Food and Beverage Analysis

A recent paper published in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy argued that near-infrared (NIR) spectroscopy technology is the most sustainable choice for food production.

A recent study published in Meat Science highlighted how visible and near-infrared (vis-NIR) spectroscopy, when combined with chemometrics, can differentiate lamb meat based on pasture-finishing durations.

A recent study examines widespread microplastic contamination in key Oregon seafood species, emphasizing the need for coordinated local and global efforts to reduce plastic pollution and protect ecosystems, public health, and cultural traditions.

A recent study from Shanghai University demonstrated aa novel method for identifying and quantifying animal-origin milk powders.

A recent study examines how vibrational spectroscopic techniques are being used to evaluate the quality of seaweed.

A new study published in Food Control introduces an approach for assessing antioxidant levels in edible oils using artificial intelligence and spectroscopy, offering significant potential for improving food quality control.

A recent study from China explored a new, non-destructive method combining terahertz time-domain spectroscopy (THz-TDS) and machine learning to accurately classify wheat gluten strength.

A recent study used Fourier transform mid-infrared (FT-IR) spectroscopy and machine learning (ML) algorithms to understand the mineral content in camel’s milk.

A recent study explored how polymer-based tea bags contribute to the release of microplastics and nanoplastics (MNPL).

Researchers from Italy have developed a Raman spectroscopy-based method for the rapid detection of Clostridium spores in milk. This technique offers significant advantages over traditional methods, reducing detection time by nearly half while maintaining sensitivity and reliability.

A recent study published in Food Research International demonstrates how visible and near-infrared spectroscopy (Vis-NIRS) combined with machine-learning algorithms can accurately authenticate meat and fat based on livestock feeding systems, offering a sustainable and reliable solution for traceability in the meat industry.

Researchers at Yanshan University have developed a groundbreaking method combining Raman spectroscopy and deep learning models to accurately identify and quantify components in blended vegetable oils.

This study aimed to assess and detect adulteration of Kelulut honey with different percentages of rice syrup using near-infrared (NIR) spectroscopy.

A recent study out of Russia introduced a new method for identifying plant-based oils and adulterated dairy products.

Researchers at Henan Agricultural University have developed a multi-channel magnetic flow device combined with surface-enhanced Raman spectroscopy (SERS) for the rapid and precise isolation, identification, and quantification of lactic acid bacteria and yeast, revolutionizing quality control in fermented food production.

A recent study examined using surface-enhanced Raman spectroscopy (SERS) imaging in pesticide residue detection.

This new study examined food contact materials (FCMs) and how mass spectrometric techniques have been used to measure harmful substances from FCMs that end up in food.

A recent study examined the use of surface-enhanced Raman spectroscopy (SERS) in detecting pollutants and pesticide residues in fruits and vegetables.

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A recent study looked at how near-infrared (NIR) spectroscopy can evaluate the chemical composition of pet food and safeguard pet health.

A recent review article explored the Brazilian coffee industry and how spectroscopic- and chemometrics-based approaches are helping to ensure the authenticity and quality of Brazilian coffee.

This study uses hyperspectral imaging (HSI) technology, in synergy with machine learning and deep learning algorithms, to innovate a non-destructive method for the assessment of chicken freshness.

A recent study demonstrated how to use mid-infrared (MIR) spectral data to predict body condition score (BCS) changes in dairy cows.

A recent study from Japan explored how to improve rice processing and other agricultural products using Raman scattering spectroscopy.

A recent study from Jiangsu University highlighted the challenges associated with the real-time application of microfluidic technology. We summarize their research here.

A recent study recently examined how proton nuclear magnetic resonance (NMR) spectroscopy can characterize debranched waxy rice starches in ice cream.

Top articles published this week include a review article on the latest research in agriculture analysis, a peer-reviewed article on near-infrared (NIR) spectroscopy, and an interview about using fluorescence spectroscopy in cheese ripening.

A joint French-Canadian study examined the ripening process of commercially popular Comté and cheddar cheeses, which are widely consumed in those countries, utilizing mid-infrared (mid-IR) and synchronous fluorescence spectroscopy (SFS) in their analysis.

Researchers from the University of Minnesota and Nanjing Agricultural University have highlighted the potential of deep learning to significantly improve the accuracy and robustness of fruit quality assessments using visible-near-infrared spectroscopy.

In the second part of this article, we dive into the methodology conducted by researchers from Yunnan Agricultural University in China that successfully used near-infrared (NIR) to analyze the protein content in chickens.