Rapsista tuotetun biodieselin ja vehnästä tuotetun bioetanolin energiavirrat ja ympäristövaikutukset Euroopan unionissa

The aim of this thesis was to study the crops currently used for biofuel production from the following aspects: 1. what should be the average yield/ ha to reach an energy balance at least 0 or positive 2. what are the shares of the primary and secondary energy flows in agriculture, transport, processing and usage, and 3. overall effects of biofuel crop cultivation, transport, processing and usage. This thesis concentrated on oilseed rape biodiesel and wheat bioethanol in the European Union, comparing them with competing biofuels, such as corn and sugarcane-based ethanol, and the second generation biofuels. The study was executed by comparing Life Cycle Assessment-studies from the EU-region and by analyzing them thoroughly from the differences viewpoint. The variables were the following: energy ratio, hectare yield (l/ha), impact on greenhouse gas emissions (particularly CO2), energy consumption in crop growing and processing one hectare of a particular crop to biofuel, distribution of energy in processing and effects of the secondary energy flows, like e.g. wheat straw. Processing was found to be the most energy consuming part in the production of biofuels. So if the raw materials will remain the same, the development will happen in processing. First generation biodiesel requires esterification, which consumes approximately one third of the process energy. Around 75% of the energy consumed in manufacturing the first generation wheat-based ethanol is spent in steam and electricity generation. No breakthroughs are in sight in the agricultural sector to achieve significantly higher energy ratios. It was found out that even in ideal conditions the energy ratio of first generation wheat-based ethanol will remain slightly under 2. For oilseed rape-based biodiesel the energy ratios are better, and energy consumption per hectare is lower compared to wheat-based ethanol. But both of these are lower compared to e.g. sugarcane-based ethanol. Also the hectare yield of wheat-based ethanol is significantly lower. Biofuels are in a key position when considering the future of the world’s transport sector. Uncertainties concerning biofuels are, however, several, like the schedule of large scale introduction to consumer markets, technologies used, raw materials and their availability and - maybe the biggest - the real production capacity in relation to the fuel consumption. First generation biofuels have not been the expected answer to environmental problems. Comparisons made show that sugarcane-based ethanol is the most prominent first generation biofuel at the moment, both from energy and environment point of view. Also palmoil-based biodiesel looks promising, although it involves environmental concerns as well. From this point of view the biofuels in this study - wheat-based ethanol and oilseed rape-based biodiesel - are not very competitive options. On the other hand, crops currently used for fuel production in different countries are selected based on several factors, not only based on thier relative general superiority. It is challenging to make long-term forecasts for the biofuel sector, but it can be said that satisfying the world's current and near future traffic fuel consumption with biofuels can only be regarded impossible. This does not mean that biofuels shoud be rejected and their positive aspects ignored, but maybe this reality helps us to put them in perspective. To achieve true environmental benefits through the usage of biofuels there must first be a significant drop both in traffic volumes and overall fuel consumption. Second generation biofuels are coming, but serious questions about their availability and production capacities remain open. Therefore nothing can be taken for granted in this issue, expect the need for development.

Optimal crop planning and conjunctive use of water resources in a coastal river basin

Due to increasing trend of intensive rice cultivation in a coastal river basin, crop planning and groundwater management are imperative for the sustainable agriculture. For effective management, two models have been developed viz. groundwater balance model and optimum cropping and groundwater management model to determine optimum cropping pattern and groundwater allocation from private and government tubewells according to different soil types (saline and non-saline), type of agriculture (rainfed and irrigated) and seasons (monsoon and winter). A groundwater balance model has been developed considering mass balance approach. The components of the groundwater balance considered are recharge from rainfall, irrigated rice and non-rice fields, base flow from rivers and seepage flow from surface drains. In the second phase, a linear programming optimization model is developed for optimal cropping and groundwater management for maximizing the economic returns. The models developed were applied to a portion of coastal river basin in Orissa State, India and optimal cropping pattern for various scenarios of river flow and groundwater availability was obtained.

Climate change and crop yields in the Indian Cardamom Hills, 1978-2007 CE

In this study we analyzed climate and crop yields data from Indian cardamom hills for the period 1978-2007 to investigate whether there were significant changes in weather elements, and if such changes have had significant impact on the production of spices and plantation crops. Spatial and temporal variations in air temperatures (maximum and minimum), rainfall and relative humidity are evident across stations. The mean air temperature increased significantly during the last 30 years; the greatest increase and the largest significant upward trend was observed in the daily temperature. The highest increase in minimum temperature was registered for June (0.37A degrees C/18 years) at the Myladumpara station. December and January showed greater warming across the stations. Rainfall during the main monsoon months (June-September) showed a downward trend. Relative humidity showed increasing and decreasing trends, respectively, at the cardamom and tea growing tracts. The warming trend coupled with frequent wet and dry spells during the summer is likely to have a favorable effect on insect pests and disease causing organisms thereby pesticide consumption can go up both during excess rainfall and drought years. The incidence of many minor pest insects and disease pathogens has increased in the recent years of our study along with warming. Significant and slight increases in the yield of small cardamom (Elettaria cardamomum M.) and coffee (Coffea arabica), respectively, were noticed in the recent years.; however the improvement of yield in tea (Thea sinensis) and black pepper (Piper nigrum L.) has not been seen in our analysis.

Parameter estimation of a two-horizon soil profile by combining crop canopy and surface soil moisture observations using GLUE

Estimation of soil parameters by inverse modeling using observations on either surface soil moisture or crop variables has been successfully attempted in many studies, but difficulties to estimate root zone properties arise when heterogeneous layered soils are considered. The objective of this study was to explore the potential of combining observations on surface soil moisture and crop variables - leaf area index (LAI) and above-ground biomass for estimating soil parameters (water holding capacity and soil depth) in a two-layered soil system using inversion of the crop model STICS. This was performed using GLUE method on a synthetic data set on varying soil types and on a data set from a field experiment carried out in two maize plots in South India. The main results were (i) combination of surface soil moisture and above-ground biomass provided consistently good estimates with small uncertainity of soil properties for the two soil layers, for a wide range of soil paramater values, both in the synthetic and the field experiment, (ii) above-ground biomass was found to give relatively better estimates and lower uncertainty than LAI when combined with surface soil moisture, especially for estimation of soil depth, (iii) surface soil moisture data, either alone or combined with crop variables, provided a very good estimate of the water holding capacity of the upper soil layer with very small uncertainty whereas using the surface soil moisture alone gave very poor estimates of the soil properties of the deeper layer, and (iv) using crop variables alone (else above-ground biomass or LAI) provided reasonable estimates of the deeper layer properties depending on the soil type but provided poor estimates of the first layer properties. The robustness of combining observations of the surface soil moisture and the above-ground biomass for estimating two layer soil properties, which was demonstrated using both synthetic and field experiments in this study, needs now to be tested for a broader range of climatic conditions and crop types, to assess its potential for spatial applications. (C) 2012 Elsevier B.V. All rights reserved.

Algal biofuel production and mitigation potential in India

Energy and energy services are the backbone of growth and development in India and is increasingly dependent upon the use of fossil based fuels that lead to greenhouse gases (GHG) emissions and related concerns. Algal biofuels are being evolved as carbon (C)-neutral alternative biofuels. Algae are photosynthetic microorganisms that convert sunlight, water and carbon dioxide (CO2) to various sugars and lipids Tri-Acyl-Glycols (TAG) and show promise as an alternative, renewable and green fuel source for India. Compared to land based oilseed crops algae have potentially higher yields (5-12 g/m(2)/d) and can use locations and water resources not suited for agriculture. Within India, there is little additional land area for algal cultivation and therefore needs to be carried out in places that are already used for agriculture, e.g. flooded paddy lands (20 Mha) with village level technologies and on saline wastelands (3 Mha). Cultivating algae under such conditions requires novel multi-tier, multi-cyclic approaches of sharing land area without causing threats to food and water security as well as demand for additional fertilizer resources by adopting multi-tier cropping (algae-paddy) in decentralized open pond systems. A large part of the algal biofuel production is possible in flooded paddy crop land before the crop reaches dense canopies, in wastewaters (40 billion litres per day), in salt affected lands and in nutrient/diversity impoverished shallow coastline fishery. Mitigation will be achieved through avoidance of GHG, C-capture options and substitution of fossil fuels. Estimates made in this paper suggest that nearly half of the current transportation petro-fuels could be produced at such locations without disruption of food security, water security or overall sustainability. This shift can also provide significant mitigation avenues. The major adaptation needs are related to socio-technical acceptance for reuse of various wastelands, wastewaters and waste-derived energy and by-products through policy and attitude change efforts.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Gene expression programming-fuzzy logic method for crop type classification

Crop type classification using remote sensing data plays a vital role in planning cultivation activities and for optimal usage of the available fertile land. Thus a reliable and precise classification of agricultural crops can help improve agricultural productivity. Hence in this paper a gene expression programming based fuzzy logic approach for multiclass crop classification using Multispectral satellite image is proposed. The purpose of this work is to utilize the optimization capabilities of GEP for tuning the fuzzy membership functions. The capabilities of GEP as a classifier is also studied. The proposed method is compared to Bayesian and Maximum likelihood classifier in terms of performance evaluation. From the results we can conclude that the proposed method is effective for classification.

Improved modeling of groundwater recharge in agricultural watersheds using a combination of crop model and remote sensing

For improved water management and efficiency of use in agriculture, studies dealing with coupled crop-surface water-groundwater models are needed. Such integrated models of crop and hydrology can provide accurate quantification of spatio-temporal variations of water balance parameters such as soil moisture store, evapotranspiration and recharge in a catchment. Performance of a coupled crop-hydrology model would depend on the availability of a calibrated crop model for various irrigated/rainfed crops and also on an accurate knowledge of soil hydraulic parameters in the catchment at relevant scale. Moreover, such a coupled model should be designed so as to enable the use/assimilation of recent satellite remote sensing products (optical and microwave) in order to model the processes at catchment scales. In this study we present a framework to couple a crop model with a groundwater model for applications to irrigated groundwater agricultural systems. We discuss the calibration of the STICS crop model and present a methodology to estimate the soil hydraulic parameters by inversion of crop model using both ground and satellite based data. Using this methodology we demonstrate the feasibility of estimation of potential recharge due to spatially varying soil/crop matrix.

Comparative evaluation of inversion approaches of the radiative transfer model for estimation of crop biophysical parameters

The inversion of canopy reflectance models is widely used for the retrieval of vegetation properties from remote sensing. This study evaluates the retrieval of soybean biophysical variables of leaf area index, leaf chlorophyll content, canopy chlorophyll content, and equivalent leaf water thickness from proximal reflectance data integrated broadbands corresponding to moderate resolution imaging spectroradiometer, thematic mapper, and linear imaging self scanning sensors through inversion of the canopy radiative transfer model, PROSAIL. Three different inversion approaches namely the look-up table, genetic algorithm, and artificial neural network were used and performances were evaluated. Application of the genetic algorithm for crop parameter retrieval is a new attempt among the variety of optimization problems in remote sensing which have been successfully demonstrated in the present study. Its performance was as good as that of the look-up table approach and the artificial neural network was a poor performer. The general order of estimation accuracy for para-meters irrespective of inversion approaches was leaf area index > canopy chlorophyll content > leaf chlorophyll content > equivalent leaf water thickness. Performance of inversion was comparable for broadband reflectances of all three sensors in the optical region with insignificant differences in estimation accuracy among them.

Occurrence of sorghum midge stenodiplosis sorghicola (Coq,) during the second crop growing season on the pacific coastal plain of Nicaragua

La mosquita de la panojas del sorgo, Stenediplosls sorghicola (Coq.) es una de las plagas mas importantes que atacan al sorgo en Nicaragua. Varios estudios fueron conducidos en el pacifico de Nicaragua durante 1998 y 1999 para determinar hospederos y la actividad de esta plaga durante la segunda fecha de siembra de este cultivo (Postrera). Hembras oviposltaron en sorgo desde mediados de Septiembre hasta los últimos dfas de Diciembre. Cuando sorgo no se encontraba presente, hembras ovipositaron en sorgo escobero, Sorghum bicolor (L.) o pastoJonson, Sorghum halepense L. Pasto Jonson florea durante todo el ano y puede servir como hospedero mientras las otras especies de sorghum no se encuentran en el campo. Cuando estos tres hospederos estaban floreando al mismo tiempo, las hembras exhibieron una fuerte preferencia para ovlpositar en sorgo. Basado en estas observaciones la mosquita de la panoja del sorgo puede estar activa durante todo el ano en el pacifico de Nicaragua. Conocimiento de la ocurrencia y comportamiento de la mosquita en el area, es muy Importante para el desarrollo de estrategias de manejo de esta plaga.

Effects of preceding crop and weed control method on weeds and common bean (Phaseoulus vulgaris L.) yield in a no-tillage cropping system

En 1994, se inició un trabajo de investigación el cual se continuo durante tres años, con el objetivo de evaluar el efecto de cultivos antecesores y métodos de control de malezas sobre el rendimiento frijol común ( P h a s e o l u s vulgaris L.) y la dinámica de las malezas. El frijol y los cultivos antecesores fueron sembrados en sistema de cero labranza. Las secuencias de cultivos estudiadas fueron: maíz (Zea mays L), seguido de frijol y frijol seguido de frijol. Se analizaron tres ciclos de los cultivos (1994, 1995 y 1996). La secuencia de cultivo que produjo el máximo rendimiento fue maíz seguido de frijol en 1994, así como también el promedio de rendimiento a través de los años. Por otro lado, los mayores valores de vainas por planta y semillas por vaina se obtuvieron cuando el frijol antecedió al frijol en 1994. Parcelas con controles de malezas mecánico y químico obtuvieron menores densidades y peso seco de malezas y mejores rendimientos que aquellas parcelas en las cuales se controlo la maleza a través de cobertura muerta.

A quantitative analysis of the phytoplankton of the Gulf of Panama II. On the relationship between C14 assimilation and the diatom standing crop

ENGLISH: The Inter-American Tropical Tuna Commission has maintained a hydro-biological station in the Gulf of Panama located at 8°45'N, 79°23'W in connection with their ecological investigation of the anchoveta (Cetengraulis mysticetus), a tuna baitfish (see Peterson, 1961, for references) . The depth is approximately 42 meters at mean low water at this station. Routine hydrographic and biological observations have been made (Schaefer, Bishop and Howard, 1958; Schaefer and Bishop, 1958; Forsbergh, 1963), including the collection of quantitative phytoplankton samples from November 1954 through May 1957 (Smayda, 1959; unpublished). The seasonal and regional variations in phytoplankton growth in the Gulf of Panama have also been investigated (Smayda, 1963). The relationships existing between C1 4 assimilation as determined by 24 hour in situ experiments and diatom standing crop at 10 meters when expressed as cell numbers, cell volume, cell surface area and cell plasma volume have been assessed for 30 observations made between November 1954 and May 1957 at 8°45'N, 79°23'W. The average cell volume and cell surface area characteristics for 110 diatom species and varieties are presented. SPANISH: Las relaciones existentes entre la asimilación del C14 , determinadas después de 24 horas de experimentos in situ, y la cosecha estable de las diatomeas a 10 metros, expresando el número de células, volumen celular, área de la superficie celular y volumen del plasma celular, han sido determinadas por medio de 30 observaciones hechas entre noviembre de 1954 y mayo de 1957, a los 8°45'N, 79°23'W. Se presenta, para 110 especies y variedades de diatomeas, el promedio de las características del volumen celular y del área de la superficie celular. (PDF contains 67 pages.)