Quantitative Prediction of Beef Quality Using Visnir Spectroscopy with Large Data Samples under Industry Conditions
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چکیده
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منابع مشابه
Field testing of a system for online classification of beef carcasses for longissimus tenderness using visible and near-infrared reflectance spectroscopy.
The present experiments were conducted to field test a system optimized for online prediction of beef LM tenderness based on visible and near-infrared (VISNIR) spectroscopy and to develop and validate a model for prediction of tenderness that would be unbiased by normal variation in bloom time before application of VISNIR. For both Exp. 1 and 2, slice shear force (SSF) was measured on fresh (ne...
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The present experiment was conducted to provide a validation of a previously developed model for online classification of US Select carcasses for LM tenderness based on visible and near-infrared (VISNIR) spectroscopy and to determine if the accuracy of VISNIR-based tenderness classification could be enhanced by making measurements after postmortem aging. Spectroscopy was conducted online, durin...
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The current experiment was conducted to evaluate the on-line application of visible and near-infrared spectroscopy (VISNIR) to US Select carcasses during commercial beef carcass grading procedures to predict tenderness of longissimus steaks after 14 days of refrigerated storage. A regression model was calibrated using 146 carcasses and tested against an additional 146 carcasses. Carcasses were ...
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