Abstract
This study was conducted to assess the potential for visible and near-infrared (Vis/NIR) spectroscopy to predict an important quality attribute, color traits, of intact broiler breast fillets (pectoralis major). A total of 214 boneless and skinless chicken fillets were procured from a commercial processing plant. The quantitative calibration models were established between five color trait parameters (CIELAB L*, a*, b*, chroma, and hue angle) and spectra from four different spectral ranges (400–2500, 400–1100, 1100–2500, and 900–1700 nm) collected from skin (ventral) and bone (dorsal) sides of fillets individually by partial least squares regressions (PLSR). Predictive ability was assessed by coefficient of determination of prediction (R p 2), ratio performance deviation (RPD), and range error ratio (RER). Models developed based on spectra collected from fillet bone side performed better than those from skin side regardless of color trait, best results were all obtained using 400–2500 nm and closely followed by 400–1100 nm. Prediction results for meat redness a* (R p 2 = 0.81; RPD = 2.21; RER = 12.13) and hue angle (R p 2 = 0.80; RPD = 2.07; RER = 12.65) were the best and for L*, b*, and chroma (R p 2 ≥ 0.72; RPD ≥ 1.81; RER ≥ 8.48) were also well. This work systematically evaluated the influence of different color trait parameters, fillet side spectra, spectral ranges, and pre-treatment methods compared with previous investigation, and results suggest that Vis/NIR spectroscopy can be a feasible method for prediction of color traits of intact broiler breast fillets, especially when spectra are collected from the fillet bone side and range of optimal partial ranges is included.
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References
Andrés S, Silva A, Soares-Pereira AL, Martins C, Bruno-Soares AM, Murray I (2008) The use of visible and near infrared reflectance spectroscopy to predict beef M. longissimus thoracis et lumborum quality attributes. Meat Sci 78:217–224
Balage JM, Silva SDLE, Gomide CA, de Nadai BM, Figueira AC (2015) Predicting pork quality using Vis/NIR spectroscopy. Meat Sci 108:37–43
Barbin DF, Elmasry G, Sun DW, Allen P (2012) Predicting quality and sensory attributes of pork using near-infrared hyperspectral imaging. Anal Chim Acta 719:30–42
Berzaghi P, Dalle Zotte A, Jansson LM, Andrighetto I (2005) Near-infrared reflectance spectroscopy as a method to predict chemical composition of breast meat and discriminate between different n-3 feeding sources. Poult Sci 84:128–136
Bowker B, Hawkins S, Zhuang H (2014) Measurement of water-holding capacity in raw and freeze-dried broiler breast meat with visible and near-infrared spectroscopy. Poultry Sci 93:1834–1841
Brewer VB, Kuttappan VA, Emmert JL, Meullenet J-FC, Owens CM (2012a) Big-bird programs: effect of strain, sex, and debone time on meat quality of broilers. Poult Sci 91:248–254
Brewer VB, Emmert JL, Meullenet J-FC, Owens CM (2012b) Small bird programs: effect of phase-feeding, strain, sex, and debone time on meat quality of broilers. Poult Sci 91:499–504
Čandek-Potokar M, Prevolnik M, Škrlep M (2006) Ability of near infrared spectroscopy to predict pork technological traits. J Near Infrared Spec 14:269–277
Cecchinato A, De Marchi M, Penasa M, Albera A, Bittante G (2011) Near-infrared reflectance spectroscopy predictions as indicator traits in breeding programs for enhanced beef quality. J Anim Sci 89:2687–2695
Cheatham BR (2005) Prediction of the tenderness of cooked poultry pectoralis major muscles by near-infrared reflectance analysis of raw meat. Inquiry 6:92–96
Cozzolino D, Barlocco N, Vadell AA, Ballesteros A, Gallieta G (2003) The use of visible and near-infrared reflectance spectroscopy to predict colour on both intact and homogenised pork muscle. LWT-Food Sci Technol 36:195–202
De Marchi M (2013) On-line prediction of beef quality traits using near infrared spectroscopy. Meat Sci 94:455–460
De Marchi M, Penasa M, Battagin M, Zanetti E, Pulici C, Cassandro M (2011) Feasibility of the direct application of near-infrared reflectance spectroscopy on intact chicken breasts to predict meat color and physical traits. Poult Sci 90:1594–1599
De Marchi M, Riovanto R, Penasa M, Cassandro M (2012) At-line prediction of fatty acid profile in chicken breast using near infrared reflectance spectroscopy. Meat Sci 90:653–657
FAO (2014) http://faostat.fao.org/site/603/default.aspx#ancor. Access 2014.11.23
Hawkins SA, Zhuang H, Sohn M, Windham WR (2014a) Effect of varying postmortem deboning time and sampling position on visible and near infrared spectra of broiler breast filets. Int J Poult Sci 13:272–278
Hawkins SA, Bowker B, Zhuang H, Gamble G, Holser R (2014b) Post-mortem chemical changes in poultry breast meat monitored with visible-near infrared spectroscopy. J Food Res 3:57–65
Hoving-Bolink AH, Vedder HW, Merks JW, De klein WJ, Reimert HG, Frankhuizen R, van den Broek WHAM, Lambooij E (2005) Perspective of NIRS measurements early post mortem for prediction of pork quality. Meat Sci 69:417–423
Jiang HZ, Zhuang H, Sohn M, Wang W (2017) Measurement of soy contents in ground beef using near-infrared spectroscopy. Appli Sci 7:97
Kapper C, Klont RE, Verdonk JMAJ, Urlings HAP (2012a) Prediction of pork quality with near infrared spectroscopy (NIRS): 1. Feasibility and robustness of NIRS measurements at laboratory scale. Meat Sci 91:294–299
Kapper C, Klont RE, Verdonk JMAJ, Williams PC, Urlings HAP (2012b) Prediction of pork quality with near infrared spectroscopy (NIRS) 2. Feasibility and robustness of NIRS measurements under production plant conditions. Meat Sci 91:300–305
Leroy B, Lambotte S, Dotreppe O, Lecocq H, Istasse L, Clinquart A (2004) Prediction of technological and organoleptic properties of beef longissimus thoracis from near-infrared reflectance and transmission spectra. Meat Sci 66:45–54
Lindahl G, Lundström K, Tornberg E (2001) Contribution of pigment content, myoglobin forms and internal reflectance to the colour of pork loin and ham from pure breed pigs. Meat Sci 59:141–151
Liu Y, Chen YR (2000) Two-dimensional correlation spectroscopy study of visible and near-infrared spectral variations of chicken meats in cold storage. Appl Spectrosc 54:1458–1470
Liu Y, Lyon BG, Windham WR, Realini CE, Pringle TD, Duckett S (2003) Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility study. Meat Sci 65:1107–1115
Liu Y, Lyon BG, Windham WR, Lyon CE, Savage EM (2004) Prediction of physical, color, and sensory characteristics of broiler breasts by visible/near infrared reflectance spectroscopy. Poult Sci 83:1467–1474
McDevitt RM, Gavin AJ, Andrés S, Murray I (2005) The ability of visible and near infrared reflectance spectroscopy to predict the chemical composition of ground chicken carcasses and to discriminate between carcasses from different genotypes. J Near Infrared Spec 13:109–117
Meullenet JF, Jonville E, Grezes D, Owens CM (2004) Prediction of the texture of cooked poultry pectoralis major muscles by near-infrared reflectance analysis of raw meat. J Texture Stud 35:573–585
Osborne BG (2006) Near-infrared spectroscopy in food analysis. Encyclopedia of Analytical Chemistry, North Ryde
Prieto N, Andrés S, Giráldez FJ, Mantecón AR, Lavín P (2008) Ability of near infrared reflectance spectroscopy (NIRS) to estimate physical parameters of adult steers (oxen) and young cattle meat samples. Meat Sci 79:692–699
Prieto N, Roehe R, Lavín P, Batten G, Andrés S (2009a) Application of near infrared reflectance spectroscopy to predict meat and meat products quality: a review. Meat Sci 83:175–186
Prieto N, Ross DW, Navajas EA, Nute GR, Richardson RI, Hyslop JJ, Simm G, Roehe R (2009b) On-line application of visible and near infrared reflectance spectroscopy to predict chemical–physical and sensory characteristics of beef quality. Meat Sci 83:96–103
Samuel D, Park B, Sohn M, Wicker L (2011) Visible-near-infrared spectroscopy to predict water-holding capacity in normal and pale broiler breast meat. Poult Sci 90:914–921
Savenije B, Geesink GH, Palen JGP, Hemke G (2006) Prediction of pork quality using visible/near-infrared reflectance spectroscopy. Meat Sci 73:181–184
Schmutzler M, Beganovic A, Böhler G, Huck CW (2015) Methods for detection of pork adulteration in veal product based on FT-NIR spectroscopy for laboratory, industrial and on-site analysis. Food Control 57:258–267
Swatland HJ (2008) How pH causes paleness or darkness in chicken breast meat. Meat Sci 80:396–400
Zhang L, Barbut S (2005) Rheological characteristics of fresh and frozen PSE, normal and DFD chicken breast meat. Brit Poultry Sci 46:687–693
Zhang L, Sun B, Xie P, Li H, Su H, Sha K, Huang CX, Lei YH, Liu X, Wang H (2015) Using near infrared spectroscopy to predict the physical traits of Bos grunniens meat. LWT-Food Sci Technol 64:602–608
Zhuang H, Savage EM (2011) Comparison of sensory descriptive flavor profiles between cooked hot-boned and cold-deboned broiler breast fillets. Int J Poult Sci 10:426–432
Zhuang H, Savage EM (2012) Postmortem aging and freezing and thawing storage enhance ability of early deboned chicken pectoralis major muscle to hold added salt water. Poult Sci 91:1203–1209
Zhuang H, Bowker BC, Buhr RJ, Bourassa DV, Kiepper BH (2013) Effects of broiler carcass scalding and chilling methods on quality of early-deboned breast fillets. Poult Sci 92:1393–1399
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The authors would like to thank the organizations or individuals who had contributed to this manuscript. This work was supported financially by the China National Science and Technology Support Program (2012BAK08B04).
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Hongzhe Jiang declares that he has no conflict of interest. Seung-Chul Yoon declares that he has no conflict of interest. Hong Zhuang declares that he has no conflict of interest. Wei Wang declares that he has no conflict of interest.
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Jiang, H., Yoon, SC., Zhuang, H. et al. Predicting Color Traits of Intact Broiler Breast Fillets Using Visible and Near-Infrared Spectroscopy. Food Anal. Methods 10, 3443–3451 (2017). https://doi.org/10.1007/s12161-017-0907-1
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DOI: https://doi.org/10.1007/s12161-017-0907-1