Across countries implementation of handheld near-infrared spectrometer for the on-line prediction of beef marbling in slaughterhouse

Ngah, Moise Kombolo; Goi, Arianna; Santinello, Matteo; Rampado, Nicola; Atanassova, Stefka; Liu, Jingjing; Faure, Pascal; Thoumy, Laure; Neveu, Alix; Andueza-Urra, Jesus-Donato; Marchi, M. Massimo De; Hocquette, Jean‐François

doi:10.1016/j.meatsci.2023.109169

Cited by 9 publications

(2 citation statements)

References 62 publications

(74 reference statements)

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“…In addition, the predictive model of the MM content in fresh ground beef proposed by Dixit et al [32] showed superior predictive capacity (RMSECV ranged from 0.03 to 0.06 and RVC ranged from 0.95 to 0.99) when compared to the models proposed in the present study for predicting the MM content of the section between the 9th and 11th ribs, especially for the bone (RMSECV ranged from 2.75 to 3.37 and RVC ranged from -0.42 to 0.09) and meat plus fat (RMSECV of 0.57 and RVC ranged from -0.09 to -0.03) fractions. According to Kombolo-Ngah et al [13], the inferior predictive capacity of models where the spectra were collected from intact samples can be attributed to the greater heterogeneity of those samples when compared to ground samples, such as those used by Dixit et al [32]. Nonetheless, it is important to highlight that the small sample size was one of the limitations of the current study.…”

Section: Composition Of the Section Between The 9 Th And 11 Th Ribsmentioning

confidence: 77%

“…Furthermore, predicting the chemical composition, carcass traits and meat quality by NIR spectra acquisition can reduce meat waste in the slaughterhouse, as well as reduce the time required to obtain the results. In fact, there has been growing interest in developing different models to predict the composition of carcass tissues [8][9][10], as well as the carcass and meat quality attributes [8,9,[11][12][13] of different animal species. However, these studies acquired spectra from meat samples that were processed or removed from the carcass [14][15][16], making this process both lengthy and expensive.…”

Section: Introductionmentioning

confidence: 99%

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

Veloso Trópia,

Reis Vilela,

de Sales Silva

et al. 2024

PLoS ONE

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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.

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Section: Composition Of the Section Between The 9 Th And 11 Th Ribsmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

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

Veloso Trópia,

Reis Vilela,

de Sales Silva

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

show abstract

An electronic equipment for marbling meat grade detection based on digital image processing and support vector machine

Cardenas,

Tabory,

Sanchez

et al. 2024

Journal of the Saudi Society of Agricultural Sciences

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Recent technological developments and future trends in the evaluation and prediction of beef sensory quality in Brazil and France

Mendes,

Briceno,

Mársico

et al. 2024

Livestock Science

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Across countries implementation of handheld near-infrared spectrometer for the on-line prediction of beef marbling in slaughterhouse

Cited by 9 publications

References 62 publications

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

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

An electronic equipment for marbling meat grade detection based on digital image processing and support vector machine

Recent technological developments and future trends in the evaluation and prediction of beef sensory quality in Brazil and France

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