The Experts below are selected from a list of 35877 Experts worldwide ranked by ideXlab platform

Lingxian Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Modelling and method for beef quality risk identification and optimization in beef Cattle Breeding
    WSEAS Transactions on Information Science and Applications archive, 2009
    Co-Authors: Jian Zhang, Lingxian Zhang, Liang Shi
    Abstract:

    The meat industry is seeking to establish reassurance on traceability and production techniques that may help to promote confidence in the integrity and origin of the products. The overall tracing of beef quality is actually the risk identification and control along the supply chains of beef production. This study focused on the identification and control methods of quality risks in China traditional beef Cattle Breeding with optimization approaches concerned. The quality risks in beef Cattle Breeding were classified by features to develop the disseminated model of these risks and its algorithms. Then the theory of quality traceability was used and a concept model of quality risk control was proposed. Tracing units were divided and tracing nodes were set through optimization. The proposed risk identification and control models were capable of identifying and handling a product and the information attached to it throughout the whole production process to retail packs.

  • Beef quality risk identification and optimization in beef Cattle Breeding
    2008
    Co-Authors: Jian Zhang, Lingxian Zhang
    Abstract:

    The meat industry is seeking to establish reassurance on traceability and production techniques that may help to promote confidence in the integrity and origin of the products. The overall tracing of beef quality is actually the risk identification and control along the supply chains of beef production. This study focused on the identification and control methods of quality risks in China traditional beef Cattle Breeding with optimization approaches concerned. The quality risks in beef Cattle Breeding were classified by features to develop the disseminated model of these risks and its algorithms. Then the theory of quality traceability was used and a concept model of quality risk control was proposed. Tracing units were divided and tracing nodes were set through optimization. The proposed risk identification and control models were capable of identifying and handling a product and the information attached to it throughout the whole production process to retail packs.

Jian Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Modelling and method for beef quality risk identification and optimization in beef Cattle Breeding
    WSEAS Transactions on Information Science and Applications archive, 2009
    Co-Authors: Jian Zhang, Lingxian Zhang, Liang Shi
    Abstract:

    The meat industry is seeking to establish reassurance on traceability and production techniques that may help to promote confidence in the integrity and origin of the products. The overall tracing of beef quality is actually the risk identification and control along the supply chains of beef production. This study focused on the identification and control methods of quality risks in China traditional beef Cattle Breeding with optimization approaches concerned. The quality risks in beef Cattle Breeding were classified by features to develop the disseminated model of these risks and its algorithms. Then the theory of quality traceability was used and a concept model of quality risk control was proposed. Tracing units were divided and tracing nodes were set through optimization. The proposed risk identification and control models were capable of identifying and handling a product and the information attached to it throughout the whole production process to retail packs.

  • Beef quality risk identification and optimization in beef Cattle Breeding
    2008
    Co-Authors: Jian Zhang, Lingxian Zhang
    Abstract:

    The meat industry is seeking to establish reassurance on traceability and production techniques that may help to promote confidence in the integrity and origin of the products. The overall tracing of beef quality is actually the risk identification and control along the supply chains of beef production. This study focused on the identification and control methods of quality risks in China traditional beef Cattle Breeding with optimization approaches concerned. The quality risks in beef Cattle Breeding were classified by features to develop the disseminated model of these risks and its algorithms. Then the theory of quality traceability was used and a concept model of quality risk control was proposed. Tracing units were divided and tracing nodes were set through optimization. The proposed risk identification and control models were capable of identifying and handling a product and the information attached to it throughout the whole production process to retail packs.

Liang Shi - One of the best experts on this subject based on the ideXlab platform.

  • Modelling and method for beef quality risk identification and optimization in beef Cattle Breeding
    WSEAS Transactions on Information Science and Applications archive, 2009
    Co-Authors: Jian Zhang, Lingxian Zhang, Liang Shi
    Abstract:

    The meat industry is seeking to establish reassurance on traceability and production techniques that may help to promote confidence in the integrity and origin of the products. The overall tracing of beef quality is actually the risk identification and control along the supply chains of beef production. This study focused on the identification and control methods of quality risks in China traditional beef Cattle Breeding with optimization approaches concerned. The quality risks in beef Cattle Breeding were classified by features to develop the disseminated model of these risks and its algorithms. Then the theory of quality traceability was used and a concept model of quality risk control was proposed. Tracing units were divided and tracing nodes were set through optimization. The proposed risk identification and control models were capable of identifying and handling a product and the information attached to it throughout the whole production process to retail packs.

Peter Sandøe - One of the best experts on this subject based on the ideXlab platform.

  • Genomic dairy Cattle Breeding: risks and opportunities for cow welfare.
    Animal Welfare, 2010
    Co-Authors: T. Mark, Peter Sandøe
    Abstract:

    The aim of this paper is to discuss the potential consequences of modern dairy Cattle Breeding for the welfare of dairy cows. The paper focuses on so-called genomic selection, which deploys thousands of genetic markers to estimate Breeding values. The discussion should help to structure the thoughts of breeders and other stakeholders on how to best make use of genomic Breeding in the future. Intensive Breeding has played a major role in securing dramatic increases in milk yield since the Second World War. Until recently, the main focus in dairy Cattle Breeding was on production traits, but during the past couple of decades more emphasis has been placed on a few rough, but useful, measures of traits relevant to cow welfare, including calving ease score and 'clinical disease or not'; the aim being to counteract the unfavourable genetic association with production traits. However, unfavourable genetic trends for metabolic, reproductive, claw and leg diseases indicate that these attempts have been insufficient. Today, novel genome-wide sequencing techniques are revolutionising dairy Cattle Breeding; these enable genetic changes to occur at least twice as rapidly as previously. While these new genomic tools are especially useful for traits relating to animal welfare that are difficult to improve using traditional Breeding tools, they may also facilitate Breeding schemes with reduced generation intervals carrying a higher risk of unwanted side-effects on animal welfare. In this paper, a number of potential risks are discussed, including detrimental genetic trends for non-measured welfare traits, the increased chance of spreading unfavourable mutations, reduced sharing of information arising from concerns over patents, and an increased monopoly within dairy Cattle Breeding that may make it less accountable to the concern of private farmers for the welfare of their animals. It is argued that there is a need to mobilise a wide range of stakeholders to monitor developments and maintain pressure on Breeding companies so that they are aware of the need to take precautionary measures to avoid negative effects on animal welfare and to invest in Breeding for increased animal welfare. Researchers are encouraged to further investigate the long-term effects of various Breeding schemes that rely on genomic Breeding values.

P.j. Boettcher - One of the best experts on this subject based on the ideXlab platform.

  • 2020 Vision? The Future of Dairy Cattle Breeding from an Academic Perspective
    Journal of Dairy Science, 2001
    Co-Authors: P.j. Boettcher
    Abstract:

    In the future, all aspects of dairy Cattle Breeding will continue to be shaped by trends in the industry that have been occurring for the past generation. Dairy farms will continue to increase in size and decrease in number. Advancement will continue in the development and adoption of computers, genomics, and other technologies, and the dairy Cattle Breeding industry will continue to become more global in its scale. These factors will both directly and indirectly affect the research and teaching activities of those who chose to follow a career path similar to Gene Freeman’s. A major consequence of these factors is that as farm sizes increase and the proportion of the public directly involved in dairy production decreases, the public support for teaching and research in dairy Cattle Breeding is also likely to diminish. Family farms will likely be increasingly viewed as businesses and asked to directly support a greater portion of their research and development activities. Nevertheless, the public will still influence research priorities. Health and well-being of Cattle and genetic diversity will likely become more important as consumers react to concerns about food safety and animal welfare. These factors will also be of direct concern to breeders, because they influence profit by affecting costs of production. Producers will put increased value on trouble-free Cattle that demand less individual attention. Computers and automated equipment will allow data for health and functional traits to be captured efficiently, which will be necessary before either traditional or genomics based selection tools can be applied. New technology resulting from research will be transferred to the field and applied more quickly. Graduate students will require very diverse training. Although graduates will probably work in very specialized fields (and probably not in academics) and perform relatively specialized tasks, they will likely be doing so as members of larger teams. The ability to interact and communicate with their collaborators, as well as breeders, industry representatives and the general public, will be paramount.