431 research outputs found
Role of Competition in Restoring Resource Poor Arid Systems Dominated by Invasive Grasses
An understanding of competition intensity and importance may be a useful step in helping managers understands how to prioritize restoration efforts in resource poor environments within the semi-arid steppe. The aims of this study were to quantify the intensity of competition among invasive annual grasses and native perennial bunchgrasses, and determine the importance of competition in explaining variation in target plant biomass and survivorship in a Wyoming big sagebrush steppe community type in southeastern Oregon, USA. Addition series experiments were conducted in 2008 and 2009 among four species. Treatments consisted of monoculture densities of each species to assess intraspecific competition, and mixtures of two, three and four species (interspecific competition), producing varying total densities and species proportions. We found no evidence that intensity of intra- or inter-specific competition were significant for the first two years species were establishing, regardless of the density used as the independent variable. Our results indicate that neither the intensity of competition nor the importance of competition explained variation in target plant biomass and survivorship for the first two years plants were establishing. Instead abiotic factors may have an overriding influence on plant biomass and survivorship.We propose four scenarios which may apply to semi-arid environments during the initial phase of restoration
Designer rice: New concept for climate change
Rice is the most important cereal crop that has been referred as global grain because of its use as prime staple food in about 100 countries of the world. Chhattisgarh popularly known as ‘Rice Bowl of India’. The rising demand saturation of cultivable field and climate change cause a supply shortage of a crop in the near future. The impact of climate change has serious implications for productivity and production of crops, thus threatening our food security and health and livelihood of millions. By the near 2025, about 785 million tonnes of paddy which is 70% more than the current production is needed to meet the growing demand. To achieve the expected yield and hike the productivity of rice, it becomes necessary to design rice according to change climate. The newly designed plant type was mainly based on the results of simulation modeling and new traits were mostly morphological. The proposed new plant type has low tillering capacity, few unproductive tillers, more filled grains per panicle, plant height of 90-100 cm, thick and sturdy stems, leaves that are thick, dark green and erect, a vigorous root system, 100-135 days crop duration and increased harvest index. Therefore, there is an urgent need for the development of designer varieties to sustain and enhance the productivity and production of agricultural crops even in changing climate regimes
Collection and conservation of extinct land races of rice from Raigarh district of Chhattisgarh
An exploration trip was conducted during kharif 2012-13 for the collection of rare and valuable rice land races from different blocks of raigarh district. A total of 97 landraces were collected by the exploration team from 41 villages of four different blocks viz., Tamnar, Gharghoda, Lailunga and Dharamjaigarh from Raigarh district. Based on the morphological and quality characters the diverse landraces were collected. The valuable landrace conserved by farmers namely, Borojhari, Boonde, Geeta, Saria, Thadvel, Bathras, Agiasal, Ratanchuri, Goirmal, Pangudi, 90 No., Ganga and Sonakathi. These valuable landraces possesses the characterstics such as fine grain, aroma, red pericarp, early maturity, submergence tolerance and good head rice recovery. The collected landraces will be utilized for the genetic enhancement and value addition of existing varieties of rice. Thus, it may be helpful not only in conserving the genetic resources but also exploit their potential in terms of yield and other quality characters
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Field growth comparisons of invasive alien annual and native perennial grasses in monocultures
Throughout the western United States, the invasive annual grass, medusahead (Taeniatherum caput-medusae L. Nevski), is rapidly invading grasslands once dominated by native perennial grasses, such as bluebunch wheatgrass (Pseudoroegneria spicata (Pursh) A). It is also invading grasslands dominated by less undesirable invasive annual grasses, especially cheatgrass (Bromus tectorum L.). Understanding medusahead growth dynamics relative to native perennial grasses and cheatgrass is central to predicting and managing medusahead invasion. We hypothesized that medusahead would have a higher relative growth rate (RGR), a longer period of growth, and as a consequence, more total biomass at the end of the growing season than the native perennial grass and cheatgrass. In 2008 (dry conditions), 250 seeds and in 2009 (wet conditions), 250 and 100 seeds of 25 each species were sown in 1 m2 plots with 5 replicates. Shoots were harvested on 3-25 day intervals throughout the growing season. The native perennial grass had more biomass and higher RGR than medusahead in the dry year, but the relationship was reversed in the wet year. Precipitation in 2008 was well-below average and this level of drought is very infrequent based on historical weather data. Medusahead had a longer period of growth and more total biomass than cheatgrass for both years. We expect that medusahead will continue to invade both native perennial and less undesirable invasive annual grasslands because of its higher RGR and extended period of growth.This is the author's after peer-review, corrected proof. It contains no copy editing. The published version is copyrighted by Elsevier and can be found here: http://www.elsevier.com/wps/find/journaldescription.cws_home/622855/description#descriptio
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Modelling outcomes after paediatric brain injury with admission laboratory values: a machine-learning approach.
BACKGROUND: Severe traumatic brain injury (TBI) is a leading cause of mortality in children, but the accurate prediction of outcomes at the point of admission remains very challenging. Admission laboratory results are a promising potential source of prognostic data, but have not been widely explored in paediatric cohorts. Herein, we use machine-learning methods to analyse 14 different serum parameters together and develop a prognostic model to predict 6-month outcomes in children with severe TBI. METHODS: A retrospective review of patients admitted to Cambridge University Hospital's Paediatric Intensive Care Unit between 2009 and 2013 with a TBI. The data for 14 admission serum parameters were recorded. Logistic regression and a support vector machine (SVM) were trained with these data against dichotimised outcomes from the recorded 6-month Glasgow Outcome Scale. RESULTS: Ninety-four patients were identified. Admission levels of lactate, H+, and glucose were identified as being the most informative of 6-month outcomes. Four different models were produced. The SVM using just the three most informative parameters was the best able to predict favourable outcomes at 6 months (sensitivity = 80%, specificity = 99%). CONCLUSIONS: Our results demonstrate the potential for highly accurate outcome prediction after severe paediatric TBI using admission laboratory data
What do we know about business strategy and environmental research? Insights from Business Strategy and the Environment
Phytophthora blight of Pigeonpea [Cajanus cajan (L.) Millsp.]: An updating review of biology, pathogenicity and disease management
Phytophthora blight (PB), Phytophthora drechsleri Tucker f.sp. cajani (Pal et al.) Kannaiyan et al. is reoccurring as an economically important disease of pigeonpea [Cajanus cajan (L.) Millsp.], especially when excessive rains fall with in short span of time and hot and humid weather persists during the crop season. A few years after the initial reviews of Kanniyan et al. (1984), the disease was coming to halt. Despite earlier investigations on pathological and physiological characteristics of P. drechsleri f. sp. cajani, the nature of infection process and genetic basis of pathogen variability have not been clearly established. Therefore, information on the biology and survival of the pathogen is needed to devise effective management strategies. Attempts have been made to develop green-house and field screening techniques three decades ago for identification of HPR. However, only few pigeonpea germplasm and breeding lines belonging to cultivated and wild Cajanus spp. were found tolerant to PB. The recent frequent recurrence of PB epidemics in the major pigeonpea growing areas prioritized the search for higher levels of disease resistance. There is a need to study the biology of the pathogen, epidemiology of the disease and refinement of the resistance screening techniques and develop integrated disease management (IDM) technology for the disease. In this review, the symptomatology of the disease, biology of pathogen including its variability, epidemiology, sources of resistance, other management options, and available information on biochemical and genetic basis of disease resistance have been updated and discussed with the identification of future research priorities
Barriers to the Development of Smart Cities in Indian Context
Smart city development is gaining considerable recognition in the systematic literature and international policies throughout the world. The study aims to identify the key barriers of smart cities from a review of existing literature and views of experts in this area. This work further makes an attempt on the prioritisation of barriers to recognise the most important barrier category and ranking of specific barriers within the categories to the development of smart cities in India. Through the existing literature, this work explored 31 barriers of smart cities development and divided them into six categories. This research work employed fuzzy Analytic Hierarchy Process (AHP) technique to prioritise the selected barriers. Findings reveal that ‘Governance’ is documented as the most significant category of barriers for smart city development followed by ‘Economic; ‘Technology’; ‘Social’; ‘Environmental’ and ‘Legal and Ethical’. In this work, authors also performed sensitivity analysis to validate the findings of study. This research is useful to the government and policymakers for eradicating the potential interferences in smart city development initiatives in developing countries like India
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