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Infrared Spectroscopy In Meat and Meat Products

Year 2021, Issue: 1, 52 - 62, 31.03.2021

Abstract

    Foods, which have the highest physical and chemical complex structure have to be analyzed for a variety of reasons. Legal authorities carry out analyzes to check whether foods comply with the regulations in the codex. The aim is to prevent unfair economic gain and the possibility of damaging consumers. Besides food analysis are also important for food manufacturers. They carry out these analyzes to ensure that the raw materials and the foods they produce meet the desired quality characteristics during the storage, production and shipping stages. Academic studies on food are in the direction of developing new and more easily applicable analysis methods, preventing the above-mentioned unwanted situations, elaborating the compounds contained in food and producing new foods with high economic value. In recent years, consumers have also become more demanding for the analytical determination of the quality of food. The frequent occurrence of food scandals in the press might be the cause of this situation. So, the rapid analysis of foods has gained importance in recent years. There are two main approaches to rapid analysis of foods. The first is to use the physical properties of foods as a source of information, the other one is to automate chemical methods. Most of the rapid analysis methods based on physical properties of foods are based on spectroscopic methods. Infrared spectroscopy is one of those spectroscopic methods.

References

  • Adapa, P. K., Karunakaran, C., Tabil, L. G. ve Schoenau, G. J. (2009). Potential applications of infrared and Raman spectromicroscopy for agricultural biomass. Agricultural Engineering International: CIGR Journal.
  • Alamprese, C., Amigo, J. M., Casiraghi, E. ve Engelsen, S. B. (2016). Identification and quantification of turkey meat adulteration in fresh, frozen-thawed and cooked minced beef by FT-NIR spectroscopy and chemometrics. Meat Science, 121, 175–181. https://doi.org/10.1016/j.meatsci.2016.06.018
  • Atkins, P. ve Paula, J. de. (2013). Elements of Physical Chemistry. OUP Oxford.
  • Ballin, N. Z. ve Lametsch, R. (2008). Analytical methods for authentication of fresh vs. Thawed meat – A review. Meat Science, 80(2), 151–158. https://doi.org/10.1016/j.meatsci.2007.12.024
  • Collell, C., Gou, P., Picouet, P., Arnau, J. ve Comaposada, J. (2010). Feasibility of near-infrared spectroscopy to predict aw and moisture and NaCl contents of fermented pork sausages. Meat Science, 6.
  • Crocombe, R. A. (2018). Portable Spectroscopy. Applied Spectroscopy, 72(12), 1701–1751. https://doi.org/10.1177/0003702818809719
  • Ertugay, M. ve Başlar, M. (2011). Gıdaların kalite özelliklerinin belirlenmesinde yakin kizilötesi (NIR) spektroskopisi. Gıda , 36 (1) , 49-54.
  • Gangidi, R. R., Proctor, A. ve Pohlman, F. W. (2003). Rapid Determination of Spinal Cord Content in Ground Beef by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy. Journal of Food Science, 68(1), 124–127. https://doi.org/10.1111/j.1365-2621.2003.tb14126.x
  • Gangidi, R. R., Proctor, A., Pohlman, F. W. ve Meullenet, J. -F. (2006). Rapid Determination of Spinal Cord Content in Ground Beef by Near-Infrared Spectroscopy. Journal of Food Science, 70(6), c397–c400. https://doi.org/10.1111/j.1365-2621.2005.tb11436.x
  • Grunert, T., Stephan, R., Ehling-Schulz, M. ve Johler, S. (2016). Fourier Transform Infrared Spectroscopy enables rapid differentiation of fresh and frozen/thawed chicken. Food Control, 60, 361–364. https://doi.org/10.1016/j.foodcont.2015.08.016
  • Hart, J. R., Norris, K. H. ve Golumbic, C. (1962). Determination of the Moisture Content of Seeds by Near-Infrared Spectrophotometry of Their Methanol Extracts. Cereal Chemistry, 39, 94–99.
  • Kodogiannis, V. S., Kontogianni, E. ve Lygouras, J. N. (2014). Neural network based identification of meat spoilage using Fourier-transform infrared spectra. Journal of Food Engineering, 142, 118–131. https://doi.org/10.1016/j.jfoodeng.2014.06.018
  • McDevitt, R. M., Gavin, A. J., Andrés, S. ve 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. Journal of Near Infrared Spectroscopy, 13(3), 109–117. https://doi.org/10.1255/jnirs.463
  • Morsy, N. ve Sun, D. -W. (2013). Robust linear and non-linear models of NIR spectroscopy for detection and quantification of adulterants in fresh and frozen-thawed minced beef. Meat Science, 93(2), 292–302. https://doi.org/10.1016/j.meatsci.2012.09.005
  • Mourot, B. P., Gruffat, D., Durand, D., Chesneau, G., Mairesse, G. ve Andueza, D. (2015). Breeds and muscle types modulate performance of near-infrared reflectance spectroscopy to predict the fatty acid composition of bovine meat. Meat Science, 99, 104–112. https://doi.org/10.1016/j.meatsci.2014.08.014
  • Norris, K. H. (1996). History of NIR. Journal of Near Infrared Spectroscopy, 4(1), 31–37. https://doi.org/10.1255/jnirs.941
  • Pico, Y. (2012). Chemical Analysis of Food: Techniques and Applications. Elsevier. https://doi.org/10.1016/C2010-0-64808-5
  • Prieto, N., Juárez, M., Larsen, I. L., López-Campos, Ó., Zijlstra, R. T. ve Aalhus, J. L. (2015). Rapid discrimination of enhanced quality pork by visible and near infrared spectroscopy. Meat Science, 110, 76–84. https://doi.org/10.1016/j.meatsci.2015.07.006
  • Prieto, N., Pawluczyk, O., Dugan, M. E. R. ve Aalhus, J. L. (2017). A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products. Applied Spectroscopy, 71(7), 1403–1426. https://doi.org/10.1177/0003702817709299
  • Prieto, N., Dugan, M. E. R., Juárez, M., López-Campos, Ó., Zijlstra, R. T. ve Aalhus, J. L. (2018). Using portable near-infrared spectroscopy to predict pig subcutaneous fat composition and iodine value. Canadian Journal of Animal Science, 98(2), 221–229. https://doi.org/10.1139/cjas-2017-0033
  • Pügner, T., Knobbe, J. ve Grüger, H. (2016). Near-Infrared Grating Spectrometer for Mobile Phone Applications. Applied Spectroscopy, 70(5), 734–745. https://doi.org/10.1177/0003702816638277
  • Rady, A. ve Adedeji, A. (2018). Assessing different processed meats for adulterants using visible-near-infrared spectroscopy. Meat Science, 136, 59–67. https://doi.org/10.1016/j.meatsci.2017.10.014
  • Rateni, G., Dario, P. ve Cavallo, F. (2017). Smartphone-Based Food Diagnostic Technologies: A Review. Sensors, 17(6), 1453. https://doi.org/10.3390/s17061453
  • Ritthiruangdej, P., Ritthiron, R., Shinzawa, H. ve Ozaki, Y. (2011). Non-destructive and rapid analysis of chemical compositions in Thai steamed pork sausages by near-infrared spectroscopy. Food Chemistry, 129(2), 684–692. https://doi.org/10.1016/j.foodchem.2011.04.110
  • Sun, D. -W. (Ed.). (2009). Infrared Spectroscopy for Food Quality Analysis and Control. Academic Press. https://doi.org/10.1016/B978-0-12-374136-3.00025-0
  • Thyholt, K. ve Isaksson, T. (1997). Differentiation of frozen and unfrozen beef using near-infrared spectroscopy. J. Sci. Food Agric., 73, 525-532. https://doi.org/10.1002/(sici)1097-0010(199704)73:4<525::aid-jsfa767>3.0.co;2-c

Kızılötesi (IR) Spektroskopinin Et ve Et Ürünlerinde Kullanımı

Year 2021, Issue: 1, 52 - 62, 31.03.2021

Abstract

    Son derece kompleks yapıya sahip gıdalar çok çeşitli nedenlerden dolayı analiz edilmek durumundadırlar. Yasa yapıcılar gıdaların Türk Gıda Kodeksine ve ilgili yönetmeliklere ve kalite parametrelerine uygunluğunun kontrolü için analizleri gerçekleştirmektedir. Analizin amacı haksız ekonomik kazancın ve tüketicilere muhtemel bir zararın oluşmasının önüne geçmektir. Bunun yanında gıda analizleri gıda üreticileri için de oldukça önemlidir. Gıda üreticileri ham maddelerin ve ürettikleri gıdaların depolama, üretim ve sevkiyat aşamalarında istenilen kalite özelliklerini taşıdıklarından emin olmak için bu analizleri gerçekleştirmektedirler. Gıda ile ilgili akademik çalışmalar ise sürekli yeni ve daha kolay uygulanabilir yöntemlerin geliştirilmesi, tüketici haklarının korunması, gıdanın içerdiği bileşiklerin detaylı bir şekilde ortaya konması ve ekonomik değeri yükseltilmiş yeni gıdaların üretilmeleri yönündedir. Son yıllarda tüketiciler de gıdaların kalitelerinin analitik olarak tespit edilmeleri hususunda daha talepkâr duruma gelmişlerdir. Bu durumun oluşmasında gıda kökenli skandalların kitle iletişim araçlarında sıkça yer almaları da etkili olmuştur. Gıdaların hızlı analizlerinde başlıca iki yaklaşım bulunmaktadır. Bunlardan ilki gıdaların fiziksel özelliklerinin bir bilgi kaynağı olarak kullanmak, diğeri ise kimyasal metotların otomatize edilmesidir. Gıdaların fiziksel özelliklerine dayanan hızlı analiz yöntemlerinin büyük bir çoğunluğu spektroskopik yöntemlere dayanmaktadır. Kızılötesi spektroskopi de bu yöntemlerden biridir.

References

  • Adapa, P. K., Karunakaran, C., Tabil, L. G. ve Schoenau, G. J. (2009). Potential applications of infrared and Raman spectromicroscopy for agricultural biomass. Agricultural Engineering International: CIGR Journal.
  • Alamprese, C., Amigo, J. M., Casiraghi, E. ve Engelsen, S. B. (2016). Identification and quantification of turkey meat adulteration in fresh, frozen-thawed and cooked minced beef by FT-NIR spectroscopy and chemometrics. Meat Science, 121, 175–181. https://doi.org/10.1016/j.meatsci.2016.06.018
  • Atkins, P. ve Paula, J. de. (2013). Elements of Physical Chemistry. OUP Oxford.
  • Ballin, N. Z. ve Lametsch, R. (2008). Analytical methods for authentication of fresh vs. Thawed meat – A review. Meat Science, 80(2), 151–158. https://doi.org/10.1016/j.meatsci.2007.12.024
  • Collell, C., Gou, P., Picouet, P., Arnau, J. ve Comaposada, J. (2010). Feasibility of near-infrared spectroscopy to predict aw and moisture and NaCl contents of fermented pork sausages. Meat Science, 6.
  • Crocombe, R. A. (2018). Portable Spectroscopy. Applied Spectroscopy, 72(12), 1701–1751. https://doi.org/10.1177/0003702818809719
  • Ertugay, M. ve Başlar, M. (2011). Gıdaların kalite özelliklerinin belirlenmesinde yakin kizilötesi (NIR) spektroskopisi. Gıda , 36 (1) , 49-54.
  • Gangidi, R. R., Proctor, A. ve Pohlman, F. W. (2003). Rapid Determination of Spinal Cord Content in Ground Beef by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy. Journal of Food Science, 68(1), 124–127. https://doi.org/10.1111/j.1365-2621.2003.tb14126.x
  • Gangidi, R. R., Proctor, A., Pohlman, F. W. ve Meullenet, J. -F. (2006). Rapid Determination of Spinal Cord Content in Ground Beef by Near-Infrared Spectroscopy. Journal of Food Science, 70(6), c397–c400. https://doi.org/10.1111/j.1365-2621.2005.tb11436.x
  • Grunert, T., Stephan, R., Ehling-Schulz, M. ve Johler, S. (2016). Fourier Transform Infrared Spectroscopy enables rapid differentiation of fresh and frozen/thawed chicken. Food Control, 60, 361–364. https://doi.org/10.1016/j.foodcont.2015.08.016
  • Hart, J. R., Norris, K. H. ve Golumbic, C. (1962). Determination of the Moisture Content of Seeds by Near-Infrared Spectrophotometry of Their Methanol Extracts. Cereal Chemistry, 39, 94–99.
  • Kodogiannis, V. S., Kontogianni, E. ve Lygouras, J. N. (2014). Neural network based identification of meat spoilage using Fourier-transform infrared spectra. Journal of Food Engineering, 142, 118–131. https://doi.org/10.1016/j.jfoodeng.2014.06.018
  • McDevitt, R. M., Gavin, A. J., Andrés, S. ve 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. Journal of Near Infrared Spectroscopy, 13(3), 109–117. https://doi.org/10.1255/jnirs.463
  • Morsy, N. ve Sun, D. -W. (2013). Robust linear and non-linear models of NIR spectroscopy for detection and quantification of adulterants in fresh and frozen-thawed minced beef. Meat Science, 93(2), 292–302. https://doi.org/10.1016/j.meatsci.2012.09.005
  • Mourot, B. P., Gruffat, D., Durand, D., Chesneau, G., Mairesse, G. ve Andueza, D. (2015). Breeds and muscle types modulate performance of near-infrared reflectance spectroscopy to predict the fatty acid composition of bovine meat. Meat Science, 99, 104–112. https://doi.org/10.1016/j.meatsci.2014.08.014
  • Norris, K. H. (1996). History of NIR. Journal of Near Infrared Spectroscopy, 4(1), 31–37. https://doi.org/10.1255/jnirs.941
  • Pico, Y. (2012). Chemical Analysis of Food: Techniques and Applications. Elsevier. https://doi.org/10.1016/C2010-0-64808-5
  • Prieto, N., Juárez, M., Larsen, I. L., López-Campos, Ó., Zijlstra, R. T. ve Aalhus, J. L. (2015). Rapid discrimination of enhanced quality pork by visible and near infrared spectroscopy. Meat Science, 110, 76–84. https://doi.org/10.1016/j.meatsci.2015.07.006
  • Prieto, N., Pawluczyk, O., Dugan, M. E. R. ve Aalhus, J. L. (2017). A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products. Applied Spectroscopy, 71(7), 1403–1426. https://doi.org/10.1177/0003702817709299
  • Prieto, N., Dugan, M. E. R., Juárez, M., López-Campos, Ó., Zijlstra, R. T. ve Aalhus, J. L. (2018). Using portable near-infrared spectroscopy to predict pig subcutaneous fat composition and iodine value. Canadian Journal of Animal Science, 98(2), 221–229. https://doi.org/10.1139/cjas-2017-0033
  • Pügner, T., Knobbe, J. ve Grüger, H. (2016). Near-Infrared Grating Spectrometer for Mobile Phone Applications. Applied Spectroscopy, 70(5), 734–745. https://doi.org/10.1177/0003702816638277
  • Rady, A. ve Adedeji, A. (2018). Assessing different processed meats for adulterants using visible-near-infrared spectroscopy. Meat Science, 136, 59–67. https://doi.org/10.1016/j.meatsci.2017.10.014
  • Rateni, G., Dario, P. ve Cavallo, F. (2017). Smartphone-Based Food Diagnostic Technologies: A Review. Sensors, 17(6), 1453. https://doi.org/10.3390/s17061453
  • Ritthiruangdej, P., Ritthiron, R., Shinzawa, H. ve Ozaki, Y. (2011). Non-destructive and rapid analysis of chemical compositions in Thai steamed pork sausages by near-infrared spectroscopy. Food Chemistry, 129(2), 684–692. https://doi.org/10.1016/j.foodchem.2011.04.110
  • Sun, D. -W. (Ed.). (2009). Infrared Spectroscopy for Food Quality Analysis and Control. Academic Press. https://doi.org/10.1016/B978-0-12-374136-3.00025-0
  • Thyholt, K. ve Isaksson, T. (1997). Differentiation of frozen and unfrozen beef using near-infrared spectroscopy. J. Sci. Food Agric., 73, 525-532. https://doi.org/10.1002/(sici)1097-0010(199704)73:4<525::aid-jsfa767>3.0.co;2-c
There are 26 citations in total.

Details

Primary Language Turkish
Subjects Food Engineering
Journal Section Derlemeler
Authors

Batuhan Tarcan 0000-0002-9724-7450

Özlem Küplülü 0000-0002-1559-2390

Publication Date March 31, 2021
Submission Date December 14, 2020
Published in Issue Year 2021 Issue: 1

Cite

APA Tarcan, B., & Küplülü, Ö. (2021). Kızılötesi (IR) Spektroskopinin Et ve Et Ürünlerinde Kullanımı. Akademik Et Ve Süt Kurumu Dergisi(1), 52-62.