Том 13 № 3

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https://card-file.ontu.edu.ua/handle/123456789/16683

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Перегляд Том 13 № 3 за Автор "S. Kraevska, O. Yeshchenko, N. Stetsenko"

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  • Документ
    OPTIMIZATION OF THE TECHNOLOGICAL PROCESS OF FLAX SEED GERMINATION
    (2019) S. Kraevska, O. Yeshchenko, N. Stetsenko
    In the world, demand for flax seeds and its processed volumes are increasing. Flax seeds are classified as natural functional food products. This is confirmed by the Ministry of Health of many countries, in particular Canada and the United States of America. Flax germination makes flax seed components biologically available. Each type of plant has its own set of germination requirements consisting of both internal and external factors. This research was aimed at studying the effect of various external factors (temperature, humidity.etc.) affecting flax seed germination energy. The temperature varied in the range 16°C to 30°C, in increments of 2°C, as further increasing the temperature requires additional equipment and, consequently, additional energy consumption. The ambient humidity was maintained at 40, 60, 70, and 95%. The flax seeds were germinated for 36 hours till seedlings, up to 3 mm long, appeared. The germination energy was determined for each combination of the controlled factors. A mathematical model of the flaxseed germination process was constructed using the regression and correlation analysis methods. The model obtained determines the optimum germination modes. In the course of the experimental research, we applied experimental design techniques and mathematical processing of the experimental data. Using the computer programmes MathCad and Microsoft Excel optimized the flax seed germination and set its optimum modes. The constructed mathematical model makes it clear that the maximum germination energy 99.64% is achieved at the temperature 27.5°C and humidity 95%. The experimental and statistical models of germination of flax seeds have been obtained, describing the process with the correlation coefficient R = 0.96–0.99. The data obtained can be used to predict the quality parameters of flax seedlings and the energy consumption to obtain them.