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Development of seed analyses by means of various matrix solutions and the MALDI-TOF MS technique
53-57Views:323The earth's population is growing steadily, currently accounting for about 7.3 billion people. Population growth causes food demand to rise, approximately 36 million people die each year due to starvation or related diseases. One solution to this problem is the continuous examination and development of the agricultural economy. In this study, matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI -TOF MS) were used to analyse of sunflower, soybean and hemp. In order to analyse the protein of maize, this method has already been applied. However, for sunflower, soy and hemp, it is necessary to develop a sample preparation method. Choosing the optimal matrix solution for ionization the traget molecule is an essential part of developing the method. Our aim is to compare two different matrix solutions (α-HCCA, SA matrix), based on the properties (intensity, noise ratio, value of spectra) of the spectra.
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Comparison of sample preparation methods for the identification of Staphylococcus Aureus by MALDI-FOF MS
9-14Views:293Coagulase-positive staphylococci include 3 species, Staphylococcus aureus, S. hyicus and S. intermedius. Of these three species, S. aureus is the most well-known human pathogen. S. aureus is part of the human and animal normal microbiota, however, it is capable of producing several staphylococcal enterotoxins (SEs) that cause intoxication symptoms of varying intensity in humans after consuming contaminated food. Selective media which are used for the determination of coagulase-positive staphylococci from foods are not able to identify isolates at a species. With the MALDI-TOF MS technique, we can identify S. aureus cheaper and faster than by using molecular methods. This paper describes the results of the study of the presence of coagulase-positive staphylococci and S. aureus in many food products, and the application of three sample preparation methods: direct sample preparation, formic acid suspension and ethanol extraction.
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Challenges and limtations of site specific crop production applications of wheat and maize
101-104Views:140The development and implementation of precision agriculture or site-specific farming has been made possible by combining the Global Positioning System (GPS) and the Geographic Information Systems (GIS). Site specific agronomic applications are of high importance concerning the efficiency of management in crop production as well as the protection and maintenance of environment and nature. Precision crop production management techniques were applied at four locations to evaluate their impact on small plot units sown by wheat (Triticum aestivum L.) and maize (Zea mays L.) in a Hungarian national case study. The results obtained suggest the applicability of the site specific management techniques, however the crops studied responded in a different way concerning the impact of applications. Maize had a stronger response regarding grain yield and weed canopy. Wheat was responding better than maize concerning plant density and protein content performance.
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Analysis of sweet corn nutritional values using multivariate statistical methods
103-108Views:258Processing large amounts of data provided by automated analytical equipment requires carefulness. Most mathematical and statistical methods have strict application conditions. Most of these methods are based on eigenvalue calculations and require variables to be correlated in groups. If this condition is not met, the most popular multivariate methods cannot be used. The best procedure for such testing is the Kaiser-Meyer-Olkin test for Sampling Adequacy. Two databases were examined using the KMO test. One of them resulted from the sweet corn measured in the scone of the study, while the other from the 1979 book of János Sváb. For both databases, MSA (measures sampling adequacy) was well below the critical value, thus they are not suitable e.g. for principal component analysis. In both databases, the values of the partial correlation coefficients were much higher than Pearson’s correlation coefficients. Often the signs of partial coefficients did not match the signs of linear correlation coefficients. One of the main reasons for this is that the correlation between the variables is non-linear. Another reason is that control variables have a non-linear effect on a given variable. In such cases, classical methods should be disregarded and expert models better suited to the problem should be chosen in order to analyse the correlation system.