Method of herd management

• US 7,278,373 B2
• Filed: 01/30/2002
• Issued: 10/09/2007
• Est. Priority Date: 01/30/2002
• Status: Expired due to Fees

• Current Assignee: James Fuqua
• Original Assignee: James Fuqua
• Inventors: Fuqua, James
• Primary Examiner(s): Price; Thomas
• Application Number:
  US10/060,616
• Publication Number:
  US 20030140865A1
• Time in Patent Office: 2,078 Days
• Field of Search: None
• US Class Current: 119/174
• CPC Class Codes: A01K 11/004 with electronic identification means, e.g. transponders
• CPC Class Codes: A01K 11/006 Automatic identification systems for animals, e.g. electronic devices, transponders for animals identification systems for access to feeding pens A01K1/0209; ear tags with electronic identification means A01K11/004
• CPC Class Codes: A01K 29/00 Other apparatus for animal husbandry

Abstract

A method and system to generate the highest level of return on investment of a cattle ranch producing beef to the consumer. Through the use of computer software integrated with an individual cow and calf identification system, the method and system disclosed herein allows a cattle producer to analyze the yearly production characteristics of each individual cow'"'"'s calf or calves through all the various phases of growth and production with an accumulation of the economic cost and gain of value up to the end product as a feeder or cull.

The total value of the carcass at the end of production, expressed as a sum of the costs associated with producing each animal minus the market value of the animal, allows the animal'"'"'s economic value to be expressed by one figure which can then be used to judge the cow'"'"'s ability to produce animals that meet all predetermined economically important genetic traits. This system and method of cow herd management provides a continuing improvement in the efficiency of the ranching operation and a better product for the consumers.

Claims

1. A method of managing a cow herd for optimal production comprising:

identifying a calf in a cow herd;

matching said calf to a cow in said cow herd;

collecting an initial set of data on the calf;

assigning said calf a quality grade, wherein said quality grade reflects a correlation of said calf'"'"'s initial set of data with a model data;

selecting the said calf as a feeder calf or a cull based on said quality grade;

linking said quality grade to said cow and a bull; and

determining whether to cull said cow or said bull based upon said quality grade.

2. The method of claim 1 wherein the identification of said calf comprises at least one of visual identification or electronic identification.

3. The method of claim 1 wherein the collection of said initial data includes at least one of ear tag number weight, location, service year, vaccination type, vaccination lot number, vaccination date, weaning weight, weaning date and percentage of cow'"'"'s body weight.

4. The method of claim 1, wherein said model data is based upon the genetic lineage of the calf.

5. The method of claim 1, wherein said model data is based upon an historic genetic line performance probabilities of said calf.

6. The method of claim 1, wherein said model data is based upon an historic data of said cow.

7. The method of claim 1, wherein said model data is based upon an historic data of said bull.

8. The method of claim 1 wherein said model data is based upon an estimated progeny differences of said cow.

9. The method of claim 8, wherein the collection of said feeder data on said feeder calf includes at least one of shipping weight, shipping date, gain at stocker and feedlot location.

10. The method of claim 8, at wherein the collection of said carcass data on said feeder calf includes at least one of days on feed, feed in weight, feed out weight, hot carcass weight, avenge daily weight gain, dressing percentage, ribeye area (REA), back fat, kidney/pelvic/bean content (KHP), yield grade and marbling score.

11. The method of claim 10, wherein the yield grade is computed in accordance with a formula which correlates the back fat, KHP, hot carcass weight and REA of said feeder calf.

12. The method of claim 11, wherein said yield grade equals 2.5+(2.5×

back fat)+(0.2+KHP)+(0.0038×

hot carcass weight)−

(0.32×

REA).

13. The method of claim 8, wherein the step of selecting said feeder calf for target market grid includes a statistical numerical analysis of the said feeder calf'"'"'s feeder data and a determination of the economic costs and gains associated with the production of the feeder calf.

14. The method of claim 8, wherein the step of selecting said feeder calf for target market grid includes a predetermined yield grade.

15. The method of claim 8, wherein the step of selecting said feeder calf for target market grid includes a predetermined quality grade.

16. The method of claim 8, wherein the carcass data on said feeder calf includes at least one of a predetermined shipping weight, days on feed, feed in weight, feed out weight hot carcass weight, average daily weight gain, dressing percentage, ribeye area, back fat, kidney/pelvic/heart fat, and marbling score.

17. The method of claim 8, wherein the step of selecting said feeder calf for target market grid includes an analysis of the genetic lineage of the feeder calf.

18. The method of claim 1, wherein said model data is based upon an estimated progeny differences of said bull.

19. The method of claim 1, further comprising:

collecting a feeder data on said feeder calf;

selecting said feeder calf for a target market grid based upon said feeder data; and

harvesting said feeder calf; and

collecting a carcass data on said feeder calf.

20. The method of claim 19, further comprising updating said model data with said feeder calf'"'"'s carcass data.

21. The method of claim 19, further comprising updating historic data of said cow with said feeder calf'"'"'s carcass data.

22. The method of claim 19, further comprising updating historic data of said bull with said feeder calf'"'"'s carcass data.