Enhancing Pork Quality and Value Using Live Animal Ultrasound Technology for Better Breeding and Marketing Decisions

Award Information
Agency:
Department of Agriculture
Branch
n/a
Amount:
$79,943.00
Award Year:
2006
Program:
SBIR
Phase:
Phase I
Contract:
2006-33610-16761
Agency Tracking Number:
2006-00153
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Biotronics, Inc.
1606 Golden Aspen Drive, Suite 104, Ames, IA, 50010
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Doyle Wilson
President
(515) 233-4161
dewilson@biotronics-inc.com
Business Contact:
Doyle Wilson
President
(515) 296-4010
dewilson@biotronics-inc.com
Research Institution:
n/a
Abstract
Over the past 15 years, the emphasis on selecting for leaner pigs with larger loineye areas and high percent lean cuts has resulted in meat with lower water-holding capacity, lower intramuscular fat (IMF), and lower scores for juiciness, flavor and overall pork quality. Swine breeders need a genetic selection tool to help reverse this trend. The purpose of this project is to build on several years of research experience with ultrasound and prediction of IMF for live beef cattle by applying the technology to live swine. Phase I involves serially scanning 400 live animals to develop mathematical models to characterize the IMF in pork samples from each pig. A database of image texture parameters that are predictive of IMF will be developed. Pigs will be harvested, visual marbling scores will be obtained at the packing plant, tissue samples will be taken at the scanning site, and a slice of the longissimus muscle from the 10th to 11th rib interface will be transported to a meat laboratory for chemical analysis. Linear and nonlinear IMF prediction models will be developed using the image texture parameters as the dependent variables and the tissue IMF (chemical fat) as the independent variable. Phase I will prove the ability to enhance IMF prediction accuracy using ultrasound in live pigs by a minimum of 10 percent over the current published research. In addition, Phase I will demonstrate the ability to port an IMF prediction model from one ultrasound equipment type to another with an incremental standard error of prediction of less than 0.25% IMF.

* information listed above is at the time of submission.

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