Breeds and muscle types modulate performance of near-infrared reflectance spectroscopy to predict the fatty acid composition of bovine meat

doi:10.1016/j.meatsci.2014.08.014

Meat Science

Volume 99, January 2015, Pages 104-112

https://doi.org/10.1016/j.meatsci.2014.08.014 Get rights and content

Highlights

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NIRS was tested to predict beef fatty acid composition.
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Using several breeds increases fatty acid variability and prediction ability.
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Fatty acid prediction varies according to the muscle used.
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For an industrial use, Rectus abdominis muscle is recommended for NIRS analyses.

Abstract

This study aimsto assess near-infrared reflectance spectroscopy feasibility for predicting beef fatty acid (FA) composition. Experimental scheme included four breeds (Angus, Blond d’Aquitaine, Charolais, Limousin) and three muscles, Longissimus thoracis (LT), Rectus abdominis (RA), Semitendinosus (ST). The results showed that 1) increasing FA content variability with several breeds increased calibration model reliability (R²CV>0.86) for the major individual and groups of FA unless polyunsaturated FAs, 2) Longissimus thoracis FAs were better predicted than RA FAs while no ST FAs were correctly predicted (R²CV<0.71). This difference could be explained by FA content, FA variability or specific muscle physico-chemical characteristics.

Introduction

The nutritional quality of beef, through its fatty acid (FA) composition, is of major importance for the beef industry. There has been a concurrent demand from human nutritionists and dieticians, and also from consumers to know the values of the nutritional composition of beef. The meat industry needs to control product quality quickly and early on the cattle slaughter process in order for consumers to be aware of the quality of food available. Gas liquid chromatography (GLC), the reference method currently used to determine this composition, is time-consuming, costly and generates chemical waste. Near-Infrared Reflectance Spectroscopy (NIRS) has been shown to provide fast, non-destructive, and cost-effective measurements. The increasing use of NIRS in food analysis has spread to all food industries: meat, dairy products, grains and seeds and fruit and vegetables (Bertrand & Dufour, 2006).

NIRS technology is used in beef to predict several parameters with varying degrees of precision: 1) proximate chemical composition of samples, and nutritional composition (Prieto et al., 2011), 2) technological parameters (De Marchi, Penasa, Cecchinato, & Bittante, 2013), 3) sensory attributes (Ripoll, Albertí, Panea, Olleta, & Sañudo, 2008) and 4) the authentication of the product (Morsy & Sun, 2013).

Concerning the FA predictions, NIRS was efficient in estimating meat FA composition especially individual saturated (SFA) and monounsaturated (MUFA) FAs (Prieto et al., 2014). Despite the considerable nutritional interest of polyunsaturated FAs (PUFA), they are not estimated with the same efficiency according to the species studied. For instance, in pork loin (González-Martín, González-Pérez, Alvarez-García, & González-Cabrera, 2005), broiler breast (Zhou, Wu, Li, Wang, & Zhang, 2012) or lamb meat (Guy, Prache, Thomas, Bauchart, & Andueza, 2011), NIRS was used to efficiently predict the most important individual and total PUFAs. In contrast, when PUFAs are present in low amounts and/or with low variability like in beef, these FAs are poorly predicted (Sierra et al., 2008, Weeranantanaphan et al., 2011). These poorer results were obtained with one or two breeds and a uniform diet per study but both factors, breeds and diets (Bureš et al., 2006, Scollan et al., 2001) had an influence on the FA muscle composition.

Our hypothesis is that the use of various breeds fed with different diets could provide a wider range of fat content and fatty acid composition which would allow for a better statistical basis for prediction of beef muscle FA composition by NIRS.

In general, only Longissimus thoracis (LT) muscle is used in NIRS prediction of muscle FA composition. However, this muscle is not the easiest to access on the carcass. From an industrial point of view, it should be more advantageous to obtain FA calibration models from other muscles. Moreover, muscle is another parameter of variability in FA composition (Purchas & Zou, 2008) and FA calibration models could differ from those obtained using LT.

Therefore, the objectives of this study were to evaluate the potential of NIRS to predict the FA composition of LT muscle using calibration models produced from meat samples of several bovine breeds (Angus, Blond d’Aquitaine, Charolais, Limousin) and diets (barley straw and concentrate with or without lipid supplementations and with or without antioxidant supplementations), and to compare NIRS calibrations for FAs from several muscles (LT, Semitendinosus (ST) and Rectus abdominis (RA)) of Charolais bulls.

Section snippets

Animals and meat samples

The muscle samples came from two different experiments in order to gather 143 bulls between 15 and 18 months old (67 Charolais, 26 Angus, 25 Blond d’Aquitaine, 25 Limousin). All the details on the experimental design and diets for the experiment on Charolais bulls were previously described by Eugène et al. (2011). All the details on the experimental design and diets for the other experiment on Angus, Blond d’Aquitaine and Limousin bulls were previously described by Gruffat et al. (2013).

At the

Fatty acid composition measured using the GLC reference method

The ranges, means and coefficients of variation (CV) of LT intramuscular lipid FA concentration observed in the database are presented in Table 1. Mean SFA and MUFA contents were similar (628.4 mg/100 g and 575.2 mg/100 g respectively), whereas mean PUFA contents were 3 times lower (198.3 mg/100 g). Oleic acid (18:1 Δ9 cis) and palmitic acid (16:0) were on average the most abundant FAs (396.4 mg/100 g of fresh muscle, ranging from 41.7 to 1427 mg/100 g and 322.9 mg/100 g of fresh muscle, ranging from 50.6

Potential of NIRS to predict the FA composition of LT muscle from several bovine breeds

Four breeds with varying lipogenesis capacities were used in this study to increase variability of FAs in LT muscle.

Some studies have confirmed the ability of NIR spectroscopy to predict the content of total lipids in beef (De Marchi et al., 2007, Tøgersen et al., 2003). All these studies reported a R²CV greater than 0.9 as in the present study. A large variability in the values of each sample set and the homogenisation of the meat explained for the reliability of NIR (Prieto, Andrés, Giráldez,

Conclusion

The results of this study show the ability of NIRS to predict the FA profile of beef muscles using different breeds and diets. Compared to the current literature, the inclusion of several bovine breeds with different lipogenic metabolism improves the performance of calibration models for total and individual SFA and MUFA content probably by increasing the variability of the range. However PUFA and CLA prediction remains insufficient. A minimum threshold FA content would appear to be necessary

Conflict of interest

There are no known conflicts of interest associated with this publication.

Acknowledgements

This work was conducted within the framework of the European ProSafeBeef Program (Project N FOOD-CT-2006-36241) and the “NOUVEAUX DEFIS A RELEVER POUR UNE PRODUCTION DURABLE DE VIANDE BOVINE” Program. The authors express their thanks to the staff of the ‘Animal, Muscle, Viande’ team for their technical assistance, particularly Agnes Thomas and Vincent Largeau. We also thank Dr. Dominique Bauchart for his scientific advice.

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Citation Excerpt :
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Breeds and muscle types modulate performance of near-infrared reflectance spectroscopy to predict the fatty acid composition of bovine meat

Highlights

Abstract

Introduction

Section snippets

Animals and meat samples

Fatty acid composition measured using the GLC reference method

Potential of NIRS to predict the FA composition of LT muscle from several bovine breeds

Conclusion

Conflict of interest

Acknowledgements

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Chemometrics and Intelligent Laboratory Systems

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