Push-pull fatigue properties of wires in an iridium - 5% tungsten alloy

Introduction This memorandum reports a series of tests to determine the fatigue properties of an iridium - 5% tungsten alloy at 600°c and 700°C. A previous memorandum, Memo. Mat. 61, reports the fatigue properties at room temperature of the same alloy

Involving Stakeholders in Crop-Livestock Systems Analysis: Innovation Platforms in Burkina Faso and Niger, West Africa

The development of markets and agricultural productivity need participative research approaches that involve farmers, stakeholders and actors in the value chains of agricultural products and inputs. This study illustrates the use of multi-stakeholder platforms to address critical issues that often curtail effective implementation of development strategies and achievement of objectives. The process used to facilitate stakeholder participation and achieve enhanced understanding of collective actions to achieve objectives is illustrated by case studies in Niger and Burkina Faso. The process that determines the causal relationships among the various problems is also presented; results from the process can be used to determine entry points for addressing system challenges. Finally, the study offers specific insights and analysis related to small-ruminant and feed value chains within Niger and Burkina Faso. The strengths and weaknesses of each node of the value chain are assessed and appropriate upgrading, management, and development strategies suggested. Entry points for action and strategies for intervention are identified to improve functioning of the crop-livestock value chain and the productivity of agro-pastoral farming systems. Participative analysis and understanding of the functioning of agricultural value chains enable farmers and actors to improve agricultural productivity and marketing. The multi-stakeholder platform approach is a more suitable tool for socio-economic analysis of integrated systems, and identification and implementation of development strategies, than traditional disciplinary research approaches

Regional Geological Visualisation Models

A series of 14 Regional Geological Visualisation Models (GV Models) for England, Wales and Northern Ireland have been produced to provide interactive, user-friendly tools for exploring the UK’s geology in three dimensions. The GV Models are designed for use on desktop/laptop computers and complement the existing range of free-of-charge digital data, maps and models that are published online by the BGS. The GV Models are based on the national fence diagram of the UK (UK3D v2015) with additional cross-sections developed along the regional boundaries, the BGS 1:625 000 scale digital bedrock geological map of the UK (DiGMapGB-625), and the BGS 1:250 000 scale marine bedrock map. These geological datasets have been combined with digital terrain, bathymetric and topographic data to develop 3D ‘block models’, displaying the bedrock geology of the upper 1.5 km of the crust. Users can manipulate the model to explore the region’s geology by switching on/off individual blocks, hiding or displaying groups of geological units, and zooming and rotating to view the blocks from any angle. The model legend provides information about the geological units, and select functions link to additional sources of information including the BGS Lexicon and scanned records of key boreholes that have informed the model’s development. The GV models can be downloaded via the following page of the BGS website: www.bgs.ac.uk/research/ukgeology/nationalGeologicalModel/GVModels.htm

Simulation of Lablab Pastures

The potential of legume-based pastures to address declining soil nitrogen on marginal cropping soils is increasingly recognised in northern Australia, as such there is a need for cost benefit analysis of pastures and crops in a mixed farming system. In highly variable rainfall environments, biophysical modelling may be the best way of identifying and quantifying interactions with mixed crop-livestock systems on a seasonal basis. This paper describes a case study where both animal productivity and lablab pasture production is simulated. Lablab (Lablab purpureus) is an annual tropical legume widely used as a short-term legume phase in crop-pasture rotations, providing high quality forage for animal production and a low risk nitrogen input for crop production

Evaluation of the feed quality of six dual purpose pearl millet varieties and growth performance of sheep fed their residues in Niger

Pearl millet (Pennisetum glaucum) is a staple food popularly cultivated by small farmers in Niger. The stover are also used as feeds for livestock (small ruminant) as basal diet, especially during the cold dry season. ICRISAT has developed many dualpurpose millet varieties that aim to increase feeds for livestock while providing grain as food to farmers. But the nutritional quality of Stover of these varieties for livestock are not known. This research aims to assess the quality of residues of the dual-purpose varieties and their effect on feed intake and live weight changes of young sheep

Innovation platforms as vehicle to strengthen stakeholders capacity to innovate for improved livelihoods in drylands in Asia and Sub Saharan Africa

Agriculture is the engine for poverty reduction and economic development in the developing nations The sector employs over 50 of the population in South Asia SA and Sub Saharan Africa SSA and contributes significantly to their Gross Domestic Product GDP McCullough Pingali and Stamoulis 2008 Majority of agricultural lands in these regions are drylands and vulnerable to droughts of various intensities These threats are far more pronounced in the semiarid and arid regions Globally drylands occupy some 609 billion ha with a population of 21 billion people nearly half of which are the poorest and most vulnerable and marginalized in the world UN 2013 Despite the importance of dryland agriculture for the livelihood security of millions of rural people the level of innovations and technological change in the sector continues to be slow and patchy Access to and adoption of technologies and innovations remain very low resulting in low productivity resource degradation and persistent poverty Many developing countries are now working towards improving rural livelihoods of smallholder farmers However achieving this goal will require transforming the traditional top down technologydriven extension model to a more decentralized farmerled and marketdriven extension system Innovation has become a focus of dryland agriculture development and innovation systems are the centre piece of many development projects These Innovation systems IS approaches emphasize the collective dimension of innovation pointing to the need to effect necessary linkages and interaction among multiple actors IS thinking also pays attention to the coevolution of innovation processes arguing that successful innovation results from alignment of technical social institutional and organizational dimensions Hall 2005 Hall 2007 These insights are increasingly informing interventions that focus on supporting multistakeholder arrangements such as innovation platforms IPs as mechanisms for enhancing agriculture innovations

Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud

The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (≥250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated fromsuch products. Thereby, the overarching goal of this study was to develop a high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, 10 time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the three timeperiods over 12 months (monsoon: Days of the Year (DOY) 151–300; winter: DOY 301–365 plus 1–60; and summer: DOY 61–150), taking the every 8-day data from Landsat-8 and 7 for the years 2013–2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the five agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledgebase for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N = 2179) in five AEZs. The classification was performed on GEE for each of the five AEZs using well-established knowledge-base and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N = 1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full-resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, atwww.croplands. org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/

Farm level rainwater harvesting across different agro climatic regions of India: Assessing performance and its determinants

Rainwater harvesting and its utilization have a very important role to play in harnessing the production potential within dryland systems. This study assesses the performance of small rainwater harvesting structures (farm-ponds) in 5 major rainfed states of India over the period 2009–2011 using data from multiple sources and stakeholders. Rainwater which is harvested using structures of varying types and sizes was used for either supplemental irrigation or recharging open-wells. In many cases, the farm level rainwater harvesting structures were highly effective for rainfed farming and had a multiplier effect on farm income. In some situations however, it was viewed by farmers as a waste of productive land. The use of farm ponds in Maharashtra, for example, resulted in a significant increase in farm productivity (12–72%), cropping intensity and consequently farm income. In the Chittoor district of Andhra Pradesh, farm pond water was profitably used for supplemental irrigation to mango plantations, vegetables or other crops and animal enterprises with net returns estimated to be between US$ 120 and 320 structure−1 annum−1. Despite such examples, the adoption of the farm ponds was low, except in Maharashtra. A functional analysis of the reasons for high adoption of water harvesting structures indicated that factors such as technical support, customized design, level of farmer participation, age, existing ownership of open wells, annual rainfall and household assets were the major determinants of performance of farm-level rainwater harvesting structures. Based on this countrywide analysis, different policy and institutional options are proposed for promoting farm-level rainwater-harvesting for dryland agriculture

Identifying Low Emissions Development Pathways – Synergies and Trade-offs: A Case Study of Mahbubnagar District, Telangana, India

This case study examines the opportunities for obtaining synergies between agricultural productivity, whole-farm profitability and greenhouse gas (GHG) mitigation and highlights where trade-offs exist. We explore how agricultural practices and systems can be designed and managed to balance the synergies and trade-offs for small-holder farmers in semi-arid India. We used data on farm-household characteristics and agricultural practices from 100 farm-households of Telangana state, India. Quantifying synergies and trade-offs between profitability, adaptation and mitigation we employed simulation modelling- crop, livestock and whole-farm simulation models, and Cool Farm Tool to estimate net GHG emissions. Our analysis reveals that specific plot-level crop management strategies and farm-level enterprise interventions can increase profitability as well as benefit climate change mitigation. It depict how farming systems can be managed to achieve synergies between profitability and mitigation outcomes and where, if any trade-offs exist. Combinations of reduced tillage, retaining crop-residue, improved nitrogen management, utilizing organic manure, improved livestock feeding practices, introducing agro-forestry could contribute to GHG abatement and improved profitability at our study site. Such multi-model systems analysis using participatory design and tools could help practitioners and policymakers to identify and promote use of management practices that can help achieve multiple objectives and guide investments towards synergistic climate smart agriculture strategies. Our study contributes empirical evidence to the debate surrounding integrated approaches to sustainable development goals and adaptation and mitigation objectives

Cross-kingdom signalling regulates spore germination in the moss <i>Physcomitrella patens</i>

Plants live in close association with microorganisms that can have beneficial or detrimental effects. The activity of bacteria in association with flowering plants has been extensively analysed. Bacteria use quorum-sensing as a way of monitoring their population density and interacting with their environment. A key group of quorum sensing molecules in Gram-negative bacteria are the N-acylhomoserine lactones (AHLs), which are known to affect the growth and development of both flowering plants, including crops, and marine algae. Thus, AHLs have potentially important roles in agriculture and aquaculture. Nothing is known about the effects of AHLs on the earliest-diverging land plants, thus the evolution of AHL-mediated bacterial-plant/algal interactions is unknown. In this paper, we show that AHLs can affect spore germination in a representative of the earliest plants on land, the Bryophyte moss Physcomitrella patens. Furthermore, we demonstrate that sporophytes of some wild isolates of Physcomitrella patens are associated with AHL-producing bacteria