Hybrid System for Ultrasound Signal, Spectral, and Image Analyses to Enhance Meat Quality Evaluation in Food Animals

Award Information
Agency:
Department of Agriculture
Branch
n/a
Amount:
$80,000.00
Award Year:
2008
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
88541
Agency Tracking Number:
2010-02811
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1606 GOLDEN ASPEN DR, Ames, IA, 50010
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
096715490
Principal Investigator:
Doyle Wilson
President
(515) 233-4161
dewilson@biotronics-inc.com
Business Contact:
Doyle Wilson
President
(515) 233-4161
dewilson@biotronics-inc.com
Research Institution:
n/a
Abstract
Determining meat quality attributes in food animals is essential for genetic selection, sorting, and marketing. Ultrasound techniques have the potential to benefit the swine industry for improvements in both quality and yield measures by non-destructive means. There is a need to continually improve percentage intramuscular fat estimation accuracy and reduced bias, especially before integration of percentage IMF levels into payment systems. A unique opportunity exists due to recent availability of a programmable ultrasound scanner with access to both unprocessed, radio frequency (RF) ultrasound backscattered signals and corresponding B-mode images, and recent reports that combining parameters from both signals and images improves accuracy, sensitivity, and specificity for tissue characterization. We hypothesize that the accuracy of percentage IMF estimation in the longissimus dorsi muscle can be improved by combining the RF signal analysis with currently used B-mode image texture analysis. Technical objectives are to: 1) demonstrate the feasibility of simultaneously acquiring B-mode images and RF signals from live animals and carcasses using the new generation of programmable digital ultrasound scanner; and 2) develop signal processing parameters for characterizing percentage IMF and prove that by combining parameters derived from RF signals with texture parameters from images, percentage IMF estimation can be improved. Phase I will include developing a protocol to acquire both ultrasound images and RF signals using a state-of-the-art ultrasound research system; in-house testing of the system, and developing procedures for scanning and processing data. The Phase I output will be the proof-of-concept that RF ultrasound signals can enhance existing image processing-based IMF prediction in swine. To our knowledge, this would be the first feasibility study to integrate ultrasound data collection and processing of both B-mode images and RF signals in ultrasound applications for food animals. Phase II will culminate in developing a prototype integrated acquisition and processing system for evaluation of feedlot animals and carcasses. The proposed hybrid system has the potential to significantly improve marketable ultrasound technology and have a long lasting impact on food animal industries. The Biotronics team is in unique position to lead this effort to develop the next generation ultrasound meat quality evaluation system.

* information listed above is at the time of submission.

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