The mucilage was isolated from mustard seeds and identification by some different methods like, thermo gravimetric, FTlR., X-ray powdered, proton NMR, FTIR spectra of the three gums contain different functional group in the gums, major peaks bands noticed were belong to OH (3410.15 – 3010.88) group from hydroxyl group, CH aliphatic (2925-2343.51), C-O (1072.42-1060.85) group and C=O 1743.65, Thermo chemical parameters of mucilage was evaluated and compared with the standard gums, Results indicated the mucilage was decomposed in 392°C and mass loss 55%, The X ray process found the mucilage had single not sharp peak at 19.9265°in highest 53.35 cts, Also the standard gums indicted not sharp peaks at 20.94°, 19.04°in highest 47.78, 52.84 cts separately, mucilage examination using nuclear magnetic resonance revealed the presence of glucose, rhamnose, galacturonic acid compared with two standard gums contain similar polysaccharide.lt was concluded The results that had that mucilage had good advantages, which might be used in various food industries showed that mustard gum is beneficial in food manufacturing.
EXTRACTION AND CHARACTERATION OF MUCILAGE EXTRACTED FROM MUSTARD SEEDS: EXTRACTION AND CHARACTERATION OF MUCILAGE EXTRACTED FROM MUSTARD SEEDS
Keywords: Mustard seeds gum
characterization
thermo gravimetric analysis
X-ray diffraction
nuclear magnetic resonance.
Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
البيانات الطولية
نموذج الشرائح B-spline التكعيبية اللامعلمية
التحليل العنقودي
طريقة الاتجاه المتناوب لخوارزمية المضاعف ADMM.
Longitudinal Data
Nonparametric Cubic B-Spline
Cluster Analysis
The Alternating Direction Method for Multiplier Algorithm ADMM.
Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
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