Agronomic characteristics of the spring forms of the wheat landraces (einkorn, emmer, spelt, intermediate bread wheat) grown in organic farming

Organic farmers look to the possibilities of growing neglected crops, such as the spring forms of hulled wheat – einkorn, emmer and spelt – for support in developing the organic farming system. In 2008, 169 landraces from the gene bank at the Crop Research Institute in Prague were tested on certifi ed organic plots. The experiment was aimed at fi nding suitable varieties for the organic farming system. In summary, our fi ndings show that einkorn (Triticum monococcum L.) and emmer wheat [Triticum dicoccum Schrank (Schuebl)] are resistant to powdery mildew and brown rust, spelt wheat (Triticum spelta L.) is less resistant to these two diseases, and the intermediate forms of bread wheat are very sensitive to such infestation. The varieties evaluated incline to lodging, as they have long and weak stems. Einkorn and emmer wheat have short and dense spikes and a low thousand grains weight, whereas spelt wheat has long and lax spikes. The level of the harvest index is low. Potentially useful varieties were found during the fi eld experiment and evaluation, and our future efforts will therefore focus on improving resistance to lodging and increasing the productivity of the spike

Detection and attribution of human influence on regional precipitation

Understanding how human influence on climate is affecting precipitation around the world is immensely important for defining mitigation policies, and for adaptation planning. Yet despite increasing evidence for the influence of climate change on global patterns of precipitation, and expectations that significant changes in regional precipitation should have already occurred as a result of human influence on climate, compelling evidence of anthropogenic fingerprints on regional precipitation is obscured by observational and modelling uncertainties and is likely to remain so using current methods for years to come. This is in spite of substantial ongoing improvements in models, new reanalyses and a satellite record that spans over thirty years. If we are to quantify how human-induced climate change is affecting the regional water cycle, we need to consider novel ways of identifying the effects of natural and anthropogenic influences on precipitation that take full advantage of our physical expectations

Improving the Classification of Multiple Disorders with Problem Decomposition

Abstract Differential diagnosis of multiple disorders is a challenging problem in clinical medicine. According to the divide-and-conquer principle, this problem can be handled more effectively through decomposing it into a number of simpler sub-problems, each solved separately. We demonstrate the advantages of this approach using abductive network classifiers on the 6-class standard dermatology dataset. Three problem decomposition scenarios are investigated, including class decomposition and two hierarchical approaches based on clinical practice and class separability properties. Two-stage classification schemes based on hierarchical decomposition boost the classification accuracy from 91% for the single-classifier monolithic approach to 99%, matching the theoretical upper limit reported in the literature for the accuracy of classifying the dataset. Such models are also simpler, achieving up to 47% reduction in the number of input variables required, thus reducing the cost and improving the convenience of performing the medical diagnostic tests required. Automatic selection of only relevant inputs by the simpler abductive network models synthesized provides greater insight into the diagnosis problem and the diagnostic value of various disease markers. The problem decomposition approach helps plan more efficient diagnostic tests and provides improved support for the decision making process. Findings are compared with established guidelines of clinical practice, results of data analysis, and outcomes of previous informatics-based studies on the dataset. Keywords: Classifiers, Abductive Networks, Neural Networks, Problem Decomposition, Divide and Conquer, Classification Accuracy, Data Reduction, Modular Networks, Medical Diagnosis, Multiple Disorders, Dermatology.

Weathering of Precambrian basement and formation of sedimentary particles in Scania

This study describes weathering pattern in saprolites of the Vånga Granite along various profiles at Ivö Klack, Scania (southern Sweden) and provides a model against which paleo-chemical weathering of ancient profiles (e.g. Utsira High) can be compared. These weathering profiles have been analyzed combining field data with XRD, thin sections and SEM analyses. Special emphasis has been on secondary minerals formation associated with paleoclimate, composition of primary minerals and its distribution in parent rock. Intrusive origin is attributed to the Vånga Granite which has composition between monzogranite and syenogranite (plotted on Streckeisen diagram). Sericite needles identified on plagioclase grains approve post-magmatic alteration of fresh granite. Two weathering profiles namely; profile-1 and profile-2, have been investigated in detail to give a representative overview on weathering processes prevailed at the locality. Two weathering stages (initial and advanced stage of weathering) have been designated to weathering profiles based on XRD% of three minerals (kaolinite, plagioclase and K-feldspar). Chemical weathering reactions largely include transformation of feldspars and phyllosilicates to kaolinite, smectite, illite and vermiculite. Plagioclase, especially anorthite content, and biotite are readily affected by weathering whereas K-feldspar stands out as more resistant mineral phase. During initial stage of weathering, pore waters achieve equilibrium with K-feldspar, kaolinite and illite. As weathering proceeds (upon total consumption of plagioclase) formation of kaolinite increases greatly due to dissolution of potassic phases. Three clay mineral phases (smectite, illite and kaolinite) are observed in both weathering profiles. In most weathered samples from both weathering profiles kaolinite˃˃ illite ˃ smectite. Deep kaolinite weathering and argillization at the study area started in humid tropical climate of the Rhaetian. Weathering of bedrock continued in humid tropical to sub-tropical climate from the Late Triassic to Late Cretaceous until Campanian Sea transgressed the area. Further, saprolites were covered and preserved with Late Cretaceous carbonates until quarrying of limestone and kaolinite in late 19th century. Keywords: Scania, Ivö Klack, weathering profiles, weathering stages, chemical weathering, secondary minerals, kaolinite weathering, XRD, clay mineralogy

Component analysis of nutritionally rich chloroplasts: recovery from conventional and unconventional green plant species

A study of the literature indicates that chloroplasts synthesise a range of molecules, many of which have nutritional value for humans, but as yet no one has established the nutritional credentials of chloroplasts recovered from plant cells. Chloroplast-rich-fractions (CRFs) were prepared from green plant species and the macro- and micronutrient composition compared with the whole leaf materials (WLMs). The results indicated that, on a dry weight basis, CRF material from a range of green biomass was enriched in lipids and proteins, and in a range of micronutrients compared with the WLM. Vitamins E, pro-vitamin A, and lutein were all greater in CRF preparations. Of the minerals, iron was most notably concentrated in CRF. Spinach CRFs possessed the highest α-tocopherol (62 mg 100 g-1 , dry weight (DW)), β-carotene (336 mg 100 g- 1 DW) and lutein (341 mg 100 g-1 DW) contents, whilst grass CRFs had the highest concentration of alpha-linolenic acid (ALA) (69.5 mg g-1). The higher concentrations of α-tocopherol, β-carotene, lutein, ALA and trace minerals (Fe and Mn) in CRFs suggest their potential use as concentrated ingredients in food formulations deficient in these nutrients

Anaerobic Digestion of food waste:eliciting sustainable water-energy-food nexus practices with Agent Based Modelling and visual analytics

Food waste is a problem for which solutions are recognised but not readily put into practice. What should be the primary objective, reducing or eliminating surplus food production, requires great change within social, cultural and economic structures. The secondary approach of redistributing surplus food to areas of deficit (in terms of socioeconomic groups and/or geographic regions) involves a significant logistical burden, and suffers the same issues as with the elimination of waste. The least desirable, but perhaps most practicable approach, is the use of food waste as a feedstock for Anaerobic Digestion (AD). The strategic adoption of AD can therefore be seen as an important step towards mitigating food waste, but the implementation of efficient AD systems on a large (county/region) scale involves significant complexity. The optimal number, size and location of AD plants, and whether they arecentralised versus decentralised, may be determined by considering factors such as supply and proximity to feedstock, transport links, emission hazards and social impact. Reaching balanced and objective decisions when faced with such disparate criteria is inevitably very difficult. To address this problem we prototype and evaluate a decision support tool for county-scale AD planning. Our approach is a hybridised Agent Based Model (ABM) with a Multi Objective Optimisation. We capture the spatio-temporal dependencies that exist in the water, energy and food systems associated with energy derived from food waste using Agent Based Modelling (ABM). The use of Visual Analytics in the form of Interactive Multi Criteria analysis offers a means to communicate the co-benefits and trade-offs that may emerge, as well as prioritise the AD strategies. Specifically, the method supports exploration of the social, environmental and economic impact of different AD strategies and decisions, linked to current issues, namely AD scale and adoption. The interactive MCA allows users to explore and understand the WEF impact of different implementations and management policies, based on the weighting of criteria. The results highlight a trade-off between transport costs and social acceptability for the AD centralised versus decentralised strategies. When low carbon options are more important, then slow, steady and aggressive decentralised strategies are the closest to the ideal, with centralised aggressive being the furthest from the ideal - i.e. worst option. Conversely, when Energy production is considered with a greater weighting, then aggressive scaling up in a centralised approach is best with slow and steady approaches being further from the ideal. The framework has demonstrated that it permits a space for dialogue and transparent prioritization of AD strategies based on WEF nexus impacts