SynthesisFrontiers in nutrition2022
Spectroscopic technologies and data fusion: Applications for the dairy industry.
Synthesis in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
9 citing papers in PubMed.
- Artificial intelligence in poultry processing: applications, validation gaps, and pathways toward intelligent and autonomous processing systems.Poultry science · 2026Review
- XAI-Supported Electronic Tongue for Estimating Milk Composition and Adulteration Indicators.Biosensors · 2026Article
- Trends on vibrational spectroscopy tools in the agri-food sector.Analytical and bioanalytical chemistry · 2026Review
- Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods.Foods (Basel, Switzerland) · 2025Review
- Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer.International journal of molecular sciences · 2024Article
- Vibrational spectroscopy data fusion for enhanced classification of different milk types.Heliyon · 2024Article
- Exploring the use of NIR and Raman spectroscopy for the prediction of quality traits in PDO cheeses.Frontiers in nutrition · 2024Article
- Mid-Level Data Fusion Combined with the Fingerprint Region for Classification DON Levels Defect of Fusarium Head Blight Wheat.Sensors (Basel, Switzerland) · 2023Article
- Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review.Foods (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increasing consumer awareness, scale of manufacture, and demand to ensure safety, quality and sustainability have accelerated the need for rapid, reliable, and accurate analytical techniques for food products. Spectroscopy, coupled with Artificial Intelligence-enabled sensors and chemometric techniques, has led to the fusion of data sources for dairy analytical applications. This article provides an overview of the current spectroscopic technologies used in the dairy industry, with an introduction to data fusion and the associated methodologies used in spectroscopy-based data fusion. The relevance of data fusion in the dairy industry is considered, focusing on its potential to improve predictions for processing traits by chemometric techniques, such as principal component analysis (PCA), partial least squares regression (PLS), and other machine learning algorithms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.