AIMC Topic: Camellia

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Extraction of polysaccharides from Camellia oleifera leaves by dual enzymes combined with deep eutectic solvents screened by ANN and COSMO-RS.

International journal of biological macromolecules Feb 16, 2025
Camellia oleifera leaves were byproduct of the C. oleifera industry which was rich in polysaccharides. Deep eutectic solvent-dual enzyme system (DES-dEAE) was established to achieve the simultaneous hydrolysis reaction of dual enzymes and DES extract...
Deep Eutectic Solvents Hydrogen-Ion Concentration Neural Networks, Computer Polysaccharides Solvents Plant Leaves Camellia Hydrolysis
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Rapid classification of Camellia seed varieties and non-destructive high-throughput quantitative analysis of fatty acids based on non-targeted fingerprint spectroscopy combined with chemometrics.

Food chemistry Feb 1, 2025
Camellia oil is a high-quality vegetable oil rich in unsaturated fatty acids (FAs), with quality standardization challenged by the diversity of Camellia seed varieties. This study compared spectroscopy techniques (Near-Infrared [NIR] vs Mid-Infrared ...
Spectroscopy, Near-Infrared Seeds Neural Networks, Computer Plant Oils Fatty Acids Discriminant Analysis Camellia Chemometrics
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Machine Learning-Based Spectral Analyses for Cultivar Identification.

Molecules (Basel, Switzerland) Jan 25, 2025
is a plant species with high cultural and biological relevance. Besides being used as an ornamental plant species, has relevant biological properties. Due to hybridization, thousands of cultivars are known, and their accurate identification is mand...
Machine Learning Spectroscopy, Near-Infrared Spectroscopy, Fourier Transform Infrared Plant Leaves Camellia
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Determination and visualization of moisture content in Camellia oleifera seeds rapidly based on hyperspectral imaging combined with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 27, 2024
Moisture content (MC) is crucial for the storage, transportation, and processing of Camellia oleifera seeds. The purpose of this study was to investigate the feasibility for detecting MC in Camellia oleifera seeds using visible near-infrared hyperspe...
Camellia Least-Squares Analysis Hyperspectral Imaging Support Vector Machine Seeds Neural Networks, Computer Algorithms Deep Learning Water Spectroscopy, Near-Infrared
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Using three-dimensional fluorescence spectroscopy and machine learning for rapid detection of adulteration in camellia oil.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 3, 2024
Camellia oil had been widely utilized in the realms of cooking, healthcare, and beauty. Nevertheless, merchants frequently adulterated pure camellia oil with low-priced oils to cut costs. This study was aimed at identifying the authenticity of camell...
Spectrometry, Fluorescence Least-Squares Analysis Food Contamination Plant Oils Discriminant Analysis Camellia Neural Networks, Computer Machine Learning Support Vector Machine
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Smartphone-Assisted Nanozyme Colorimetric Sensor Array Combined "Image Segmentation-Feature Extraction" Deep Learning for Detecting Unsaturated Fatty Acids.

ACS sensors Sep 19, 2024
Conventional methods for detecting unsaturated fatty acids (UFAs) pose challenges for rapid analyses due to the need for complex pretreatment and expensive instruments. Here, we developed an intelligent platform for facile and low-cost analysis of UF...
Plant Oils Manganese Compounds Oxides Catalysis Colorimetry Camellia Smartphone Fatty Acids, Unsaturated Deep Learning Platinum Palladium
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Adulteration detection of multi-species vegetable oils in camellia oil using Raman spectroscopy: Comparison of chemometrics and deep learning methods.

Food chemistry Sep 16, 2024
Oil adulteration is a global challenge in the production of high value-added natural oils. Raman spectroscopy combined with mathematical modeling can be used for adulteration detection of camellia oil (CAO). In this study, the advantages of tradition...
Food Contamination Chemometrics Plant Oils Camellia Deep Learning Spectrum Analysis, Raman
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The inhibition of advanced glycation end-products by five fractions and three main flavonoids from Camellia nitidissima Chi flowers.

Journal of food and drug analysis Apr 18, 2017
Camellia nitidissima Chi (CNC), belonging to Camellia genus (Theaceae family), is a medicinal and edible plant in China. Among the whole plant, the CNC flowers are especially precious, but the biological activities and the compositions of the CNC flo...
Magnetic Resonance Spectroscopy Camellia Flowers Glucose Phenols Glycation End Products, Advanced Plant Extracts Chromatography, High Pressure Liquid Molecular Structure Flavonoids Tandem Mass Spectrometry Spectrometry, Mass, Electrospray Ionization
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