Semantic Scholar Open Access 2023 40 sitasi

Spectroscopic technologies and data fusion: Applications for the dairy industry

E. Hayes Derek Greene C. O’Donnell N. O'Shea M. Fenelon

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Abstrak

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.

Topik & Kata Kunci

Medicine

Penulis (5)

E. Hayes

Derek Greene

C. O’Donnell

N. O'Shea

M. Fenelon

Format Sitasi

APA MLA BibTeX

Hayes, E., Greene, D., O’Donnell, C., O'Shea, N., Fenelon, M. (2023). Spectroscopic technologies and data fusion: Applications for the dairy industry. https://doi.org/10.3389/fnut.2022.1074688

Akses Cepat

Lihat di Sumber doi.org/10.3389/fnut.2022.1074688

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Total Sitasi: 40×
Sumber Database: Semantic Scholar
DOI: 10.3389/fnut.2022.1074688
Akses: Open Access ✓