AIMC Topic: Spectroscopy, Near-Infrared

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Near-infrared spectroscopy assisted by random forest for predicting the physicochemical indicators of yak milk powder.

Food chemistry Mar 1, 2025
High-efficiency and cost-effective detection of physicochemical indicators is essential for the quality control of yak milk powder. Herein, a rapid and simultaneous detection method based on miniaturized near-infrared (NIR) spectroscopy and chemometr...
Animals Spectroscopy, Near-Infrared Milk Powders Milk Proteins Fats Cattle Random Forest Quality Control
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Leveraging infrared spectroscopy for cocoa content prediction: A dual approach with Kohonen neural network and multivariate modeling.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 28, 2025
People of all ages enjoy chocolate, and its popularity is attributed to its pleasant taste and aroma, as well as its associated health benefits. Produced through both artisanal and industrial processes, which involve harvesting, selecting, fermenting...
Neural Networks, Computer Spectroscopy, Near-Infrared Multivariate Analysis Principal Component Analysis Cacao Chocolate
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Predicting oleogels properties using non-invasive spectroscopic techniques and machine learning.

Food research international (Ottawa, Ont.) Feb 26, 2025
Oleogelators are considered food additives that require approval from regulatory authorities. Therefore, classifying these ingredients that may have characteristics (e.g., waxiness), cost and origin (e.g., animal or vegetable) is crucial to ensure co...
Principal Component Analysis Sunflower Oil Machine Learning Least-Squares Analysis Organic Chemicals Spectroscopy, Near-Infrared Food Additives Fatty Acids, Nonesterified Spectrum Analysis, Raman Soybean Oil Cellulose Waxes
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A machine learning approach fusing multisource spectral data for prediction of floral origins and taste components of Apis cerana honey.

Food research international (Ottawa, Ont.) Feb 25, 2025
This study explores the use of near-infrared (NIR), mid-infrared (MIR), and Raman spectral fusion for the rapid prediction of floral origins and main taste components in Apis cerana (A. cerana) honey. Feature-level fusion with the partial least squar...
Spectrum Analysis, Raman Machine Learning Bees Honey Animals Least-Squares Analysis Sugars Spectroscopy, Near-Infrared Amino Acids Taste Flowers
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Effect of Parallel Cognitive-Motor Training Tasks on Hemodynamic Responses in Robot-Assisted Rehabilitation.

Brain connectivity Feb 20, 2025
Previous studies suggest that the combination of robot-assisted training with other concurrent tasks may promote the functional recovery and improvement better than the single task. It is well-established that robot-assisted rehabilitation training ...
Hemodynamics Cognition Brain Mapping Motor Cortex Sensorimotor Cortex Humans Robotics Male Brain Psychomotor Performance Spectroscopy, Near-Infrared Female Prefrontal Cortex Young Adult Adult
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Using visible and NIR hyperspectral imaging and machine learning for nondestructive detection of nutrient contents in sorghum.

Scientific reports Feb 19, 2025
Nondestructive, rapid, and accurate detection of nutritional compositions in sorghum is crucial for agricultural and food industries. In our study, the crude protein, tannin, and crude fat contents of sorghum variety samples were taken as the researc...
Least-Squares Analysis Nutrients Nutritive Value Machine Learning Algorithms Spectroscopy, Near-Infrared Hyperspectral Imaging Tannins Sorghum
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Unveiling the potential of Brachiaria ruziziensis: Comparative analysis of multivariate and machine learning models for biomass and NPK prediction using Vis-NIR-SWIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 18, 2025
This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of Brachiaria ruziziensis L. The approach utilized Vis-NIR-SWI...
Nitrogen Potassium Phosphorus Multivariate Analysis Brachiaria Support Vector Machine Machine Learning Biomass Plant Leaves Spectroscopy, Near-Infrared Least-Squares Analysis
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Non-destructive origin and ginsenoside analysis of American ginseng via NIR and deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 17, 2025
American ginseng is widely in demand as a famous medicinal herb, but the production conditions affect the content of ginsenosides in American ginseng, which in turn affects its medicinal value. Currently, it remains a challenge to simultaneously iden...
Ginsenosides Panax Spectroscopy, Near-Infrared Deep Learning
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A review: Integration of NIRS and chemometric methods for tea quality control-principles, spectral preprocessing methods, machine learning algorithms, research progress, and future directions.

Food research international (Ottawa, Ont.) Feb 15, 2025
With the steady rise in tea production, the need for effective tea quality monitoring has become increasingly pressing. Traditional sensory evaluation and wet chemical detection methods are insufficient for real-time tea quality monitoring. As an eme...
Tea Quality Control Chemometrics Machine Learning Spectroscopy, Near-Infrared Plant Leaves
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Characterizing drivers of change in intraoperative cerebral saturation using supervised machine learning.

Journal of clinical monitoring and computing Feb 7, 2025
Regional cerebral oxygen saturation (rSO) is used to monitor cerebral perfusion with emerging evidence that optimization of rSO may improve neurological and non-neurological outcomes. To manipulate rSO an understanding of the variables that drive its...
Humans Machine Learning Algorithms Brain Oximetry Carbon Dioxide Oxygen Saturation Cerebrovascular Circulation Spectroscopy, Near-Infrared Hemodynamics Monitoring, Intraoperative Signal Processing, Computer-Assisted Supervised Machine Learning ROC Curve Adult Female Oxygen Male Reproducibility of Results Middle Aged Aged
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