Can Technologies, Inc.

Brian J Knudson

David A Cook

Steve R Burghardi

Mark A Oedekoven

Loren Peterson

Kari Juhani Ruohonen

Adel El-mowafi

Christian De Santis

Disclosed are various approaches for determining an animal feed formulation. In some implementations, a system may obtain data that provides characteristics of an animal population located at a site. The system may identify a target growth schedule for the animal population. The system may use a data processing model to predict nutrition requirements for tissue growth in the animal population, using the target growth schedule and the characteristics of the animal population, as the model predicts nutrition requirements based on projected nitrogenous energy requirements for the tissue growth. The system may identify a feed formulation producible from a combination of animal feed ingredients to satisfy the nutrition requirements for tissue growth. The system may generate a data output for use of the feed formulation with the animal population, the data output indicating the identified feed formulation producible from the combination of animal feed ingredients.

Energy-based animal nutrition modeling and formulation systems

A method and system for creating a customized animal feed is disclosed. The method and system include having ingredient data from more than one location, animal data, evaluation data, and optimization weighting data. The specifications for a customized feed are generated using ingredient data representative of the mix of ingredients available at one or more locations. A customized feed is generated which is designed to fulfill the nutritional requirements for the animal's diet. The nutritional requirements are derived from the animal data. Furthermore, the feed is optimized based upon the profile data, the feed data, the evaluation data, and the optimization weighting data.

Computer system for determining a customized animal feed

A method and system for creating a customized animal feed is disclosed. The method and system include having ingredient data from more than one location, animal data, and representative of the mix of ingredients available at one or more locations. A customized feed is generated which is designed to fulfill the nutritional requirements for the animal's diet. The nutritional requirements are derived from the animal data. Furthermore, the feed is optimized to fulfill the requirements of the evaluation criteria. Evaluation criteria such as (i) animal production rate, (ii) the cost of feed per unit animal weight gain, and (iii) the feed weight per unit animal weight gain, are then utilized together with the feed data and animal data to provide a customized feed which has been generated based upon evaluation data which is representative of one or more of the evaluation criteria.

A method and system for creating a customized animal feed includes having ingredient data from more than one location, animal data, and evaluation data. The specifications for a customized feed are generated using ingredient data representative of the mix of ingredients available at one or more locations. A customized feed is generated which is designed to fulfill the nutritional requirements for the animal's diet. The nutritional requirements are derived from the animal data. Furthermore, the feed is optimized to fulfil the requirements of the evaluation criteria. Evaluation criteria such as (i) animal production rate, (ii) the cost of feed per unit animal weight gain, and (iii) the feed weight per unit animal weight gain, are then utilized together with the feed data and animal data to provide a customized feed which has been generated based upon evaluation data which is representative of one or more of the evaluation criteria.

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Chanhassen, MN, United States of America

Brian J Knudson