Visual Assessment of the State of the Chocolate Mass Using a Vision System

Introduction: The issues of improving the quality of food 3D printing with chocolate and chocolate glaze have been addressed in many modern studies. Most of the works is devoted to the development of extruders, cooling systems and changes in the composition of raw materials, but the 3D food printing process has not been considered from the point of view of automation. In this work, it is proposed to evaluate the aggregate state of the top layer of the applied material for adaptive control of printing modes. Correct determination of the current state of the material will allow you to increase or decrease the application speed, influence the quality of the product and the overall time of constructing the model. The study conducted practical experiments on cooling chocolate mass using a vision system.

Purpose: To reveal the dependence of the shade of the applied chocolate mass on its temperature during natural cooling, in order to evaluate the possibility of using technical vision as a visual sensor an automated control system for the process of 3D printing with chocolate mass. According to the research hypothesis, the aggregate state of the applied material can be controlled using a technical vision system, based on changes in its shade.

Materials and Methods: The object of the study was the process of natural cooling of liquid chocolate mass (Belgostar chocolate glaze and Belgian Callebaut chocolate). Practical experiments on cooling raw materials were carried out, as a result of which numerical data were obtained. Using the method of data analysis and cleaning, filtered values were obtained, from which graphs were constructed of the dependence of the average color values of the channels: “R”, “G”, “B” in the RGB color space on temperature and cooling time. To study the graphs, the method of visual analysis was used. To control the color of raw materials, a Web camera, a computer and auxiliary software based on the OpenCV library were used. Lighting conditions were studied to conduct a visual assessment of the state of aggregation of chocolate using a Web camera. To conduct the experiment, a light diffuser and several light sources (3000K, 4000K, 5000K) were used.

Results: The dependence of the shade of the applied material on its temperature during natural cooling was revealed. In the course of visual analysis of the constructed graphs, a tendency was established for a sharp change in the color of the samples in all color channels "R", "G", "B" at the time of the onset of crystallization. The most informative color channel was revealed - "B", which showed the largest amplitude of change at the moment of crystallization in all experiments, both for glaze and for chocolate. The lighting conditions for visual assessment of the state of aggregation of chocolate using a Web camera have been studied. The greatest change in color is observed under illumination with a color temperature of 3000K (warm light).

Conclusion: The technical vision system is capable of recording a change in the color of the chocolate mass during its cooling: the moment of the beginning of crystallization of the chocolate mass coincides with the moment of a sharp change in its color, which indicates the presence of an interdependence between the shade of the chocolate mass and its state of aggregation. To actually determine the crystallization process begins, it is necessary to analyze the graph of color changes and find an anomalous and uncharacteristic change.

1. Chachlioutaki, K.; Karavasili, C.; Mavrokefalou, E.E.; Gioumouxouzis, C.I.; Ritzoulis, C.; Fatouros, D.G. Quality control evaluation of paediatric chocolate-based dosage forms: 3D printing vs mold-casting method. Int J. Pharm 2022, 624, 121991, ISSN 0378-5173, https://doi.org/10.1016/j.ijpharm.2022.121991

2. Godoi, F. C., Prakash, S., & Bhandari, B. R. (2016). 3d printing technologies applied for food design: Status and prospects. Journal of Food Engineering, 179, 44–54. https://doi.org/10.1016/j.jfoodeng.2016.01.025

3. Holzmond, O., & Li, X. (2017). In situ real time defect detection of 3D printed parts. Additive Manufacturing, 17, 135–142. https://doi.org/10.1016/j.addma.2017.08.003

4. Izdebska, J., & Zołek-Tryznowska, Z. (2016). 3D food printing - Facts and future. In Agro Food Industry Hi-Tech.

5. Karavasili, C., Gkaragkounis, A., Moschakis, T., Ritzoulis, & C., Fatouros, D. G., Pediatric-friendly chocolate-based dosage forms for the oral administration of both hydrophilic and lipophilic drugs fabricated with extrusion-based 3D printing, European Journal of Pharmaceutical Sciences, Volume 147, 2020, 105291, ISSN 0928-0987, https://doi.org/10.1016/j.ejps.2020.105291.

6. Lafeber, I., Tichem, J.M., Ouwerkerk, N., van Unen, A.D., van Uitert, J.J.D., Bijleveld-Olierook, H.C.M., Kweekel, D.M., Zaal, W.M., Le Brun, P.P.H., Guchelaar, H.J., Schimmel, K.J.M., 3D printed furosemide and sildenafil tablets: innovative production and quality control. Int J Pharm 2021; 603: 120694. http://doi.org/10.1016/j.ijpharm.2021.120694

7. Lanaro, M., Desselle, M. R., & Woodruff, M. A. (2019). 3D Printing Chocolate. Fundamentals of 3D Food Printing and Applications, January, 151–173. https://doi.org/10.1016/b978-0-12-814564-7.00006-7

8. Lanaro, M., Forrestal, D. P., Scheurer, S., Slinger, D. J., Liao, S., Powell, S. K., & Woodruff, M. A. (2017). 3D printing complex chocolate objects: Platform design, optimization and evaluation. Journal of Food Engineering. https://doi.org/10.1016/j.jfoodeng.2017.06.029

9. Mantihal, S., Prakash, S., Godoi, F. C., & Bhandari, B. (2017). Optimization of chocolate 3D printing by correlating thermal and flow properties with 3D structure modeling. Innovative Food Science and Emerging Technologies. https://doi.org/10.1016/j.ifset.2017.09.012

10. Nuchitprasitchai, S., Roggemann, M., & Pearce, J. (2017). Three Hundred and Sixty Degree Real-Time Monitoring of 3-D Printing Using Computer Analysis of Two Camera Views. In Journal of Manufacturing and Materials Processing (Vol. 1, Issue 1). https://doi.org/10.3390/jmmp1010002

11. Outrequin, T.C.R.; Gamonpilas, C.; Siriwatwechakul, W.; Sreearunothai, P. Extrusion-based 3D printing of food biopolymers: A highlight on the important rheological parameters to reach printability. J. Food Eng. 2023, 342, 111371, ISSN 0260-8774, https://doi.org/10.1016/j.jfoodeng.2022.111371

12. Straub, J. (2015). Initial work on the characterization of additive manufacturing (3D printing) using software image analysis. Machines, 3(2), 55–71. https://doi.org/10.3390/machines3020055

13. You, S., Huang Q., Lu X., Development of fat-reduced 3D printed chocolate by substituting cocoa butter with water-in-oil emulsions, Food Hydrocolloids, Volume 135, 2023, 108114, ISSN 0268-005X, https://doi.org/10.1016/j.foodhyd.2022.108114.

14. Blagoveshchensky, I. G. (2015). Using a computer vision system for online control of the quality of raw materials and finished products of the food industry. Food Industry, 9–13.

15. Blagoveshchensky, I. G., Blagoveshchenskaya, M. M., Nosenko, A. S., & Nosenko, S. M. (2016). Automation of control of quality indicators and detection of defective products using a computer vision system. Confectionery Production, 26–30.

16. Blagoveshchensky, I. G., Nosenko, S. M., & Nosenko, A. S. (2015). Expert intelligent system for monitoring the molding process of fondant candies using a vision system. Food Industry, 32–35.

17. Blagoveshchensky, I. G., Shibanov, E. D., & Zagorodnikov, K. A. (2020). OPTIMIZATION OF 3D PRINTING ON THE EXAMPLE OF USING CHOCOLATE GLAZE. Food Industry, 70–73. https://doi.org/10.24411/0235-2486-2020-10147

18. Martekha, A. N. Optimization of 3D printing of chocolate mass by correlating rheological properties with 3D modeling of the structure / A. N. Martekha, V. N. Andreev // Science, technology, personnel - the basis for achieving breakthrough results in the agro-industrial complex: Scientific collection -practical materials of the International Scientific and Practical Conference, Kazan, May 26–27, 2021. Volume Issue XV. Part 2. - Kazan: Federal State Budgetary Educational Institution of Additional Professional Education "Tatar Institute for the Retraining of Agribusiness Personnel", 2021. - P. 571-578. – EDN EDMMYK.

19. Semenov A. S. 3D printing technologies in the food industry / A. S. Maksimov, A. S. Maksimov, E. M. Besfamilnaya, D. V. Talmazova // Young scientist. - 2021. - No. 21 (363). - S. 41-43. – EDN WZJNGE.

20. Skomorokhova A. I. Production of souvenir chocolate using additive technologies / A. I. Skomorokhova, Yu. decision: Collection of articles based on the materials of the I International Scientific and Practical Conference, Nizhny Novgorod, April 30, 2021. - Knyaginino: Nizhny Novgorod State Engineering and Economic Institute, 2021. - P. 164-166. – EDN UBPENG.