Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-26T04:54:46.090Z Has data issue: false hasContentIssue false
  • English
  • Français

Potential use of spectroscopic techniques for assessing table eggs and hatching eggs

Published online by Cambridge University Press:  20 August 2019

Q. ZHAO ,
L. BAN ,
J. ZHENG ,
G. XU ,
Z. NING  and
L. QU
Q. ZHAO
Affiliation:
State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
L. BAN
Affiliation:
Department of Grassland Science, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
J. ZHENG
Affiliation:
State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
G. XU
Affiliation:
State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
Z. NING
Affiliation:
State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
L. QU*
Affiliation:
State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
*
Corresponding author: [email protected]
Get access

Abstract

In evaluating the quality of table eggs and the developmental stages of embryonic eggs, spectroscopic techniques provide greater efficiency than traditional, time-consuming and laborious approaches. This review summarises recent developments in the spectroscopic analysis of table eggs, including the determination of the chemical composition (ratios of performance to standard deviation of 4.38, 2.25, 2.28, 2.31, and 3.03 for fat, moisture, and protein in egg yolk and moisture and protein in egg albumen, respectively, have been reported). A Haugh unit detection accuracy RMSEP (root mean square error of prediction) for quality of 6.29 was obtained by hyperspectral imaging) for table eggs and fertility detection (for white-shell eggs, fertility detection has been realised at a promising rate of 93.5%) and gender determination in hatching eggs. In conclusion, hyperspectral imaging generally outperforms visible or near-infrared reflectance spectroscopy when evaluating both consumption eggs and hatching eggs, and near-infrared reflectance Raman and fluorescence spectroscopy exhibit a strong potential for gender determination prior to hatching. Scientists have attained a correct sexing rate above 90% at 3.5 d of egg incubation without removing the inner shell membrane. In the detection of blood-spot eggs or fertile eggs, eggshell colour proved to be a negative factor.

Keywords

table egghatching eggqualityspectroscopic technique
Type
Review
Information
World's Poultry Science Journal , Volume 75 , Issue 3 , September 2019 , pp. 445 - 456
Copyright
Copyright © World's Poultry Science Association 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

ABDEL-NOUR, N. and NGADI, M. (2011) Detection of omega-3 fatty acid in designer eggs using hyperspectral imaging. International Journal of Food Sciences and Nutrition 62: 418-422.Google Scholar
ABDEL-NOUR, N., NGADI, M., PRASHER, S. and KARIMI, Y. (2011) Prediction of egg freshness and albumen quality using visible/near infrared spectroscopy. Food and Bioprocess Technology 4: 731-736.Google Scholar
ABOONAJMI, M. and NAJAFABADI, T.A. (2014) Prediction of poultry egg freshness using Vis-NIR spectroscopy with maximum likelihood method. International Journal of Food Properties 17: 2166-2176.Google Scholar
ABOONAJMI, M., SABERI, A., ABBASIAN NAJAFABADI, T. and KONDO, N. (2016) Quality assessment of poultry egg based on visible-near infrared spectroscopy and radial basis function networks. International Journal of Food Properties 19: 1163-1172.Google Scholar
BAMELIS, F.R., TONA, K., DE BAERDEMAEKER, J.G. and DECUYPERE, E.M. (2002) Detection of early embryonic development in chicken eggs using visible light transmission. British Poultry Science 43: 204-212.Google Scholar
BERARDINELLI, A., GIUNCHI, A., GUARNIERI, A., PEZZI, F. and RAGNI, L. (2005) Shell egg albumen height assessment by FT--NIR spectroscopy. Transactions of the ASAE 48: 1423-1428.Google Scholar
BIEDERMAN, I. and SHIFFRAR, M.M. (1987) Sexing day-old chicks: A case study and expert systems analysis of a difficult perceptual-learning task. Journal of Experimental Psychology: Learning, memory, and cognition 13: 640.Google Scholar
BURLEY, R.W. and VADEHRA, D.V. (1989) The avian egg, chemistry and biology. Wiley Publisher Inc. New York.Google Scholar
CHEN, M., ZHANG, L.R. and XU, H.R. (2015) On-line detection of blood spot introduced into brown-shell eggs using visible absorbance spectroscopy. Biosystems Engineering 131: 95-101.Google Scholar
CLOSE, B., BANISTER, K., BAUMANS, V., BERNOTH, E.M., BROMAGE, N., BUNYAN, J., ERHARDT, W., FLECKNELL, P., GREGORY, N., HACKBARTH, H., MORTON, D. and WARWICK, C. (1997) Recommendations for euthanasia of experimental animals: Part 2. Laboratory Animals 31: 1-32.Google Scholar
CORONEL-REYES, J., RAMIREZ-MORALES, I., FERNANDEZ-BLANCO, E., RIVERO, D. and PAZOS, A. (2018) Determination of egg storage time at room temperature using a low-cost NIR spectrometer and machine learning techniques. Computers and Electronics in Agriculture 145: 1-10.Google Scholar
DALLE ZOTTE, A., BERZAGHI, P., JANSSON, L. and ANDRIGHETTO, I. (2006) The use of near-infrared reflectance spectroscopy (NIRS) in the prediction of chemical composition of freeze-dried egg yolk and discrimination between different n-3 PUFA feeding sources. Animal Feed Science and Technology 128: 108-121.Google Scholar
DAS, K. and EVANS, M.D. (1992) Detecting fertility of hatching eggs using machine vision I. Histogram characterization method. Transactions of the ASAE 35: 1335-1341.Google Scholar
DE KETELAERE, B., BAMELIS, F., KEMPS, B., DECUYPERE, E. and DE BAERDEMAEKER, J. (2004) Non-destructive measurements of the egg quality. World's Poultry Science Journal 60: 289-302.Google Scholar
DE KETELAERE, B., MERTENS, K., KEMPS, B., BAMELIS, F., DECUYPERE, E. and DE BAERDEMAKER, J. (2005) Improved blood detection in consumption eggs using combined reflection-transmission spectroscopy. Proceedings of the 11th European Symposium on the Quality of Eggs and Egg Products, Netherlands, pp. 23-26.Google Scholar
DONG, X.G., DONG, J., PENG, Y.K. and TANG, X.Y. (2017a) Comparative study of albumen pH and whole egg pH for the evaluation of egg freshness. Spectroscopy Letters 50: 463-469.Google Scholar
DONG, X.G., TANG, X.Y., PENG, Y.K. and DONG, J. (2017b) Nondestructive assessment of eggshell thickness by VIS/NIR spectroscopy. In 2017 ASABE Annual International Meeting, Washington, p.1.Google Scholar
GALIS, A.M., DALE, L.M., BOUDRY, C. and THEWIS, A. (2012) The potential use of near-infrared spectroscopy for the quality assessment of eggs and egg products. Scientific Works. C Series. Veterinary Medicine 58: 294-307.Google Scholar
GALLI, R., PREUSSE, G., SCHNABEL, C., BARTELS, T., CRAMER, K., KRAUTWALD-JUNGHANNS, M., KOCH, E. and STEINER, G. (2018) Sexing of chicken eggs by fluorescence and Raman spectroscopy through the shell membrane. PLoS One 13: e192554.Google Scholar
GALLI, R., PREUSSE, G., UCKERMANN, O., BARTELS, T., KRAUTWALD-JUNGHANNS, M., KOCH, E. and STEINER, G. (2016) In ovo sexing of domestic chicken eggs by raman spectroscopy. Analytical Chemistry 88: 8657-8663.Google Scholar
GALLI, R., PREUSSE, G., UCKERMANN, O., BARTELS, T., KRAUTWALD-JUNGHANNS, M., KOCH, E. and STEINER, G. (2017) In ovo sexing of chicken eggs by fluorescence spectroscopy. Analytical and Bioanalytical Chemistry 409: 1185-1194.Google Scholar
GIUNCHI, A., BERARDINELLI, A., RAGNI, L., FABBRI, A. and SILAGHI, F.A. (2008) Non-destructive freshness assessment of shell eggs using FT-NIR spectroscopy. Journal of Food Engineering 89: 142-148.Google Scholar
GÖHLER, D., FISCHER, B. and MEISSNER, S. (2016) In-ovo sexing of 14-day-old chicken embryos by pattern analysis in hyperspectral images (VIS/NIR spectra): A non-destructive method for layer lines with gender-specific down feather color. Poultry Science 96: 1-4.Google Scholar
HAUGH, R.R. (1937) The Haugh unit for measuring egg quality.Google Scholar
HOU, Z.C., YANG, N., LI, J.Y. and XU, G.Y. (2009) Egg quality prediction by using Fourier transform near infrared reflectance spectroscopy (FT-NIR). Spectroscopy and Spectral Analysis 29: 2063-2068.Google Scholar
ISLAM, M.H., KONDO, N., OGAWA, Y., FUJIURA, T., SUZUKI, T. and FUJITANI, S. (2017) Detection of infertile eggs using visible transmission spectroscopy combined with multivariate analysis. Engineering in Agriculture, Environment and Food 10: 115-120.Google Scholar
ISLAM, M.H., KONDO, N., OGAWA, Y., FUJIURA, T., SUZUKI, T., NAKAJIMA, S. and FUJITANI, S. (2015) Prediction of chick hatching time using visible transmission spectroscopy combined with partial least squares regression. Engineering in Agriculture, Environment and Food 8: 61-66.Google Scholar
KAROUI, R., NICOLAÏ, B. and DE BAERDEMAEKER, J. (2008) Monitoring the Egg Freshness During Storage Under Modified Atmosphere by Fluorescence Spectroscopy. Food and Bioprocess Technology 1: 346-356.Google Scholar
KEMPS, B.J., BAMELIS, F.R., MERTENS, K., DECUYPERE, E.M., DE BAERDEMAEKER, J.G. and DE KETELAERE, B. (2010) Assessment of embryonic growth in chicken eggs by means of visible transmission spectroscopy. BiotechnologyPprogress 26: 512-516.Google Scholar
KEMPS, B.J., BAMELIS, F.R., DE KETELAERE, B., MERTENS, K., TONA, K., DECUYPERE, E.M. and DE BAERDEMAEKER, J.G. (2006) Visible transmission spectroscopy for the assessment of egg freshness. Journal of the Science of Food and Agriculture 86: 1399-1406.Google Scholar
KEMPS, B.J., DE KETELAERE, B., BAMELIS, F.R., MERTENS, K., DECUYPERE, E.M., DE BAERDEMAEKER, J.G. and SCHWÄGELE, F. (2007) Albumen freshness assessment by combining visible near-infrared transmission and low-resolution proton nuclear magnetic resonance spectroscopy. Poultry Science 86: 752-759.Google Scholar
LAWRENCE, K., SMITH, D., WINDHAM, W., HEITSCHMIDT, G., PARK, B. and YOON, S.C. (2007) Egg embryo development detection with hyperspectral imaging. International Journal of Poultry Science 5: 964-969.Google Scholar
LAWRENCE, K.C., YOON, S.C., HEITSCHMIDT, G.W., JONES, D.R. and PARK, B. (2008) Imaging system with modified-pressure chamber for crack detection in shell eggs. Sensing and Instrumentation for Food Quality and Safety 2: 116-122.Google Scholar
LIN, H., ZHAO, J.W., SUN, L., CHEN, Q.S. and ZHOU, F. (2011) Freshness measurement of eggs using near infrared (NIR) spectroscopy and multivariate data analysis. Innovative Food Science & Emerging Technologies 12: 182-186.Google Scholar
LIN, H., ZHAO, J.W., SUN, L., BI, X.K. and CAI, J.R (2015) Effective variables selection in eggs freshness graphically oriented local multivariate analysis using NIR spectroscopy. International Conference on Chemical, Material and Food Engineering.Google Scholar
LIU, L. and NGADI, M.O. (2013) Detecting fertility and early embryo development of chicken eggs using near-infrared hyperspectral imaging. Food and Bioprocess Technology 6: 2503-2513.Google Scholar
LIU, Y.D., YING, Y.B., OUYANG, A. and LI, Y.B. (2007) Measurement of internal quality in chicken eggs using visible transmittance spectroscopy technology. Food Control 18: 18-22.Google Scholar
LUNVEN, P., DE ST MARCQ, C.L.C., CARNOVALE, E. and FRATONI, A. (1973) Amino acid composition of hen's egg. British Journal of Nutrition 30: 189-194.Google Scholar
NARUSHIN, V.G., VAN KEMPEN, T.A., WINELAND, M.J. and CHRISTENSEN, V.L. (2004) Comparing infrared spectroscopy and egg size measurements for predicting eggshell quality. Biosystems Engineering 87: 367-373.Google Scholar
SASIC, S. and OZAKI, Y. (2001) Short-wave near-infrared spectroscopy of biological fluids. 1. Quantitative analysis of fat, protein, and lactose in raw milk by partial least-squares regression and band assignment. Analytical Chemistry 73: 64-71.Google Scholar
SILVERSIDES, F.G. and SCOTT, T.A. (2001) Effect of storage and layer age on quality of eggs from two lines of hens. Poultry Science 80: 1240-1245.Google Scholar
SMITH, D.P., LAWRENCE, K.C. and HEITSCHMIDT, G.W. (2008) Fertility and embryo development of broiler hatching eggs evaluated with a hyperspectral imaging and predictive modeling system. International Journal of Poultry Science 7: 1001-1004.Google Scholar
SMITH, D.P., MAULDIN, J.M., LAWRENCE, K.C., PARK, B. and HEITSCHMIDT, G.W. (2005) Detection of fertility and early development of hatching eggs with hyperspectral imaging. Proceedings of the 11th European Symposium on the Quality of Eggs and Egg Products, Netherlands, pp. 176-180.Google Scholar
SONG, K.T., CHOI, S.H. and OH, H.R. (2000) A comparison of egg quality of pheasant, chukar, quail and guinea fowl. Asian Australasian Journal of Animal Sciences 13: 986-990.Google Scholar
SUGINO, H., NITODA, T. and JUNEJA, L.R. (1996) General chemical composition of hen eggs, in: YAMAMOTO, T., JUNEJA, L.R., HATTA, H. & KIM, M. (Eds) Hen Eggs, Their Basic and Applied Science, pp. 13-24. (New York, CRC Press).Google Scholar
SUKTANARAK, S. and TEERACHAICHAYUT, S. (2017) Non-destructive quality assessment of hens’ eggs using hyperspectral images. Journal of Food Engineering 215: 97-103.Google Scholar
TIAN, L. and MA, X.L. (2011) Design and implementation of unfertilized eggs verification system based on computer vision. Journal of Agricultural Mechanization Research 8: 039.Google Scholar
USUI, Y., NAKANO, K. and MIZUTANI, J. (2005) Studies on nondestructive detection of abnormal eggs (part 2) -the detection of blood spots in white-shelled eggs using visible spectroscopy. Journal of Social Agriculture Structure 36: 11-16.Google Scholar
USUI, Y., NAKANO, K. and SAITOU, M. (2006) Studies on nondestructive detection of abnormal eggs (part 3) -the detection of blood spots in brown-shelled eggs using visible spectroscopy. Journal of Social Agriculture Structure 36: 209-214.Google Scholar
WEHLING, R.L., PIERCE, M.M. and FRONING, G.W. (1988) Determination of moisture, fat and protein in spray-dried whole egg by near infrared reflectance spectroscopy. Journal of Food Science 53: 1355-1359.Google Scholar
XIE, C.Q. and HE, Y. (2016) External characteristic determination of eggs and cracked eggs identification using spectral signature. Scientific Reports 6: 21130.Google Scholar
XIONG, H., XU, H.R., ZHOU, W.H., YAO, Y. and CHEN, H.R. (2013) Detection of eggshell quality based on NIR spectra. Transactions of the Chinese Society of Agricultural Engineering: S1.Google Scholar
XIONG, L.R., ZHU, Z.H., WU, L.L. and WANG, S.C. (2011) Detection of crack eggs based on near infrared reflectance spectrum and discriminant analysis. Scientific Research and Essays 6: 6250-6253.Google Scholar
XU, H.R., XU, W.H., CHEN, H.R, YAO, Y. and ZHANG, A.H. (2014) Detection of blood spots in brown eggs based on spectroscopic techniques. Transactions of the Chinese Society for Agricultural Machinery 45: 194-198.Google Scholar
ZHANG, W., PAN, L.Q., TU, S.C., ZHAN, G. and TU, K. (2015) Non-destructive internal quality assessment of eggs using a synthesis of hyperspectral imaging and multivariate analysis. Journal of Food Engineering 157: 41-48.Google Scholar
ZHAO, Q.N., LV, X.Z., JIA, Y.X., CHEN, Y., XU, G.Y. and QU, L.J. (2018) Rapid determination of the fat, moisture, and protein contents in chicken eggs based on near infrared reflectance spectroscopy. Poultry Science 97: 2239-2245.Google Scholar
ZHAO, J.W., LIN, H., CHEN, Q.S., HUANG, X.Y., SUN, Z.B. and ZHOU, F. (2010) Identification of egg's freshness using NIR and support vector data description. Journal of Food Engineering 98: 408-414.Google Scholar
ZHU, Z.H., WANG, Q.H., WANG, S.C., DAI, M.Y. and MA, M.H. (2012) The detection of hatching eggs prior to incubation by the near infrared spectrum. Spectroscopy and Spectral Analysis 32: 962-965.Google Scholar
ZHU, Z.H., LIU, T., XIONG, L.Y. and MA, M.H. (2014) Identification of the hatching egg before the incubation based on hyperspectral imaging and GA-BP network. Computer Modelling & New Technologies 18: 388-393.Google Scholar
ZHU, Z.H., XIE, D.J., LI, W.Q., WANG, Q.H. and MA, M.H. (2015) Abnormal eggs detection based on spectroscopy technology and multiple classifier fusion. Transactions of the Chinese Society of Agricultural Engineering 31: 312-318.Google Scholar
ZHU, Z.H., LI, W.Q., WANG, Q.H., TANG, Y., CAO, F.L. and MA, R. (2017) Online discriminant model of blood spot eggs based on spectroscopy. Journal of Food Process Engineering 40: doi.org/10.1111/jfpe.12435.Google Scholar