Computer system for determining a customized animal feed

• US 20060283393A1
• Filed: 02/06/2006
• Published: 12/21/2006
• Est. Priority Date: 12/15/2000
• Status: Active Grant

• Current Assignee: Can Technologies, Inc. (Cargill Incorporated)
• Original Assignee: Can Technologies, Inc. (Cargill Incorporated)
• Inventors: Knudson, Brian J., Cook, David A., Burghardi, Steve R., Oedekoven, Mark A., Peterson, Loren
• Granted Patent: US 7,296,537 B2
• Time in Patent Office: Days
• US Class Current: 119/51.10
• CPC Class Codes: A01K 5/02 Automatic devices automatic identification devices for stock A01K11/006
• CPC Class Codes: A23K 20/142 Amino acids; Derivatives thereof
• CPC Class Codes: A23K 40/00 Shaping or working-up of animal feeding-stuffs
• CPC Class Codes: A23K 50/10 for ruminants
• CPC Class Codes: A23K 50/30 for swines
• CPC Class Codes: A23K 50/80 for aquatic animals, e.g. fish, crustaceans or molluscs
• CPC Class Codes: Y02A 40/818 Alternative feeds for fish, e.g. in aquacultures

Abstract

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.

Claims

1-2. -2. (canceled)

3. A system for determining customized feed for at least one animal, the system comprising:

a first memory portion configured to store animal data representative of the characteristics of the animal;

a second memory portion configured to store feed data representative of the feed ingredients located at at least one location;

a third memory portion configured to store evaluation data representative of at least two evaluation criteria;

a data processing circuit in communication with the memory portions and configured to generate nutrient profile data representative of a nutrient profile for the animal based upon the animal data, the data processing circuit being further configured to generate ration data representative of a combination of ingredients from the at least one location, the ration data being generated by the data processing circuit based upon the profile data, the feed data and the evaluation data; and

a fourth memory portion in communication with the data processing circuit and configured to store optimization weighting data representative of the effect a respective evaluation criteria has on the generation of the ration data, the data processing circuit further generating the ration data based upon the optimization weighting data.

4. The system of claim 3, wherein the animal data is representative of at least one of a beginning weight of the animal;

a desired weight of the animal;

an environment of the animal;

a feed form;

an actual or desired production level of the animal; and

a relationship of animal muscle to fat of the animal.

5. The system of claim 3, wherein the feed ingredients include at least one of a grain source, a protein source, a vitamin source, a mineral source and a fat source.

10. The system of claim 3, wherein the optimization weighting data may be selected to cause one of the evaluation criteria to have no effect on the generation of the ration data.

11. The system of claim 3, wherein the memory portions are portions of a digital memory and a parallel data bus is coupled between the digital memory and the data processing circuit to facilitate communication therebetween.

12. The system of claim 3, wherein the memory portions are portions of a plurality of digital memories and a network couples the digital memories to the data processing circuit to facilitate communication therebetween.

13. The system of claim 3, wherein the nutrient profile data is representative of at least two nutrient components, and the system further includes a fifth memory portion in communication with the digital processor, the fifth memory portion storing variation data representative of a range for the nutrient components of the nutrient profile and the digital processor generates a set of ration data based upon the variation data.

14. The system of claim 13, wherein the nutrient components include at least true digestible lysine and net energy.

15. The system of claim 3, wherein the feed data includes an amount for each feed ingredient.

16. The system of claim 15, wherein the amount for each feed ingredient can be constrained according to one or more criteria.

17. The system of claim 16, wherein the amount of each feed ingredient can be constrained according to at least two criteria.

18. The system of claim 3, wherein the animal data includes an animal characteristic related to at least one of an environment, a current condition, a desired final condition, a genotype, a feed form, a current production level and a desired production level.

19. The system of claim 3, wherein the at least one animal is one or more cattle, swine, poultry, fish, or crustaceans.

20. The system of claim 3, wherein the animal data includes a parameter related to an animal production level.

21. The system of claim 3, wherein the animal data includes a parameter related to an animal genotype.

22. The system of claim 3, wherein the animal data includes a parameter related to an animal environment.

23. The system of claim 3, wherein the animal data includes a parameter related to an animal feeding regime.

24. The system of claim 3, wherein the feed data includes supplier feed data representative of sets of ingredients located at a supplier site and on-farm feed data representative of sets of ingredients located at an on-farm site,

wherein the on-farm feed data include data representative of costs and amounts of ingredients located at the on-farm site.

25. The system of claim 3, wherein the evaluation criteria include at least one of cost/gain, cost/output, animal production rate, and feed/gain.

26. The system of claim 3, wherein the evaluation criteria include data representative of an amount of feed required to produce a unit of gain.

27. The system of claim 3, wherein the evaluation criteria include data representative of a rate of weight gain of an animal.

28. The system of claim 3, wherein the evaluation criteria include data representative of a cost of feed required to produce a unit of weight gain of an animal.

29. The system of claim 3, wherein the ration data include data representative of a cost associated with the ration data data representative of a feed weight associated with the ration data, and data representative of projected animal performance associated with the ration data.

6. The system of clam 5, wherein the animal data is representative of at least one of a beginning weight of the animal;

a desired weight of the animal;

an environment of the animal;

a feed form;

an actual or desired production level of the animal; and

a relationship of animal muscle to fat of the animal.

7. The system of claim 6, wherein the evaluation criteria include at least two of (i) animal production rate, (ii) the cost of feed per unit animal weight gain, and (iii) the feed weight per unit animal weight gain.

8. The system of claim 7, wherein the feed ingredients include at least one of a grain source, a protein source, a vitamin source, a mineral source and a fat source.

9. The system of claim 7, wherein the animal production rate is at least one of a milk production rate, an egg production rate and a rate of lean weight gain.

30. A system for determining customized feed for at least one animal, the system comprising:

first memory means for storing animal data representative of the characteristics of the animal;

second memory means for storing feed data representative of the feed ingredients located at at least one location;

third memory for storing evaluation data representative of at least two evaluation criteria;

processing means for generating profile data representative of a nutrient profile for the animal based upon the animal data, process means further generating ration data representative of a combination of ingredients from the location, the ration data being generated by the processing means based upon the profile data, the feed data and the evaluation data; and

fourth memory means for storing optimization weighting data representative of the effect a respective evaluation criteria has on the generation of the ration data, the processing means further generating the ration data based upon the optimization weighting data.

31. The system of claim 30, wherein the animal data is representative of at least one of a beginning weight of the animal;

a desired weight of the animal;

an environment of the animal;

a feed form;

an actual or desired production level of the animal; and

a relationship of animal muscle to fit of the animal and the feed indents include at least one of a grain source, a protein source, a vitamin source, a mineral source and a fat source.

32. The system of claim 30, wherein die evaluation criteria include at least two of (i) animal production rate, (ii) the cost of feed per unit animal weight gain, and (iii) the feed weight per unit animal weight gain.

33. The system of claim 32, wherein the feed ingredients include at least one of a grain source, a protein source, a vitamin source, a mineral source and a fat source.

34. A method for determining customized feed for at least one animal, the method comprising:

storing animal data representative of the characteristics of the animal;

storing feed data representative of the feed ingredients located at at least one location;

storing evaluation data representative of at least two evaluation criteria;

storing optimization weighting data representative of the effect a respective evaluation criteria;

generating profile data representative of a nutrient profile for the animal based upon the animal data; and

generating ration data representative of a combination of ingredients from the location, the ration data being generated based upon the profile data, the feed data, the evaluation data, and the optimization weighting data.

35. The method of claim 34, wherein the feed data includes an amount for each feed ingredient.