{"id":{"repo_id":"mo-state","oai_identifier":"oai:bearworks.missouristate.edu:theses-1882"},"canonical_url":"https://search.dev.ndltd.org/etd/mo-state/oai:bearworks.missouristate.edu:theses-1882","repository":{"repo_id":"mo-state","name":"Missouri State University","base_url":"https://bearworks.missouristate.edu/do/oai/"},"display":{"title":"Predicting Beef Tenderness Using Ultrasound Technology","abstract":"The objective of this study was to evaluate the subjective prediction of tenderness via ultrasound as compared to actual tenderness of a carcass determined by Warner-Bratzler shear force. The study utilized 51 head of crossbred commercial feedlot steers. The cattle were selected on a criteria consisting of: Not more that 37.50% Bos Indicus influence, and not more than 18 months in age, with visual appraisal for fitness. A non-certified ultrasound technician, using an Aloka 500V ultrasound unit and CVI interpretation software, collected images and measured: percent intramuscular fat (%FatU), ribeye area (REAU), and fat thickness (FTU). The cattle were then harvested, and carcass ribeye area (REAC), carcass fat thckness (FTC), and calculated yield grade (CYG) were collected 48 hours after harvest to allow for chilling. The left side strip loin was obtained from each carcass, labeled according to test subject and carcass side, and evaluated for tenderness following established guidelines for Warner-Bratzler shear force (WBS). A subjective tenderness value (TSU), based on a proprietary formula (patent pending), was assigned to each %FatU image. The means for hot carcass weight (HCW), REAU, FTU, REAC, FTC, CYG, %FatU, WBS, and TSU were: 353.90±46.57 kg, 87.33±12.80 cm², 0.79±0.30 cm, 92.56±12.33 cm², 0.90±0.35 cm, 2.56±0.87, 3.30±0.37%, 3.50±0.61 kg, and 2.37±0.72 respectively. Correlations for REAU and REAC, FTU and FTC, REAC and CYG, REAU and CYG, FTC and CYG, and FTU and CYG, WBS and TSU, were: 0.01, 0.77, -0.74, 0.08, 0.53, 0.51, and 0.014 respectively. These data suggest little relationship between carcass tenderness and the subjective ultrasound tenderness value. Therefore, more research data must be collected to improve the accuracy of predicting tenderness (based on proprietary formula) using ultrasound technology.","abstract_html":"The objective of this study was to evaluate the subjective prediction of tenderness via ultrasound as compared to actual tenderness of a carcass determined by Warner-Bratzler shear force. The study utilized 51 head of crossbred commercial feedlot steers. The cattle were selected on a criteria consisting of: Not more that 37.50% Bos Indicus influence, and not more than 18 months in age, with visual appraisal for fitness. A non-certified ultrasound technician, using an Aloka 500V ultrasound unit and CVI interpretation software, collected images and measured: percent intramuscular fat (%FatU), ribeye area (REAU), and fat thickness (FTU). The cattle were then harvested, and carcass ribeye area (REAC), carcass fat thckness (FTC), and calculated yield grade (CYG) were collected 48 hours after harvest to allow for chilling. The left side strip loin was obtained from each carcass, labeled according to test subject and carcass side, and evaluated for tenderness following established guidelines for Warner-Bratzler shear force (WBS). A subjective tenderness value (TSU), based on a proprietary formula (patent pending), was assigned to each %FatU image. The means for hot carcass weight (HCW), REAU, FTU, REAC, FTC, CYG, %FatU, WBS, and TSU were: 353.90±46.57 kg, 87.33±12.80 cm², 0.79±0.30 cm, 92.56±12.33 cm², 0.90±0.35 cm, 2.56±0.87, 3.30±0.37%, 3.50±0.61 kg, and 2.37±0.72 respectively. Correlations for REAU and REAC, FTU and FTC, REAC and CYG, REAU and CYG, FTC and CYG, and FTU and CYG, WBS and TSU, were: 0.01, 0.77, -0.74, 0.08, 0.53, 0.51, and 0.014 respectively. These data suggest little relationship between carcass tenderness and the subjective ultrasound tenderness value. Therefore, more research data must be collected to improve the accuracy of predicting tenderness (based on proprietary formula) using ultrasound technology.","abstract_has_math":false,"creators":["Howard, Jason V."],"institution":null,"degree_name":"Master of Natural and Applied Science in Agriculture","degree_level":"Masters","degree_discipline":"College of Agriculture","degree_department":null,"school":null,"contributors":["Thomas Perkins"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003-07-01T07:00:00Z","date_published":"2003-07-01T07:00:00Z","updated_at":"2026-07-24T03:15:54Z","subjects":["Agriculture"],"languages":[],"rights":["© Jason V Howard"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://bearworks.missouristate.edu/theses/881","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Thomas Perkins"]},{"key":"dc:creator","label":"Author","values":["Howard, Jason V."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["College of Agriculture"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Natural and Applied Science in Agriculture"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Agriculture"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["© Jason V Howard"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://bearworks.missouristate.edu/theses/881"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The objective of this study was to evaluate the subjective prediction of tenderness via ultrasound as compared to actual tenderness of a carcass determined by Warner-Bratzler shear force. The study utilized 51 head of crossbred commercial feedlot steers. The cattle were selected on a criteria consisting of: Not more that 37.50% Bos Indicus influence, and not more than 18 months in age, with visual appraisal for fitness. A non-certified ultrasound technician, using an Aloka 500V ultrasound unit and CVI interpretation software, collected images and measured: percent intramuscular fat (%FatU), ribeye area (REAU), and fat thickness (FTU). The cattle were then harvested, and carcass ribeye area (REAC), carcass fat thckness (FTC), and calculated yield grade (CYG) were collected 48 hours after harvest to allow for chilling. The left side strip loin was obtained from each carcass, labeled according to test subject and carcass side, and evaluated for tenderness following established guidelines for Warner-Bratzler shear force (WBS). A subjective tenderness value (TSU), based on a proprietary formula (patent pending), was assigned to each %FatU image. The means for hot carcass weight (HCW), REAU, FTU, REAC, FTC, CYG, %FatU, WBS, and TSU were: 353.90±46.57 kg, 87.33±12.80 cm², 0.79±0.30 cm, 92.56±12.33 cm², 0.90±0.35 cm, 2.56±0.87, 3.30±0.37%, 3.50±0.61 kg, and 2.37±0.72 respectively. Correlations for REAU and REAC, FTU and FTC, REAC and CYG, REAU and CYG, FTC and CYG, and FTU and CYG, WBS and TSU, were: 0.01, 0.77, -0.74, 0.08, 0.53, 0.51, and 0.014 respectively. These data suggest little relationship between carcass tenderness and the subjective ultrasound tenderness value. Therefore, more research data must be collected to improve the accuracy of predicting tenderness (based on proprietary formula) using ultrasound technology."]},{"key":"dc:title","label":"Title","values":["Predicting Beef Tenderness Using Ultrasound Technology"]}]}],"canonical_facts":{"dc:contributor":["Thomas Perkins"],"dc:creator":["Howard, Jason V."],"dc:description.abstract":["The objective of this study was to evaluate the subjective prediction of tenderness via ultrasound as compared to actual tenderness of a carcass determined by Warner-Bratzler shear force. The study utilized 51 head of crossbred commercial feedlot steers. The cattle were selected on a criteria consisting of: Not more that 37.50% Bos Indicus influence, and not more than 18 months in age, with visual appraisal for fitness. A non-certified ultrasound technician, using an Aloka 500V ultrasound unit and CVI interpretation software, collected images and measured: percent intramuscular fat (%FatU), ribeye area (REAU), and fat thickness (FTU). The cattle were then harvested, and carcass ribeye area (REAC), carcass fat thckness (FTC), and calculated yield grade (CYG) were collected 48 hours after harvest to allow for chilling. The left side strip loin was obtained from each carcass, labeled according to test subject and carcass side, and evaluated for tenderness following established guidelines for Warner-Bratzler shear force (WBS). A subjective tenderness value (TSU), based on a proprietary formula (patent pending), was assigned to each %FatU image. The means for hot carcass weight (HCW), REAU, FTU, REAC, FTC, CYG, %FatU, WBS, and TSU were: 353.90±46.57 kg, 87.33±12.80 cm², 0.79±0.30 cm, 92.56±12.33 cm², 0.90±0.35 cm, 2.56±0.87, 3.30±0.37%, 3.50±0.61 kg, and 2.37±0.72 respectively. Correlations for REAU and REAC, FTU and FTC, REAC and CYG, REAU and CYG, FTC and CYG, and FTU and CYG, WBS and TSU, were: 0.01, 0.77, -0.74, 0.08, 0.53, 0.51, and 0.014 respectively. These data suggest little relationship between carcass tenderness and the subjective ultrasound tenderness value. Therefore, more research data must be collected to improve the accuracy of predicting tenderness (based on proprietary formula) using ultrasound technology."],"dc:identifier":["https://bearworks.missouristate.edu/theses/881"],"dc:rights":["© Jason V Howard"],"dc:subject":["Agriculture"],"dc:title":["Predicting Beef Tenderness Using Ultrasound Technology"],"thesis:degree_discipline":["College of Agriculture"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Natural and Applied Science in Agriculture"]},"updated_at":"2026-07-24T03:15:54Z"}