• Korean Journal of Ichthyology
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• v.32 no.4
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• pp.210-221
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• 2020

Since the introduction of Israeli carp into Korea for farming in 1973, there are no breeding studies on developing Korea Israeli carp (domestic) so far. This study performed gene-based cross-breeding studies to restore genetic diversity of lowered Israeli carp through continuous inbreeding, and for rapid growth and better scales. This study produced four cross-breeding groups (F1) using Koean Israeli carp and Chinese Songpu mirror carp for the improvement of growth and scale of Israeli carp in Korea. And mating scheme for breeding groups was set in consideration of the morphological analysis and genetic distance of broodstock. In addition, this study used microsatellite markers and genotype data to analyze genetic diversity and parentage analysis. As a result, the average N_A and H_E values of Korean select broodstock are 8.3 and 0.743, and F1 is 13.0 and 0.764. This study shows that the genetic diversity of F1 has been recovered over Korean Israeli carp through breeding between Korean Israeli carp and Chinese Songpu mirror carp. Common Israeli carp in Korea reached 1.7 kg in 17 months, and improved Israeli carp reached to 2.2 kg. The KC (Korea×China, KC) group was 2.52 and broodstock group was 3.15. F1 showed lower scale score (0.63) than broodstock. The improved carp (F1; CK, KC) had 20% better scales than the parent group (F0), which improved 27% in weight and 25% in scales compared to common Israeli carp. The Israeli carp developed by the genetics-based breeding grew quicker and had improved genetic diversity and fewer scales, which will be of great value for Korean Israeli aquaculture industry due to good marketability.

• The Journal of the Convergence on Culture Technology
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• v.4 no.2
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• pp.197-204
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• 2018

One of the hottest issues in our 21st century is AI. Just as the automation of manual labor has been achieved through the Industrial Revolution in the agricultural society, the intelligence information society has come through the SW Revolution in the information society. With the advent of Google 'Alpha Go', the computer has learned and predicted its own machine learning, and now the time has come for the computer to surpass the human, even to the world of Baduk, in other words, the computer. Machine learning ML (machine learning) is a field of artificial intelligence. Machine learning ML (machine learning) is a field of artificial intelligence, which means that AI technology is developed to allow the computer to learn by itself. The time has come when computers are beyond human beings. Many companies use machine learning, for example, to keep learning images on Facebook, and then telling them who they are. We also used a neural network to build an efficient energy usage model for Google's data center optimization. As another example, Microsoft's real-time interpretation model is a more sophisticated translation model as the language-related input data increases through translation learning. As machine learning has been increasingly used in many fields, we have to jump into the AI industry to move forward in our 21st century society.