A spatial analysis of lime resources and their potential for improving soil magnesium concentrations and pH in grassland areas of England and Wales

Magnesium (Mg) is essential for animal health. Low Mg status (hypomagnesaemia) can be potentially fatal in ruminants, like cattle and sheep, and is widespread in Europe with economic impacts on farming. The application of Mg-rich agricultural lime products can help to ensure pasture forage consumed by animals contains sufficient Mg and, in areas of low pH, has the dual benefit of reducing soil acidity to levels best suited for grass production. This aim of this study was to determine if Mg-rich lime products could be used in a more effective manner in agricultural production systems. Potential resources of carbonate rocks (limestone, dolostone and chalk) in the UK, and their Mg:Ca status were identified, using datasets from the British Geological Survey (BGS). These data were combined with the locations of agricultural lime quarries, and areas where soils are likely to be deficient in Mg and/or require liming. Areas of potential demand for Mg-rich agricultural lime include areas in south east Wales, the Midlands and North East England. Although, areas where this may be an effective solution to low soil Mg values are restricted by the availability of suitable products. Conversely, areas of low soil pH in England and Wales are often found close to quarries with the ability to supply high Ca limes, suggesting that the low rates of lime use and liming is not due to supply factors. This study provides information that can help to guide on-farm decision making for use of Mg-rich and other lime resources. This could be used in conjunction with other options to reduce risks of Mg deficiency in livestock, and improve soil pH

Juvenile root traits show limited correlation with grain yield, yield components and grain mineral composition traits in Indian wheat under hostile soils

Correlations between juvenile wheat root traits, and grain yield and yield component traits under optimal field conditions have previously been reported in some conditions. The aim of this study was to test the hypothesis that juvenile wheat root traits correlate with yield, yield components and grain mineral composition traits under a range of soil environments in India. A diverse panel of 36 Indian wheat genotypes were grown for ten days in ‘pouch and wick’ high-throughput phenotyping (HTP) system (20 replicates). Correlations between juvenile root architecture traits, including primary and lateral root length, and grain yield, yield components and grain mineral composition traits were determined, using field data from previously published experiments at six sites in India. Only a limited number of juvenile root traits correlated with grain yield (GYD), yield components, and grain mineral composition traits. A narrow root angle, potentially representing a ‘steep’ phenotype, was associated with increased GYD and harvest index (HI) averaged across sites and years. Length related root traits were not correlated with GYD or HI at most sites, however, the total length of lateral roots and lateral root number correlated with GYD at a sodic site of pH 9.5. The total length of lateral roots (TLLR) correlated with grain zinc (Zn) concentration at one site. A wider root angle, representing a shallow root system, correlated with grain iron (Fe) concentration at most sites. The total length of all roots (TLAR) and total length of primary roots (TLPR) correlated with grain S concentration at most sites. Narrow root angle in juvenile plants could be a useful proxy trait for screening germplasm for improved grain yield. Lateral root and shallow root traits could potentially be used to improve grain mineral concentrations. The use of juvenile root traits should be explored further in wheat breeding for diverse environments

Iodine source apportionment in the Malawian diet

The aim of this study was to characterise nutritional-I status in Malawi. Dietary-I intakes were assessed using new datasets of crop, fish, salt and water-I concentrations, while I status was assessed for 60 women living on each of calcareous and non-calcareous soils as defined by urinary iodine concentration (UIC). Iodine concentration in staple foods was low, with median concentrations of 0.01 mg kg−1 in maize grain, 0.008 mg kg−1 in roots and tubers, but 0.155 mg kg−1 in leafy vegetables. Freshwater fish is a good source of dietary-I with a median concentration of 0.51 mg kg−1. Mean Malawian dietary-Iodine intake from food, excluding salt, was just 7.8 μg d−1 compared to an adult requirement of 150 μg d−1. Despite low dietary-I intake from food, median UICs were 203 μg L−1 with only 12% defined as I deficient whilst 21% exhibited excessive I intake. Iodised salt is likely to be the main source of dietary I intake in Malawi; thus, I nutrition mainly depends on the usage and concentration of I in iodised salt. Drinking water could be a significant source of I in some areas, providing up to 108 μg d−1 based on consumption of 2 L d−1

Quantitative trait loci (QTLs) linked with root growth in lettuce (Lactuca sativa) seedlings

In-field variation of transplanted lettuce (Lactuca sativa L.) due to variable soil and environmental conditions is one of the major restrictions in the optimization of production and yield. Marker-assisted breeding for lettuce varieties with a more rapid rooting phenotype has the potential to improve the performance of lettuce transplants. This study aimed to identify traits linked with increased primary root length, lateral root length and lateral root emergence in 14-day L. sativa seedlings from an intra-specific cross (Saladin × Iceberg). In total, 16 significant quantitative trait loci (QTLs) were associated with increased root growth traits that would allow direct introgression of the traits. Six of the QTLs were associated with increased primary root growth, accounting for 60.2% of the genetic variation for the trait. Three QTLs were associated with lateral root growth (38.6% of genetic variation); two QTLs were associated with lateral root length density (27.6% of genetic variation) and three with root number density (33.4% of genetic variation), and two QTLs were associated with mean lateral root length (21.1% of genetic variation). The statistical QTLs were located across 9 different linkage groups (LGs) representing loci on 7 of the 9 L. sativa chromosomes. A combination of restriction fragment length polymorphism (RFLPs) and Kompetitive allele specific PCR (KASPs) markers linked to these rooting traits were identified, which could allow breeders to select for a rapid establishment phenotype

Spatial prediction of the concentration of selenium (Se) in grain across part of Amhara Region, Ethiopia

Grain and soil were sampled across a large part of Amhara, Ethiopia in a study motivated by prior evidence of selenium (Se) deficiency in the Region's population. The grain samples (teff, Eragrostis tef, and wheat, Triticum aestivum) were analysed for concentration of Se and the soils were analysed for various properties, including Se concentration measured in different extractants. Predictive models for concentration of Se in the respective grains were developed, and the predicted values, along with observed concentrations in the two grains were represented by a multivariate linear mixed model in which selected covariates, derived from remote sensor observations and a digital elevation model, were included as fixed effects. In all modelling steps the selection of predictors was done using false discovery rate control, to avoid over-fitting, and using an α-investment procedure to maximize the statistical power to detect significant relationships by ordering the tests in a sequence based on scientific understanding of the underlying processes likely to control Se concentration in grain. Cross-validation indicated that uncertainties in the empirical best linear unbiased predictions of the Se concentration in both grains were well-characterized by the prediction error variances obtained from the model. The predictions were displayed as maps, and their uncertainty was characterized by computing the probability that the true concentration of Se in grain would be such that a standard serving would not provide the recommended daily allowance of Se. The spatial variation of grain Se was substantial, concentrations in wheat and teff differed but showed the same broad spatial pattern. Such information could be used to target effective interventions to address Se deficiency, and the general procedure used for mapping could be applied to other micronutrients and crops in similar settings

Epidemiology of neuromyelitis optica spectrum disorder and its prevalence and incidence worldwide

Neuromyelitis optica spectrum disorder (NMOSD) is an uncommon inflammatory disease of the central nervous system, manifesting clinically as optic neuritis, myelitis, and certain brain and brainstem syndromes. Cases clinically diagnosed as NMOSD may include aquaporin 4 (AQP4)-antibody-seropositive autoimmune astrocytopathic disease, myelin oligodendrocyte glycoprotein (MOG)-antibody-seropositive inflammatory demyelinating disease, and double-seronegative disease. AQP4-antibody disease has a high female-to-male ratio (up to 9:1), and its mean age at onset of ~40 years is later than that seen in multiple sclerosis. For MOG-antibody disease, its gender ratio is closer to 1:1, and it is more common in children than in adults. Its clinical phenotypes differ but overlap with those of AQP4-antibody disease and include acute disseminated encephalomyelitis, brainstem and cerebral cortical encephalitis, as well as optic neuritis and myelitis. Double-seronegative disease requires further research and clarification. Population-based studies over the past two decades report the prevalence and incidence of NMOSD in different populations worldwide. One relevant finding is the varying prevalence observed in different racial groups. Consistently, the prevalence of NMOSD among Whites is ~1/100,000 population, with an annual incidence of <1/million population. Among East Asians, the prevalence is higher, at ~3.5/100,000 population, while the prevalence in Blacks may be up to 10/100,000 population. For MOG-antibody disease, hospital-based studies largely do not observe any significant racial preponderance so far. This disorder comprises a significant proportion of NMOSD cases that are AQP4-antibody-seronegative. A recent Dutch nationwide study reported the annual incidence of MOG-antibody disease as 1.6/million population (adult: 1.3/million, children: 3.1/million). Clinical and radiological differences between AQP4-antibody and MOG-antibody associated diseases have led to interest in the revisions of NMOSD definition and expanded stratification based on detection of a specific autoantibody biomarker. More population-based studies in different geographical regions and racial groups will be useful to further inform the prevalence and incidence of NMOSD and their antibody-specific subgroups. Accessibility to AQP4-antibody and MOG-antibody testing, which is limited in many centers, is a challenge to overcome. Environmental and genetic studies will be useful accompaniments to identify other potential pathogenetic factors and specific biomarkers in NMOSD

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives