216 resultados para fertilizing
Resumo:
This study determined the relationship between two measures of field fertility of I I high-use Australian artificial insemination (AI) dairy bulls and thirty standard laboratory assessments of spermatozoal post-thaw viability. The two measures of field fertility used, conception rates (cCR) and non-return rates (cNRR), were both corrected for all major non-bull variables. Sperm viability assessments were conducted on semen collected within the same season as that used to derive the field fertility estimates. These assessments measured sperm concentration, motility, morphology and membrane integrity at thawing, after 2 h incubation and after the swim-up sperm selection procedure. Derivations of these measures and in vitro embryo fertilizing and developmental capacity were also determined. The Genstat Statistical Package [Genstat 5 Release 4.2 Reference Manual, VSN International, Oxford, 20001 was used to conduct an analysis of variance on the viability parameters across semen straws and bulls, and to calculate the strength of correlation between each semen parameter, cNRR and cCR in a correlation matrix. Step forward multiple regression identified the combination of semen parameters that were most highly correlated with cCR and with cNRR. The sperm parameters identified as being most predictive of cCR were the percentage of morphologically normal sperm immediately post-thaw (zeroNorm), the number of morphologically normal sperm after the swim-up procedure (nSuNorm), and the rate of zygote cleavage in vitro (Clv); the predictive equation formed by these parameters accounted for 70% of variance. The predictive equation produced for cNRR contained the variables zeroNorm, the proportion of membrane intact sperm after 2 h incubation at 37 degreesC (twoMem) and Clv and accounted for 76.5% of the variation. ZeroNorm was found to be consistent across straws and semen batches within-bull and the sperm parameter with the strongest individual predictive capacity for both cCR (P = 0.1) and cNRR (P = 0.001). Post-thaw sperm parameters can be used to predict field fertility of Australian dairy sires; the calculated predictive equations are particularly useful for identifying and monitoring bulls of very high and very low potential fertility within a group. (C) 2003 Elsevier B.V. All rights reserved.
Resumo:
The production of agricultural and horticultural products requires the use of nitrogenous fertiliser that can cause pollution of surface and ground water and has a large carbon footprint as it is mainly produced from fossil fuels. The overall objective of this research project was to investigate fast pyrolysis and in-situ nitrogenolysis of biomass and biogenic residues as an alternative route to produce a sustainable solid slow release fertiliser mitigating the above stated problems. A variety of biomasses and biogenic residues were characterized by proximate analysis, ultimate analysis, thermogravimetric analysis (TGA) and Pyrolysis – Gas chromatography – Mass Spectroscopy (Py–GC–MS) for their potential use as feedstocks using beech wood as a reference material. Beech wood was virtually nitrogen free and therefore suitable as a reference material as added nitrogen can be identified as such while Dried Distillers Grains with Solubles (DDGS) and rape meal had a nitrogen content between 5.5wt.% and 6.1wt.% qualifying them as high nitrogen feedstocks. Fast pyrolysis and in-situ nitrogenolysis experiments were carried out in a continuously fed 1kg/h bubbling fluidized bed reactor at around 500°C quenching the pyrolysis vapours with isoparaffin. In-situ nitrogenolysis experiments were performed by adding ammonia gas to the fast pyrolysis reactor at nominal nitrogen addition rates between 5wt.%C and 20wt.%C based on the dry feedstock’s carbon content basis. Mass balances were established for the processing experiments. The fast pyrolysis and in-situ nitrogenolysis products were characterized by proximate analysis, ultimate analysis and GC– MS. High liquid yields and good mass balance closures of over 92% were obtained. The most suitable nitrogen addition rate for the in-situ nitrogenolysis experiments was determined to be 12wt.%C on dry feedstock carbon content basis. However, only a few nitrogen compounds that were formed during in-situ nitrogenolysis could be identified by GC–MS. A batch reactor process was developed to thermally solidify the fast pyrolysis and in-situ nitrogenolysis liquids of beech wood and Barley DDGS producing a brittle solid product. This was obtained at 150°C with an addition of 2.5wt% char (as catalyst) after a processing time of 1h. The batch reactor was also used for modifying and solidifying fast pyrolysis liquids derived from beech wood by adding urea or ammonium phosphate as post processing nitrogenolysis. The results showed that this type of combined approach was not suitable to produce a slow release fertiliser, because the solid product contained up to 65wt.% of highly water soluble nitrogen compounds that would be released instantly by rain. To complement the processing experiments a comparative study via Py–GC–MS with inert and reactive gas was performed with cellulose, hemicellulose, lignin and beech wood. This revealed that the presence of ammonia gas during analytical pyrolysis did not appear to have any direct impact on the decomposition products of the tested materials. The chromatograms obtained showed almost no differences between inert and ammonia gas experiments indicating that the reaction between ammonia and pyrolysis vapours does not occur instantly. A comparative study via Fourier Transformed Infrared Spectroscopy of solidified fast pyrolysis and in-situ nitrogenolysis products showed that there were some alterations in the spectra obtained. A shift in frequencies indicating C=O stretches typically related to the presence of carboxylic acids to C=O stretches related to amides was observed and no double or triple bonded nitrogen was detected. This indicates that organic acids reacted with ammonia and that no potentially harmful or non-biodegradable triple bonded nitrogen compounds were formed. The impact of solid slow release fertiliser (SRF) derived from pyrolysis and in-situ nitrogenolysis products from beech wood and Barley DDGS on microbial life in soils and plant growth was tested in cooperation with Rothamsted Research. The microbial incubation tests indicated that microbes can thrive on the SRFs produced, although some microbial species seem to have a reduced activity at very high concentrations of beech wood and Barley DDGS derived SRF. The plant tests (pot trials) showed that the application of SRF derived from beech wood and barley DDGS had no negative impact on germination or plant growth of rye grass. The fertilizing effect was proven by the dry matter yields in three harvests after 47 days, 89 days and 131 days. The findings of this research indicate that in general a slow release fertiliser can be produced from biomass and biogenic residues by in-situ nitrogenolysis. Nevertheless the findings also show that additional research is necessary to identify which compounds are formed during this process.
Resumo:
Shallow seagrass ecosystems frequently experience physical disturbance from vessel groundings. Specific restoration methods that modify physical, chemical, and biological aspects of disturbances are used to accelerate recovery. This study evaluated loss and recovery of ecosystem structure in disturbed seagrass meadows through plant and soil properties used as proxies for primary and secondary production, habitat quality, benthic metabolism, remineralization, and nutrient storage and exchange. The efficacy of common seagrass restoration techniques in accelerating recovery was also assessed. Beyond removal of macrophyte biomass, disturbance to seagrass sediments resulted in loss of organic matter and stored nutrients, and altered microbial and infaunal communities. Evidence of the effectiveness of restoration actions was variable. Fill placement prevented additional erosion, but the resulting sediment matrix had different physical properties, low organic matter content and nutrient pools, reduced benthic metabolism, and less primary and secondary production relative to the undisturbed ecosystem. Fertilization was effective in increasing nitrogen and phosphorus availability in the sediments, but concurrent enhancement of seagrass production was not detected. Seagrass herbivores removed substantial seagrass biomass via direct grazing, suggesting that leaf loss to seagrass herbivores is a spatially variable but critically important determinant of seagrass transplanting success. Convergence of plant and sediment response variables with levels in undisturbed seagrass meadows was not detected via natural recovery of disturbed sites, or through filling and fertilizing restoration sites. However, several indicators of ecosystem development related to primary production and nutrient accumulation suggest that early stages of ecosystem development have begun at these sites. This research suggests that vessel grounding disturbances in seagrass ecosystems create more complex and persistent resource losses than previously understood by resource managers. While the mechanics of implementing common seagrass restoration actions have been successfully developed by the restoration community, expectations of consistent or rapid recovery trajectories following restoration remain elusive.
Resumo:
This data set comprises time series of aboveground community plant biomass (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 several experiments at the field site of a large grassland biodiversity experiment (the Jena Experiment; see further details below). Aboveground community biomass was normally harvested twice a year just prior to mowing (during peak standing biomass twice a year, generally in May and August; in 2002 only once in September) on all experimental plots in the Jena Experiment. This was done by clipping the vegetation at 3 cm above ground in up to four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned by random selection of new coordinates every year within the core area of the plots. 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 the biomass measures on the community level 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. The following series of datasets are contained in this collection: 1. Plant biomass form the Main Experiment: 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). 2. Plant biomass from the Dominance Experiment: In the Dominance Experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 species that can be dominant in semi-natural grassland communities of the study region. 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, 3, 4, 6, and 9 species). 3. Plant biomass from the monoculture plots: In the monoculture plots the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species like the other experiments in May 2002. All plots were maintained by bi-annual weeding and mowing.
Resumo:
This collection contains measurements of abundance and diversity of different groups of aboveground invertebrates sampled on the plots of the different sub-experiments at the field site 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. The following series of datasets are contained in this collection: 1. Measurements of ant abundance (number of individuals attracted to baits) and ant occurrence (binary data) in the Main Experiment in 2006 and 2013. Ants where sampled using two types of baited traps receiving ~10g of Tuna or ~10g of honey/Sucrose. After 30min the occurrence (presence = 1 / absence = 0) and abundance (number) of ants at the two types of baits was recorded and pooled per plot.
Resumo:
This collection contains measurements of vegetation and soil surface cover measured on the plots of the different sub-experiments at the field site 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. The following series of datasets are contained in this collection: 1. Measurements of 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 species that have been sown into the plots to create the gradient of plant diversity.
Resumo:
This collection contains measurements on physical soil properties of the plots of the different sub-experiments at the field site 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
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 2009, 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 2009, in addition to the four community level cover estimates, cover of the moss layer was 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 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:
Soil temperature (in °C) was determined using a frequency domain sensor probe (WET-2 Sensor, Delta-T Devices, Cambridge, United Kingdom) on 1st August 2013. The device was inserted from the top 6 cm deep (length of the prongs) into the soil. The average of three measurements on the same day was calculated. All data where measured in 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 in the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, or 4 functional groups). Plots were maintained by bi-annual weeding and mowing.
Resumo:
Soil porosity is the fraction of total volume occupied by pores or voids measured at matric potential 0. To measure soil porosity, soil samples were taken from each plot using sample rings with an internal diameter of 57 mm and height of 40.5 mm (inner volume of Vs=100 cm3). The samples were placed on a sand bed box with water level set to allow saturation of the samples with water. After 48 h the samples were weighed (ms), oven dried at 105 °C and weighed again to determine the dry weight (md). We calculated soil porosity (n [%]) using the density of water (?w=1 g cm?3), n=100 ? (mw-md) / (?w?Vs). To account for the spatial variation of soil properties, three replicates were taken per plot, approximately 2, 3 and 4 weeks after the flood that occurred at the field site during June 2013. Data are the average soil porosity values per plot. All data where measured in 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 in the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, or 4 functional groups). Plots were maintained by bi-annual weeding and mowing.
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.