{"id":827,"date":"2023-04-24T15:33:32","date_gmt":"2023-04-24T18:33:32","guid":{"rendered":"https:\/\/opta.siteup.dev\/aplicacao-da-modelagem-matematica-em-frangos-de-corte\/"},"modified":"2023-04-24T15:33:32","modified_gmt":"2023-04-24T18:33:32","slug":"aplicacao-da-modelagem-matematica-em-frangos-de-corte","status":"publish","type":"post","link":"https:\/\/opta.siteup.dev\/en\/aplicacao-da-modelagem-matematica-em-frangos-de-corte\/","title":{"rendered":"Application of mathematical modeling in broiler chickens"},"content":{"rendered":"

Modern poultry farming demands practical solutions that reduce costs and maximize profit margins. Based on this narrative, technological advancements have allowed us to progress in generating creative solutions applicable to the daily problems faced with nutrition, health, and animal welfare, all in real time. For example, mathematical modeling has become an increasingly important tool in various fields of knowledge, including broiler farming. Through mathematical models, it is possible to predict the performance of a flock of birds, identify risk factors, and determine the best management strategies to maximize production and minimize losses.<\/p>\n

Understanding mathematical modeling<\/strong><\/h3>\n

Mathematical modeling is the process of using models to describe biological or physical phenomena. Mathematical models are constructed using equations and variables that represent the properties of the system. It can be used in a variety of fields, especially in animal production systems, allowing researchers to study, explore, and predict the behavior of complex systems, helping them understand how different factors interact and affect the system.<\/p>\n

What is the difference between mathematical modeling and machine learning?<\/strong><\/h3>\n

Mathematical modeling is based on principles or laws that govern a system (physical, chemical, or other) and uses mathematical equations to describe the relationships between variables. These equations are usually developed from theories or experiments and are used to predict the system's behavior in different situations. It can be applied in areas such as exact sciences, biological sciences, agronomy, health sciences, among others.<\/p>\n

On the other hand, machine learning is a data-driven modeling technique that uses algorithms to learn patterns and make predictions or classifications in new data. Machine learning models are not based on mathematical equations or physical theories, but on algorithms that learn from large datasets. Machine learning is used in areas such as image recognition, natural language processing (such as animal behavior patterns), demand forecasting in various sectors, among others, and is an excellent tool for process automation.<\/p>\n

Application of mathematical modeling in broiler chickens<\/strong><\/h3>\n

The Gompertz equation is one of the most widely used tools in mathematical modeling for broiler chickens and can be applied to describe the growth of a flock over time, predict the average weight of birds at any age, and identify risk factors such as disease, stress, and nutritional deficiencies. The equation is described as:<\/p>\n

\n
\"Equa\u00e7\u00e3o<\/figure>\n<\/div>\n

For example, if the growth rate B is decreasing relative to what is expected, it may indicate a health or nutritional problem in the flock. This equation is based on the principle that growth is exponential at the beginning, but slows down as the birds reach maturity.<\/p>\n

To apply the Gompertz equation to broiler farming, it is necessary to collect weight data from birds at different ages and adjust the equation parameters to better describe the growth of the flock. Based on the adjusted parameters, it is possible to manage and improve the productivity and profitability of your breeding system by calculating the maximum and relative growth rates of broilers, allowing you to optimize their nutrition and flock size\u2014functions that are easily managed using the BroilerOPT\u2122 tool.<\/p>\n

Get to know BroilerOPT\u2122<\/a><\/p>\n

An indispensable tool in broiler poultry farming: BroilerOPT\u2122<\/strong><\/h3>\n

The BroilerOPT\u2122 software was developed by Frank Ivey, CEO of the American company. FEED2GAIN<\/a>. It was created to assist producers and integrators in managing broiler growth and maximizing flock productivity, using mathematical modeling to estimate production costs and evaluate animal nutrition in pursuit of better results, maximizing the productive potential of the specific breed and the impact on body mass deposition in the cuts of greatest interest to the industry. Observe some economic results obtained through optimization using the BroilerOPT\u2122 software:<\/p>\n

\n
\"\"<\/figure>\n<\/div>\n

Access the article \u201c"Feed costs for broiler chickens and growth curve, optimized with BroilerOPT\u2122 software"\u201d<\/a> For more information about the study, or to contact our consultants, stay informed about our updates through... LinkedIn<\/a>.<\/p><\/p>","protected":false},"excerpt":{"rendered":"

A avicultura moderna tem exigido solu\u00e7\u00f5es pr\u00e1ticas que reduzam custos e maximizem margens de contribui\u00e7\u00e3o. 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