Summary: To investigate the uptake and long‐distance translocation of sulphate in plants, we have characterized three cell‐type‐specific sulphate transporters, Sultr1;1, Sultr2;1 and Sultr2;2 in Arabidopsis thaliana. Heterologous expression in the yeast sulphate transporter mutant indicated that Sultr1;1 encodes a high‐affinity sulphate transporter (K_m for sulphate 3.6 ± 0.6 μm), whereas Sultr2;1 and Sultr2;2 encode low‐affinity sulphate transporters (K_m for sulphate 0.41 ± 0.07 m m and ≥ 1.2 m m, respectively). In Arabidopsis plants expressing the fusion gene construct of the Sultr1;1 promoter and green fluorescent protein (GFP), GFP was localized in the lateral root cap, root hairs, epidermis and cortex of roots. β‐glucuronidase (GUS) expressed with the Sultr2;1 promoter was specifically accumulated in the xylem parenchyma cells of roots and leaves, and in the root pericycles and leaf phloem. Expression of the Sultr2;2 promoter–GFP fusion gene showed specific localization of GFP in the root phloem and leaf vascular bundle sheath cells. Plants continuously grown with low sulphate concentrations accumulated high levels of Sultr1;1 and Sultr2;1 mRNA in roots and Sultr2;2 mRNA in leaves. The abundance of Sultr1;1 and Sultr2;1 mRNA was increased remarkably in roots by short‐term stress caused by withdrawal of sulphate. Addition of selenate in the sulphate‐sufficient medium increased the sulphate uptake capacity, tissue sulphate content and the abundance of Sultr1;1 and Sultr2;1 mRNA in roots. Concomitant decrease of the tissue thiol content after selenate treatment was consistent with the suggested role of glutathione (GSH) as a repressive effector for the expression of sulphate transporter genes.

All crops require nitrogen (N) for the production of a photosynthetically active canopy, whose functionality will strongly influence yield. Cereal crops also require N for storage proteins in the grain, an important quality attribute. Optimal efficiency is achieved by the controlled remobilization of canopy-N to the developing grain during crop maturation. Whilst N will always be required for crop production, targeting efficient capture and use will optimise consumption of this valuable macronutrient. Efficient management of N through agronomic practice and use of appropriate germplasm are essential for sustainability of agricultural production. Both the economic demands of agriculture and the need to avoid negative environmental impacts of N-pollutants, such as nitrate in water courses or release of N-containing greenhouse gases, are important drivers to seek the most efficient use of this critical agronomic input. New cultivars optimised for traits relating to N-use efficiency rather than yield alone will be required. Targets for genetic improvement involve maximising capture, partitioning and remobilization in the canopy and to the grain, and yield per se. Whilst there is existing genetic diversity amongst modern cultivars, substantial improvements may require exploitation of a wider germplasm pool, utilizing land races and ancestral germplasm.

Se is an essential element for animals. In man low dietary Se intakes are associated with health disorders including oxidative stress-related conditions, reduced fertility and immune functions and an increased risk of cancers. Although the reference nutrient intakes for adult females and males in the UK are 60 and 75 μg Se/d respectively, dietary Se intakes in the UK have declined from >60 μg Se/d in the 1970s to 35 μg Se/d in the 1990s, with a concomitant decline in human Se status. This decline in Se intake and status has been attributed primarily to the replacement of milling wheat having high levels of grain Se and grown on high-Se soils in North America with UK-sourced wheat having low levels of grain Se and grown on low-Se soils. An immediate solution to low dietary Se intake and status is to enrich UK-grown food crops using Se fertilisers (agronomic biofortification). Such a strategy has been adopted with success in Finland. It may also be possible to enrich food crops in the longer term by selecting or breeding crop varieties with enhanced Se-accumulation characteristics (genetic biofortification). The present paper will review the potential for biofortification of UK food crops with Se.

There is a growing need to increase global crop yields, whilst minimising use of resources such as land, fertilisers and water. Agricultural researchers use ground-based observations to identify, select and develop crops with favourable genotypes and phenotypes; however, the ability to collect rapid, high quality and high volume phenotypic data in open fields is restricting this. This study develops and assesses a method for deriving crop height and growth rate rapidly from multi-temporal, very high spatial resolution (1 cm/pixel), 3D digital surface models of crop field trials produced via Structure from Motion (SfM) photogrammetry using aerial imagery collected through repeated campaigns flying an Unmanned Aerial Vehicle (UAV) with a mounted Red Green Blue (RGB) camera. We compare UAV SfM modelled crop heights to those derived from terrestrial laser scanner (TLS) and to the standard field measurement of crop height conducted using a 2 m rule. The most accurate UAV-derived surface model and the TLS both achieve a Root Mean Squared Error (RMSE) of 0.03 m compared to the existing manual 2 m rule method. The optimised UAV method was then applied to the growing season of a winter wheat field phenotyping experiment containing 25 different varieties grown in 27 m² plots and subject to four different nitrogen fertiliser treatments. Accuracy assessments at different stages of crop growth produced consistently low RMSE values (0.07, 0.02 and 0.03 m for May, June and July, respectively), enabling crop growth rate to be derived from differencing of the multi-temporal surface models. We find growth rates range from −13 mm/day to 17 mm/day. Our results clearly display the impact of variable nitrogen fertiliser rates on crop growth. Digital surface models produced provide a novel spatial mapping of crop height variation both at the field scale and also within individual plots. This study proves UAV based SfM has the potential to become a new standard for high-throughput phenotyping of in-field crop heights.