Linking Animal Feed Formulation to Milk Quantity, Quality, and Animal Health Through Data-Driven Decision-Making DOI Creative Commons

Oreofeoluwa A. Akintan,

K. G. Gebremedhin, Daniel Dooyum Uyeh

и другие.

Animals, Год журнала: 2025, Номер 15(2), С. 162 - 162

Опубликована: Янв. 10, 2025

The global demand for high-quality animal products, particularly dairy, has intensified the need more precise and efficient livestock feed formulation. This review connects data-driven decision-making in optimizing formulation to enhance milk quantity quality while addressing health implications. Modern evolved into a sophisticated, data-centric process by integrating diverse data sources such as nutritional databases, environmental data, performance metrics. Leveraging advanced analytical techniques, machine learning optimization algorithms, have created highly accurate formulations tailored specific needs. These innovations increase yield contribute developing dairy products with higher value. Decision Support Systems play complementary role offering real-time capabilities, enabling farmers make data-informed adjustments composition based on changing conditions. However, despite its potential, widespread adoption of faces challenges quality, technological limitations, industry resistance, mostly disjointed processes. objectives this are: (i) explore current advancements formulation, focusing connection (ii) highlight how optimized strategy improves sustainable production.

Язык: Английский

Linking Animal Feed Formulation to Milk Quantity, Quality, and Animal Health Through Data-Driven Decision-Making DOI Creative Commons

Oreofeoluwa A. Akintan,

K. G. Gebremedhin, Daniel Dooyum Uyeh

и другие.

Animals, Год журнала: 2025, Номер 15(2), С. 162 - 162

Опубликована: Янв. 10, 2025

The global demand for high-quality animal products, particularly dairy, has intensified the need more precise and efficient livestock feed formulation. This review connects data-driven decision-making in optimizing formulation to enhance milk quantity quality while addressing health implications. Modern evolved into a sophisticated, data-centric process by integrating diverse data sources such as nutritional databases, environmental data, performance metrics. Leveraging advanced analytical techniques, machine learning optimization algorithms, have created highly accurate formulations tailored specific needs. These innovations increase yield contribute developing dairy products with higher value. Decision Support Systems play complementary role offering real-time capabilities, enabling farmers make data-informed adjustments composition based on changing conditions. However, despite its potential, widespread adoption of faces challenges quality, technological limitations, industry resistance, mostly disjointed processes. objectives this are: (i) explore current advancements formulation, focusing connection (ii) highlight how optimized strategy improves sustainable production.

Язык: Английский

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