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Hans Komen - One of the best experts on this subject based on the ideXlab platform.

  • genetic parameters for fillet traits and Body Measurements in nile tilapia oreochromis niloticus l
    Aquaculture, 2005
    Co-Authors: Michael J. Rutten, Henk Bovenhuis, Hans Komen
    Abstract:

    Fillet weight is an economically important trait in Nile tilapia production for the European market which asks for fish with average Body weights of at least 700 g. Genetic parameters to design or optimize breeding programs for these Body weights are lacking. In an earlier study we showed that high phenotypic correlations exist between Body Measurements and fillet weight and low phenotypic correlations exist between Body Measurements and fillet yield. To evaluate the potential of mass selection for fillet traits, however, genetic parameters are required. The aim of the current study was to estimate genetic parameters for Body weight, fillet weight, fillet yield and Body Measurements. Therefore, slaughter data was collected on 1884 pedigreed Nile tilapias. Measurements of Body weight, length, width, corrected (=fillet) length and head length were taken on each fish. Filleting machines were used to fillet fish and Measurements of fillet weight, fillet yield and head weight were collected. Subsequently, genetic parameters were estimated. Heritabilities were 0.26 for Body weight, 0.24 for fillet weight and 0.12 for fillet yield. The genetic correlation between Body weight and fillet weight was 0.99 and between Body weight and fillet yield 0.74. The genetic correlation between fillet weight and fillet yield was 0.81. Genetic correlations between fillet weight and Body Measurements were 0.89 for length, 0.70 for head length, 0.94 for width and 0.91 for corrected length. Genetic correlations between fillet yield and Body Measurements were 0.62 for length, 0.47 for head length, 0.98 for width and 0.60 for corrected length. The potential of mass selection aiming to improve fillet weight was evaluated by a number of selection indexes. The accuracy of a selection index including only Body weight indicated that in this way almost the same amount of the selection response could be achieved compared to what hypothetical direct selection for fillet weight would. The use of only width in the selection index would result in 8.5% lower selection response than the use of Body weight. We conclude that Body weight is the best predictor for fillet weight compared to Body Measurements.

  • modeling fillet traits based on Body Measurements in three nile tilapia strains oreochromis niloticus l
    Aquaculture, 2004
    Co-Authors: Michael J. Rutten, Henk Bovenhuis, Hans Komen
    Abstract:

    In Nile tilapia, breeding programs focus mainly on growth, and information on genetic improvement of fillet yield is scarce. In this study, slaughter data were collected on 1215 tilapia and used to analyze the relationship between Body Measurements and fillet weight and fillet yield. Fish were obtained from three different origins/strains, and raised in a commercial farm in the Netherlands in closed recirculation systems until a final mean weight of 700 g. Body weight, length, height, width and corrected (= fillet) length were taken prior to slaughter, and used to predict fillet weight and fillet yield using linear regression models. Average fillet yield was 35.7% with large differences between strains (range 34.4-38%). There was a strong almost linear relationship between Body Measurements and fillet weight, but relationships with fillet yield were weak. R-2 of the regression model for fillet weight was 0.95 and the correlation between observed and predicted values of fillet weight 0.98. The effect of strain/origin was significant for each Body measurement. The effect of sex and strain x sex was significant for length and corrected (= fillet) length. The fillet yield model explained 15% of the observed variance; the correlation between observed and predicted fillet yield was 0.38, but there were large differences within strains. We conclude that in Nile tilapia, predicting fillet yield based on Body Measurements is possible, but correlations can be improved if more accurate methods for measuring Body width become available. (C) 2004 Elsevier B.V. All rights reserved.

Michael J. Rutten - One of the best experts on this subject based on the ideXlab platform.

  • genetic parameters for fillet traits and Body Measurements in nile tilapia oreochromis niloticus l
    Aquaculture, 2005
    Co-Authors: Michael J. Rutten, Henk Bovenhuis, Hans Komen
    Abstract:

    Fillet weight is an economically important trait in Nile tilapia production for the European market which asks for fish with average Body weights of at least 700 g. Genetic parameters to design or optimize breeding programs for these Body weights are lacking. In an earlier study we showed that high phenotypic correlations exist between Body Measurements and fillet weight and low phenotypic correlations exist between Body Measurements and fillet yield. To evaluate the potential of mass selection for fillet traits, however, genetic parameters are required. The aim of the current study was to estimate genetic parameters for Body weight, fillet weight, fillet yield and Body Measurements. Therefore, slaughter data was collected on 1884 pedigreed Nile tilapias. Measurements of Body weight, length, width, corrected (=fillet) length and head length were taken on each fish. Filleting machines were used to fillet fish and Measurements of fillet weight, fillet yield and head weight were collected. Subsequently, genetic parameters were estimated. Heritabilities were 0.26 for Body weight, 0.24 for fillet weight and 0.12 for fillet yield. The genetic correlation between Body weight and fillet weight was 0.99 and between Body weight and fillet yield 0.74. The genetic correlation between fillet weight and fillet yield was 0.81. Genetic correlations between fillet weight and Body Measurements were 0.89 for length, 0.70 for head length, 0.94 for width and 0.91 for corrected length. Genetic correlations between fillet yield and Body Measurements were 0.62 for length, 0.47 for head length, 0.98 for width and 0.60 for corrected length. The potential of mass selection aiming to improve fillet weight was evaluated by a number of selection indexes. The accuracy of a selection index including only Body weight indicated that in this way almost the same amount of the selection response could be achieved compared to what hypothetical direct selection for fillet weight would. The use of only width in the selection index would result in 8.5% lower selection response than the use of Body weight. We conclude that Body weight is the best predictor for fillet weight compared to Body Measurements.

  • modeling fillet traits based on Body Measurements in three nile tilapia strains oreochromis niloticus l
    Aquaculture, 2004
    Co-Authors: Michael J. Rutten, Henk Bovenhuis, Hans Komen
    Abstract:

    In Nile tilapia, breeding programs focus mainly on growth, and information on genetic improvement of fillet yield is scarce. In this study, slaughter data were collected on 1215 tilapia and used to analyze the relationship between Body Measurements and fillet weight and fillet yield. Fish were obtained from three different origins/strains, and raised in a commercial farm in the Netherlands in closed recirculation systems until a final mean weight of 700 g. Body weight, length, height, width and corrected (= fillet) length were taken prior to slaughter, and used to predict fillet weight and fillet yield using linear regression models. Average fillet yield was 35.7% with large differences between strains (range 34.4-38%). There was a strong almost linear relationship between Body Measurements and fillet weight, but relationships with fillet yield were weak. R-2 of the regression model for fillet weight was 0.95 and the correlation between observed and predicted values of fillet weight 0.98. The effect of strain/origin was significant for each Body measurement. The effect of sex and strain x sex was significant for length and corrected (= fillet) length. The fillet yield model explained 15% of the observed variance; the correlation between observed and predicted fillet yield was 0.38, but there were large differences within strains. We conclude that in Nile tilapia, predicting fillet yield based on Body Measurements is possible, but correlations can be improved if more accurate methods for measuring Body width become available. (C) 2004 Elsevier B.V. All rights reserved.

Henk Bovenhuis - One of the best experts on this subject based on the ideXlab platform.

  • genetic parameters for fillet traits and Body Measurements in nile tilapia oreochromis niloticus l
    Aquaculture, 2005
    Co-Authors: Michael J. Rutten, Henk Bovenhuis, Hans Komen
    Abstract:

    Fillet weight is an economically important trait in Nile tilapia production for the European market which asks for fish with average Body weights of at least 700 g. Genetic parameters to design or optimize breeding programs for these Body weights are lacking. In an earlier study we showed that high phenotypic correlations exist between Body Measurements and fillet weight and low phenotypic correlations exist between Body Measurements and fillet yield. To evaluate the potential of mass selection for fillet traits, however, genetic parameters are required. The aim of the current study was to estimate genetic parameters for Body weight, fillet weight, fillet yield and Body Measurements. Therefore, slaughter data was collected on 1884 pedigreed Nile tilapias. Measurements of Body weight, length, width, corrected (=fillet) length and head length were taken on each fish. Filleting machines were used to fillet fish and Measurements of fillet weight, fillet yield and head weight were collected. Subsequently, genetic parameters were estimated. Heritabilities were 0.26 for Body weight, 0.24 for fillet weight and 0.12 for fillet yield. The genetic correlation between Body weight and fillet weight was 0.99 and between Body weight and fillet yield 0.74. The genetic correlation between fillet weight and fillet yield was 0.81. Genetic correlations between fillet weight and Body Measurements were 0.89 for length, 0.70 for head length, 0.94 for width and 0.91 for corrected length. Genetic correlations between fillet yield and Body Measurements were 0.62 for length, 0.47 for head length, 0.98 for width and 0.60 for corrected length. The potential of mass selection aiming to improve fillet weight was evaluated by a number of selection indexes. The accuracy of a selection index including only Body weight indicated that in this way almost the same amount of the selection response could be achieved compared to what hypothetical direct selection for fillet weight would. The use of only width in the selection index would result in 8.5% lower selection response than the use of Body weight. We conclude that Body weight is the best predictor for fillet weight compared to Body Measurements.

  • modeling fillet traits based on Body Measurements in three nile tilapia strains oreochromis niloticus l
    Aquaculture, 2004
    Co-Authors: Michael J. Rutten, Henk Bovenhuis, Hans Komen
    Abstract:

    In Nile tilapia, breeding programs focus mainly on growth, and information on genetic improvement of fillet yield is scarce. In this study, slaughter data were collected on 1215 tilapia and used to analyze the relationship between Body Measurements and fillet weight and fillet yield. Fish were obtained from three different origins/strains, and raised in a commercial farm in the Netherlands in closed recirculation systems until a final mean weight of 700 g. Body weight, length, height, width and corrected (= fillet) length were taken prior to slaughter, and used to predict fillet weight and fillet yield using linear regression models. Average fillet yield was 35.7% with large differences between strains (range 34.4-38%). There was a strong almost linear relationship between Body Measurements and fillet weight, but relationships with fillet yield were weak. R-2 of the regression model for fillet weight was 0.95 and the correlation between observed and predicted values of fillet weight 0.98. The effect of strain/origin was significant for each Body measurement. The effect of sex and strain x sex was significant for length and corrected (= fillet) length. The fillet yield model explained 15% of the observed variance; the correlation between observed and predicted fillet yield was 0.38, but there were large differences within strains. We conclude that in Nile tilapia, predicting fillet yield based on Body Measurements is possible, but correlations can be improved if more accurate methods for measuring Body width become available. (C) 2004 Elsevier B.V. All rights reserved.

András Gáspárdy - One of the best experts on this subject based on the ideXlab platform.

  • connection among Body Measurements and flying speed of racing pigeon
    International Journal of Agricultural Science and Food Technology, 2017
    Co-Authors: Steven Mercieca, Bertalan Jilly, András Gáspárdy
    Abstract:

    The ability of racing pigeons to navigate and to fi nd their way home is determined by many factors. The aim of this investigation was to prove the outer and inner environmental impacts on the fl ying performances of racing pigeon fl ock. The fi eldwork consisted of taking down of various Body Measurements of 49 birds, which was improved by collection of racing-, meteorological-, geographical-, and pedigree data.

  • Connection among Body Measurements and Flying Speed of Racing Pigeon†
    International Journal of Agricultural Science and Food Technology - Peertechz Publications, 2017
    Co-Authors: Steven Mercieca, Bertalan Jilly, András Gáspárdy
    Abstract:

    The ability of racing pigeons to navigate and to find their way home is determined by many factors. The aim of this investigation was to prove the outer and inner environmental impacts on the flying performances of racing pigeon flock. The fieldwork consisted of taking down of various Body Measurements of 49 birds,  which was improved by collection of racing-, meteorological-, geographical-, and pedigree data.According to the age corrected Body Measurements the birds of actual flock were longer in wing length, narrower in wing width and lighter in Body weight than birds in Horn’s study. The breeding value for flying speed (BV speed) was calculated by an individual animal model taking the proven environmental effects (fixed: year of race, wind direction, rain fall, reproductive status; covariates: distance, temperature-humidity index) into consideration next to the genetic relatedness.The BV speed showed significant association with the real flying speed only (r=0.71), and there were no statistically proven correlations with the Body Measurements and the Body condition loss as well. While the wing length stayed in a closer negative connection (r=-0.40, p<0.05) to the loss in Body condition.Association of traits was further evaluated by use of factor analysis, from which it is concluded that the measurement responsible for Body capacity, the Measurements contributing the wing surface area, and the speed of bird are belonging to different determining groups (factors).Over and above, from the investigation it can be concluded that the flying speed of the racing pigeon is not  clearly determined by their Body Measurements, by their live weights and condition losses. However, the contribution of the Body weight, chest depth (as breast muscle volume), and wing length to the flying success is strongly imaginable, which needs further research

Steven Mercieca - One of the best experts on this subject based on the ideXlab platform.

  • connection among Body Measurements and flying speed of racing pigeon
    International Journal of Agricultural Science and Food Technology, 2017
    Co-Authors: Steven Mercieca, Bertalan Jilly, András Gáspárdy
    Abstract:

    The ability of racing pigeons to navigate and to fi nd their way home is determined by many factors. The aim of this investigation was to prove the outer and inner environmental impacts on the fl ying performances of racing pigeon fl ock. The fi eldwork consisted of taking down of various Body Measurements of 49 birds, which was improved by collection of racing-, meteorological-, geographical-, and pedigree data.

  • Connection among Body Measurements and Flying Speed of Racing Pigeon†
    International Journal of Agricultural Science and Food Technology - Peertechz Publications, 2017
    Co-Authors: Steven Mercieca, Bertalan Jilly, András Gáspárdy
    Abstract:

    The ability of racing pigeons to navigate and to find their way home is determined by many factors. The aim of this investigation was to prove the outer and inner environmental impacts on the flying performances of racing pigeon flock. The fieldwork consisted of taking down of various Body Measurements of 49 birds,  which was improved by collection of racing-, meteorological-, geographical-, and pedigree data.According to the age corrected Body Measurements the birds of actual flock were longer in wing length, narrower in wing width and lighter in Body weight than birds in Horn’s study. The breeding value for flying speed (BV speed) was calculated by an individual animal model taking the proven environmental effects (fixed: year of race, wind direction, rain fall, reproductive status; covariates: distance, temperature-humidity index) into consideration next to the genetic relatedness.The BV speed showed significant association with the real flying speed only (r=0.71), and there were no statistically proven correlations with the Body Measurements and the Body condition loss as well. While the wing length stayed in a closer negative connection (r=-0.40, p<0.05) to the loss in Body condition.Association of traits was further evaluated by use of factor analysis, from which it is concluded that the measurement responsible for Body capacity, the Measurements contributing the wing surface area, and the speed of bird are belonging to different determining groups (factors).Over and above, from the investigation it can be concluded that the flying speed of the racing pigeon is not  clearly determined by their Body Measurements, by their live weights and condition losses. However, the contribution of the Body weight, chest depth (as breast muscle volume), and wing length to the flying success is strongly imaginable, which needs further research