AIMC Topic: Spectroscopy, Near-Infrared

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Non-destructive assessment of tissue engineered cartilage maturity using visible and near infrared spectroscopy combined with machine learning.

Biosensors & bioelectronics
Tissue engineering is a promising approach to address the unmet clinical need for treating cartilage damage. Monitoring the characteristics of tissue-engineered cartilage constructs (TECs) during culture is critical for optimizing culture conditions ...

Compositional analysis of alternative protein blends using near and mid-infrared spectroscopy coupled with conventional and machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive real-time analysis of the composition of alternative, plant-based protein sources is important to control high moisture extrusion processes and ensure the quality and texture of the final extrudates used in the elaboration of meat an...

Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly sensitive and minimally invasive early diagnostic methods. Near-infrared spectroscopy (NIRS) offers unique advantages in probing molecular vibrational i...

Near-infrared spectroscopy coupled with Gramian angular field two-dimensional convolutional neural network for white tea adulteration detection.

Journal of the science of food and agriculture
BACKGROUND: The flavor profile and product quality of white tea, heavily dependent on its place of origin, significantly influence consumers' purchasing decisions. Quantitative adulteration testing for tea origin has encountered challenges due to the...

Fusion of near-infrared and Raman spectroscopy with machine learning strategies: Non-destructive rapid assessment of freshness and TVB-N value prediction in Pacific white shrimp (Litopenaeus vannamei).

Food research international (Ottawa, Ont.)
Total volatile base nitrogen (TVB-N) is a key indicator of shrimp freshness. Nevertheless, traditional detection methods are cumbersome, time-intensive, and destructive. Here, a rapid and non-destructive method based on near-infrared (NIR) and Raman ...

Fingerprinting of Boletus bainiugan: FT-NIR spectroscopy combined with machine learning a new workflow for storage period identification.

Food microbiology
Food authenticity and food safety issues have threatened the prosperity of the entire community. The phenomenon of selling porcini mushrooms as old mixed with new jeopardizes consumer safety. Herein, nucleoside contents and spectra of 831 Boletus bai...

Simultaneous detection of citrus internal quality attributes using near-infrared spectroscopy and hyperspectral imaging with multi-task deep learning and instrumental transfer learning.

Food chemistry
Simultaneous determination of multiple quality attributes of citrus fruits using hyperspectral imaging (HSI) and near-infrared (NIR) spectroscopy and successfully transferring the models among different instruments are two main challenges. In this st...

Application of artificial intelligence in the rapid determination of moisture content in medicine food homology substances.

Food chemistry
Moisture content is crucial in quality testing of medicine food homology substances. This study aimed to present a new modeling method for moisture content based on near-infrared spectroscopy. When comparing three methods of partial least squares reg...

Decoding Hidden Features in Near-Infrared Fluorescence Spectra of Single-Walled Carbon Nanotubes via Machine Learning for Multiplexed Virus Identification.

ACS nano
Single-walled carbon nanotubes (SWCNTs) exhibit rich spectral diversity in their near-infrared (nIR) fluorescence, offering strong potential for multiplexed optical sensing via diverse signal features, even with a single sensor. However, conventional...

Model updating strategy study about sex identification of silkworm pupae using transfer learning and NIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This paper proposes a novel model updating strategy named SilkwormNet for the first time to address the sex discrimination problem of silkworm pupae with new species. SilkwormNet integrates a ResNet block, a multi-head attention mechanism, and a Sche...