Changes in morphological characteristics of selected wine yeasts and lactic acid bacteria in the presence of ochratoxin A

Jedan od vaţnijih problema današnjice je kontaminacija prehrambenih proizvoda mikotoksinima. Izuzev čovjeka, ţivotinja i biljaka, toksično djelovanje mikotoksina dokazano je i na mikroorganizmima. Budući da postoji ograničen broj istraţivanja o utjecaju mikotoksina na stanice bakterija i kvasaca, cilj ovog rada bio je odrediti djelovanje okratoksina A na krivulju rasta i morfološke osobine vinskih kvasaca S.cerevisiae i S.bayanus tijekom 168 sati, te na bakteriju Lactobacillus plantarum B tijekom 72 sata. Mikrobni rast prikazan u obliku krivulje rasta, odreĎen je brojanjem poraslih kolonija na čvrstoj hranjivoj podlozi, dok je veličina stanica, odreĎena metodom mikrometrije upotrebom objektnog i okularnog mikrometra. Iz dobivenih rezultata moţe se uočiti da okratoksin A neznatno utječe na rast i morfologiju i Lactobacillus plantarum B i kvasce S.cerevisiae i S.bayanus što se moţe objasniti da su i bakterija i kvasci razvili odreĎenu otpornost na toksičnost okratoksina A.One of the most important problems today is the contamination of food products with mycotoxins. Apart from humans, animals and plants, toxicity of mycotoxins has been demonstrated in microorganisms. Since there is a limited number of studies on the effects of mycotoxins on bacteria and yeast cells, the goal of this study was to determine the effects of ochratoxin A on growth curve and morphological properties of wine yeasts S.cerevisiae and S. bayanus during 168 hours and on bacterium Lactobacillus plantarum B during 72 hours. The microbial growth shown in the form of growth curves was determined by counting the growing colonies on a solid nutrient medium, while the cell size was determined by a micrometric method using the stage and ocular micrometers. From the obtained results, it can be seen that ochratoxin A has a slight influence on growth and morphology and Lactobacillus plantarum B and yeasts S. cerevisiae and S. bayanus. Which can be explained that both bacteria and yeasts developed a certain resistance to ochratoxin A

Changes in morphological characteristics of selected wine yeasts and lactic acid bacteria in the presence of ochratoxin A

Jedan od vaţnijih problema današnjice je kontaminacija prehrambenih proizvoda mikotoksinima. Izuzev čovjeka, ţivotinja i biljaka, toksično djelovanje mikotoksina dokazano je i na mikroorganizmima. Budući da postoji ograničen broj istraţivanja o utjecaju mikotoksina na stanice bakterija i kvasaca, cilj ovog rada bio je odrediti djelovanje okratoksina A na krivulju rasta i morfološke osobine vinskih kvasaca S.cerevisiae i S.bayanus tijekom 168 sati, te na bakteriju Lactobacillus plantarum B tijekom 72 sata. Mikrobni rast prikazan u obliku krivulje rasta, odreĎen je brojanjem poraslih kolonija na čvrstoj hranjivoj podlozi, dok je veličina stanica, odreĎena metodom mikrometrije upotrebom objektnog i okularnog mikrometra. Iz dobivenih rezultata moţe se uočiti da okratoksin A neznatno utječe na rast i morfologiju i Lactobacillus plantarum B i kvasce S.cerevisiae i S.bayanus što se moţe objasniti da su i bakterija i kvasci razvili odreĎenu otpornost na toksičnost okratoksina A.One of the most important problems today is the contamination of food products with mycotoxins. Apart from humans, animals and plants, toxicity of mycotoxins has been demonstrated in microorganisms. Since there is a limited number of studies on the effects of mycotoxins on bacteria and yeast cells, the goal of this study was to determine the effects of ochratoxin A on growth curve and morphological properties of wine yeasts S.cerevisiae and S. bayanus during 168 hours and on bacterium Lactobacillus plantarum B during 72 hours. The microbial growth shown in the form of growth curves was determined by counting the growing colonies on a solid nutrient medium, while the cell size was determined by a micrometric method using the stage and ocular micrometers. From the obtained results, it can be seen that ochratoxin A has a slight influence on growth and morphology and Lactobacillus plantarum B and yeasts S. cerevisiae and S. bayanus. Which can be explained that both bacteria and yeasts developed a certain resistance to ochratoxin A

OPTIMIZATION OF ETHANOL/WATER SOLVENT EXTRACTION OF BIOACTIVE COMPONENTS ORIGINATING FROM INDUSTRIAL HEMP (Cannabis sativa L.)

Hemp (Cannabis sativa L.) contains a wide range of biocompounds with different beneficial properties such as anti-inflammatory, antithrombotic, antiarrhythmic, hypolipidemic and antioxidative. Response Surface Methodology (RSM) coupled with Box-Behnken design (BBD) was applied to determine the influence of extraction temperature, liquid to solid ratio, extraction time, rotational speed and ethanol/water solvent ratios at three levels on the solid-liquid extraction of the bioactives from the hemp (flowers, leaves, seeds, stems). Based on the obtained results, liquid to solid ratio, temperature and ethanol/water solvent ratio had statistically significant effects on the total polyphenolic content (TPC), while extraction time and rotational speed had no influence on the TPC extraction. Regarding antioxidant activity (AOX) determined by the DPPH method, only liquid to solid ratio had a statistically significant effect. Liquid to solid ratio, ethanol/water solvent ratio, temperature and rotational speed significantly influenced AOX determined by the FRAP method. According to BBD, the optimum extraction conditions were as follows: extraction temperature 45 °C, liquid to solid ratio 30 mL/g, extraction time 25 min, rotational speed 500 rpm, ethanol/water solvent ratio 25%. RSM coupled with a BBD model was shown to be effective for optimization the solid-liquid extraction of hemp

Optimization of the extraction conditions of biologically active compounds from industrial hemp (Cannabis sativa L.)

Cilj ovog rada bio je ispitati utjecaj temperature, otapala, brzine miješanja, vremena ekstrakcije i omjera tekuće i krute faze na fizikalna (vodljivost, TDS, pH, suha tvar) i kemijska (ukupni polifenoli, antioksidacijska aktivnost određena DPPH i FRAP metodama) svojstva ekstrakata industrijske konoplje. Optimiranje procesa klasične ekstrakcije provedeno je metodom odzivnih površina (RSM), zajedno sa Box-Behnken dizajnom (BBD). Prema metodi odzivnih površina, optimalni uvjeti ekstrakcije bili su sljedeći: temperatura 45 °C, omjer tekuće i krute faze 30 mL g-1, vrijeme ekstrakcije 25 min, brzina miješanja 500 rpm, udio etanola u vodi 25 %. Razvijeni su modeli višestruke linearne regresije, nelinearne regresije i lokalne linearne regresije, kao i umjetne neuronske mreže, za predviđanje fizikalno-kemijskih svojstava pripremljenih ekstrakata konoplje, na temelju procesnih parametara klasične ekstrakcije. Na temelju dobivenih koeficijenata determinacije, utvrđeno je kako se modeli lokalne linearne regresije mogu primijeniti za predviđanje fizikalno-kemijskih svojstava ekstrakata konoplje, za razliku od modela linearne i nelinearne regresije. Rezultati dobiveni primjenom umjetnih neuronskih mreža pokazali su se najpouzdanijim za predviđanje antioksidacijske aktivnosti određene DPPH metodom (R2 = 0,978).The aim of this study was to investigate the influence of temperature, solvent, mixing speed, extraction time and liquid to solid ratio on physical (conductivity, total dissolved solids, pH, dry matter) and chemical (total polyphenols, antioxidant activity determined by DPPH and FRAP methods) properties of hemp extracts. Classical extraction process was optimized using Response Surface Methodology (RSM) coupled with Box-Behnken design (BBD). According to RSM, the optimal extraction conditions were as follows: T = 45 °C, liquid to solid ratio 30 mL g-1, extraction time 25 min, mixing speed 500 rpm, ethanol content 25 %. Based on the extraction process parameters, multiple linear regression, nonlinear regression, piecewise linear regression and artificial neural networks models were developed for prediction of physical-chemical characteristics of hemp extracts. According to calculated determination coefficients, piecewise regression could be applied for prediction of physical and chemical characteristics of hemp extracts, unlike linear and nonlinear models. The results obtained using artificial neural networks have proven to be the most reliable for the prediction of antioxidant activity determined by DPPH method (R2 = 0.978)