Determination of cow's milk fat content based on segmented dielectric relaxation parameters combined with characteristic variables

Journal of Food Composition and Analysis, Journal Year: 2025, Volume and Issue: unknown, P. 107623 - 107623

Published: April 1, 2025

Language: Английский

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A metabolic profiling approach to characterize and discriminate plant-based beverages and milk

Journal of Dairy Science, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

The rising demand for nondairy and nonanimal protein sources has increased plant-based beverages (PBB) consumption. However, research on their functional properties, metabolic profile, discrimination potential is limited. This study evaluated the of proton nuclear magnetic resonance (1H NMR) spectroscopy as an authentication method to discriminate milk (cow goat) PBB macro-groups, including soy-based, fruit-based (almond coconut), cereal-based (rice oat) beverages, based profile. A total 22 (soy-, almond-, coconut-, rice-, oat-based beverages), 4 cow milk, goat cartons were analyzed with 1H NMR obtain Relevant metabolites macro-groups identified through Mann-Whitney U test partial least squares-discriminant analysis. Results revealed that uridine diphosphate, glucose, adenosine key identification milk. At same time, choline guanosine emerged important markers different macro-group detection. In addition, lactose played a significant role in differentiating from PBB. conclusion, these findings represent initial step toward applying nutritional analysis PBB, opening door further into authenticity profiling.

Language: Английский

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Uncovering key factors in differentiating fermented milk by feeding type and probiotic potential with E-nose and NIRS techniques

Food Control, Journal Year: 2025, Volume and Issue: unknown, P. 111376 - 111376

Published: April 1, 2025

Language: Английский

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Future trends in Food Science and Foodomics: a perspective view by the Editorial Team of Exploration of Foods and Foodomics

Published: Nov. 28, 2024

In this perspective article, several internationally recognized experts, members of the editorial team journal, discuss a selection current hot topics identified in Food Science and Foodomics. The are comprised main areas Foodomics, namely, food safety, authenticity, processing, bioactivity. Logically, discussed involve more than one mentioned areas. Regarding use analytical nanotechnology, nanometrology, nano-chromatography; determination organic contaminants based on MS NMR; impact microplastics nanoplastics or contamination foods with plant toxins. paper discusses role MS, NMR, biosensors new trends foodomics for authentication. terms work shows interesting perspectives novel processing technologies, effect gut microbiota interaction among secondary metabolites macromolecules; development active packaging, potential effects introducing recycled plastics packaging; green extraction encapsulation strategies bioactive compounds from by-products; anti-biofilm capacity natural compounds/extracts/vegetal oils essential oils. bioactivity relation between health includes bioavailability bioaccessibility compounds; challenges nutraceuticals biological systems; how matrix impacts nutrients study biodiversity, human through one-health concept. We anticipate elaborations these will promote further studies

Language: Английский

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Determination of Cow's Milk Fat Content Based on Segmented Dielectric Relaxation Parameters Combined with Characteristic Variables

Published: Jan. 1, 2024

Language: Английский

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Real-Time Detection of Milk Adulteration with a Portable Multispectral Analysis Device: A Multispectral Sensor and Optimized Logistic Regression Approach

Journal of Advanced Research in Natural and Applied Sciences, Journal Year: 2024, Volume and Issue: 10(4), P. 968 - 980

Published: Dec. 31, 2024

This study presents the development of a portable, low-cost, and edge computing-based system for real-time milk adulteration detection. Utilizing an AS7265x multispectral sensor Arduino Nano 33 BLE Sense microcontroller, this employs optimized logistic regression model to identify starch in samples with near-perfect accuracy. Unlike complex neural network models, offers simplicity, low power consumption, efficient operation on microcontrollers. The collected spectral data is processed real-time, results are transmitted via Bluetooth immediate analysis. demonstrates high accuracy, portability, cost-effectiveness, making it suitable use various stages supply chain, including farms, processing facilities, retail points. Future work will explore detection other adulterants integration cloud-based analytics enhance monitoring capabilities. provides innovative approach ensuring quality consumer safety.

Language: Английский

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Chemometric techniques for the prediction of milk composition from MIR spectral data: A review

Food Chemistry, Journal Year: 2024, Volume and Issue: 469, P. 142465 - 142465

Published: Dec. 13, 2024

Language: Английский

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