نوع مقاله : مقاله مروری
نویسندگان
1 دانشجوی دکتری تخصصی ژنتیک و اصلاح نژاد دام و طیور، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران ، کرج، ایران
2 دانشیار ژنتیک و اصلاح نژاد دام و طیور، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران
3 کارشناسی ارشد ژنتیک و اصلاحنژاد دام، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
The general perspective of livestock and poultry breeding is being transferred to the digital era with high operational capacity, in which high-throughput technologies are utilized to boost the accuracy of phenotypic records collection and estimation of breeding values. Then, using advanced software and large computers, high amount of data is processed. The advent of NGS and the identification of SNPs along with new statistical methods for using this data to estimate the breeding value has led to the widespread use of genomic selection in dairy cattles and poultry. The development of data mining algorithms related to big data plays a significant role in estimating breeding values. A range of novel technologies, such as artificial intelligence, machine learning and deep learning, provide proper opportunities compared to traditional methods for examining economic traits with complex architecture. These approaches have made it possible to analyze large data sets and large genomic information in order to achieve desirable results. The purpose of this study is to provide a brief explanation of the new methods and novel technologies in animal sciences which are widely used in phenotype data collection and data registration in order to estimate accurate breeding values, in such a way as to lead to a digital future. Therefore, increasing the potential of big data analysis, along with new methods for recording phenotypic traits and estimating the breeding values, will dramatically augment genetic improvement.
کلیدواژهها [English]