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Pasteurization

Pasteurization is a process of heating a liquid or food product to a specific temperature for a set duration, with the goal of killing harmful microorganisms while preserving the product's quality and nutritional content.
This technique, named after the renowned scientist Louis Pasteur, is widely used in the dairy, beverage, and food processing industries to enhance food safety and extend shelf life.
Pasteurization can be optimized through the use of advanced AI-driven tools, such as PubCompare.ai, which allow researchers to easily identify the best pasteurization protocols and products from the scientific literature, preprints, and patent databases.
By leveraging these intelligent tools, researchers can enhance the reproducibility and accuracy of their pasteurization research, leading to improved food quality and safety for consumers.
Experieence the power of AI-assisted pasteurization optimization with PubCompare.ai.

Most cited protocols related to «Pasteurization»

Monitoring and Event Sampling of Microbial Water Quality

Water samples were taken from LKAS2 between June 2004 and December 2006 with fortnightly sampling in summer (May to September) and monthly sampling during the rest of the year (Monitoring, n = 42). Additionally, two Events during high discharge conditions after heavy precipitation were sampled in August 2005 (Event 05; 17 days period; n = 24) and in August 2006 (Event 06; 18 days period; n = 27) with a higher time resolution (intervals between 1 h and 48 h). Sampling for the Monitoring was continued independently during the Event sampling.
Water samples were collected in clean and autoclaved Nalgene (Nalge Europe Ltd., Hereford, UK) sampling bottles (volume 4.2 l), stored in dark cooling boxes at 4 °C during transport and processed within 6 h after collection. For molecular biological analysis a known volume (usually 4.2 l) of spring water was filtered through polycarbonate membrane filters (Isopore™, 45 mm diameter, 0.2 μm pore size, Millipore Corp., Bedford, USA). Immediately after filtration, filters were frozen and stored at −80 °C until nucleic acid extraction. Nucleic acid extraction was performed as described by Griffiths et al. (2000) (link), with a DNA precipitation using isopropanol instead of the polyethylene glycol. Recovered DNA was redissolved in 50 μl of sterile bi-distilled water and stored at −80 °C until further analysis. All extracted sample DNAs were checked for amplifiable bacterial DNA and PCR inhibition by applying a general 16S rRNA gene PCR assay (Winter et al., 2007 (link)). Occasionally during Monitoring replicate samples (2 or 3 times 4.2 litres) were taken and processed separately (n =9). The sample replicates yielded very reproducible quantitative microbial source tracking results (e.g. the median coefficient of variation of BacR ME was 7%). The DNA from four samples (one each from May, April and September 2005 and one from January 2006) apparently was lost during PCR extraction and the respective sampling dates were excluded from all analysis. Enumeration of E. coli, enterococci, presumptive Clostridium perfringens and heterotrophic plate count at 22°C was performed as described in the respective ISO standard methods (ISO, 1999 , 2000a , 2000b , 2002 ). Numbers of aerobic sporeforming bacteria were determined by pasteurisation of the water sample at 60°C for 15 min, membrane filtration and incubation on yeast extract agar at 22°C for 7 days.

Reischer G.H., Haider J.M., Sommer R., Stadler H., Keiblinger K.M., Hornek R., Zerobin W., Mach R.L, & Farnleitner A.H. (2008). Quantitative microbial faecal source tracking with sampling guided by hydrological catchment dynamics. Environmental Microbiology, 10(10), 2598-2608.

Publication 2008

Agar Bacteria, Aerobic Biological Assay Biopharmaceuticals Clostridium perfringens DNA, A-Form DNA, Bacterial DNA Replication Enterococcus Escherichia coli Filtration Freezing Genes Heterotrophy Isopropyl Alcohol Nucleic Acids Pasteurization Patient Discharge polycarbonate Polyethylene Glycols Psychological Inhibition RNA, Ribosomal, 16S Saccharomyces cerevisiae Sterility, Reproductive Tissue, Membrane

NOVA Food Classification and Cohort Dietary Intake

The NOVA classification considers the extent and purpose of processing of the food item and includes four groups – (1) unprocessed or minimally processed food, (2) processed culinary ingredients, (3) processed foods and (4) ultra-processed foods. The first three NOVA groups include food products that have undergone processing methods like grinding, roasting, pasteurisation, freezing, vacuum packaging or non-alcoholic fermentation (minimally processed foods), centrifuging, refining or extracting (processed culinary ingredients) or preservation methods such as canning and bottling (processed foods)^{(1 (link))}. The category of ultra-processed foods includes food items that normally undergo more intensive industrial processing like hydrolysis, or hydrogenation, extrusion, moulding and pre-frying.
A four-stage process was undertaken to identify the ultra-processed foods from both the adult and the youth FFQs. First, all food items in the FFQs across different waves of data collection were complied. Food items that were nearly identical between FFQs but were presented with minor differences were captured as separate items (e.g., ‘Cold breakfast cereal (1 bowl)’ and ‘Cold breakfast cereal (1 serving)’). This was done to make sure that no food item was overlooked. FFQs from every 4 years of the NHS-I (1986–2010), the NHS-II (1991–2015), the HPFS (1986–2014), from 1996, 1998, 2001 for GUTS-I and from 2004, 2006, 2008, 2011 for GUTS-II were used.
Second, three researchers working independently assigned foods in the adult (N.K, S.R, E.M) and the youth (N.K, M.D, E.M) cohorts to one of the four NOVA groups based on their grade of processing – unprocessed/minimally processed foods (G1), processed culinary ingredients (G2), processed foods (G3) and ultra-processed foods (G4). Food assignment was guided by the definition, examples and supplementary material published by the proponents of the NOVA classification^{(1 (link))}. Categorisation was an iterative process requiring the review of the original FFQs used at each wave of data collection to contextualise food items within the larger food lists. Food preparations made from multiple ingredients or different food items that were presented jointly in the FFQ were not disaggregated into their different components. Additionally, the nutrient profile of food items, their actual amounts consumed by the study participants or participant demographics were not considered at any point in the categorisation process. Instead, the original food item as it was listed in the FFQ was categorised in its entirety.
At the third stage, categorisation between researchers was triangulated. Food items for which there was consensus in the categorisation among all researchers were assigned to their NOVA group. A food item was flagged for further scrutiny and shortlisted in case a researcher was unable to assign it to a NOVA group or in cases of disagreement in categorisation by any two researchers.
At stage four, an expert panel comprising of three senior nutrition epidemiologists (F.F.Z; T.F; Q.S) with substantial experience working with the dietary intake in these cohorts, was convened to review and discuss the categorisation of the short-listed products. All discussions were additionally informed by the following resources:

Consultations with the research dietitians. The team of research dietitians, led by L.S, was responsible for overseeing the collection of dietary data and for ascertaining the nutrient composition of food items across all Harvard cohorts. They shared their insights obtained from gathering supplementary data, tracking new and reformulated products available in the supermarket, and conducting multiple pilot studies with cohort participants.

Cohort-specific documents. These resources provided more insight into the extent of processing of certain FFQ food items by highlighting information on the specific ingredients used in recipes and food preparations, the proportion by weight of individual ingredients to the final recipe or a more detailed description of food items (whether the food was canned or salted or boiled, the brand name of certain packaged foods, etc.).

Supermarket scans. The ingredient lists of the first five brands of specific products that were displayed on the Walmart website in 2019 and 2020 were scrutinised. They served as a proxy for establishing the level of processing for a small proportion of food items for which limited information was available from the resources listed above.

The process of categorisation of food items at this stage was also iterative and at the end of stage four, all products were categorised into one of the four NOVA groups. The compilation and categorisation of food items from both the adult and the youth cohorts was done in Microsoft Excel (Microsoft 365, academic license).

Khandpur N., Rossato S., Drouin-Chartier J.P., Du M., Steele E.M., Sampson L., Monteiro C., Zhang F.F., Willett W., Fung T.T, & Sun Q. (2021). Categorising ultra-processed foods in large-scale cohort studies: evidence from the Nurses’ Health Studies, the Health Professionals Follow-up Study, and the Growing Up Today Study. Journal of Nutritional Science, 10, e77.

Publication 2021

Adult Alcoholics Biologic Preservation Cereals Cold Temperature Diet Dietitian Epidemiologists Fermentation Food Food, Processed Gastrointestinal Tract Hydrogenation Hydrolysis Nutrients Pasteurization Radionuclide Imaging Vacuum Youth

Estimating Live Microbial Levels in Food Codes

The estimated quantities of live microbes (per gram) for 9388 food codes contained in 48 subgroups in the NHANES database were determined by 4 experts in the field (MLM, MES, RH , and CH). Because of the expected variation in the numbers of living microorganisms in each food type, the foods were assigned to categories with ranges defined as low (Lo; <10⁴ CFU/g), medium (Med; 10⁴–10⁷ CFU/g), or high (Hi; >10⁷ CFU/g) levels of live microbes. These levels of Lo, Med, and Hi were chosen to reflect the approximate numbers of viable microbes expected to be present in pasteurized foods (<10 ⁴ CFU/g), fresh fruits and vegetables eaten unpeeled (10⁴–10⁷ CFU/g), and unpasteurized fermented foods and probiotic supplements (>10⁷ CFU/g).
As a first step, food subgroups estimated to contain only food codes having <10⁴ CFU/g were identified by 3 individuals (MLM, MES, and RH) ( Supplemental Table 1). For these assessments, experts relied on reported values in the primary literature (10–15 (link), 17 (link), 18 (link), 23–32 (link)), authoritative reviews (33 ), or inferred values based on known effects of food processing (for example, pasteurization) on microbial viability. Next, the remaining 6317 food codes contained in 25 food subgroups were assessed by the experts working in teams of 2. Team 1 (RH and CH) and Team 2 (MLM and MES) assessed 2856 and 3461 food codes, respectively, comprising subgroups indicated in Supplemental Table 1. Assignments were based on professional knowledge of the field and by reviewing primary publications that assessed the indicated foods. Disagreement between the 2 experts occurred for ∼150 food codes (Team 1) and ∼250 food codes (Team 2). For Team 1, most disagreements were for cheese and formulated foods such as salads, sandwiches, or dips containing cheese or cultured dairy foods. These were resolved by consulting the literature (34 ), the relative expected weight of the live microbe–containing food compared with the other ingredients (for example, bread), and the use of preservation methods (for example, pasteurization). For example, a sandwich containing processed American cheese was categorized in the Lo category. Sandwiches containing cheese and other major components (for example, steak) were similarly categorized in the Lo category. Cheddar cheese and general cheese sandwiches were labeled as Med, to take into account the weight of the bread and other potential condiments (for example, mayonnaise). For Team 2, 24 of these food codes were described as “pickled” fruits or vegetables. Reviewers subsequently reconciled these differences by consultation within and between the teams (MLM, MES, RH, and CH) and by external consultation with Fred Breidt, USDA Agricultural Research Service Microbiologist, Food Science and Market Quality and Handling Research Unit, Raleigh, NC.
Although “pickled” fruits or vegetables could be acidified and not fermented, the food descriptions were inadequate to distinguish between these 2 possibilities. The experts agreed to assume these were fermented or partially fermented in the case of refrigerated and non-heat-treated products and assigned all such pickled foods to Med. For the last step, intakes of Med and Hi categories were determined by linking microbe definitions to food codes. A fourth category was also developed, MedHi, consisting of an aggregate of consumers of foods from Med, Hi, or both Med and Hi categories.

Marco M.L., Hutkins R., Hill C., Fulgoni VL I.I.I., Cifelli C.J., Gahche J., Slavin J.L., Merenstein D., Tancredi D.J, & Sanders M.E. (2022). A Classification System for Defining and Estimating Dietary Intake of Live Microbes in US Adults and Children. The Journal of Nutrition, 152(7), 1729-1736.

Publication 2022

3,5-diisopropylsalicylic acid Biologic Preservation Bread Cheese Condiments Eating Fermented Foods Food Food, Formulated Fruit Microbial Viability Pasteurization Probiotics Salads Vegetables

Characterization of Maqui-Citrus Beverage Polyphenols

Fresh, dry organic maqui berry powder was provided by Maqui New Life S.A. (Santiago de Chile, Chile). Cítricos de Murcia S.L. (Ceutí, Spain) and AMC Grupo Alimentación Fresco y Zumos S.A. (Espinardo, Spain) provided the citrus juices. Sucrose was provided by AB Azucarera Iberia S.L. (Madrid, Spain), Stevia by AgriStevia S.L. (Murcia, Spain), and Sucralose by Zukan (Murcia, Spain).
For preparing the maqui-citrus beverages, maqui powder was mixed with citrus juices to obtain the base beverage. Then, the three selected sweeteners were added, in different concentrations, in order to obtain an acceptable taste and to obtain the different beverages analyzed in the present work. The beverages underwent a pasteurization treatment through the application of 85 °C for 58 s. Afterwards, the mixtures were bottled and stored at 5 °C until being consumed by the volunteers.
As a preliminary task, the beverages developed were characterized on their polyphenolic composition. With this objective, the juices were centrifuged at 10,500 rpm, for 5 min (Sigma 1–13, B. Braun Biotech International, Osterode, Germany). The supernatants were filtered through a 0.45 µm PVDF filter (Millex HV13, Millipore, Bedford, MA, USA) and analyzed by RP-HPLC-DAD. The identification and quantification of anthocyanins was performed by applying the method previously reported [16 (link),31 (link)]. Briefly, a chromatographic analysis of samples (10 µL), for the identification and quantification of anthocyanins was carried out on a Luna 5µm C18(2)100 Å column (250 × 4.6 mm), using Security Guard Cartridges PFD 4 × 3.0 mm, both supplied by Phenomenex (Torrance, CA, USA). The solvents used for the chromatographic separation were Milli-Q water/formic acid (95.0:5.0, v/v) (solvent A) and methanol (solvent B), in a linear gradient (time, %B) (0, 15%); (20, 30%); (30, 40%); (35, 60%); (40, 90%); (44, 90%); (45, 15%), and (50, 15%), using an Agilent Technologies 1220 Infinity Liquid Chromatograph, equipped with an autoinjector (G1313, Agilent Technologies) and a Diode Array Detector (1260, Agilent Technologies, Santa Clara, CA, USA). Chromatograms were recorded and processed on an Agilent ChemStation (Santa Clara, CA, USA) for LC 3D systems. The flow rate was 0.9 mL/min. The quantification of anthocyanins was done on UV chromatograms recorded at 520 nm as cyanidin-3-O-glucoside at 520 nm and expressed as mg per 100 mL of juice.

Agulló V., Villaño D., García-Viguera C, & Domínguez-Perles R. (2020). Anthocyanin Metabolites in Human Urine after the Intake of New Functional Beverages. Molecules, 25(2), 371.

Publication 2020

Anthocyanins Berries Beverages Chromatography Citrus cyanidin 3-O-glucoside formic acid High-Performance Liquid Chromatographies Liquid Chromatography Methanol Pasteurization polyvinylidene fluoride Powder Secure resin cement Solvents Stevia sucralose Sucrose Sweetening Agents Taste Voluntary Workers

Pasta Filata Cheese Production Protocol

The production of pasta filata cheese involves normalization and pasteurization of milk or a mixture of cow’s and sheep’s milk, and production of the curd and its acidification, followed texturization of the acidified curd, which involves heating, kneading, and stretching by soaking the curd in hot water. The milk or milk mixture was pasteurized (75 °C, 15 s) in MILKY FJ15 (Franz Janschitz GmbH, Althofen, Austria). After cooling to 40 °C, thermophilic starter culture Lyofast SAB 440B of Sacco (Cadorago, Italy) was added to the milk in an amount of 8 UC (dosage units) to 20 L of milk. The starter culture consisted of: Streptococcus thermophilus, Lactobacillus acidophilus and Bifidobacterium animalis subsp. lactis. At pH 6.5, Beaugel 5 rennet (Ets COQUARD, Villefranche Sur Saône, France) with a chymosin activity above 150 mg/L at a strength of 1/3000 was added in the amount of 14 mL per 20 L of milk. This amount was used to form the curd after 30 min. The curd was cut into 1 × 1 cm cubes and set aside for 20 min until pH 5.9 was reached. The cheese curd was drained at 23 °C for 2 h to pH 5.2. Plasticization (kneading and stretching) was carried out in water with salt (77–80 °C). The formed cheese was cooled in water with salt (16%, 12 °C). The cheese was packed with a brine and stored at 3 °C in the form of spheres with a weight of 220 g. The range of changes of cheese quality features of the model were rated after 2 days of manufacturing at 3 ± 0.5 °C storage.
Test specimens were taken from different production batches (n = 5). Approximately 3.8 kg cheese (17 balls) was obtained from 20 L of milk. Each ball of cheese was 220 g. The cheese was prepared in pilot plant scale using pilot industrial equipment, and each batch was analyzed twice.

Biegalski J., Cais-Sokolińska D., Tomaszewska-Gras J, & Baranowska H.M. (2021). The Effect of Freezing Sheep’s Milk on the Meltability, Texture, Melting and Fat Crystallization Profiles of Fresh Pasta Filata Cheese. Animals : an Open Access Journal from MDPI, 11(9), 2740.

Publication 2021

Bifidobacterium animalis brine Cheese Chymosin Cuboid Bone Domestic Sheep Lactobacillus acidophilus Milk, Cow's Pastes Pasteurization Plants rennet Sodium Chloride Streptococcus thermophilus

Most recents protocols related to «Pasteurization»

Pooled and Individual Milk Samples Processing

Frozen DM samples from 21 donors were provided by the regional HMB (Lactarium Régional de Lille, CHU Lille). Written informed consent of each donor mothers for the use of their breast milk for research studies was obtain by our HMB and validated by the Lille Hospital [authorization number DOC/LAC/009–2012, Lactarium Régional de Lille, Hôpital Jeanne de Flandre, supervisor: Dr. Véronique Pierrat (MD, PhD)]. To study the effects of HoP and HP treatments, two series of milk samples were used. In the first cohort, we pooled milk samples from 11 women. As previously described (7 (link)), after thawing of individual milk samples, 8 different batches of DM were created by mixing various volumes (from 10 to 30 mL) of all DM samples, primarily in order to homogenize DM composition between batches. Then, three aliquots of DM were prepared for each batch: one fraction was stored at −80°C without any other treatment (raw milk); one fraction was subjected to HoP (HoP-DM) according to the standard pasteurization protocol (62.5°C for 30 min) in our HMB and the last fraction was subjected to HP processing as previously described (HP-DM) (7 (link), 10 (link)). The set of HP parameters was: 4 cycles of 5 min of a pressure of 350 MPa and at a temperature of 38°C. The second cohort of DM samples used in this study was individual DM samples from 10 donors. Each individual sample was treated similarly by HoP and HP processing. All milk fractions were kept at −80°C until analysis.

Tran L.C., Marousez L., De Lamballerie M., McCulloch S., Hermann E., Gottrand F., Ley D, & Lesage J. (2023). The metabolome of human milk is altered differentially by Holder pasteurization and high hydrostatic pressure processing. Frontiers in Nutrition, 10, 1107054.

Publication 2023

Donors Freezing Milk Milk, Human Mothers Pasteurization Pressure Tissue Donors Woman

Aseptic Filling of Heated Syrup

After conventional pasteurization and OH, aseptic filling was carried out into sterile glass bottles (250 mL) within a vertical laminar airflow cabinet (Steril Gemini, Apeldoorn, The Netherlands). Hot filling was carried out after heating the syrup to a temperature of 88°C using the tubular heat exchanger, into the same glass bottles, with and without external cooling (cold water bath at 10°C for 30 min).

Sevenich R., Gratz M., Hradecka B., Fauster T., Teufl T., Schottroff F., Chytilova L.S., Hurkova K., Tomaniova M., Hajslova J., Rauh C, & Jaeger H. (2023). Differentiation of sea buckthorn syrups processed by high pressure, pulsed electric fields, ohmic heating, and thermal pasteurization based on quality evaluation and chemical fingerprinting. Frontiers in Nutrition, 10, 912824.

Publication 2023

Asepsis Bath Cold Temperature Pasteurization Sterility, Reproductive

Cultivation of Akkermansia muciniphila under Anaerobic Conditions

Akk strain (ATCC BAA-835) was grown in brain-heart-infusion (BHI) media supplemented with 0.4% porcine mucin (Sigma-Aldrich, St. Louis, MO, USA) and 0.05% cysteine (Sigma-Aldrich, St. Louis, MO, USA) under strict anaerobic conditions (99%N₂ at 37 °C). The concentration of bacteria was estimated by measuring the absorbance at the wavelength of 600 nm as previously described [20 (link)]. In one group of the experiment, Akk was inactivated by pasteurization at 70 °C for 30 min.

Xu Y., Duan J., Wang D., Liu J., Chen X., Qin X.Y, & Yu W. (2023). Akkermansia muciniphila Alleviates Persistent Inflammation, Immunosuppression, and Catabolism Syndrome in Mice. Metabolites, 13(2), 194.

Publication 2023

Bacteria Brain Cysteine Heart MUC4 protein, human Pasteurization Pigs Strains

Milk Vendor Training Intervention in Nairobi

The MoreMilk survey was conducted in 3 periurban subcounties of Nairobi beginning in October 2019: Dagoretti North, Dagoretti South, and Kasarani. The survey was the baseline assessment for a randomized-controlled trial (RCT) that was stopped due to COVID-19 (clinicaltrials.gov registration: NCT04109521). The objective of the trial was to assess the impact of training, certification, and marketing intervention for milk vendors in the informal sector on milk safety and nutrition outcomes in children in urban and periurban areas of Kenya. The study participants were dairy vendors and their client households. The inclusion criteria for dairy vendors included selling unpacked liquid milk (that is, milk that had not gone through an industrial pasteurization and packaging process, commonly referred to as “milk from the informal market”) ≥5 d/wk to individual customer, having the intention to remain in the business for ≥12 mo; and operating a milkbar (that is, exclusively licensed to sell dairy products and eggs) or a shop/kiosk (that is, licensed to sell food and nonfood products), or being a street vendor (that is, not selling in a fixed building structure but selling from a fixed location along the street). Middlemen (individuals that purchase and transport milk from farms to distribute to businesses) and vendors catering exclusively to other commercial establishments were excluded, as were mobile street vendors (that is, selling from a mobile premise like a cart, motorbike, etc.) and vendors operating a milk dispenser (also called a milk-ATM) or selling exclusively at farm gate. These criteria were designed to ensure participants were representative of the type of vendors that sell most milk in periurban Nairobi and, considering the high turnaround of dairy businesses in the city, maximize the likelihood that participants recruited in the study will remain in business for the duration of the study. The household inclusion criteria were purchasing unpacked milk, obtaining ≥50% of the weekly milk supply from a vendor recruited in the study, and having ≥1 child between 12 and 48 mo of age at the time of recruitment. This age range was chosen to avoid promoting the consumption of cow milk in children under 1 y of age and to ensure that children would be <5 y of age at follow-up.

Alonso S., Angel M.D., Muunda E., Kilonzi E., Palloni G., Grace D, & Leroy J.L. (2023). Consumer Demand for Milk and the Informal Dairy Sector Amidst COVID-19 in Nairobi, Kenya. Current Developments in Nutrition, 7(4), 100058.

Publication 2023

CART protein, human Child Child Nutritional Physiological Phenomena COVID 19 Dairy Products Eggs Food Households Milk, Cow's Pasteurization Safety SELL protein, human

Ultra-High Pressure Homogenization for Extended Beverage Shelf-Life

Two different pasteurizing UHPH treatments were performed by using an ultra-high pressure homogenizer, at a flow rate of 120 L/h (Model: DRG No. FPG11300:400 Hygienic Homogenizer, Stansted Fluid Power Ltd., Harlow, UK) at two different pressures, 200 and 300 MPa, and the same inlet temperature (Ti) of 40 °C. The temperature of UHPH-treated beverages increased by 24.2 °C between pressures ranging from 200 to 300 MPa [8 (link)]. Temperature after the UHPH valve corresponded to 92.1 ± 1.7 and 116.3 ± 4.3 °C for the 200 and 300 MPa treatments, respectively, and the residence time of the product at these temperatures was estimated to be <0.7 s. The outlet temperature of products corresponded to 15.3 ± 1.1 and 17.1 ± 1.6 °C in 200 and 300 MPa treatments, respectively.
Conventional treatment of Homogenization-Pasteurization (H-P) was also applied to the RP using an indirect heat system composed of a double-stage homogenizer positioned upstream (Model X68, Soavi B. and Figli, S.P.A., Parma, Italy) and a multitube tubular heat exchanger at a flow rate of 1000 L/h (laminar flow) (6500/010, GEA Finnah GmbH, Ahaus, Germany). Beverages were homogenized at pressures of 18 MPa (first stage-valve) and 4 MPa (second stage-valve) at 65 °C, and subsequently pasteurized at 80 °C for a holding time of 15 s. Samples (RP, H-P, 200 MPa, and 300 MPa) were collected in sterile glass bottles of 1 L of capacity with twist-off caps (Apiglass Envases y Material Apícola, S.L., Barcelona, Spain) inside a laminar flow cabin (Mini-V cabin, Telstar Technologies, S.L., Terrassa, Spain) and were stored at refrigeration temperature (4 °C) until their analyses
Microbiological shelf-life of stored beverages corresponded to 3, 5, 30 and 57 days for the RP, H-P and UHPH processed beverages at 200 and 300 MPa, respectively, according to Codina-Torrella et al. [9 (link)].

Codina-Torrella I., Gallardo-Chacón J.J., Juan B., Guamis B, & Trujillo A.J. (2023). Effect of Ultra-High Pressure Homogenization (UHPH) and Conventional Thermal Pasteurization on the Volatile Composition of Tiger Nut Beverage. Foods, 12(4), 683.

Publication 2023

Beverages Pasteurization Sterility, Reproductive

Top products related to «Pasteurization»

Circulating water bath by Julabo

Sourced in Germany

The Circulating Water Bath is a laboratory equipment designed to maintain a constant temperature in a fluid medium. It circulates the water within the bath to ensure uniform temperature distribution. The core function of this product is to provide a controlled temperature environment for various applications in the laboratory setting.

Centrifuge 5702r by Eppendorf

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The Centrifuge 5702R is a compact, versatile centrifuge designed for a wide range of laboratory applications. It features a refrigerated rotor with a maximum speed of 4,500 rpm and a maximum RCF of 3,234 xg. The centrifuge can accommodate a variety of sample tube sizes and formats, making it suitable for various centrifugation tasks.

Gaspak 100 system by BD

The GasPak 100 system is a laboratory equipment designed for gas generation and anaerobic incubation. It provides a controlled anaerobic environment for microbial cultivation and other anaerobic applications.

Maldi tof ms by Bruker

Sourced in Germany, United States, France, United Kingdom, Japan, Italy, Switzerland, Canada, Poland

MALDI-TOF MS is a type of mass spectrometry instrument that uses Matrix-Assisted Laser Desorption/Ionization (MALDI) as the ionization technique and Time-of-Flight (TOF) as the mass analyzer. It is designed to analyze and identify a wide range of compounds, including proteins, peptides, lipids, and small molecules.

Lm egd e atcc baa 679 strain by American Type Culture Collection

Lm EGD-e (ATCC BAA-679) is a well-characterized strain of Listeria monocytogenes. This strain is frequently used in research and has a known genome sequence.

Trizol reagent by Thermo Fisher Scientific

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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.

Columbia blood agar by Thermo Fisher Scientific

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Columbia blood agar is a general-purpose microbiological growth medium used for the isolation and identification of a wide range of microorganisms, including aerobic and anaerobic bacteria. It contains sheep blood, which enables the detection of hemolytic reactions.

Brain heart infusion media by BD

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Brain heart infusion media is a nutrient-rich growth medium used for the cultivation of a wide range of microorganisms, including bacteria, fungi, and fastidious organisms. It provides essential nutrients and growth factors required for the optimal growth and isolation of these microbes in a laboratory setting.

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MRS agar is a growth medium used for the isolation and cultivation of lactic acid bacteria, particularly Lactobacillus species. It provides essential nutrients and growth factors required by these microorganisms. The formulation is based on de Man, Rogosa, and Sharpe's (MRS) original recipe.

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Prism 6 is a data analysis and graphing software developed by GraphPad. It provides tools for curve fitting, statistical analysis, and data visualization.

More about "Pasteurization"

Pasteurization is a critical food processing technique that leverages controlled heat application to eliminate harmful microorganisms while preserving the quality and nutritional content of various liquid and solid food products.
This process, named after the renowned scientist Louis Pasteur, is widely employed in the dairy, beverage, and broader food industries to enhance food safety and extend product shelf life.
Optimizing pasteurization parameters can be facilitated through the use of advanced AI-driven tools like PubCompare.ai.
These intelligent platforms enable researchers to easily identify the most effective pasteurization protocols and products by analyzing scientific literature, preprints, and patent databases.
By leveraging PubCompare.ai's capabilities, researchers can enhance the reproducibility and accuracy of their pasteurization research, leading to improved food quality and safety for consumers.
Pasteurization techniques can be further enhanced through the use of specialized equipment and analytical methods.
Circulating water baths provide precise temperature control for experimental pasteurization, while centrifuges like the Centrifuge 5702R enable efficient sample separation and preparation.
Microbial analysis techniques, such as the GasPak 100 system and MALDI-TOF MS, can be employed to verify the efficacy of pasteurization in eliminating target pathogens like the Lm EGD-e (ATCC BAA-679) strain.
Additionally, tools like TRIzol reagent and Columbia blood agar can be utilized for nucleic acid extraction and microbial culturing, respectively, to support pasteurization research.
By combining the power of AI-driven optimization, specialized equipment, and advanced analytical methods, researchers can drive continuous improvements in pasteurization processes, ensuring the delivery of safe, high-quality, and nutritious food products to consumers.
Experieence the transformative impact of AI-assisted pasteurization optimization with PubCompare.ai.