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Fluorescence Spectroscopy for the Monitoring of Food Processes

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Measurement, Modeling and Automation in Advanced Food Processing

Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 161))

Abstract

Different analytical techniques have been used to examine the complexity of food samples. Among them, fluorescence spectroscopy cannot be ignored in developing rapid and non-invasive analytical methodologies. It is one of the most sensitive spectroscopic approaches employed in identification, classification, authentication, quantification, and optimization of different parameters during food handling, processing, and storage and uses different chemometric tools. Chemometrics helps to retrieve useful information from spectral data utilized in the characterization of food samples. This contribution discusses in detail the potential of fluorescence spectroscopy of different foods, such as dairy, meat, fish, eggs, edible oil, cereals, fruit, vegetables, etc., for qualitative and quantitative analysis with different chemometric approaches.

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Abbreviations

ANNs:

Artificial neural networks

ATP:

Adenosine triphosphate

CCA:

Canonical component analysis

CCSWA:

Common component specific weight analysis

DDT:

Dough development time

EEM:

Excitation emission matrix

FADH:

Flavin adenine dinucleotide

FDA:

Factorial discriminant analysis

FMN:

Flavin adenine mononucleotide

GLSW:

Generalized least square weighting

HCA:

Hierarchical cluster analysis

ICA:

Independent component analysis

LDA:

Linear discriminant analysis

LWR:

Locally weighted regression

NADH:

Nicotinamide adenine dinucleotide

N-PLS:

Multi-way partial least square regression

PARAFAC:

Parallel factor analysis

PCA:

Principal component analysis

PCR:

Principal component regression

PCs:

Principal components

PLS-DA:

Partial least square discriminant analysis

PLSR:

Partial least square regression

RPD:

Ratio of standard deviation to root mean square errors of cross-validation

SFS:

Synchronous fluorescence spectroscopy

SIMCA:

Soft independent modeling by class analogy

SNV:

Standard normal variate

TBA:

Thiobarbituric acid

TVC:

Total viable count

UHT:

Ultra high temperature

UV:

Ultra violet

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Authors and Affiliations

  1. National Institute of Food Science and Technology, Faculty of Food, Nutrition and Home Sciences, University of Agriculture, Faisalabad, Pakistan

    Muhammad Haseeb Ahmad & Amna Sahar

  2. Department of Process Analytics and Cereal Science, Institute of Food Science and Biotechnology, University of Hohenheim, Garbenstrasse 23, 70599, Stuttgart, Germany

    Muhammad Haseeb Ahmad & Bernd Hitzmann

  3. Department of Food Engineering, Faculty of Agricultural Engineering, University of Agriculture, Faisalabad, Pakistan

    Amna Sahar

Authors
  1. Muhammad Haseeb Ahmad
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  2. Amna Sahar
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  3. Bernd Hitzmann
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Correspondence to Bernd Hitzmann .

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Editors and Affiliations

  1. Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Baden-Württemberg, Germany

    Bernd Hitzmann

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Ahmad, M.H., Sahar, A., Hitzmann, B. (2017). Fluorescence Spectroscopy for the Monitoring of Food Processes. In: Hitzmann, B. (eds) Measurement, Modeling and Automation in Advanced Food Processing. Advances in Biochemical Engineering/Biotechnology, vol 161. Springer, Cham. https://doi.org/10.1007/10_2017_11

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