Alps food authentication, typicality and intrinsic quality by near infrared spectroscopy

Huck-Pezzei, V. A.; Seitz, Ina; Karer, Regina; Schmutzler, Matthias; Benedictis, Lorenzo De; Wild, Birgit; Huck, Christian

doi:10.1016/j.foodres.2014.05.021

Cited by 32 publications

(18 citation statements)

References 28 publications

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“…In the agrifood sector, the potential of NIRS have been widely investigated, this is a very powerful tool that provides meaningful information about internal and external properties of fruits, such as sugar content, total acidity, pH, soluble solid content, dry matter, firmness, and bruises, to mention some [36]. Moreover, NIRS can be applied to a wide variety of problems such as determination of particle size [38], determination of the best harvesting time [37], and investigation of geographical origin of foods such as apples, meat, and cheese [39].…”

Section: Applications Of Carbohydrates Analysis By Nirsmentioning

confidence: 99%

Carbohydrate Analysis by NIRS-Chemometrics

López¹,

García-González²,

Franco‐Robles³

2017

Developments in Near-Infrared Spectroscopy

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Near-infrared spectroscopy (NIRS) is a high-throughput, low-cost, solvent-free, and nondestructive analytical tool. Chemometrics is the science that employs statistical and mathematical methods to explain near-infrared spectra; it has been proven that when they are coupled, their effectiveness highly improved in-depth carbohydrate characterization. This chapter focuses on the fundamentals of near-infrared spectroscopy in the study of carbohydrates, as well as the application of partial least squares regression (PLSR) and principal component analysis (PCA), as the most useful chemometric techniques involved in carbohydrate analysis. The theoretical aspects and practical applications starting from simple to complex carbohydrates mixtures are covered. Indeed, the contributions from different fields extend the implementation of near-infrared spectroscopy from industrial quality control to scientific research.

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Section: Applications Of Carbohydrates Analysis By Nirsmentioning

confidence: 99%

Carbohydrate Analysis by NIRS-Chemometrics

López¹,

García-González²,

Franco‐Robles³

2017

Developments in Near-Infrared Spectroscopy

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“…More recent approaches also focus on minor components, like vitamins, minerals and carotenoids [10,11]. But lately, near-infrared spectroscopy (NIRS) was also used to identify sensory properties, as well as the origin of cheese [12,13,14,15,16]. Cheese is not spatially homogeneous, which poses a challenge for spectral analysis [10].…”

Section: Introductionmentioning

confidence: 99%

“…NIRS is widely applied in food analyses [17,18,19,20], as well as in other fields including pharmaceutical sciences and petrochemistry [21,22,23,24]. NIR excites molecular vibrations and thus overtones and combination bands can be observed in a NIR spectrum [15]. The main advantages of NIRS are its comparatively low cost, fast measurements and easy handling [25,26].…”

Section: Introductionmentioning

confidence: 99%

Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis

et al. 2019

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The performance of a newly developed pocket-sized near-infrared (NIR) spectrometer was investigated by analysing 46 cheese samples for their water and fat content, and comparing results with a benchtop NIR device. Additionally, the automated data analysis of the pocket-sized spectrometer and its cloud-based data analysis software, designed for laypeople, was put to the test by comparing performances to a highly sophisticated multivariate data analysis software. All developed partial least squares regression (PLS-R) models yield a coefficient of determination (R2) of over 0.9, indicating high correlation between spectra and reference data for both spectrometers and all data analysis routes taken. In general, the analysis of grated cheese yields better results than whole pieces of cheese. Additionally, the ratios of performance to deviation (RPDs) and standard errors of prediction (SEPs) suggest that the performance of the pocket-sized spectrometer is comparable to the benchtop device. Small improvements are observable, when using sophisticated data analysis software, instead of automated tools.

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“…In the majority of the applications, the primary objective is rapid and safe on-site identification of unknown—often hazardous or toxic—materials or for authenticating the origin of goods by trained users—but not necessarily scientists [58].…”

Section: Principles Of Infrared Spectroscopic Analysis Techniquesmentioning

confidence: 99%

Recent Developments in Solid-Phase Extraction for Near and Attenuated Total Reflection Infrared Spectroscopic Analysis

Huck

2016

Molecules

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A review with more than 100 references on the principles and recent developments in the solid-phase extraction (SPE) prior and for in situ near and attenuated total reflection (ATR) infrared spectroscopic analysis is presented. New materials, chromatographic modalities, experimental setups and configurations are described. Their advantages for fast sample preparation for distinct classes of compounds containing different functional groups in order to enhance selectivity and sensitivity are discussed and compared. This is the first review highlighting both the fundamentals of SPE, near and ATR spectroscopy with a view to real sample applicability and routine analysis. Most of real sample analyses examples are found in environmental research, followed by food-and bioanalysis. In this contribution a comprehensive overview of the most potent SPE-NIR and SPE-ATR approaches is summarized and provided.

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Alps food authentication, typicality and intrinsic quality by near infrared spectroscopy

Cited by 32 publications

References 28 publications

Carbohydrate Analysis by NIRS-Chemometrics

Carbohydrate Analysis by NIRS-Chemometrics

Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis

Recent Developments in Solid-Phase Extraction for Near and Attenuated Total Reflection Infrared Spectroscopic Analysis

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