5 resultados para Impact of compositional constraints-on correlation and covariance

em Universitätsbibliothek Kassel, Universität Kassel, Germany


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Energy production from biomass and the conservation of ecologically valuable grassland habitats are two important issues of agriculture today. The combination of a bioenergy production, which minimises environmental impacts and competition with food production for land with a conversion of semi-natural grasslands through new utilization alternatives for the biomass, led to the development of the IFBB process. Its basic principle is the separation of biomass into a liquid fraction (press fluid, PF) for the production of electric and thermal energy after anaerobic digestion to biogas and a solid fraction (press cake, PC) for the production of thermal energy through combustion. This study was undertaken to explore mass and energy flows as well as quality aspects of energy carriers within the IFBB process and determine their dependency on biomass-related and technical parameters. Two experiments were conducted, in which biomass from semi-natural grassland was conserved as silage and subjected to a hydrothermal conditioning and a subsequent mechanical dehydration with a screw press. Methane yield of the PF and the untreated silage was determined in anaerobic digestion experiments in batch fermenters at 37°C with a fermentation time of 13-15 and 27-35 days for the PF and the silage, respectively. Concentrations of dry matter (DM), ash, crude protein (CP), crude fibre (CF), ether extract (EE), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent ligning (ADL) and elements (K, Mg, Ca, Cl, N, S, P, C, H, N) were determined in the untreated biomass and the PC. Higher heating value (HHV) and ash softening temperature (AST) were calculated based on elemental concentration. Chemical composition of the PF and mass flows of all plant compounds into the PF were calculated. In the first experiment, biomass from five different semi-natural grassland swards (Arrhenaterion I and II, Caricion fuscae, Filipendulion ulmariae, Polygono-Trisetion) was harvested at one late sampling (19 July or 31 August) and ensiled. Each silage was subjected to three different temperature treatments (5°C, 60°C, 80°C) during hydrothermal conditioning. Based on observed methane yields and HHV as energy output parameters as well as literature-based and observed energy input parameters, energy and green house gas (GHG) balances were calculated for IFBB and two reference conversion processes, whole-crop digestion of untreated silage (WCD) and combustion of hay (CH). In the second experiment, biomass from one single semi-natural grassland sward (Arrhenaterion) was harvested at eight consecutive dates (27/04, 02/05, 09/05, 16/05, 24/05, 31/05, 11/06, 21/06) and ensiled. Each silage was subjected to six different treatments (no hydrothermal conditioning and hydrothermal conditioning at 10°C, 30°C, 50°C, 70°C, 90°C). Energy balance was calculated for IFBB and WCD. Multiple regression models were developed to predict mass flows, concentrations of elements in the PC, concentration of organic compounds in the PF and energy conversion efficiency of the IFBB process from temperature of hydrothermal conditioning as well as NDF and DM concentration in the silage. Results showed a relative reduction of ash and all elements detrimental for combustion in the PC compared to the untreated biomass of 20-90%. Reduction was highest for K and Cl and lowest for N. HHV of PC and untreated biomass were in a comparable range (17.8-19.5 MJ kg-1 DM), but AST of PC was higher (1156-1254°C). Methane yields of PF were higher compared to those of WCD when the biomass was harvested late (end of May and later) and in a comparable range when the biomass was harvested early and ranged from 332 to 458 LN kg-1 VS. Regarding energy and GHG balances, IFBB, with a net energy yield of 11.9-14.1 MWh ha-1, a conversion efficiency of 0.43-0.51, and GHG mitigation of 3.6-4.4 t CO2eq ha-1, performed better than WCD, but worse than CH. WCD produces thermal and electric energy with low efficiency, CH produces only thermal energy with a low quality solid fuel with high efficiency, IFBB produces thermal and electric energy with a solid fuel of high quality with medium efficiency. Regression models were able to predict target parameters with high accuracy (R2=0.70-0.99). The influence of increasing temperature of hydrothermal conditioning was an increase of mass flows, a decrease of element concentrations in the PC and a differing effect on energy conversion efficiency. The influence of increasing NDF concentration of the silage was a differing effect on mass flows, a decrease of element concentrations in the PC and an increase of energy conversion efficiency. The influence of increasing DM concentration of the silage was a decrease of mass flows, an increase of element concentrations in the PC and an increase of energy conversion efficiency. Based on the models an optimised IFBB process would be obtained with a medium temperature of hydrothermal conditioning (50°C), high NDF concentrations in the silage and medium DM concentrations of the silage.

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This paper uses the data of 1338 rural households in the Northern Mountainous Region of Vietnam to examine the extent to which subsidised credit targets the poor and its impacts. Principal Component Analysis and Propensity Score Matching were used to evaluate the depth of outreach and the income impact of credit. To address the problem of model uncertainty, the approach of Bayesian Model Average applied to the probit model was used. Results showed that subsidised credit successfully targeted the poor households with 24.10% and 69.20% of clients falling into the poorest group and the three bottom groups respectively. Moreover, those who received subsidised credit make up 83% of ethnic minority households. These results indicate that governmental subsidies are necessary to reach the poor and low income households, who need capital but are normally bypassed by commercial banks. Analyses also showed that ethnicity and age of household heads, number of helpers, savings, as well as how affected households are by shocks were all factors that further explained the probability at which subsidised credit has been assessed. Furthermore, recipients obtained a 2.61% higher total income and a 5.93% higher farm income compared to non-recipients. However, these small magnitudes of effects are statistically insignificant at a 5% level. Although the subsidised credit is insufficient to significantly improve the income of the poor households, it possibly prevents these households of becoming even poorer.

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The high cost of maize in Kenya is basically driven by East African regional commodity demand forces and agricultural drought. The production of maize, which is a common staple food in Kenya, is greatly affected by agricultural drought. However, calculations of drought risk and impact on maize production in Kenya is limited by the scarcity of reliable rainfall data. The objective of this study was to apply a novel hyperspectral remote sensing method to modelling temporal fluctuations of maize production and prices in five markets in Kenya. SPOT-VEGETATION NDVI time series were corrected for seasonal effects by computing the standardized NDVI anomalies. The maize residual price time series was further related to the NDVI seasonal anomalies using a multiple linear regression modelling approach. The result shows a moderately strong positive relationship (0.67) between residual price series and global maize prices. Maize prices were high during drought periods (i.e. negative NDVI anomalies) and low during wet seasons (i.e. positive NDVI anomalies). This study concludes that NDVI is a good index for monitoring the evolution of maize prices and food security emergency planning in Kenya. To obtain a very strong correlation for the relationship between the wholesale maize price and the global maize price, future research could consider adding other price-driving factors into the regression models.

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The Upper Blue Nile River Basin (UBNRB) located in the western part of Ethiopia, between 7° 45’ and 12° 45’N and 34° 05’ and 39° 45’E has a total area of 174962 km2 . More than 80% of the population in the basin is engaged in agricultural activities. Because of the particularly dry climate in the basin, likewise to most other regions of Ethiopia, the agricultural productivity depends to a very large extent on the occurrence of the seasonal rains. This situation makes agriculture highly vulnerable to the impact of potential climate hazards which are about to inflict Africa as a whole and Ethiopia in particular. To analyze these possible impacts of future climate change on the water resources in the UBNRB, in the first part of the thesis climate projection for precipitation, minimum and maximum temperatures in the basin, using downscaled predictors from three GCMs (ECHAM5, GFDL21 and CSIRO-MK3) under SRES scenarios A1B and A2 have been carried out. The two statistical downscaling models used are SDSM and LARS-WG, whereby SDSM is used to downscale ECHAM5-predictors alone and LARS-WG is applied in both mono-model mode with predictors from ECHAM5 and in multi-model mode with combined predictors from ECHAM5, GFDL21 and CSIRO-MK3. For the calibration/validation of the downscaled models, observed as well as NCEP climate data in the 1970 - 2000 reference period is used. The future projections are made for two time periods; 2046-2065 (2050s) and 2081-2100 (2090s). For the 2050s future time period the downscaled climate predictions indicate rise of 0.6°C to 2.7°C for the seasonal maximum temperatures Tmax, and of 0.5°C to 2.44°C for the minimum temperatures Tmin. Similarly, during the 2090s the seasonal Tmax increases by 0.9°C to 4.63°C and Tmin by 1°C to 4.6°C, whereby these increases are generally higher for the A2 than for the A1B scenario. For most sub-basins of the UBNRB, the predicted changes of Tmin are larger than those of Tmax. Meanwhile, for the precipitation, both downscaling tools predict large changes which, depending on the GCM employed, are such that the spring and summer seasons will be experiencing decreases between -36% to 1% and the autumn and winter seasons an increase of -8% to 126% for the two future time periods, regardless of the SRES scenario used. In the second part of the thesis the semi-distributed, physically based hydrologic model, SWAT (Soil Water Assessment Tool), is used to evaluate the impacts of the above-predicted future climate change on the hydrology and water resources of the UBNRB. Hereby the downscaled future predictors are used as input in the SWAT model to predict streamflow of the Upper Blue Nile as well as other relevant water resources parameter in the basin. Calibration and validation of the streamflow model is done again on 1970-2000 measured discharge at the outlet gage station Eldiem, whereby the most sensitive out the numerous “tuneable” calibration parameters in SWAT have been selected by means of a sophisticated sensitivity analysis. Consequently, a good calibration/validation model performance with a high NSE-coefficient of 0.89 is obtained. The results of the future simulations of streamflow in the basin, using both SDSM- and LARS-WG downscaled output in SWAT reveal a decline of -10% to -61% of the future Blue Nile streamflow, And, expectedly, these obviously adverse effects on the future UBNRB-water availibiliy are more exacerbated for the 2090’s than for the 2050’s, regardless of the SRES.

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Vegetables represent a main source of micro-nutrients which can improve the health status of malnourished poor in the world. Spinach (Spinacia oleracea L.) is a popular leafy vegetable in many countries which is rich with several important micro-nutrients. Thus, consuming Spinach helps to overcome micro-nutrient deficiencies. Pests and pathogens act as major yield constraints in food production. Root-knot nematodes, Meloidogyne species, constitute a large group of highly destructive plant pests. Spinach is found to be highly susceptible for these nematode attacks. Though agricultural production has largely benefited from modern technologies and innovations, some important dimensions which can minimize the yield losses have been neglected by most of the growers. Pre-plant or initial nematode density in soil is a crucial biotic factor which is directly responsible for crop losses. Hence, information on preplant nematode densities and the corresponding damage is of vital importance to develop successful control procedures to enhance crop production. In the present study, effect of seven initial densities of M. incognita, i.e., 156, 312, 625, 1250, 2,500, 5,000 and 10,000 infective juveniles (IJs)/plant (equivalent to 1000cm3 soil) on the growth and root infestation on potted spinach plants was determined in a screen house. In order to ensure a high accuracy, root infestation was ascertained by the number of galls formed, the percentage galled-length of feeder roots and galled-feeder roots, and egg production, per plant. Fifty days post-inoculation, shoot length and weight, and root length were suppressed at the lowest IJs density. However, the pathogenic effect was pronounced at the highest density at which 43%, 46% and 45% reduction in shoot length and weight, and root length, respectively, was recorded. The highest reduction in root weight (26%) was detected at the second highest density. The Number of galls and percentage galled-length of feeder roots/per plant showed significant progressive increase across the increasing IJs density with the highest mean value of 432.3 and 54%, respectively. The two shoot growth parameters and root length showed significant inverse relationship with the increasing gall formation. Moreover, the shoot and root length were shown to be mutually dependent on each other. Suppression of shoot growth of spinach greatly affects the grower’s economy. Hence, control measures are essentially needed to ensure a better production of spinach via reducing the pre-plant density below the level of 0.156 IJs/cm3.