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Will Automatic Shell Strength Detection be a game changer in the egg industry?


 

Everybody knows the effect that despite choosing the right carton of eggs, placing it in a safe spot of your supermarket trolley and even in a safe corner of your car, one of the eggs is broken when the carton reaches your kitchen.

 

This can be caused by 2 things: either the egg had already a hairline crack that opens up with minor pressure on the egg during transport, or the eggshell was very weak in the first place. Finding hairline cracks and even bigger cracks in egg shells is done by high-tech systems in the egg industry for already more than 2 decades. Before that, it were human eyes inspecting the eggs while passing in large volumes on roller conveyors. The so called candling process.

 

But for the shell strength there was no solid solution. The best the industry could do is to monitor the collective quality of a flock of layers and take samples from batches of eggs. Smart devices carry out a destructive test where an increasing amount of pressure is put on an egg until it breaks. The amount of pressure is a measure for the egg shell quality of that particular egg. By taking a few samples from a batch of eggs, a sort of average shell quality rating can be given.


There are 2 problems with this method:

 

1)    Sample size: The statistical sample needs to be significant to really monitor a flock. In order to measure not only the average quality but also get more insights in distribution of quality within a flock, more eggs would need to be tested and thus broken. This is of course a waste of costly food.

 

2)    From lab tests we know that especially on older flocks, the average shell quality goes down but this is caused by sometimes only as little as 10..20% of all eggs. This implies that often batches of eggs are found to be “not processable as table eggs”  while 80%..90% of all eggs are still having a good quality.


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The above example shows that although the average quality in an older flock is not decreasing dramatically, the wider distribution results in outliers in the low quality segment. This makes the batch of eggs unusable. This is just one example; true mass statistics yet need to be discovered in industry.

 

Research by the Katholieke Universiteit Leuven, Belgium, already showed various ways for non-destructive tests that could measure the shell strength of an egg.


Bart De Ketelaere, Research Manager at Katholieke Universiteit Leuven, Belgium:  “Publications about potential non-invasive techniques to measure the shell strength of an egg date back to the last millennium. Already in 2006 articles were published about the scientific connection between egg breakage, shell strength and ways to measure these. (See references below)


But between finding principles and implementing these in high volume egg graders is long and difficult process. Our scientific team in Leuven and the Research and Development team of Moba spent years on lab tests and field tests. But we did it: today is a technology available that is capable of reading the shell quality of each egg passing in a grader. The results match to a high degree the ratings from the ‘good old’ destructive tests, but now with only a small gentle touch and if needed at a capacity of 70 eggs per second!”

 

Since the technology is brand new, the possibilities for use in an egg grader is still under discussion. Moba will work the coming months with a few “early adopters” to find out what are the best and most economical ways to use the technology before releasing it as a complete product in the course of next year.

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Mike Burgers, Product Owner and in charge of the R&D team working on Shell Strength detection: “By using smart and patented technology we managed to get more information from the taps on the egg that were already used in the Crack Detector. This means we don’t even need more egg touching and floor space in the grader; the Crack Detector simply becomes a true “Shell Inspector. With all the advantages already well known like having all technology above the egg flow.”



Moba foresees basically the following 3 applications for the Shell Strength Detection:


1)    Accurate monitoring of flocks of layers: By creating not only an average reading per flock but also measure how the various qualities are scattered a better tool for farm management will become available. Once integrated in the soon to be released farm module of iMoba easy to read egg quality parameters will be added to all the trend-graphs and even early warning systems for diseases are potentially possible.

 

2)    Separating weak shelled eggs from good eggs:  In a batch of eggs with good quality, the system will be able to find incidental outliers and create an even better premium quality by removing these incidental weak shelled eggs and send them to another destination like industry use.

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3)    Another application of separating weak shelled eggs from good eggs: In a batch of eggs with bad quality, for example the worst 20% eggs can be send to industry while the best 80% of the eggs still are able to combine into a premium product. Practical use has to prove the value of this function, but it is quite reasonable to believe that this could lead to extra flock-production of a few weeks.


Some of these applications will have huge impact on egg production and therefore Moba is convinced that Shell Strength Detection will become a true game changer in the industry.


References

Probability of an egg cracking during packing can be predicted using a

simple non-destructive acoustic test

M.M. BAIN, I.C. DUNN1, P.W. WILSON1, N. JOSEPH1, B. DE KETELAERE2,

J. DE BAERDEMAEKER2

AND D. WADDINGTON1

Division of Cell Sciences, ICM, University of Glasgow Veterinary School, Glasgow, 1Roslin Institute

(Edinburgh), Roslin, Midlothian, Scotland, and 2Department of Agro-Engineering and Economics, Katholieke

Universiteit Leuven, Luven (Heverlee), Belgium

 

Monitoring of Eggshell Breakage and Eggshell Strength

in Different Production Chains of Consumption Eggs

K. Mertens,1 F. Bamelis,1 B. Kemps,12 B. Kamers,12 E. Verhoelst,2 B. De Ketelaere,1 M. Bain,3

E. Decuypere,2 and J. De Baerdemaeker,2

1 Department of Biosystems, Division of Mechatronics, Biostatistics and Sensors, and 2 Division of

Livestock-Nutrition-Quality, Katholieke Universiteit Leuven, 3001 Heverlee, Belgium; and 3Division of Cell Sciences, Institute of Comparative Medicine, University of Glasgow Veterinary School, G61 1QH, Scotland





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