АНАЛИЗ НА МЕТОДИ ЗА ОБРАБОТКА НА СЕНЗОРНИ ХАРАКТЕРИСТИКИ НА КИСЕЛО МЛЯКО, Мирела Йорданова, Ели Костадинова
2016-12-07 | T+ | T- |

Резюме: В доклада е анализирана възможността за приложение на непара-метрични методи за анализ на кисело мляко. Направен е избор на методи за анализ. Представен е пример за обработка на дегустационни оценки и прогнозиране на органолептични показатели чрез избраните методи.

Ключови думи: Кисело мляко, Сензорни характеристики, Анализ на главните компоненти, Частична регресия на най-малките квадрати

Фиг.3. Стойности на коефициент R2 при прогнозиране на сензорни показатели

5. Литература

[1] AOAC. (1990). Official Methods of Analysis.(15thed.). Association of analytical chemist. Washington DC.

[2] Buckle, K.A., R.A. Edwars, G.H. Fleet, R.A. Souness, M.Wooton. (1982). Food science laboratory. Training course, Udayana University. School of Food Technology, The University of New South Wales, Kensington. NSW. Australia.

[3] Georgieva, K., Ts. Georgieva, E. Kirilova, P. Daskalov. (2015). Classification of healthy and diseased vine leaves using color features. ARTTE, Vol. 3, No. 4, ISSN 1314-8796, pp.296-302.

[4] Mladenov, M., S. Penchev, M. Deyanov. (2015). Complex assessment of food products quality using analysis of visual images, spectrophotometric and hyperspectral characteristics. International Journal of Engineering and Innovative Technology (IJEIT), Vol. 4, Iss. 12, ISSN: 2277-3754, pp.23-32.

[5] Shivacheva, I. (2016). E-Learning as supporting technology in the pedagogical preparation. Journal of Innovation and entrepreneurship, year IV, vol.2, ISSN 1314-9180, pp.3-16.

[6] Suriasih, K., M. Hartawan, N. Sucipta, S. A. Lindawati, I.A. Okarini. (2014). Microbiological, chemical and sensory characteristics of yoghurt prepared from blended cow and goat milk. Food Science and Quality Management, Vol.34, www.iiste.org, ISSN 2225-0557, pp.93-102.

[7] Tasev, G., K. Krastev. (2011). Exploration of mathematical model for optimization of frequency of diagnosis of the elements of machines. Proceedings of The 11th International Conference, Reliability and statistics in transportation and communication, Latvia, ISBN 978-9984-818-34-4, pp.115-119.

[8] Vasilev, M., I. Taneva, M. Velikova, R. Mihova. (2016). Interpreting sensory data of cheese "Krema" by Principal component analysis. ARTTE Vol. 4, No. 2, ISSN 1314-8796, pp.139-144.

[9] Yankov, K. (2013). Data structures of models in system identification. 27th International Conference on Information Technologies (InfoTech-2013), 19th – 20th September 2013, Varna – St. St. Constantine and Elena resort, Bulgaria, ISSN:1314-1023, pp.312-319.

[10] Zlatev Z., G. Shivacheva, A. Dimitrova, M. Vasilev. (2015). Analysis of data from sensory evaluation of yogurt. Proceedings of XXIV International conference Management and quality for young scientists, Yambol, Bulgaria, 15-16.10.2015, ISSN 1314-4669, pp.128-136.

[11] Zlatev, Z., I. Penchev, S. Ribarski, S. Baycheva. (2016). Analysis of sensory data of perishable boiled-smoked sausages. Innovation and entrepreneurship – Applied scientific journal, Vol.4, No.3, ISSN 1314-9253, pp.3-15.

[12] Zlatev, Z., M. Petev, A. Dimitrova, V. Simeonova, S. Dinev, J. Dineva. (2015). Analysis of methods and tools for evaluation the quality of yogurt. Journal of Innovation and entrepreneurship, year III, vol.1-2, ISSN 1314-9180, pp.41-57.

Контакти:

Мирела Стоянова Йорданова - e-mail: buffy23@mail.bg

Ели Стоянова Костадинова - e-mail: elikostadinova_1994@abv.bg

Тракийски университет, факултет „Техника и технологии“,

ул. „Граф Игнатиев“ No.38, 8602, Ямбол, България