The Effect of Incubation Temperature on the Survival and Growth of Yeasts in Sethemi, South African Naturally Fermented Milk

The effect of temperature on the growth of yeasts during the production of Sethemi, South African naturally fermented milk (NFM), was studied by incubating raw milk and milk inoculated with selected yeast strains at 7, 15, 25 and 37 °C. The different temperatures were selected to represent the average ambient temperatures around Bloemfontein, South Africa, during winter, spring, summer, and in the human body, respectively. The yeast strains used had previously been isolated from Sethemi and identified as Kluyveromyces marxianus, Saccharomyces cerevisiae, Candida albicans and Debaryomyces hansenii. The yeast strains were inoculated into raw milk separately and also as a mixture of the four strains. The yeast counts, lactic acid bacteria counts and pH were monitored over a period of 20 days. It was observed that although all the yeast strains grew in the milk at all temperatures, the fastest growth was at 37 °C but there was a prolonged lag phase at 7 and 15 °C. The highest yeast counts of 8.30 log (CFU/mL) were obtained at 25 °C in the milk inoculated with K. marxianus. At all temperatures, the initial yeast count in the control was significantly (p<0.05) lower than the counts in the inoculated milk. Lactic acid bacteria also grew to high numbers both with added yeast and in the control. The highest LAB counts of about 11.59 log (CFU/mL) were obtained in the presence of S. cerevisiae after about 4 days of incubation at 25 °C. The addition of different yeast strains did not affect significantly the growth of LAB at all temperatures. After 3 days, the LAB counts decreased rapidly at 37 °C, while from day 2 to day 5 the LAB numbers remained stable at 25 °C. There was a rapid decrease in pH at higher temperatures than at 7 or 15 °C, corresponding to the LAB growth. A temperature of 25 °C was found to be ideal for producing fermented milk with high LAB counts, low pH and a visually acceptable coagulum

Utjecaj temperature inkubacije na preživljavanje i rast kvasca u južnoafričkom prirodno fermentiranom mlijeku Sethemi

The effect of temperature on the growth of yeasts during the production of Sethemi, South African naturally fermented milk (NFM), was studied by incubating raw milk and milk inoculated with selected yeast strains at 7, 15, 25 and 37 °C. The different temperatures were selected to represent the average ambient temperatures around Bloemfontein, South Africa, during winter, spring, summer, and in the human body, respectively. The yeast strains used had previously been isolated from Sethemi and identified as Kluyveromyces marxianus, Saccharomyces cerevisiae, Candida albicans and Debaryomyces hansenii. The yeast strains were inoculated into raw milk separately and also as a mixture of the four strains. The yeast counts, lactic acid bacteria counts and pH were monitored over a period of 20 days. It was observed that although all the yeast strains grew in the milk at all temperatures, the fastest growth was at 37 °C but there was a prolonged lag phase at 7 and 15 °C. The highest yeast counts of 8.30 log (CFU/mL) were obtained at 25 °C in the milk inoculated with K. marxianus. At all temperatures, the initial yeast count in the control was significantly (p<0.05) lower than the counts in the inoculated milk. Lactic acid bacteria also grew to high numbers both with added yeast and in the control. The highest LAB counts of about 11.59 log (CFU/mL) were obtained in the presence of S. cerevisiae after about 4 days of incubation at 25 °C. The addition of different yeast strains did not affect significantly the growth of LAB at all temperatures. After 3 days, the LAB counts decreased rapidly at 37 °C, while from day 2 to day 5 the LAB numbers remained stable at 25 °C. There was a rapid decrease in pH at higher temperatures than at 7 or 15 °C, corresponding to the LAB growth. A temperature of 25 °C was found to be ideal for producing fermented milk with high LAB counts, low pH and a visually acceptable coagulum.Inkubacijom svježeg mlijeka i mlijeka inokuliranog odabranim sojevima kvasca na 7, 15, 25 i 37 °C istražen je utjecaj temperature na rast kvasca pri dobivanju južnoafričkog prirodno fermentiranog mlijeka (naturally fermented milk – NFM) Sethemi. Odabrane su različite temperature fermentacije koje predstavljaju prosječnu zimsku, ljetnu i proljetnu temperaturu zraka u okolici grada Bloemfontein (Južna Afrika), te prosječnu temperaturu ljudskoga tijela. Upotrijebljeni su sojevi kvasca Kluyveromyces marxianus, Saccharomyces cerevisiae, Candida albicans i Debaryomyces hansenii izolirani iz mlijeka Sethemi. Sojevi su inokulirani zasebno i kao mješovita kultura u svježe mlijeko. Tijekom 20 dana praćen je broj kvasaca i mliječno-kiselih bakterija te pH-vrijednost. Iako je primijećen rast sojeva kvasca pri svim vrijednostima temperature korištenim u istraživanju, najbrže su rasli pri temperaturi od 37 °C, a na 7 i 15 °C došlo je do produljenja lag faze. Najveći broj kvasaca, i to od 8,30 log (CFU/mL), postignut je u mlijeku inokuliranom s K. marxianus pri temperaturi od 25 °C. Početni broj kvasaca u kontrolnom uzorku bio je značajno (p<0,05) niži nego u inokuliranom mlijeku pri svim temperaturnim vrijednostima. Porastao je i broj mliječno-kiselih bakterija (LAB) u kontrolnom i inokuliranom uzorku. Najveći broj LAB (11,59 log (CFU/mL)) postignut je u prisutnosti S. cerevisiae nakon 4 dana inkubacije na 25 °C. Dodatak različitih sojeva kvasca nije značajno utjecao na rast LAB bez obzira na temperaturnu vrijednost. Nakon 3 dana na 37 °C drastično je smanjen broj LAB, dok je nakon 2-5 dana pri 25 °C ostao nepromijenjen. Pri temperaturama višim od 7 i 15 °C uvelike se snizio pH zbog povećanja broja LAB. Temperatura od 25 °C ocijenjena je idealnom za proizvodnju fermentiranog mlijeka zbog velikog broja LAB, niske pH-vrijednosti i prihvatljivog izgleda koaguluma

Assessing the reliability of predicted plant trait distributions at the global scale

Aim: Predictions of plant traits over space and time are increasingly used to improve our understanding of plant community responses to global environmental change. A necessary step forward is to assess the reliability of global trait predictions. In this study, we predict community mean plant traits at the global scale and present a systematic evaluation of their reliability in terms of the accuracy of the models, ecological realism and various sources of uncertainty. Location: Global. Time period: Present. Major taxa studied: Vascular plants. Methods: We predicted global distributions of community mean specific leaf area, leaf nitrogen concentration, plant height and wood density with an ensemble modelling approach based on georeferenced, locally measured trait data representative of the plant community. We assessed the predictive performance of the models, the plausibility of predicted trait combinations, the influence of data quality, and the uncertainty across geographical space attributed to spatial extrapolation and diverging model predictions. Results: Ensemble predictions of community mean plant height, specific leaf area and wood density resulted in ecologically plausible trait–environment relationships and trait–trait combinations. Leaf nitrogen concentration, however, could not be predicted reliably. The ensemble approach was better at predicting community trait means than any of the individual modelling techniques, which varied greatly in predictive performance and led to divergent predictions, mostly in African deserts and the Arctic, where predictions were also extrapolated. High data quality (i.e., including intraspecific variability and a representative species sample) increased model performance by 28%. Main conclusions: Plant community traits can be predicted reliably at the global scale when using an ensemble approach and high-quality data for traits that mostly respond to large-scale environmental factors. We recommend applying ensemble forecasting to account for model uncertainty, using representative trait data, and more routinely assessing the reliability of trait predictions. © 2020 The Authors. Global Ecology and Biogeography published by John Wiley and Sons Lt

Assessing the reliability of predicted plant trait distributions at the global scale

International audienceAbstractAim: Predictions of plant traits over space and time are increasingly used to improve our understanding of plant community responses to global environmental change. A necessary step forward is to assess the reliability of global trait predictions. In this study, we predict community mean plant traits at the global scale and present a sys- tematic evaluation of their reliability in terms of the accuracy of the models, ecologi- cal realism and various sources of uncertainty.Location: Global.Time period: Present.Major taxa studied: Vascular plants.Methods: We predicted global distributions of community mean specific leaf area, leaf nitrogen concentration, plant height and wood density with an ensemble model- ling approach based on georeferenced, locally measured trait data representative of the plant community. We assessed the predictive performance of the models, the plausibility of predicted trait combinations, the influence of data quality, and the un- certainty across geographical space attributed to spatial extrapolation and diverging model predictions.Results: Ensemble predictions of community mean plant height, specific leaf area and wood density resulted in ecologically plausible trait–environment relationships and trait–trait combinations. Leaf nitrogen concentration, however, could not be predicted reliably. The ensemble approach was better at predicting community trait means than any of the individual modelling techniques, which varied greatly in pre- dictive performance and led to divergent predictions, mostly in African deserts and the Arctic, where predictions were also extrapolated. High data quality (i.e., including intraspecific variability and a representative species sample) increased model perfor- mance by 28%.Main conclusions: Plant community traits can be predicted reliably at the global scale when using an ensemble approach and high-quality data for traits that mostly re- spond to large-scale environmental factors. We recommend applying ensemble fore- casting to account for model uncertainty, using representative trait data, and more routinely assessing the reliability of trait predictions

Iogurte probiótico produzido com leite de cabra suplementado com Bifidobacterium spp

Avaliaram-se iogurtes de leite de cabra contendo ou não Bifidobacterium longum, B. breve, B. pseudolongum ou B. bifidum, adicionados ou não de aroma de morango. Os dados obtidos nas análises higiênico-sanitárias e físico-químicas foram dentro dos valores exigidos pela legislação brasileira; apenas o valor encontrado para lactose esteve abaixo do recomendado. Quanto às bactérias do iogurte, não houve diferença na contagem de Streptococcus salivarius subsp. thermophilus durante a estocagem, e não foi detectado Lactobacillus delbrueckii subsp. bulgaricus nas diluições utilizadas. A enumeração de Bifidobacterium spp. manteve-se entre 10(6) e 10(8)UFC/mL e não diferiu entre as espécies ao longo do tempo. Considerando-se a adição ou não de aroma, a análise das variáveis tempo e aroma não mostrou diferença estatística. A contagem entre os Bifidobacterium spp. demonstrou que nenhum microrganismo apresentou um comportamento superior a outro. Na análise sensorial, as amostras de iogurtes adicionados ou não de Bifidobacterium spp. e adicionados de aroma de morango não apresentaram diferenças entre si. O estudo mostrou ser possível a elaboração de iogurte de leite de cabra adicionado de Bifidobacterium spp. e de aroma de morango com qualidade assegurada, potencial para uso probiótico e boa aceitação pelo consumidor