Artificial intelligence applied to enzymatic hydrolysis of lactose: improving the control of industrial processes
DOI:
https://doi.org/10.5433/1679-0359.2022v43n4p1637Keywords:
Artificial intelligence, Beta-galactosidase, Cryoscopy, HPLC, Lactose.Abstract
Lactose is the main carbohydrate in milk and its absorption occurs due to enzymatic hydrolysis, generating glucose and galactose. Lactose intolerance is the reduction of the intestinal hydrolysis capacity due to hypolactasia, promoving the need to consume dairy foods with low content of this carbohydrate. The beta-galactosidase enzymes are used in dairy industries to hydrolyze lactose, providing the possibility of eating dairy products without harm to health to the intolerant consumer. Alternative and official analytical methods are used to quantify the carbohydrate content resulting from the enzymatic hydrolysis. The objective of this study was to evaluate the enzymatic hydrolysis of two distinct industrial enzymes produced by the microorganisms Bacillus licheniformis and Kluyveromyces lactis using three analytical methods: enzymatic method, cryoscopy and HPLC using artificial intelligence to improve the control of industrial processes. After adding the enzymes to the skim milk, time kinetics was performed collecting samples at time 0, every 10 minutes until completing 1hour of reaction, and every 30 minutes until the closure of 05 hours of hydrolysis reaction. In 97% of the cases, the decrease in lactose concentration were observed by HPLC followed (by) the deepening of the cryoscopic point. Glucose measurements by absorbance and HPLC quantification were correlated (r = 0.79; p < 0.01), but not concordant (p < 0.01). It was concluded that by means of the artificial intelligence it is possible to indirectly estimate the lactose concentration from an algorithm that associates cryoscopy and glucose concentration.
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