Evaluation of protein extraction methods to obtain protein concentrate from cassava leaf

The cassava leaf, waste generated in the harvest of the roots, is characterized by high content of protein, vitamins and minerals; however, its use is limited due to the high fiber content and antinutritional substances, which can be removed by obtaining protein concentrates. In this context, the objective of this study was to evaluate protein extraction processes, aiming the use of cassava leaves (Manihot esculenta Crantz) as an alternative protein. Four methods were tested: 1) Coagulation of Proteins by Lowering the Temperature, 2) Extraction by Isoelectric Precipitation, 3) Solubilization of Proteins and 4) Fermentation of Filter Leaf Juice. To obtain the concentrates, the use of fresh or dried leaves and extraction in one or two steps were also evaluated. The solubilization of proteins (method 3) showed a higher extraction yield; however, with concentrate of low quality. The fermentation of the juice (method 4) produced concentrates with higher quality and lower costs and the isoelectric precipitation (method 2) promoted the obtention of concentrates in less time, both with good prospects for use. The use of two extraction steps was not advantageous to the process and there was no difference between the use of fresh or dried leaf, and the use of fresh leaves is presented as a good option for the simplicity of the method.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Estimation methods of reference evapotranspiration (ETo) for Uberlândia -MG

One approach to verify the adequacy of estimation methods of reference evapotranspiration is the comparison with the Penman-Monteith method, recommended by the United Nations of Food and Agriculture Organization - FAO, as the standard method for estimating ET0. This study aimed to compare methods for estimating ET0, Makkink (MK), Hargreaves (HG) and Solar Radiation (RS), with Penman-Monteith (PM). For this purpose, we used daily data of global solar radiation, air temperature, relative humidity and wind speed for the year 2010, obtained through the automatic meteorological station, with latitude 18° 91' 66" S, longitude 48° 25' 05" W and altitude of 869m, at the National Institute of Meteorology situated in the Campus of Federal University of Uberlandia - MG, Brazil. Analysis of results for the period were carried out in daily basis, using regression analysis and considering the linear model y = ax, where the dependent variable was the method of Penman-Monteith and the independent, the estimation of ET0 by evaluated methods. Methodology was used to check the influence of standard deviation of daily ET0 in comparison of methods. The evaluation indicated that methods of Solar Radiation and Penman-Monteith cannot be compared, yet the method of Hargreaves indicates the most efficient adjustment to estimate ETo.

Bankruptcy prediction using fuzzy methods

In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.

Ion selective electrodes for determination of low and ultra low concentrations of lead (II) in natural waters

Att övervaka förekomsten av giftiga komponenter i naturliga vattendrag är nödvändigt för människans välmående. Eftersom halten av föroreningar i naturens ekosystem bör hållas möjligast låg, pågår en ständig jakt efter kemiska analysmetoder med allt lägre detektionsgränser. I dagens läge görs miljöanalyser med dyr och sofistikerad instrumentering som kräver mycket underhåll. Jonselektiva elektroder har flera goda egenskaper som t.ex. bärbarhet, låg energiförbrukning, och dessutom är de relativt kostnadseffektiva. Att använda jonselektiva elektroder vid miljöanalyser är möjligt om deras känslighetsområde kan utvidgas genom att sänka deras detektionsgränser. För att sänka detektionsgränsen för Pb(II)-selektiva elektroder undersöktes olika typer av jonselektiva membran som baserades på polyakrylat-kopolymerer, PVC och PbS/Ag2S. Fast-fas elektroder med membran av PbS/Ag2S är i allmänhet enklare och mer robusta än konventionella elektroder vid spårämnesanalys av joniska föroreningar. Fast-fas elektrodernas detektionsgräns sänktes i detta arbete med en nyutvecklad galvanostatisk polariseringsmetod och de kunde sedan framgångsrikt användas för kvantitativa bestämningar av bly(II)-halter i miljöprov som hade samlats in i den finska skärgården nära tidigare industriområden. Analysresultaten som erhölls med jonselektiva elektroder bekräftades med andra analytiska metoder. Att sänka detektionsgränsen m.hj.a. den nyutvecklade polariseringsmetoden möjliggör bestämning av låga och ultra-låga blyhalter som inte kunde nås med klassisk potentiometri. Den verkliga fördelen med att använda dessa blyselektiva elektroder är möjligheten att utföra mätningar i obehandlade miljöprov trots närvaron av fasta partiklar vilket inte är möjligt att göra med andra analysmetoder. Jag väntar mig att den nyutvecklade polariseringsmetoden kommer att sätta en trend i spårämnesanalys med jonselektiva elektroder.

Techno-Economic Feasibility of Novel On-Line Condition Monitoring Methods in Low Voltage Distribution Networks

The focus in this thesis is to study both technical and economical possibilities of novel on-line condition monitoring techniques in underground low voltage distribution cable networks. This thesis consists of literature study about fault progression mechanisms in modern low voltage cables, laboratory measurements to determine the base and restrictions of novel on-line condition monitoring methods, and economic evaluation, based on fault statistics and information gathered from Finnish distribution system operators. This thesis is closely related to master’s thesis “Channel Estimation and On-line Diagnosis of LV Distribution Cabling”, which focuses more on the actual condition monitoring methods and signal theory behind them.

A Case Study of Agile Software Engineering Methods and Practices in the MeeGo Harmattan Open Source and Product Context

The aim of this master’s thesis is to study how Agile method (Scrum) and open source software are utilized to produce software for a flagship product in a complex production environment. The empirical case and the used artefacts are taken from the Nokia MeeGo N9 product program, and from the related software program, called as the Harmattan. The single research case is analysed by using a qualitative method. The Grounded Theory principles are utilized, first, to find out all the related concepts from artefacts. Second, these concepts are analysed, and finally categorized to a core category and six supported categories. The result is formulated as the operation of software practices conceivable in circumstances, where the accountable software development teams and related context accepts a open source software nature as a part of business vision and the whole organization supports the Agile methods.

Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i

Simulation methods in the modelling of bioaffinity assays

Computational model-based simulation methods were developed for the modelling of bioaffinity assays. Bioaffinity-based methods are widely used to quantify a biological substance in biological research, development and in routine clinical in vitro diagnostics. Bioaffinity assays are based on the high affinity and structural specificity between the binding biomolecules. The simulation methods developed are based on the mechanistic assay model, which relies on the chemical reaction kinetics and describes the forming of a bound component as a function of time from the initial binding interaction. The simulation methods were focused on studying the behaviour and the reliability of bioaffinity assay and the possibilities the modelling methods of binding reaction kinetics provide, such as predicting assay results even before the binding reaction has reached equilibrium. For example, a rapid quantitative result from a clinical bioaffinity assay sample can be very significant, e.g. even the smallest elevation of a heart muscle marker reveals a cardiac injury. The simulation methods were used to identify critical error factors in rapid bioaffinity assays. A new kinetic calibration method was developed to calibrate a measurement system by kinetic measurement data utilizing only one standard concentration. A nodebased method was developed to model multi-component binding reactions, which have been a challenge to traditional numerical methods. The node-method was also used to model protein adsorption as an example of nonspecific binding of biomolecules. These methods have been compared with the experimental data from practice and can be utilized in in vitro diagnostics, drug discovery and in medical imaging.