Propolis is a bee product that has been extensively used in alternative medicine and recently has gained interest on a global scale as an essential ingredient of healthy foods and cosmetics. Propolis is also considered to improve human health and to prevent diseases such as inflammation, heart disease, diabetes and even cancer. However, the claimed effects are anticipated to be correlated to its chemical composition. Since propolis is a natural product, its composition is consequently expected to be variable depending on the local flora alignment. In this work, we present the development of a novel HPLC-PDA-ESI/MS targeted method, used to identify and quantify 59 phenolic compounds in Greek propolis hydroalcoholic extracts. Amongst them, nine phenolic compounds are herein reported for the first time in Greek propolis. Alongside GC-MS complementary analysis was employed, unveiling eight additional newly reported compounds. The antioxidant activity study of the propolis samples verified the potential of these extracts to effectively scavenge radicals, with the extract of Imathia region exhibiting comparable antioxidant activity to that of quercetin.

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SummaryNon-destructive assessment of herbicide effects may be able to support integrated weed management. To test whether effects of herbicides on canopy variables could be detected by sensors, two crops were used as models and treated with herbicides at BBCH 20 using a logarithmic sprayer. Twelve days after spraying at BBCH 25 and 42 days after sowing, nine sensor systems scanned a spring barley and an oilseed rape field experiment sown at different densities and sprayed with increasing field rates of glyphosate and tribenuron-methyl. The objective was to compare ED 50 s for crops and weeds derived by the different sensors in relation to crop density and herbicides. Although sensors were not directly developed to detect herbicide symptoms, they all detected changes in canopy colours or height and crop density. Generally ED 50 s showed the same pattern in response to crop density within herbicide, but there were marked differences between barley and oilseed rape. We suggest that the results of comparing the various sensor outputs could become a stepping stone to future standardisation for the benefit of the research and development of sensors that will detect herbicide effect on crops and weeds, particularly at the most vulnerable stages of development of the canopy.

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Farmers need to make decisions that in most cases incorporate the concept of prediction and can hardly be revoked. One such decision is the application of fertilizing inputs. During past crop management and decision-making on fertilizing practices, many significant errors have been recorded, which have led and continue to lead to reduced production and environmental burden. The methodology followed in this paper involves the use of GIS, fuzzy logic and expert knowledge, in order to model physical processes associated with nitrogen balance in cultivated ecosystems and to evaluate the capabilities of or limitations on the use of certain fertilizers, based on spatial criteria. An original spatial decision support system was designed, developed and applied in a given study area. The system is composed of two modules ("fertilizing rate" and "fertilizing type"), making use of soil, climate and cultivation practices' data, as recorded in the area of interest in quantitative or categorical form. The results of the application spatially classify the involved area according to its demand for nitrogen on the basis of the characteristics of each sub-region. The "fertilizing rate" module suggests reduced fertilizing doses of nitrogenous fertilizers compared to those already applied in the area. The system further divides the area into zones where specific types of fertilizers should be applied, giving a certain prescription for the method and time of application. OPEN ACCESSSustainability 2015, 7 6685