity resistances. Such a programme with field and laboratory evaluation at the outset will speed up delivery of varieties with improved root systems for higher yield.

Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops

In mammals, cadmium is widely considered as a non-genotoxic carcinogen acting through a methylation-dependent epigenetic mechanism. Here, the effects of Cd treatment on the DNA methylation patten are examined together with its effect on chromatin reconfiguration in Posidonia oceanica. DNA methylation level and pattern were analysed in actively growing organs, under short- (6 h) and long- (2 d or 4 d) term and low (10 mM) and high (50 mM) doses of Cd, through a Methylation-Sensitive Amplification Polymorphism technique and an immunocytological approach, respectively. The expression of one member of the CHROMOMETHYLASE (CMT) family, a DNA methyltransferase, was also assessed by qRT-PCR. Nuclear chromatin ultrastructure was investigated by transmission electron microscopy. Cd treatment induced a DNA hypermethylation, as well as an up-regulation of CMT, indicating that de novo methylation did indeed occur. Moreover, a high dose of Cd led to a progressive heterochromatinization of interphase nuclei and apoptotic figures were also observed after long-term treatment. The data demonstrate that Cd perturbs the DNA methylation status through the involvement of a specific methyltransferase. Such changes are linked to nuclear chromatin reconfiguration likely to establish a new balance of expressed/repressed chromatin. Overall, the data show an epigenetic basis to the mechanism underlying Cd toxicity in plants.

/pdf/in-posidonia-oceanica-cadmium-induces-changes-in-dna-3cu7uj83mr.pdf

In Posidonia oceanica cadmium induces changes in DNA methylation and chromatin patterning

Plant phenotyping refers to a quantitative description of the plant’s anatomical, ontogenetical, physiological and biochemical properties. Today, rapid developments are taking place in the field of non-destructive, image-analysis -based phenotyping that allow for a characterization of plant traits in high-throughput. During the last decade, ‘the field of image-based phenotyping has broadened its focus from the initial characterization of single-plant traits in controlled conditions towards ‘real-life’ applications of robust field techniques in plant plots and canopies. An important component of successful phenotyping approaches is the holistic characterization of plant performance that can be achieved with several methodologies, ranging from multispectral image analyses via thermographical analyses to growth measurements, also taking root phenotypes into account.

/pdf/plant-phenotyping-from-bean-weighing-to-image-analysis-3tmd3wun7o.pdf

Plant phenotyping: from bean weighing to image analysis

Matching roots to their environment

The soil holds twice as much carbon as does the atmosphere, and most soil carbon is derived from recent photosynthesis that takes carbon into root structures and further into below-ground storage via exudates therefrom. Nonetheless, many natural and most agricultural crops have roots that extend only to about 1 m below ground. What determines the lifetime of below-ground C in various forms is not well understood, and understanding these processes is therefore key to optimising them for enhanced C sequestration. Most soils (and especially subsoils) are very far from being saturated with organic carbon, and calculations show that the amounts of C that might further be sequestered (http://dbkgroup.org/carbonsequestration/rootsystem.html) are actually very great. Breeding crops with desirable below-ground C sequestration traits, and exploiting attendant agronomic practices optimised for individual species in their relevant environments, are therefore important goals. These bring additional benefits related to improvements in soil structure and in the usage of other nutrients and water.

/pdf/large-scale-sequestration-of-atmospheric-carbon-via-plant-uulewnvg2f.pdf

Large-scale sequestration of atmospheric carbon via plant roots in natural and agricultural ecosystems: why and how.

This paper extends an earlier one5. The relationship between electrical capacitance of a plant root system (C) and size (weight, volume, surface) of the root system (x) can be expressed by equation of the line

$$C = a + bx$$

ifa equals size of parasitic capacitance of measurement, i.e. capacitance of soil, wires,etc. andb equals regression coefficient influenced by type of soil plant species, measuring frequency and voltage,etc.

Oldrich Chloupek

Papers

Evaluation of the size of a plant's root system using its electrical capacitance