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  • Random regression models for genetic evaluation of performance of the Hungarian show-jumping horse population
    87-91
    Views:
    145

    The aim of the study was to estimate genetic parameters for show-jumping competition performance using random regression model. Show-jumping competition results collected between 1996 and 2009 were analyzed. The database contained 272 951 starts of 8020 horses. Identity number and gender of the horse, rider, competition date, the level of the competition and placing were recorded in the database. Competition levels were categorized into five groups. Weighted – competition level used – square root transformed placing was used to measure performance of horses. The random regression model included fixed effects for gender, year and place of competition, and random effects for rider, animal and permanent environment.

    Later performance of show-jumping horses measured with weighted square root ranks is less influenced by rider and permanent environmental effects than performance at the beginning of a horse’s sporting career. Heritability increased continuously from 6.3 years of age (2296 age in days), values were in the range of 0.07 and 0.37. Higher heritability was found in later ages. Weak genetic and phenotypic correlation was found between the early 4–5–6 years of age and older (7, 8, 8+) age classes. From 8.5 years of age (3132 days old) there were strong genetic and phenotypic correlations between neighboring age groups. For the same age classes moderate and strong genetic and phenotypic correlation was found. Genetic correlation between 13.5 years of age and older horses was very strong.

  • Evaluation of Hungarian show-jumping results using different measurement variables
    81-85
    Views:
    182

    The aim of the study was to compare different fitted models for show-jumping results of sporthorses and to estimate heritability and repeatability value. Show-jumping competition results collected between 1996 and 2011 were analyzed. The database contained 358 342 starts of 10 199 horses. Identity number, name and gender of the horse, rider, competition year, the level and location of the competition and placing were recorded in the database. To measure performance of horses, placing, number of starters and competition level were used. Competitions were categorized into five groups based on their difficulty level. The used repeatability animal model included fixed effects for age, gender, competition place, year of competition (and competition level in case of non-weighted measurement variables), and random effects for rider, animal and permanent environment effect. Variance components were estimated with VCE-6 software package. The goodness-of-fit of the models was low and moderate. Heritability and repeatability values were low for each measurement variables. The best goodness-of-fit model the weighted square root of placing resulted the highest heritability and repeatability value h2=0.074 and R=0.296.

  • Genetic analysis of selected body measurements of Hungarian Sport Horse mares
    40-43
    Views:
    179

    The authors made their analysis based on the body measurements of 3080 Hungarian Sport Horse mares listed in the Hungarian Sport Horse Studbook. Height at withers by stick, height at withers by tape, heart girth and cannon-bone circumference were measured in Hungarian Sport Horse mare performance tests.
    Phenotypic correlations among height at the withers and heart girth and cannon-bone circumference varied within a range of 0.45-0.55. There was close genetic correlation (r=0.63-0.82) between the body measurement traits. Heritability values were moderate for height at withers by stick, height at withers by tape and heart girth (h2=0.31-0.49). There were high heritability values (h2=0.51) for cannon-bone circumference.
    There were low phenotypic correlations between frame (as conformational trait) and height at the withers (measured by tape and stick) and heart girth.

  • Determination of the validation parameters of inductively coupled plasma mass spectrometer (iCP-mS): response curve linearity in the case of arsenic and selenium
    67-71
    Views:
    167

    In the field of elemental analysis inductively coupled plasma mass spectrometers (ICP-MS) have the best sensitivity that means the lowest limit of detection, subsequently their applicability for the detection of essential and toxic elements in foods and foodstuffs is prominent. For the most elements could be measured the detection limit is between μg kg-1 (ppb) and ng kg-1 (ppt) e.g. for arsenic and selenium.

    Considering an analytical task (sample type, analytes and their concentration, pretreatment procedure etc.) the applicability of an analytical method is determined by its performance characteristics. The purpose of validation is to ensure that the method would be used fulfills the requirements of the given task. In this article we describes one of the performance characteristics, the linearity, and the whole validation procedure aims measurement of arsenic and selenium in foodstuffs by inductively coupled plasma mass spectrometer (Thermo XSeries I.); but because of the limited number of pages the results are demonstrated only for arsenic.

    The linearity of calibration was evaluated in three concentration ranges (0.1–1 μg l-1; 1–10 μg l-1; 10–50 μg l-1), with nine line-fit possibilities (without weighting, weighting with absolute or relative deviation; with or without forcing the curve through blank or origin) and different methods (graphical examination, correlation coefficient, analysis of variance).

    The best method to ensure the linearity of correspondence between signal and concentration was the ANOVA test. In view of calibrations it was found that the range of 10–50 μg l-1 could be regarded as linear with four line-fit possibilities, and was non-linear between 0.1–1 μg l-1 and 1–10 μg l-1.

  • Element content analyses in the Institute for Food Sciences, Quality Assurance and Microbiology
    203-207
    Views:
    132

    The role of chemical elements to ensure and promote our health is undisputed. Some of them are essential for plants, animals and human, others can cause diseases. The major source of mineral constituents is food, drinking water has a minor contribution to it, so the knowledge of elemental intake through food is crucial and needs continuous monitoring and by this way it promotes the food quality assurance and dietetics.
    With the evolution of spectroscopic methods increasingly lower concentrations could be determined, so the elemental composition of a sample could be more precisely and fully described. Due to the results the gathered knowledge up to the present is supported and new observations can be done helping us to understand such complex systems as biological organisms are.
    The quality of a food is determined by the full process of its production, consequently it starts with agricultural production so elemental-analysis usually cover the whole soil – plant – (animal) – food chain, by this way the „Fork-to-Farm” precept is true in elemental analysis field also.
    The history of elemental analysis in the University of Debrecen, Centre for Agricultural and Applied Economic Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Food Processing, Quality Assurance and Microbiology goes back to 1980s when the so called Regional Measurement Central gave the background for research. The continuous deployment resulted in an obtain of an inductively coupled plasma atomic emission spectrometer (ICP-AES) in 1988, which extended the scope of examinations due to its excellent performance characteristics
    compared to flame atom absorption (FAAS) and flame emission spectrometers (FES). The instrumental park retain up to date correlate to the developing analytical techniques due to acquiring a newer ICPAES in 1998 and an inductively coupled plasma mass spectrometer in 2004 – which sensitivity is three order of magnitude better compared to ICP-AES. The Institute supports the work with its own ICP-AES and ICP-MS since 2011. 

  • Exploration of relations among the members of the supply chain on the basis of relationship indicators
    177-190
    Views:
    148

    Today the various business units on the market are not competing individually against each other, but doing this as members of a supply chain, which are delivering the products or services to the customers with coordination. The participants are cooperating in the process of purchasing, production and sale. Their common objective is to deliver for the consumer demand. The supply chain approach of the enterprises is a business philosophy, which requires trust, commitment, coordination, shared objectives, support from the management, and the understanding and acceptance of the mutual dependence (Német, 2009). The main objective of our study is to analyse the relationships among the players of the supply chain through several relationship indicators, such as trust, economical satisfaction, social satisfaction, compelling power, non-compelling power, dependence, reputation and conflict. The relationship among the players of the supply chain has been analysed from two aspects, through the position and through the role of the players of the supply chain. This study aims to present the results of the analysis highlighting the critical points.