Abstract
This paper proposed a non-destructive method for online estimation of egg freshness based on machine vision and dynamic weighing. The machine vision system and the dynamic weighing system were developed for the measurement of egg external physical characteristic and weight. Digital signal processing was employed to denoise, analyze, and extract the effective feature information from the images and vibration signals. Then, the method of multiple linear regressions was used to build model for Haugh unit prediction using the parameters of long axis, minor axis, and weight. The performance of the predictive model using six variables was achieved, with R (correlation coefficient) of 0.8653 and RMSEP (root mean square error of prediction) of 3.7454 in prediction set. The speed of the system reaches four eggs per second for every measurement. Good consistence confirmed that the proposed method has a significant potential application in online estimation of the egg freshness.
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References
Abdel-Nour N, Ngadi M, Prasher S, Karimi Y (2011) Prediction of egg freshness and albumen quality using visible/near infrared spectroscopy. Food Bioprocess Technol 4(5):731–736
Aiken LS, West SG, Pitts SC (2003) Multiple linear regression. Handbook of psychology
Bamelis F, Kemps B, Mertens K, Verhoelst E, Ketelaere Bd, Decuypere E, Baerdemaeker Jd (2005) VIS-NIR transmission for the assessment of internal egg quality, Proceedings of the XVII European Symposium on the Quality of Poultry Meat and XI European Symposium on the Quality of Eggs and Egg Products, Golden Tulip Parkhotel Doorwerth, Doorwerth, Netherlands, 23-26 May 2005. World’s Poultry Science Association (WPSA), pp. 222-228
Berardinelli A, Giunchi A, Guarnieri A, Pezzi F, Ragni L (2005) Shell egg albumen height assessment by FT-NIR spectroscopy. Trans ASAE 48(4):1423–1428
Commission E (2003) Commission Regulation (EC) No 2295/2003 of 23 December 2003, introducing detailed rules for implementing Council Regulation (EEC) No 1907/90 on certain marketing standards for eggs. Off J Eur Communities L 340:16–34
Dutta R, Hines EL, Gardner JW, Udrea DD, Boilot P (2003) Non-destructive egg freshness determination: an electronic nose based approach. Meas Sci Technol 14(2):190
Giunchi A, Berardinelli A, Ragni L, Fabbri A, Silaghi FA (2008) Non-destructive freshness assessment of shell eggs using FT-NIR spectroscopy. J Food Eng 89(2):142–148
Haugh R (1937) A new method for determining the quality of an egg. US Egg Poult 39:27–49
Jiang S, Qi H, Wang G, Jiang X (2012) Analysis and experiment on basic properties of poultry eggs. Nongye Jixie Xuebao(Trans Chin Soc Agric Mach) 43(4):137–142
Karoui R, Kemps B, Bamelis F, De Ketelaere B, Decuypere E, De Baerdemaeker J (2006) Methods to evaluate egg freshness in research and industry: a review. Eur Food Res Technol 222(5–6):727–732
Köller J (2009) Mathematische Basteleien. Pentagondodekaeder. www.mathematische-basteleien.de/pentagondodekaeder.htm
Lin H, Zhao J, Sun L, Chen Q, Zhou F (2011) Freshness measurement of eggs using near infrared (NIR) spectroscopy and multivariate data analysis. Innov Food Sci Emerg Technol 12(2):182–186
Narushin V (2005) Egg geometry calculation using the measurements of length and breadth. Poult Sci 84(3):482–484
Ragni L, Gradari P, Berardinelli A, Giunchi A, Guarnieri A (2006) Predicting quality parameters of shell eggs using a simple technique based on the dielectric properties. Biosyst Eng 94(2):255–262
Roberts JR (2004) Factors affecting egg internal quality and egg shell quality in laying hens. J Poult Sci 41(3):161–177
Rossi M, Pompei C, Hidalgo A (1995) Freshness criteria based on physical and chemical modifications occurring in eggs during aging. Ital J Food Sci 7(2):147–156
Schmilovitch Z, Hoffmann A, Egozi H, Klein E (2002) Determination of egg freshness by NNIR spectroscopy. AgEng 2002
Scott T, Silversides F (2000) The effect of storage and strain of hen on egg quality. Poult Sci 79(12):1725–1729
Silversides F, Scott T (2001) Effect of storage and layer age on quality of eggs from two lines of hens. Poult Sci 80(8):1240–1245
Williams P, Norris K (1987) Near-infrared technology in the agricultural and food industries. American Association of Cereal Chemists, Inc
Acknowledgments
This work has been financially supported by the “Twelfth Five-Year" Plan key projects supported by National Science and Technology (Grant No. 2012BAD29B04-4), National Natural Science Foundation of P.R. China (Grant No. 31201451) and open foundation of agricultural product physical processing laboratory (Grant No. JAPP2013-9).
Conflict of Interest
Li Sun declares that she has no conflict of interest. Lei-ming Yuan declares that he has no conflict of interest. Jian-rong Cai declares that he has no conflict of interest. Hao Lin declares that he has no conflict of interest. Jie-wen Zhao declares that he has no conflict of interest. This article does not contain any studies with human or animal subjects.
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Sun, L., Yuan, Lm., Cai, Jr. et al. Egg Freshness on-Line Estimation Using Machine Vision and Dynamic Weighing. Food Anal. Methods 8, 922–928 (2015). https://doi.org/10.1007/s12161-014-9944-1
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DOI: https://doi.org/10.1007/s12161-014-9944-1