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Canola Oil

Canola oil is a type of vegetable oil derived from the seeds of the canola plant, a cultivar of the rapeseed plant.
It is known for its low erucic acid content and is widely used in cooking, baking, and food processing.
Canola oil is a popular choice due to its mild flavor, high smoke point, and favorable nutritional profile, including a balance of monounsaturated and polyunsaturated fatty acids.
Researchers studying canola oil may utilize PubCompare.ai's AI-driven platform to optimize their research protocols, enhance reproducibility and accuracy, and easily locate relevant protocols from literature, pre-prints, and patents.
The platform's AI-based comparisons can help identify the best protocols and products for canola oil research, streamlining the research process.

Most cited protocols related to «Canola Oil»

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Publication 2010
alpha-Linolenic Acid BLOOD Canola Oil Diet Docosahexaenoic Acids Eating Eggs Eicosapentaenoic Acid Fishes Food Juglans Linseed oil Nutrients Oil, Cod Liver Plasma Polyunsaturated Fatty Acids Seafood Shellfish
The fatty acid composition of TG in canola oil was analyzed by GC. Fresh canola oil (5 mg) was mixed with an internal standard (50 µg of heptadecanoic acid) in a screw cap test tube. Then, 2 mL of methanolic hydrogen chloride (5%, v/v) with 0.2 mL of benzene and 2 µL of BHT methanolic solution (0.01%, wt%) were added. The sample was methyl esterified at 100 °C under a nitrogen atmosphere. After 1 h, 5 mL of aqueous potassium carbonate (6%, wt%) and 1 mL of hexane were added. The mixture was partitioned by centrifugation (1000 × g for 5 min at 4 °C) into two layers. The upper hexane layer was collected, and remaining aqueous layer was re-extracted with 1 mL of hexane. The combined hexane layer was evaporated under a nitrogen gas stream, and the residue was dissolved in 1 mL of hexane. A 2 µL aliquot was analyzed with GC-4000 (GL Sciences Inc., Tokyo, Japan) equipped with a DB-225 column (length, 30 m; internal diameter, 0.32 mm; film thickness, 0.25 µm; Agilent Technologies, Santa Clara, CA, USA). Helium gas was used as the mobile phase. The injector and detector temperatures were set at 220 and 250 °C respectively. The gradient profile was as follows: 140–180 °C (8 °C/min linear), 180–220 °C (3 °C/min linear), and 220 °C (for 25 min).
TG molecular species were analyzed by Q1 mass- and product ion-scan mode using LC–MS/MS. A Prominence liquid chromatography system (Shimadzu, Kyoto, Japan) was equipped with a 4000 QTRAP mass spectrometer (SCIEX, Tokyo, Japan). Fresh canola oil was 10,000-fold diluted with methanol/2-propanol (100:1, v/v) and analyzed using an ODS column (5C18-MS-II, 5 µm, 4.6 × 250 mm, nacalai tesque, Kyoto, Japan) with a binary gradient consisting of solvent A (methanol containing 0.1 mM sodium acetate) and solvent B (2-propanol containing 0.1 mM sodium acetate). The gradient profile was as follows: 0–20 min, 50–70% B linear. The flow rate was 1.0 mL/min, and the column temperature was 40 °C. Elution was split at the post-column and one of the split eluents was sent to the MS/MS system at 0.2 mL/min. The MS parameters are shown in SI 5-Method 1 and 2. A 10 µL sample was injected into the LC–MS/MS system.
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Publication 2018
1-Propanol Atmosphere Benzene Canola Oil Centrifugation Chlorides Deuterium Fatty Acids Helium Liquid Chromatography margaric acid Methanol n-hexane Nitrogen potassium carbonate Radionuclide Imaging Sodium Acetate Solvents Tandem Mass Spectrometry
We provide here a description of the system and the general approach used in estimating the four evaluated compartments. A previous description of the EchoMRI-AH QMR system at this level is lacking and leaves an important gap when interpreting the studies that follow. The earlier Echo Medical Systems’ QMR instruments and DXA were developed and validated against classic carcass chemical analysis for use in small animals (7 (link),8 (link)). The reported precision (CV) for fat measurement in mice was 0.34–0.71% for QMR compared with 3.06–12.60% for DXA (8 (link)).
The QMR system has a patient capacity of up to 250 kg. The resistive magnet bore size is 29 × 29 inches and external dimensions are L × W × H is 144 × 57 × 60 inches. The field of view is 27.5 × 27.5 × 63 inches (X × Y × Z axis) and the system is self-shielded. Static magnetic field homogeneity in the QMR system over the whole body is about 0.3% as measured by a non-NMR method. Measurement of an ECHO WIDTH for samples weighing ~100 kg (i.e., large adult human) demonstrates a static magnetic field homogeneity of ~0.2%. The QMR operating system is based on Windows XP Professional Edition. Measuring time is typically <3 min, with three or four repeat measurements taking about 10 min; there is a recommended daily system test in the most recent software. The system output includes fat mass, lean tissue mass, free water mass, and total water mass in units of kilograms.
The QMR system produces an optimized sequence of radio pulses consisting of several segments separated by pauses of varying duration that are designed to capture relevant relaxation time scales. The captured signals, as shown in the human example presented in Figure 1a, reflect the combined signals of TBF, lean, and free water. Examples of separate measurements of canola oil, lean pork, and water phantoms normalized to unit mass are shown in Figure 1b.
The key principal of the QMR method is that each scan produces a record of NMR responses (echoes) to a radiofrequency pulse sequence. The sequence is composed of several periodic Carr-Purcell-Meiboom-Gill parts separated by pauses of different duration. The lengths of the periodic parts and the pause durations are designed to capture all relevant characteristic (relaxation) time scales of the NMR responses (transverse, “T2”, and longitudinal, “T1”, relaxation) typical for fat, lean, and free water. The whole-body signal is a linear combination of fat, lean, and free water contributions, and the differences between the relaxation rates of the three basic substances make it possible to use linear regression analysis formulas calibrated to fat (canola oil), lean (chicken breast, small animals; lean pork, larger animals), and free water (tap water) phantoms. The algorithm for optimizing these regression formulas is a variant of multivariate calibration, which is typical of chemometric analyses (9 ), employing partial least squares optimization combined with principal component analysis for high-dimensional regressions.
Total water is calculated from the same records but in a different way as the contributions of protons associated with proteins and other “solid” materials are negligible at the time scales employed by the QMR system. The “lean” signal therefore comes mainly from water bound within the lean tissues. There is also a substantial contribution from protons in fat molecules. The difference between an estimate of the total amount of protons participating in the record and an estimate of fat found by regression analysis yields an estimate of the amount of total water included in lean together with free water. Therefore, fat mass and TBW are not measured independently of each other.
In sum, the main QMR pulse sequence is used to derive fat, lean mass, and free water using multiple linear regression prediction formulas calibrated against canola oil, lean animal tissues, and tap water, respectively. QMR body mass (BM) is then estimated as the sum of fat mass, lean mass, and free water mass; bone mineral, with high calcium and phosphorus content and gastrointestinal solids are not detected using the QMR system. QMR BM thus reflects the sum of three measured compartments, fat, lean, and free water mass.
Publication 2010
Adult Animals Bones Breast Calcium Canola Oil Chickens Diet, Formula ECHO protocol Epistropheus Gills Homo sapiens Human Body Magnetic Fields Minerals Mus Patients Phosphorus Pork Proteins Protons Pulse Rate Pulses Radionuclide Imaging Tissues
Body composition was objectively quantified by a single-blinded and experienced operator [77 (link)]. Bodyweight, free water (systemic extracellular water, ECW), total water, body fat, and lean mass were recorded longitudinally. Mice were measured every tenth day between 50–100 days using quantitative magnetic resonance (QMR) technology with an EchoMRITM 4-in-1 Analyzer (Echo Medical Systems, Houston, TX, USA). The machine was calibrated daily per standard operating procedure using the provided canola oil (54.3 g) phantom. Briefly, mice were weighed (Scout Pro SP401, Ohaus Corporation, Pine Brook, NJ, USA) and loaded into a tube restrainer specific to the system. Mice were fully conscious and minimally restrained throughout each 60–90 s recording and were returned to their home enclosure following measurement.
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Publication 2019
Body Composition Body Fat Body Weight Canola Oil Consciousness ECHO protocol Magnetic Resonance Imaging Mus Pinus
A Siemens Acuson S2000 automated breast volume scanning system (ABVS) was used to acquire volumetric ultrasound RF echo data in this study. As shown in figure 1, the system consists of two parts, a Siemens S2000 ultrasound system and the ABVS attachment. The ABVS is composed of a support tower, an arm, and a transducer pod assembly containing a 15cm long, 768-element 1D array ultrasound transducer (14L5BV). The transducer excitation frequency was set to 11MHz. Elevational transducer motion was controlled by a motor inside the pod assembly that sweeps the transducer in the elevational direction within the pod.
The commercial system uses an open-mesh screen that couples the transducer to the breast. In this study, that screen assembly was replaced with a compliant, fluid-filled coupling bag. The liquid in the coupling bag for this study was canola oil. “Wings” were attached to the transducer face (see figure 1) to extend the flat scanning surface in the elevational direction. The wings limit the elevational scanning range (but provide a flat reference surface for eventual elastic modulus reconstructions). A motor in the tower was added to lift or lower counterweights which offset the weight of the arm and transducer pod assembly, thus allowing the arm to move vertically (up or down) and apply or release vertical load on the breast. The S2000 was programmed to control the motion of the counterweights (and therefore the arm) and transducer pod. The maximum range for 3D scanning for a single volume with the modified system was 6cm ×15cm × 18cm (axial × lateral × elevational).
Data were acquired using the AXIUS Direct ultrasound research interface27 to obtain radiofrequency echo data sampled at 40 MHz for each scan line in the 3D volume. Data were stored on the S2000 imaging system and downloaded for offline analysis. The electronic signal to noise ratio (SNR) of the echo signal was estimated by the Thomoson’s multitaper method28 to verify that the SNR exceeded 30dB (well above the lower limit for low displacement estimate variance).29 The echo signal correlation cell size and its spatial sampling (beam spacing) for this imaging system were characterized for the purposes of optimizing motion tracking kernel sizes. The selection of the size of correlation kernel was based on several of our previous publications23 (link)–26 . The size of the motion tracking kernel for guided-search block matching algorithms involves a tradeoff – large kernels can provide unique data matching; small kernels are more computational efficient and minimize decorrelation within the post-deformation match to the tracking kernel. It is also necessary that adjacent spatial samples of the RF echo field are highly correlated so that an accurate estimate of motion at one location is highly correlated with the RF echo data at its adjacent locations and therefore provides a good prediction of motion in its immediate neighborhood (thus allowing a reduction in the search region size)23 (link)–25 (link).
Publication 2017
Breast Canola Oil ECHO protocol Face Radionuclide Imaging Reconstructive Surgical Procedures Transducers Ultrasonics

Most recents protocols related to «Canola Oil»

Not available on PMC !

Example 12

The composite plant-MCT flour of any of Examples 1-11 is modified by including one or more supplemental oils in addition to and/or that replace a portion of the MCT oil, including one or more of avocado oil, Brazil nut oil, canola oil, corn oil, cottonseed oil, flaxseed oil, grape see oil, hemp seed oil, olive oil, palm oil, peanut oil, rice bran oil, safflower oil (e.g., high oleic), sesame oil, soybean oil, walnut oil, hazelnut oil, sunflower oil, or butterfat.

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Patent 2024
Brazil Nuts Canola Oil Corn oil Flour Food Grapes Hazelnuts hempseed oil Juglans Linseed oil MCTS1 protein, human Oil, Cottonseed Oil, Olive Oil, Sunflower Palm Oil Peanut Oil Persea americana Plants Rice Bran Oil Safflower oil Sesame Oil SLC16A11 protein, human Soybean oil
Not available on PMC !

Example 4

A Rancimat stability study was performed using the crude DHA canola oil and reference blend described in Examples 1 and 2, respectively. The method involved testing about 2.5 g of test material using the standard procedures for a Metrohm 743 Rancimat at 90° C.

The table below summarises the results obtained from these oils at 90° C. The experiments were performed in duplicate.

OilTime
DHA Canola oil 7 hrs 29 min 7 hrs 17 min
Reference oil10 hrs 26 min10 hrs 11 min

The DHA canola oil showed consistently poorer stability than the reference oil.

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Patent 2024
Canola Oil DHA-10 Petroleum
LB liquid medium was used to explore the optimal growth, lipase production temperature and pH of the WCO-9 strain, and ρ-nitrophenyl decanoate (C10), ρ-nitrophenyl laurate (C12), ρ-nitrophenyl myristate (C14), ρ-nitrophenyl palmitate (C16) and ρ-nitrophenyl stearate (C18) was chosen as the substrate for the lipase activity assay [34 (link)]. Oil degradation assays were performed on rhodamine B oil plates [35 (link)] using corn oil, soybean oil, peanut oil, canola oil and olive oil mixed with a solution of 4% polyvinyl alcohol (PVA) in a 1:3 volume ratio and emulsified by sonication for 10 min. Then, 25 mL of the emulsion was added to 200 mL of medium and stained with 10% rhodamine B solution. The WCO-9 and A. junii ATCC 17908 strains were activated by plate streaking, and single colonies were incubated in a liquid medium at 30 °C and shaken at 200 r/min for 12 h to prepare a seed solution, which was then inoculated in fresh liquid medium starting with an OD600 of 0.1. When both strains reached an OD600 of 0.7 ± 0.05, the bacterial concentrations of the two strains were adjusted to the same OD600 value. The oil plate was punched, and 10 μL of the two bacterial solutions with the same OD600 value was injected into the well and incubated at 30 °C for 4 days. The plate was observed under UV light, and the size of the transparent circle was measured as the parameter of oil degradation capabilities. The oil degradation activity was tested by GB/T_23535-2009 method with the five oils mentioned above.
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Publication 2023
Bacteria Biological Assay Canola Oil Corn oil Decanoates Emulsions Lipase Myristate Oil, Olive Oils Palmitate Peanut Oil Polyvinyl Alcohol rhodamine B Soybean oil Stearates Strains Ultraviolet Rays
A surplus amount of βC was added to 1 mL of different oils, including gingelly oil-GGO; rice bran oil-RBO; soya bean oil-SBO; Canola oil-CNO; olive oil- OLO; ethyl oleate-EO and Capmul- C.P.Surfactants including Labrafil-LFIL; Gelucire 44/14-GLE; tween 20-T20; span 20-S20 and span 80-S80. Co-surfactants include propylene glycol-PG, Transcutol-P-TP and Acconon—ACN. The samples were then stored in an isothermal shaker for 72 h at 25 ± 02 °C to attain equilibrium. The samples were centrifuged at 6000 rpm (REMI, Maharashtra, India, Ultracentrifuge) for 10 min. The collected supernatant was filtered using a 0.22 μm membrane filter, and the β-crt content was determined at 461 nm by UV-visible spectrophotometer 1700, Shimadzu, Columbia, MD, USA [18 (link)].
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Publication 2023
Canola Oil Capmul ethyl oleate gelucire 44-14 Oil, Olive Propylene Glycol Rice Bran Oil Soybean oil Span 20 Span 80 Surfactants Tissue, Membrane transcutol P Tween 20
The same instant pot (Instant Pot Duo Mini 3 Qt; model number: IPDUOMINI 3 Qt) was used for the stir-frying operations using its in-built sauté function according to the method described by Nugrahedi et al. [17 (link)], with minor modifications. The vegetable-to-oil ratio of 10:1 was used for the stir-frying operations using canola oil (complements brand, Winnipeg, Manitoba). The stir-frying operation was conducted at 250 °C for 5 min. The vegetables were cut into pieces measuring 2 cm × 2 cm in size after the stir-frying, and they were freeze-dried as per the method described in Section 2.3.1 (Figure 1).
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Publication 2023
Canola Oil Complement System Proteins Freezing Vegetable Oils Vegetables

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Canola oil is a refined vegetable oil extracted from the seeds of the canola plant. It is a clear, light-colored oil with a mild flavor. Canola oil is commonly used for cooking, baking, and food preparation purposes.
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More about "Canola Oil"

Canola, also known as rapeseed, is a type of vegetable oil derived from the seeds of the brassica napus plant.
It is a popular cooking oil due to its low erucic acid content, mild flavor, and high smoke point.
Canola oil is a balanced blend of monounsaturated and polyunsaturated fatty acids, making it a healthier choice for cooking, baking, and food processing.
Researchers studying canola oil may utilize various techniques and tools to analyze its properties and composition.
Sodium hydroxide (NaOH) is commonly used for saponification, while the Mastersizer 2000 instrument can be employed for particle size analysis.
Bovine serum albumin (BSA) may serve as a standard for protein quantification, and Milli-Q water is often used to prepare solutions.
In addition to the main canola oil, other related substances like sodium azide, methanol, and hydrochloric acid (HCl) may be used in research protocols.
The Ultra-Turrax T25 basic homogenizer can be utilized for sample preparation, and SUPRO® MAX 5050 is a soy-based ingredient that may be compared or combined with canola oil in various applications.
Researchers can leverage PubCompare.ai's AI-driven platform to optimize their canola oil research protocols, enhance reproducibility and accuracy, and easily locate relevant protocols from literature, pre-prints, and patents.
The platform's AI-based comparisons can help identify the best protocols and products for canola oil research, streamlining the overall research process.