A SWEET solution to rice blight

Bacterial blight is an important disease of rice that is particularly destructive in Southeast Asia and sub-Saharan Africa, exacerbated by the heavy rains of the monsoon seasons. Estimated crop loss due to bacterial blight may be as high as 75%, with millions of hectares of rice affected annually. In this issue, an international team of researchers describes the use of CRISPR editing to generate rice plants that are broadly resistant to the main pathogen that causes rice blight, Xanthomonas oryzae pv. oryzae (Xoo)1. To enhance the durability and management of resistance, the team has also developed a kit to trace the disease, and its virulence and resistance alleles2

Geographic patterns of phenotypic diversity in sorghum (Sorghum bicolor (L.) Moench) landraces from North Eastern Ethiopia

Understanding the pattern of genetic variability is an important component of germplasm collection and conservation as well as the crop’s improvement process including the selection of parents for making new genetic recombination. Nine hundred seventy four sorghum landraces from North Eastern (NE) Ethiopia were evaluated for agro-morphologic characters to assess geographic patterns of phenotypic diversity and to identify whether there are specific areas of high diversity for particular traits. The Shannon-Weaver diversity index (H′) for qualitative traits ranged from 0.30 to 0.93 (mean = 0.67) for grain covering and grain color, respectively. The landraces also displayed highly significant differences (p<0.01) for all the quantitative traits with days to flowering ranging from 64 to 157 days (range = 93), days to maturity from 118 to 215 (range=97) days, plant height from 115 to 478 cm; 1000-seeds weight from 18 to 73 g, and grain number from 362 to 9623. The first five principal component axes captured 71% of the total variation with days to flowering and maturity, leaf number and length, panicle weight, grain weight and number per panicle, panicle length, length of primary branches, 1000-seeds weight and internode length accounting for most of the variability. Cluster analysis grouped the landraces into ten clusters. The clustering of zones and districts revealed close relationship between geographic locations based on proximities and agro-ecological similarities. Differentiation analysis showed that most of the landraces variability was within rather than between geographic origins of the landraces, indicating weak genetic differentiation among landraces from predefined geographic origins such as political administrative zones and districts. The weak differentiation might be due to frequent gene flow across the study area because of seed exchanges among farmers

DNA markers reveal genetic structure and localized diversity of Ethiopian sorghum landraces

North Eastern Ethiopia is a major sorghum-growing region. A total of 415 sorghum landraces were sampled to represent the range of agro-ecologies (three altitude ranges) as well as spatial heterogeneity, that is, 4 zones: North Welo, South Welo, Oromiya and North Shewa with each zone containing 2 to 5 districts. The landraces were genotyped with simple sequence repeats (SSR) and inter simple sequence repeats (ISSR) markers. High genetic diversity was observed among the landraces for both marker systems. STRUCTURE analysis revealed 4 clusters of genetically differentiated groups of landraces. Cluster analysis revealed a close relationship between landraces along geographic proximity with genetic distance between landraces increasing with an increase in geographic distance. The grouping of landraces based on districts was influenced by clinal trend and geographic proximity. The FST statistics showed significant geographic differentiation among landraces at various levels of predefined geographic origin but a large portion of the variation was among landraces within rather than between predefined populations. The landraces from North Shewa were predominantly in one cluster, and landraces from this area also exhibited the greatest allelic diversity and the highest number of private alleles. There was low variation among the highland Zengada landraces, but these landraces were quite strongly differentiated and fell into one population cluster. The low to moderate genetic differentiation between landraces from various geographic origins could be attributed to gene flow across the region as a consequence of seed exchange among farmers

A 3-D wavelet analysis of substructure in the Coma cluster: statistics and morphology

Evidence for clustering within the Coma cluster is found by means of a multiscale analysis of the combined angular-redshift distribution. We have compiled a catalogue of 798 galaxy redshifts from published surveys from the region of the Coma cluster. We examine the presence of substructure and of voids at different scales ranging from $\sim 1 to \sim 16 h^{-1}$ Mpc, using subsamples of the catalogue, ranging from $cz=3000$ km/s to $cz=28000$ km/s. Our substructure detection method is based on the wavelet transform and on the segmentation analysis. The wavelet transform allows us to find out structures at different scales and the segmentation method allows us a quantitative statistical and morphological analysis of the sample. From the whole catalogue we select a subset of 320 galaxies, with redshifts between cz=5858 km/s and cz=8168 km/s that we identify as belonging to the central region of Coma and on which we have performed a deeper analysis, on scales ranging from $180 h^{-1}$ kpc to $1.44 h^{-1}$ Mpc. Our results are expressed in terms of the number of structures or voids and their sphericity for different values of the threshold detection and at all the scales investigated. According to our analysis, there is strong evidence for multiple hierarchical substructure, on scales ranging from a few hundreds of kpc to about $4 h^{-1}$ Mpc. The morphology of these substructures is rather spherical. On the scale of $720 h^{-1}$ kpc we find two main subclusters which where also found before, but our wavelet analysis shows even more substructures, whose redshift position is approximatively marked by these bright galaxies: NGC 4934 & 4840, 4889, 4898 & 4864, 4874 & 4839, 4927, 4875.Comment: 24 pages, 6 figures. ApJ (Main Journal), accepted for publication. Added one section on statistical tests and slightly modified text and abstrac

Peak residential electricity demand and social practices: deriving flexibility and greenhouse gas intensities from time use and locational data

Peak residential electricity demand takes place when people conduct simultaneous activities at specific times of the day. Social practices generate patterns of demand and can help understand why, where, with whom and when energy services are used at peak time. The aim of this work is to make use of recent UK time use and locational data to better understand: (i) how a set of component indices on synchronisation, variation, sharing and mobility indicate flexibility to shift demand; and (ii) the links between people’s activities and peaks in greenhouse gases’ intensities. The analysis is based on a recent UK time use dataset, providing 1 minute interval data from GPS devices and 10 minute data from diaries and questionnaires for 175 data days comprising 153 respondents. Findings show how greenhouse gases’ intensities and flexibility to shift activities vary throughout the day. Morning peaks are characterised by high levels of synchronisation, shared activities and occupancy, with low variation of activities. Evening peaks feature low synchronisation, and high spatial mobility variation of activities. From a network operator perspective, the results indicate that periods with lower flexibility may be prone to more significant local network loads due to the synchronization of electricity-demanding activities

Genomic interventions for sustainable agriculture

Agricultural production faces a Herculean challenge to feed the increasing global population. Food production systems need to deliver more with finite land and water resources while exerting the least negative influence on the ecosystem. The unpredictability of climate change and consequent changes in pests/pathogens dynamics aggravate the enormity of the challenge. Crop improvement has made significant contributions towards food security, and breeding climate-smart cultivars are considered the most sustainable way to accelerate food production. However, a fundamental change is needed in the conventional breeding framework in order to respond adequately to the growing food demands. Progress in genomics has provided new concepts and tools that hold promise to make plant breeding procedures more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing delineate breeding targets that could contribute to securing future food supply. In this review, we highlight key breakthroughs in plant genome sequencing and explain how the presence of these genome resources in combination with gene editing techniques has revolutionized the procedures of trait discovery and manipulation. Adoption of new approaches such as speed breeding, genomic selection and haplotype-based breeding could overcome several limitations of conventional breeding. We advocate that strengthening varietal release and seed distribution systems will play a more determining role in delivering genetic gains at farmer’s field. A holistic approach outlined here would be crucial to deliver steady stream of climate-smart crop cultivars for sustainable agriculture

Technological perspectives for plant breeding

New Breeding Technologies? For some, both inside and outside the scientific community, this phrase is synonymous with gene editing—or used exclusively to describe the application of CRISPR/Cas9 to plant improvement. Much as, historically, the term ‘biotech crops’ has been hijacked to only mean crop plants produced using genetic engineering. However, ‘breeding technologies’ refers not only to genetic modification using techniques of molecular biology, but also to a vast number of other techniques developed for breeding via the application of scientific advancements emanating from disciplines such as computer science, plant biology, statistics, automation, robotics and artificial intelligence. This concept is not new: in reality, technology has been a feature of crop improvement since early in the last century..

Differences in grass pollen allergen exposure across Australia

© 2015 The Authors © 2015 Public Health Association of Australia. Objective: Allergic rhinitis and allergic asthma are important chronic diseases posing serious public health issues in Australia with associated medical, economic, and societal burdens. Pollen are significant sources of clinically relevant outdoor aeroallergens, recognised as both a major trigger for, and cause of, allergic respiratory diseases. This study aimed to provide a national, and indeed international, perspective on the state of Australian pollen data using a large representative sample. Methods: Atmospheric grass pollen concentration is examined over a number of years within the period 1995 to 2013 for Brisbane, Canberra, Darwin, Hobart, Melbourne, and Sydney, including determination of the 'clinical' grass pollen season and grass pollen peak. Results: The results of this study describe, for the first time, a striking spatial and temporal variability in grass pollen seasons in Australia, with important implications for clinicians and public health professionals, and the Australian grass pollen-allergic community. Conclusions: These results demonstrate that static pollen calendars are of limited utility and in some cases misleading. This study also highlights significant deficiencies and limitations in the existing Australian pollen monitoring and data. Implications: Establishment of an Australian national pollen monitoring network would help facilitate advances in the clinical and public health management of the millions of Australians with asthma and allergic rhinitis