Determination of 7-ketocholesterol and 7-hydroxycholesterol in meat samples by TLC with densitometric detection

2003 ◽  
Vol 16 (3) ◽  
pp. 186-191 ◽  
Author(s):  
Beata Janoszka ◽  
Lidia Warzecha ◽  
Cezary Dobosz ◽  
Danuta Bodzek
Keyword(s):  
Densitometric Detection ◽  
Meat Samples

Ultrasensitive determination of chloramphenicol in pork and chicken meat samples using a portable electrochemical sensor: effects of 2D nanomaterials on the sensing performance and stability

2021 ◽  
Author(s):  
Ngo Xuan Dinh ◽  
Tuyet Nhung Pham ◽  
Tran Quang Huy ◽  
Do Quang Trung ◽  
Pham Anh Tuan ◽  
...  
Keyword(s):  
Electrochemical Sensor ◽  
Food Samples ◽  
Chicken Meat ◽  
Electrochemical Sensing ◽  
Portable Sensors ◽  
2D Nanomaterials ◽  
Meat Samples ◽  
Sensing Performance

This work contributes to a deeper understanding of the effects of functional 2D nanomaterials on the electrochemical sensing performance of SPE-based portable sensors for the rapid, accurate, and on-site determination of CAP in food samples.

Nondestructive NIR and NIT Determination of Protein, Fat, and Water in Plastic-Wrapped, Homogenized Meat

1992 ◽  
Vol 46 (11) ◽  
pp. 1685-1694 ◽  
Author(s):  
Tomas Isaksson ◽  
Charles E. Miller ◽  
Tormod Næs
Keyword(s):  
Diffuse Reflectance ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Errors ◽  
Optimal Test ◽  
Meat Samples ◽  
Water Contents

In this work, the abilities of near-infrared diffuse reflectance (NIR) and transmittance (NIT) spectroscopy to noninvasively determine the protein, fat, and water contents of plastic-wrapped homogenized meat are evaluated. One hundred homogenized beef samples, ranging from 1 to 23% fat, wrapped in polyamide/polyethylene laminates, were used. Results of multivariate calibration and prediction for protein, fat, and water contents are presented. The optimal test set prediction errors (root mean square error of prediction, RMSEP), obtained with the use of the principal component regression method with NIR data, were 0.45, 0.29 and 0.50 weight % for protein, fat, and water, respectively, for plastic-wrapped meat (compared to 0.40, 0.28 and 0.45 wt % for unwrapped meat). The optimal prediction errors for the NIT method were 0.31, 0.52 and 0.42 wt % for protein, fat, and water, respectively, for plastic-wrapped meat samples (compared to 0.27, 0.38, and 0.37 wt % for unwrapped meat). We can conclude that the addition of the laminate only slightly reduced the abilities of the NIR and NIT method to predict protein, fat, and water contents in homogenized meat.

scholarly journals Determination of Chemical Content and some Physical Properties and Meat Pigments (Myoglobin, Meta Myoglobin and Oxymyoglobin) in Different Parts of Slaughtered Animals

2019 ◽  
Vol 32 ◽  
pp. 302-319
Author(s):  
Khadeeja S.J. Al-Husseiny ◽  
Maryam T. Khrebish
Keyword(s):  
The Body ◽  
Water Holding Capacity ◽  
Fresh Meat ◽  
Ph Values ◽  
Significant Difference ◽  
Chemical Content ◽  
Meat Samples ◽  
Water Holding ◽  
Different Parts

The current study aimed to estimate the pigments of some muscles parts taken from cows, sheep and chicken (thigh, chest and back). The chemical content including moisture, protein, lipids and ash, as well as the pH and the water holding capacity have been evaluated. Results showed that the moisture differed among three animals with high percentage of moisture, ash and lipid in back in compared with other parts of cows. while significant difference in the percentage of ash of back with other parts and in protein in chest with other parts of sheep. The significant differences were recorded in percentage of ash of three parts of chicken, also significant differences between chest and back. The water holding capacity of fresh meat samples taken from thigh, chest and back of cows, sheep and chicken significantly differ among samples. pH values which reflect a confect in water holding capacity of meat samples taken from different parts of the body and from different animal. In addition, there was a significant differences in the percentage of the presences of myoglobin, metmyoglobin and oxymyoglobin in different samples taken from different parts of the slaughtered animals.

Microwave Oven Method for Rapid Determination of Moisture in Meat

1975 ◽  
Vol 58 (6) ◽  
pp. 1188-1193 ◽  
Author(s):  
Julio D Pettinati
Keyword(s):  
Rapid Determination ◽  
Linear Regression Analysis ◽  
Microwave Oven ◽  
Moisture Determination ◽  
Oven Method ◽  
Sources Of Variation ◽  
Aoac Method ◽  
Air Blower ◽  
Meat Samples

Abstract A new, rapid procedure was developed for moisture determination in meat. Results with the method were evaluated by comparative analysis with AOAC method 24.003(b). The new method is accurate, precise, and simple. Samples were prepared for drying by admixture with ferrous oxide and sodium chloride in glass weighing bottles and heating 2.5 mill in a domestic-type 1000 watt microwave oven. After heating, the residues were exposed 1 min in the stream of the oven chamber air blower, then covered and weighed. From comparative determinations on 67 meat samples containing from 3.5 to 77.9% moisture, meat type and moisture level were not significant (P = 0.05) sources of variation as determined by t-tests. Mean moisture content was 0.05% higher by the microwave oven method than by the AOAC method. Repeatability between duplicates was ± 0.47% moisture by microwave oven and ±0.45% by the AOAC method. Precision between paired determinations by the 2 methods was ±0.57% moisture. Both the t-test for significance (P = 0.05) and linear regression analysis of the comparative determinations indicated that the 2 methods were equivalent for determining moisture. Continued study of the method is recommended.

Determination of budesonide R(+) and S(−) isomers in pharmaceuticals by thin-layer chromatography with UV densitometric detection

2002 ◽  
Vol 56 (11-12) ◽  
pp. 759-762 ◽  
Author(s):  
J. Krzek ◽  
U. Hubicka ◽  
M. Dabrowska-Tylka ◽  
E. Leciejewicz-Ziemecka
Keyword(s):  
Thin Layer ◽  
Thin Layer Chromatography ◽  
Densitometric Detection ◽  
Layer Chromatography

Determination of N-nitrosoproline in meat samples

1978 ◽  
Vol 26 (5) ◽  
pp. 1253-1255 ◽  
Author(s):  
John K. Baker ◽  
Cheng-Yu Ma
Keyword(s):  
Meat Samples

Rapid Determination of Fat in Meat and Meat Products by Foss-let Solvent Extraction and Density Measurement

1975 ◽  
Vol 58 (6) ◽  
pp. 1182-1187
Author(s):  
Julio D Pettinati ◽  
Clifton E Swift
Keyword(s):  
Rapid Determination ◽  
Density Measurement ◽  
Meat Products ◽  
Fat Content ◽  
Digital Potentiometer ◽  
Sources Of Variation ◽  
Aoac Method ◽  
Meat Samples ◽  
Meat Type

Abstract The commercially available Foss-let fat analyzer was evaluated for the determination of fat in meat and meat products by comparison with AOAC method 24.005(a). With the Foss-let procedure, mechanical and instrumental equipment is used to determine fat in 7–10 min. A sample is extracted with tetrachloroethylene in a mechanical orbital shaker for 2 min and the specific gravity of the extract is measured in a magnetic float cell controlled by a digital potentiometer. During extraction, anhydrous calcium sulfate absorbs moisture droplets originating from the sample. The variations of comparative determinations on 67 meat samples containing 1.1–95.4% fat and 17 frankfurter samples containing 17.3–37.3% fat were analyzed statistically by grouping the data according to meat type (beef or pork) or frankfurters and into 6 ranges of fat content, and by treating the entire set of data. Error analysis of the differences and standard deviation of each grouping of paired determinations by the Fosslet and AOAC methods indicated that meat type and fat content >7.5% were not significant (P = 0.05) sources of variation as determined by t-tests on the statistics from the blocks of data. Determinations on samples containing ≤7.5% fat were consistently low and an additive correction of 0.25% was indicated. From the overall results, the accuracy and precision of the method were characterized as follows: the mean Foss-let method determination was high by 0.08% fat relative to that by the AOAC method; repeatability of ± 0.31% fat between duplicate determinations compared favorably with ±0.38% obtained with the AOAC method; and precision between paired determinations by the 2 methods was ±0.44%. Both a t-test for significance (P = 0.05) and the linear regression of the 84 comparative determinations indicated that the Foss-let method was equivalent to the AOAC method for determining fat.

Automation of Methods for Meat and Meat Products. I. Determination of Protein

1970 ◽  
Vol 53 (5) ◽  
pp. 907-910 ◽  
Author(s):  
Jon E Mcneal ◽  
Albert Karasz ◽  
Elmer George
Keyword(s):  
Meat Products ◽  
Automated Method ◽  
Kjeldahl Method ◽  
Standards Development ◽  
Meat Samples ◽  
Selection Of

Abstract An automated method for the analysis of protein in meat was studied. The investigation included selection of proper standards, development of a method for presolubilizing meat samples for presentation to the AutoAnalyzer, and the construction of AutoAnalyzer manifolds to give protein results comparable to those obtained by the official AOAC Kjeldahl method. The method was found to be applicable to meat and meat products ranging from 5 to 25% protein.

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