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Animal sorting and grading system using MRI to predict maximum value

a grading system and animal technology, applied in the field of animal grading system using mri to predict maximum value, can solve the problems of not finding the correct 30 animals, several days of no weight gain for the remaining 270 animals, and too much fat, so as to reduce, if not eliminate, the dollar loss

Inactive Publication Date: 2005-09-29
ELLIS JAMES S
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0034] As animals enter the feedlot they are evaluated with the MRI / 3DS and given a PDVM. The PDMV is then recorded by a unique tag for the animal or with the animal's feedlot identification means used throughout the feedlot computer system. The computer system then sorts the animal by PDMV and directs the animal to a pen with animals that have identical PDMVs or similar PDMV ranges. The result is that all of the animals in a particular feedlot feeding pen go to market on or about the same PDMV day which dramatically reduces, if not eliminates, the dollars lost with the over-fed / under-fed dilemma.
[0035] The present invention also has advantages in the cow-calf segment and the carcass segment of the beef industry. Using similar techniques the cow-calf operators can evaluate their calf crop using MRI / 3DS along with computer means to rank, compare and sort the offspring for future sales, herd replacement and herd sire selection. Carcasses can be accurately measured using the MRI / 3DS evaluations along with computer systems to rank, compare and sort carcasses in a grading system that is like or similar to the current USDA grading system.

Problems solved by technology

One of the greatest challenges facing the meat producing industry today is to provide consistent uniform quality and conformity for their end products.
Within a pen of animals, an average of 5% or 15 head are over-fed resulting in being too fat.
This solution creates two additional problems.
First of all, a human visual sorting will only be partially accurate when compared to the results at the processing plant, therefore, one may not find the correct 30 animals.
Secondly, the disturbance of sorting 30 animals out of the pen and the disturbance as the remaining animals re-align the pecking order within the pen can cause several days of no weight gain for the remaining 270 animals.
This likely will cost the cattle feeder more than the yield grade discounts.
Another inconsistency is the portion of animals within the pen that need more than 120 days on feed to reach their maximum potential carcass value.
A final inconsistency is caused by a lack of genetics that prevent a portion of the animals from reaching even the minimum carcass values.
Additional days on feed will only result in additional unwanted backfat.
This would not improve the quality of the meat within the carcass nor the potential carcass value.
With over 25 million beef cattle fed annually, these uncaptured values are costing the industry well over $1 billion.
Cow-calf operators also face the challenge to provide consistent uniform quality and conformity for their calf crops that eventually become the selected meat cuts on the store shelf.
Annually, cow-calf operators struggle with critical decisions that directly effect their profits at the point of sale of their male calf crop.
However, there are 2.4 million bred heifers sold annually into dairy herds that have no history of ancestor performance and very little or no identification.
More recently, systems have evolved using two-dimensional video techniques in an attempt to measure external animal conformation, however, these systems have been very limited in that they are only able to measure a few linear conformation traits.
However, ultrasound has a very low accuracy for determining the percent intramuscular fat within the animal / carcass because of an unsolvable problem referred to as “speckle”, wherein the sound waves splash in all directions when encountering a fat cell.
However, it is possible, that when several systems with limited accuracies are combined it produces a multiplying effect on the inaccuracies of the entire system.
In addition to the low accuracy with 2-D measuring, the muscle must be severed to acquire the video images.
The exit way pen or exit way path may be an unnecessary step in the sorting process.

Method used

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  • Animal sorting and grading system using MRI to predict maximum value
  • Animal sorting and grading system using MRI to predict maximum value
  • Animal sorting and grading system using MRI to predict maximum value

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Embodiment Construction

, Belk thoroughly explains the use of a color video IA system to determine palatability and yield. He also provides a very limited and very brief explanation of the use of tomographics (CAT or PET) and ultrasound for his (IA) system to secure the palatability and yield results. Belk fails to describe in any manner the means by which the MRI would be used in his image analysis (IA) system and makes no attempt to explain the method or means in which MRI could determine or provide palatability and yield predictions of meat. Additionally, Belk fails to explain that one advantage of MRI technology is the fact that the carcass does not need to be severed to attain intramuscular fat distribution, I. Fat percentages and ribeye surface area measurements that are used in part to determine palatability and yield.

[0026] It is thus apparent that there is a need in the art for an improved process for comparing, sorting and grading animals in to groups of like kinds by evaluating and predicting a ...

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PUM

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Abstract

A system that compares, ranks, sorts and grades animals or carcasses into groups of like kinds according to previously determined predicted maximum values. For live animals, the system uses magnetic resonance imaging (MRI) on a single occasion to evaluate the animal and determine a number of days the animal must be fed to reach a maximum value. For carcasses, the system evaluates the carcass to grade the quality and quantity of meat the carcass will provide. The system also combines MRI imaging with a three-dimensional system to refine the number of days remaining for the animal to reach a maximum value, and the system, when used in a feedlot, will direct the animal to a feed pen based on the number of days remaining for the animal to reach maximum value.

Description

FIELD OF THE INVENTION [0001] This invention relates to a process for comparing, ranking, grading and sorting animals or carcasses into groups of like kinds by using internal evaluations on a single occasion and predicting a timeframe in which an animal or carcass reaches a predetermined maximum value. More particularly, the invention uses magnetic resonance imaging (MRI) for those evaluations that result in predicting the time frame for the desired maximum value. Even more particularly, this invention relates to the use of MRI on a single occasion, preferably in concert with structured light, light pattern triangulation and / or laser light three-dimensional animal surface modeling systems, 3-D systems (3DS), to evaluate an animal or carcass to predict the timeframe to achieve a desired predetermined maximum value and compare, rank, grade or sort them accordingly. BACKGROUND OF THE INVENTION [0002] One of the greatest challenges facing the meat producing industry today is to provide ...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): A01K29/00
CPCA01K29/00
Inventor ELLIS, JAMES S.
Owner ELLIS JAMES S
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