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• W4207041570 abstract "Abstract Background: An optimal selective breeding program must balance ethical risks and operational costs without necessarily compromising its effectiveness and aims. For this purpose, a modular breeding simulator was used. Modular simulation acts as a preliminary evaluation instrument to predict the entire likelihood of outputs from a complex selective breeding program. Methods: A web-based modular stochastic simulator (MoBPSweb) facilitates the design-test-analysis workflow of the meat-type Pelung chicken selective breeding program with the nickname Gama Ayam Kambro. Several specific selective parameters were formulated and tested against the actual breeding scheme according to Gama Ayam Kambro's research. Three selection scenarios applied to Gama Ayam Kambro's breeding scheme, constructed based on three technical principles of crossings. These scenarios were compared based on accuracy, F  coefficient, kinship, and observed phenotypes. An available feature on MoBPSweb also allowed the projections of specific economic parameters. Results: Crossing techniques, selection model scenarios, and breeding schemes determine the accuracy, F coefficient, kinship, and observed phenotypes. The selection accuracy of male 5 th Kambro and Pelung could be optimized using the design of genomic selection scenario_1 and outbreeding crossing techniques, both for Broiler and Pelung selection index. The selection model scenario and similar crossing technique are also quite effective in controlling the F coefficient. However, the outbreeding crossing technique is less effective in increasing the achievements of AFE, BW49D, EN, and FCR, contrarily for FEML, TL, and BW56D. Therefore, for AFE and FEML, the selection of 5 th Kambro dan Pelung males could be more optimal by using scenario_2 (BV) and scenario_3 (PHEN), respectively. Meanwhile, for BW49D and EN, the reciprocal applies. Therefore, the selection of 5 th Kambro and Pelung males for FCR and BW56D would be more optimal if scenario_1 (GEN) and scenario_3 (PHEN) were used, respectively. Meanwhile, for TL, it would be more optimal if scenario_3 with a phenotype selection design was used for both. The projection of economic parameters indicates that the total operational cost per year is required around ±500 million rupiahs for these three selection model scenarios using Gama Ayam Kambro breeding scheme with 100 intensive rearing enclosure units and 50 breeding generations. In addition, the projected operational cost must consider the inflation and interest rate of rupiah per year. Conclusions: Digitalization of selective breeding program using MoBPSweb stochastic simulator allows the design-test-analysis (DTA) procedure in Gama Ayam breeding scheme and its parameters and scenarios to be executed immediately and the results evaluated in real-time. However, there are at least two things to consider about this research. Firstly, genomic parameters that are specific cause a niche of reference, which means that this research is difficult to compare with other relevant studies. Therefore, the only solution is to do directly testing in the field. Implicitly, it is projected that there will be an exponential increase in the amount of data that must be accommodated by greater computing power to maintain and increase the simulation sensitivity. Therefore, these computational requirements may need to be considered one of the operational cost components, especially for the digital integrated poultry industry." @default.
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• W4207041570 date "2022-01-24" @default.
• W4207041570 modified "2023-10-03" @default.
• W4207041570 title "Simulated Comparison Between Different Scenarios of Modular Chicken Breeding Program using MoBPSweb v.1.6.62" @default.
• W4207041570 doi "https://doi.org/10.21203/rs.3.rs-1289983/v1" @default.
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