THE STRUCTURE OF THE MATHEMATICAL MODEL OF MAIZE GERMINATION REGIMES ON THE BASIS OF CHANGE OF THE QUANTITY OF ANTIOXIDANTS

Statistical processing of experimental studies allowed to scientifically substantiate and describe mathematically the optimization of the parameters of the technological process with the mutual influence of temperature and the duration of germination on the change in the biological and nutritional value of maize corn.The research results showed that at the germination temperature of 24 °C, antioxidant activity shows the highest result than at 18 and 300 ° C. At a germination temperature of 24 °C, all of the above figures at day 5 reach the maximum mark. Of the studied hybrids, at a temperature of 24°C on the fifth day of germination in “Arman 689” corn, the SSA increased by 3.1 times (68%) compared with the control. Under the same conditions, in the hybrid “Turan 480 SV”, the SSA increased 3.2 times (by 68.7%), in the hybrid “Turgen 5/87” - 4.2 times (by 76%). Compared with the “Turan 480 CB” and “Turgen 5/87” hybrids, in the “Arman 689” hybrid, the SSA is 1.3 and 1.03 times higher, respectively, 22.8 and 2.9%. Based on the data obtained, mathematical model of germination of corn hybrids

COMPUTER MODELLING OF OBJECTS AND PROCESSES IN FOOD MANUFACTURES

In article are shown results of necessity of wide application of mathematical modelling of objects and processes for food manufactures is shown. Main principles of computer modelling, examples of mathematical models of processes and objects are resulted.An example of modeling apple juice with given parameters from composite juice from apples of the Lemon, Aport, Stolovka varieties is given. As a result, with the help of prospective regulatory modeling on Microsoft Excel, a calculation was made of the percentage of added juices to ensure titrated acidity of 0.3% and vitamin C 0.02%

Quantification of Lactobacillus helveticus in a mixture of lactic acid bacteria using qPCR in cheese

Conventional quantification of L. helveticus, in presence of other lactobacilli species, using classical plate method employing low selective media is very inaccurate. Determination of L. helveticus using quantitative PCR (qPCR) was performed in six artisanal Kazakh soft cheeses made from cow’s milk or from a mixture of cow’s and goat’s milk. L. helveticus was quantified by species-specific qPCR, monitoring the presence of genes encoding for peptidoglycan hydrolases. Quantification of L. helveticus based on qPCR ranged from 2.6×106 to 4.1×108 CFU·g−1 according to the type of the cheese. The microflora of cheese consisted of a mixture of starter and non-starter lactic acid bacteria