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2023, № 107

UDC: 636.5.034
GSNTI: 68.41.05

Mathematical modeling of the dependence of productivity and resistance indicators of laying hens on feed, feed additives and conditions of industrial poultry farming

The purpose of the work was to study the effect of the brown algae feed additive on the biochemical processes in the body of birds, on the productivity and resistance of laying hens and on their blood parameters. To achieve this goal, a computational neural network EuclidNN was created, which makes it possible to evaluate the effect of a feed additive with brown algae on the biochemical processes in the body of birds and on the indicators of their egg production based on the blood parameters of birds. The forecasts obtained in the study regarding the use of brown algae are planned to be used in industrial poultry farming to increase the productivity and quality of agricultural products. To analyze BigData, computer programs from the “artificial intelligence” series were used. Computational neural networks of this series make it possible to search for feed additives that ensure minimal loss of useful feed components and stimulate the gastrointestinal microflora to ensure full symbiosis of microorganisms with the body of chickens. When analyzing the blood leukogram parameters of laying hens, significant changes were revealed in the experimental group - the proportion of pseudoeosinophils increased by 50% and the proportion of lymphocytes decreased by 6% compared to the control group. Also, the proportion of pseudoeosinophils increased by 22% and the proportion of lymphocytes decreased by 4%. This indicates normalization of the immune status. A significant decrease in the number of eosinophils in the experimental group relative to the control group by 67% was revealed, which may indicate a lower allergic reaction of the body’s immune system, which can occur, for example, in response to parasitic infestations. When assessing blood phagocytosis indicators, phagocytic activity increased by 23%. It is also noteworthy that in the control group, the indicators of phagocytic activity and phagocytic index relative to the first sampling also tended to decrease. As a result of the research, a mathematical model and a neural network using this model were developed for the first time to analyze the productivity and resistance of poultry under the influence of a feed additive from brown algae.
Keywords: Poultry farming, broiler chickens, feeding, feed additive, brown algae, productivity, blood parameters, EuclidNN computational neural network.
DOI: 10.21515/1999-1703-107-236-244

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Authors:

1. Karpenko Larisa Yurievna, DSc in Biology, professor, Head, FSBEI HE "St. Petersburg State University of Veterinary Medicine".
2. Bakhta Alesya Aleksandrovna, PhD in Biology, associate professor, FSBEI HE "St. Petersburg State University of Veterinary Medicine".
3. Borisova Solomonida Dmitrievna, Graduate student, FSBEI HE "St. Petersburg State University of Veterinary Medicine".
4. Vorobyov Nikolay Ivanovich, PhD in Technology, leading researcher, FSBSI "All-Russia Research Institute for Agricultural Microbiology".
5. Nikonov Ilia Nikolaevitch, PhD in Biology, senior researcher, FSАEI HE "Immanuel Kant Baltic Federal University".
6. Laishev Kasim Anverovich, DSc in Veterinary, academician of the RAS, Chief Researcher, Saint Petersburg Federal Research Center of the RAS.