Regression models from portable NIR spectra for predicting the carcass traits and meat quality of beef cattle

• Published in: PloS one Vol. 19; no. 5; p. e0303946
• Main Authors: Veloso Trópia, Nathália, Reis Vilela, Rizielly Saraiva, de Sales Silva, Flávia Adriane, Andrade, Dhones Rodrigues, Costa, Adailton Camêlo, Cidrini, Fernando Alerrandro Andrade, de Souza Pinheiro, Jardeson, Pucetti, Pauliane, Chizzotti, Mario Luiz, Filho, Sebastião de Campos Valadares
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 31-05-2024; Public Library of Science (PLoS)
• Subjects: Animal sciences; Animals; Beef; Beef cattle; Body composition; Bones; Carcasses; Cattle; Chemical composition; Dry matter; Female; Laboratories; Male; Meat; Meat - analysis; Meat quality; Muscle, Skeletal - chemistry; Muscles; Portability; Red Meat - analysis; Regression Analysis; Regression models; Spectra; Spectroscopy, Near-Infrared - methods; Spectrum analysis; Zoology; Brazil; United States > US; Italy
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0303946

The aims of this study were to predict carcass and meat traits, as well as the chemical composition of the 9th to 11th rib sections of beef cattle from portable NIR spectra. The 9th to 11th rib section was obtained from 60 Nellore bulls and cull cows. NIR spectra were acquired at: P1 -center of Longissimus muscle; and P2 -subcutaneous fat cap. The models accurately estimated (P ≥ 0.083) all carcass and meat quality traits, except those for predicting red (a*) and yellow (b*) intensity from P1, and 12th-rib fat from P2. However, precision was highly variable among the models; those for the prediction of carcass pHu, 12th rib fat, toughness from P1, and those for 12th rib fat, a* and b* from P2 presented high precision (R2 ≥ 0.65 or CCC ≥ 0.63), whereas all other models evaluated presented moderate to low precision (R2 ≤ 0.39). Models built from P1 and P2 accurately estimated (P ≥ 0.066) the chemical composition of the meat plus fat, bones and, meat plus fat plus bones, except those for predicting the ether extract (EE) and crude protein (CP) of bones and the EE of Meat plus bones fraction from P2. However, precision was highly variable among the models (-0.08 ≤ R2 ≤ 0.86) of the 9th and 11th rib section. Those models for the prediction of dry matter (DM) and EE of the bones from P1; of EE from P1; and of EE, mineral matter (MM), CP from P2 of meat plus fat plus bones presented high precision (R2 ≥ 0.76 or CCC ≥ 0.62), whereas all other models evaluated presented moderate to low precision (R2 ≤ 0.45). Thus, models built from portable NIR spectra acquired at different points of the 9th to 11th rib section were recommended for predicting carcass and muscle quality traits as well as for predicting the chemical composition of this section of beef cattle. However, it is noteworthy, that the small sample size was one of the limitations of this study.