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Year 2021, Volume: 2 Issue: 1, 124 - 132, 30.06.2021

Abstract

References

  • Anderson KE (2011). Comparison of fatty acid, cholesterol, and vitamin A and E composition in eggs from hens housed in conventional cage and range production facilities. Poultry Science, 90(7): 1600-1608.
  • Bazyar P, Jafari A, Alimardani R and Mohammadi V (2019). Small-scale head of combine for harvesting sesame. Electronic Journal of Polish Agricultural Universities (EJPAU), 22(4), Article 02.
  • Brant AW, Otte AW and Norris KH (1951). Recommended standards for scoring and measuring opened egg quality. Food Technology, 5: 356-361.
  • Davies ER (2012). Computer and machine vision: theory, algorithms, practicalities. Academic Press.
  • Du CJ and Sun DW (2004). Recent developments in the applications of image processing techniques for food quality evaluation. Trends in Food Science & Technology, 15(5): 230-249.
  • Earle MD and Earle RL (1997). Food Industry research and development. In Government and the Food Industry: Economic and Political Effects of Conflict and Co-Operation (pp. 125-140). Springer, Boston, MA.
  • Heredia FJ, González-Miret ML, Álvarez C and Ramírez A (2006). DigiFood®. Registro Nº SE-01298. Hough RR (1937). The haugh unit for measuring egg quality. US Egg and Poultry Magazine, 43: 522–555, 572–573.
  • Karsten HD, Patterson PH, Stout R and Crews G (2010). Vitamins A, E and fatty acid composition of the eggs of caged hens and pastured hens. Renewable Agriculture and Food Systems, 25(1): 45-54.
  • Luo MR, Cui CG. and Li C (2001). British patent (Application No. 0124683.4) entitled apparatus and method for measuring colour (DigiEye® System). Derby University Enterprises Limited, 4.
  • Manual UEG (2000). Agricultural Marketing Service. Agricultural Handbook, 75.
  • Mitra A (2016). Fundamentals of quality control and improvement. John Wiley & Sons.
  • Moore DV and Sandground JH (1956). The relative egg producing capacity of Schistosoma Mansoni and Schistosoma Japonicum 1, 2. The American Journal of Tropical Medicine and Hygiene, 5(5): 831-840.
  • Omid M, Soltani M, Dehrouyeh MH, Mohtasebi SS and Ahmadi H (2013). An expert egg grading system based on machine vision and artificial intelligence techniques. Journal of Food Engineering, 118(1): 70-77.
  • Otsu N (1979). A threshold selection method from gray-scale histogram. IEEE Trans. Syst., Man, Cyber, pp.62-66.
  • Ramírez-Gutiérrez KA, Medina-Santiago A, Martínez-Cruz A, AlgredoBadillo I and Peregrina-Barreto H (2019). Eggshell deformation detection applying computer vision. Computers and Electronics in Agriculture, 158: 133-139.
  • Şekeroǧlu A and Altuntaş E (2009). Effects of egg weight on egg quality characteristics. Journal of the Science of Food and Agriculture, 89(3): 379-383.
  • Zhang W, Pan L, Tu S, 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.

Design and Fabrication of Egg Quality Assessment System Based on Image Processing

Year 2021, Volume: 2 Issue: 1, 124 - 132, 30.06.2021

Abstract

Eggs are a nutritious and important food in human daily diet, which is considered as a protein source of food. The most acceptable index for evaluating egg quality is Haugh unit with two factors, i.e. the weight of intact egg and the height of broken egg’s albumin. Hauge unit has three classification: firm (higher than 72), reasonably firm (higher than 72), and weak (less than 60). Average results for Haugh unit on the first, fourth, eighth, twelfth, and sixteenth days (five eggs in each step) were 113.39, 91.47, 74.56, 72.04, and 64.14 respectively. On the first, fourth and eighth days, eggs were intact but the quality of the eggs decreases on the next days. This research aims to sort healthy eggs from others and swell the rate of sorting.

Supporting Institution

university of Tehran, faculty of biosystem engineering

References

  • Anderson KE (2011). Comparison of fatty acid, cholesterol, and vitamin A and E composition in eggs from hens housed in conventional cage and range production facilities. Poultry Science, 90(7): 1600-1608.
  • Bazyar P, Jafari A, Alimardani R and Mohammadi V (2019). Small-scale head of combine for harvesting sesame. Electronic Journal of Polish Agricultural Universities (EJPAU), 22(4), Article 02.
  • Brant AW, Otte AW and Norris KH (1951). Recommended standards for scoring and measuring opened egg quality. Food Technology, 5: 356-361.
  • Davies ER (2012). Computer and machine vision: theory, algorithms, practicalities. Academic Press.
  • Du CJ and Sun DW (2004). Recent developments in the applications of image processing techniques for food quality evaluation. Trends in Food Science & Technology, 15(5): 230-249.
  • Earle MD and Earle RL (1997). Food Industry research and development. In Government and the Food Industry: Economic and Political Effects of Conflict and Co-Operation (pp. 125-140). Springer, Boston, MA.
  • Heredia FJ, González-Miret ML, Álvarez C and Ramírez A (2006). DigiFood®. Registro Nº SE-01298. Hough RR (1937). The haugh unit for measuring egg quality. US Egg and Poultry Magazine, 43: 522–555, 572–573.
  • Karsten HD, Patterson PH, Stout R and Crews G (2010). Vitamins A, E and fatty acid composition of the eggs of caged hens and pastured hens. Renewable Agriculture and Food Systems, 25(1): 45-54.
  • Luo MR, Cui CG. and Li C (2001). British patent (Application No. 0124683.4) entitled apparatus and method for measuring colour (DigiEye® System). Derby University Enterprises Limited, 4.
  • Manual UEG (2000). Agricultural Marketing Service. Agricultural Handbook, 75.
  • Mitra A (2016). Fundamentals of quality control and improvement. John Wiley & Sons.
  • Moore DV and Sandground JH (1956). The relative egg producing capacity of Schistosoma Mansoni and Schistosoma Japonicum 1, 2. The American Journal of Tropical Medicine and Hygiene, 5(5): 831-840.
  • Omid M, Soltani M, Dehrouyeh MH, Mohtasebi SS and Ahmadi H (2013). An expert egg grading system based on machine vision and artificial intelligence techniques. Journal of Food Engineering, 118(1): 70-77.
  • Otsu N (1979). A threshold selection method from gray-scale histogram. IEEE Trans. Syst., Man, Cyber, pp.62-66.
  • Ramírez-Gutiérrez KA, Medina-Santiago A, Martínez-Cruz A, AlgredoBadillo I and Peregrina-Barreto H (2019). Eggshell deformation detection applying computer vision. Computers and Electronics in Agriculture, 158: 133-139.
  • Şekeroǧlu A and Altuntaş E (2009). Effects of egg weight on egg quality characteristics. Journal of the Science of Food and Agriculture, 89(3): 379-383.
  • Zhang W, Pan L, Tu S, 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.
There are 17 citations in total.

Details

Primary Language English
Subjects Agricultural Engineering
Journal Section Research Articles
Authors

Ehsan Sheydaee 0000-0003-4463-9650

Pourya Bazyar 0000-0003-1882-8941

Publication Date June 30, 2021
Submission Date November 21, 2020
Acceptance Date February 7, 2021
Published in Issue Year 2021 Volume: 2 Issue: 1

Cite

APA Sheydaee, E., & Bazyar, P. (2021). Design and Fabrication of Egg Quality Assessment System Based on Image Processing. Turkish Journal of Agricultural Engineering Research, 2(1), 124-132.

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