626 resultados para Marrubium vulgare
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2010, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2013, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2008, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers.
Resumo:
This data set contains aboveground community biomass in 2009 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2009 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in three rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for all biomass measures are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.
Resumo:
This data set contains aboveground community biomass in 2010 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2010 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for all biomass measures are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2002, vegetation cover was estimated only once in Septemper just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2002, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2003, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2003, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2005, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2005, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2006, vegetation cover was estimated twice in June and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2006, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2007, vegetation cover was estimated twice in June and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2007, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2004, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2004, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.
Resumo:
An ethnobotanical survey of medicinal plants was carried out in the Central Middle Atlas in the years 2013 and 2014 to establish the catalog of medicinal plants used in traditional medicine in the treatment of diabetes. Thus, 1560 people were interviewed, using questionnaires. The latter enabled us to gather information on traditional healing practices of the local population including scientific name, French name, vernacular name, plant parts used , therapeutic indications , revenues and mode of administration. The results show that 76 medicinal species were inventoried in the study area. These plant species are included into 67 genus and 40 families. The most represented families are: Lamiaceae (12 species), Asteraceae and Brassicaceae species with 14 each. Of 76 medicinal species found in the region, four species are reported for the first time in the traditional treatment of diabetes in Morocco. They are Pistacia atlantica, Ptychotis verticillata, Anacyclus pyrethrum, Alyssum spinosum, Cistus albidus, Juniperus thurifera, Ephedra nebrodensis, Thymus algeriensis, Th. munbyanus, Th. zygis, Abelmoschus esculentus, Fraxinus augustifolia, Sorghum vulgare and, Eriobotrya japonica. The leaves are the most used organs (38%). The decoction is the dominant mode of preparation (50%) and administration is mostly for oral use (97%).
Resumo:
The processing of meats at the factory level can trigger the onset of lipid oxidation, which can lead to meat quality deterioration. Warmed over flavor is an off-flavor, which is associated with oxidative deterioration in meat. To avoid or delay the auto-oxidation process in meat products, synthetic and natural antioxidants have been successfully used. Grape (Vitis Vinifera) is of special interest due to its high content of phenolic compounds. Grape seed extract sold commercially as a dietary supplement, has the potential to reduce lipid oxidation and WOF in cooked ground beef when added at 1%. The objective of study 1 was to compare the antioxidant activity of natural antioxidants including grape seed extract and some herbs belonging to the Lamiaciae family: rosemary (Rosmarinus Officinalis), sage (Salvia Officinalis) and oregano (Origanum Vulgare) with commercial synthetic antioxidants like BHT, BHA, propyl gallate and ascorbic acid using the ORAC assay. All sample solutions were prepared to contain 1.8 gm sample/10 ml solvent. The highest antioxidant activity was observed for the grape seed extract sample (359.75 µM TE), while the lowest was observed for BHA, propyl gallate and rosemary also showed higher antioxidant potential with ORAC values above 300 μmol TE/g. ORAC values obtained for ascorbic acid and Sage were between 250-300μ mol TE/g while lowest values were obtained for Butylated Hydroxytoluene (28.50 µM TE). Based on the high ORAC values obtained for grape seed extract, we can conclude that byproducts of the wine/grape industry have antioxidant potential comparable to or better than those present in synthetic counterparts. The objective of study 2 was to compare three levels of grape seed extract (GSE) to commonly used antioxidants in a pre-cooked, frozen, stored beef and pork sausage model system. Antioxidants added for comparison with control included grape seed extract (100, 300, 500 ppm), ascorbic acid (AA, 100 ppm of fat) and propyl gallate (PG, 100 ppm of fat). Product was formed into rolls, frozen, sliced into patties, cooked on a flat griddle to 70C, overwrapped in PVC, and then frozen at –18C for 4 months. GSE- and PG-containing samples retained their fresh cooked beef odor and flavor longer (p<0.05) than controls during storage. Rancid odor and flavor scores of GSE-containing samples were lower (p<0.05) than those of controls after 4 months of storage. The L* value of all samples increased (p<0.05) during storage. Thiobarbituric acid reactive substances (TBARS) of the control and AA-containing samples increased (p<0.05); those of GSE-containing samples did not change significantly (p>0.05) over the storage period.
Resumo:
In the present study, natural occurrence of fungi and aflatoxin B1 (AFB1) in pellet feed and feed ingredients used for rainbow trout was investigated with emphasis to Aspergillus section Flavi members and medicinal plants inhibitory to Aspergillus growth and/or AF production. The feed samples were cultured on the standard isolation media including dichloran rosebengal chloramphenicol agar (DRCA) and Aspergillus flavus/parasiticus agar (AFPA) for 2 weeks at 28 °C. Identification of fungal isolates was implemented based on the macro- and microscopic morphological criteria. AFs were detected using high performance liquid chromatography (HPLC). Based on the results obtained, a total of 109 fungal isolates were identified of which Aspergillus was the prominent genus (57.0%), followed by Penicillium (12.84%), Absidia (11.01%) and Pseudallscheria (10.10%). The most frequent Aspergillus species was A. flavus (60.66%) isolated from all the feed ingredients as well as pellet feed. Among 37 A. flavus isolates, 19 (51.35%) were able to produce AFB1 on yeast extract-sucrose (YES) broth in the range of 10.2 to 612.8 [tg/g fungal dry weight. HPLC analyses of trout feed showed that pellet feed and all feed ingredients tested except gluten were contaminated with different levels of AFB1 in the range of 1.83 to 67.35 lig/kg. In order to finding natural inhibitors of fungal growth and/or AF production, essential oils (EOs) and extracts of 49 medicinal plants were studied against an aflatoxin-producing A. parasiticus using a microbioassay technique. The EOs was analyzed by gas chromatography/mass spectrometry (GC/MS). Based on the results obtained, Achillea millefolium sub sp. elborsensis, Ferula gummosa, Mentha spicata, Azadirachta indica, Conium maculatum and Artemisia dracunculus remarkably inhibited A. parasiticus growth without affecting AF production by the fungus. Besides of Thymus vulgaris and Citrus aurantifolia, the EO of Foeniculum vulgare significantly inhibited both fungal growth (-70.0%) and AFs B1 and G1 (-99.0%) production. The EO of Carum carvi and ethyl acetate extract of Platycladus orientalis suppressed AFs B1 and G1 by more than 90.0%, without any obvious effect on fungal growth. The IC50 values of bioactive plants for AFs B1 and G1 were determined in the ranges of 90.6 to 576.2 and 2.8 to 61.9 µg/ml, respectively. Overall, results of the present study indicate the importance of AF contamination of trout feed as a risk factor for fish farming and thus, an urgent necessity for constant monitoring of trout feed for any unacceptable levels of AF contamination. Likewise, antifungal activities of bioactive plants introduced here would be an important contribution to explain the use of these plants as effective antimicrobial candidates to protect feeds from toxigenic fungus growth and subsequent AF contamination.
Resumo:
Foeniculum vulgare Mill. (fennel) and Matricaria recutita L. (chamomile) are two examples of plants with reported antioxidant and antimicrobial properties, which can be related with their composition in phenolic compounds [1,2]. Furthermore, according to previous results of our research group, the direct incorporation of the aqueous extracts showed capacity to maintain the nutritional properties of the cottage cheeses, up to 7 days of storage, while improving the antioxidant potential. However, after 14 days, a decrease in the antioxidant properties was observed [1,2], which can be related with factors such as light, moisture, temperature and pH, that can cause bioactive compounds degradation. Therefore, the aim of the present study was to prepare microcapsules with the aqueous extracts of fennel and chamomile for incorporation in cottage cheese samples, in order to protect the bioactive molecules present in the extracts, such as phenolic compounds, and prevent the decrease of the antioxidant activity observed after the 14 days period. The microspheres were prepared using an atomization/coagulation technique. Sodium alginate was used as the matrix material to produce the microspheres that were characterized through optical microscopy (OM), during and after atomization, for inspecting morphology. The encapsulation efficiency (EE) was determined by HPLC-DAD by an indirect method by analysing the coagulation solution. FTIR was also used to attest the presence of the extract inside of the alginate matrix. These microencapsulated extracts were incorporated in cottage cheese samples that were further characterized in terms of nutritional properties and antioxidant potential right after incorporation, and after 7 and 14 days of storage at 4•c. The EE was estimated as -100% and the FTIR analysis confirmed the presence of the extracts inside the microspheres. The results showed that the incorporation of the microencapsulated extracts did not cause changes in the nutritional value of cottage cheeses (through a comparison with control samples without extracts). The predominant fatty acids were palmitic (C16:0) and oleic (CI8:0) acids. The order of abundance of fatty acids was as follows: saturated fatty acids (SF A)> monounsaturatcd fatty acids (MUF A)> polyunsaturated fatty acids (PUF A). Regarding free sugars, lactose was the only sugar identified and quantified in all samples. Regarding the antioxidant activity, the samples functionalized with the microencapsulated extracts showed a higher preservation of this property even after the 7th day of storage. Overall, the incorporation of the protected plant extracts in dairy foods can be a strategy to provide health benefits to consumers.