Total Metals Analysis of Digested Plant Tissue Using an Agilent 4200 Microwave Plasma-AES

Researchers at Wittenborg University of Applied Sciences have developed a non-destructive method using hyperspectral imaging combined with chemometrics and machine learning to accurately predict fat and protein content in diverse cheese types.

Researchers from the Institute of Agrifood Research and Technology (IRTA) in Catalunya, Spain used fluorescence and Raman spectroscopy to explore complex tissue changes behind wooden breast myopathy in chickens.

Because the United Arab Emirates is seeing an increase in pet ownership, the quality of both dry and wet pet food is undergoing greater scrutiny to ensure its safety and efficacy. Lucy Semerjian, who works as a Chair and Associate Professor in the Department of Environmental Health Science at the University of Sharjah in Sharjah, United Arab Emirates, recently explored this topic in a recent paper

A recent study conducted in the Journal of Food Composition and Analysis examined the concentrations of ten metals in 52 commercially available wet and dry cat food samples, assessing their compliance with U.S. and European pet food safety standards. The lead author of this study, Lucy Semerjian, recently sat down with Spectroscopy to discuss the findings of her study.

Researchers from Hebei University and Hebei University of Engineering have developed a hyperspectral imaging method combined with data fusion and machine learning to accurately and non-destructively assess walnut quality and classify storage periods.

A new study demonstrates that paper bagging significantly enhances Fuji apple quality and appearance. Hyperspectral imaging combined with machine learning offers a powerful, non-destructive method for evaluating fruit grown under different cultivation conditions.