Predicting the performance of handheld near-infrared photonic sensors from a master benchtop device

Schoot, Mark; Alewijn, Martin; Weesepoel, Yannick; Müller-Maatsch, Judith; Kapper, C.; Postma, G.J.; Buydens, L.M.C.; Jansen, Jeroen J.

doi:10.1016/j.aca.2022.339707

Cited by 7 publications

(6 citation statements)

References 22 publications

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“…Nevertheless, the high importance of the uncertainty of the measurements is to be highlighted in the monitoring of measurement systems, and it could provide several helpful pieces of information about the experimental and instrumental conditions. The estimation of spectrometers' recalibration times and the evaluation of model maintenance (i.e., the calibration transfer strategies between different instruments and within the same devices) [18][19][20][21][22] could undoubtedly benefit from the identification and characterization of the sources of variance related to the analysis in different conditions. As a matter of fact, if one would intend the instrument life as a process, and every session of analysis as a steady state of the process, knowing the uncertainties at each stage represents a fundamental notion of taking them under control [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

On the Importance of Investigating Data Structure in Miniaturized NIR Spectroscopy Measurements of Food: The Case Study of Sugar

Gorla

Taborelli

Alamprese

et al. 2023

Foods

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Alongside the increasing proofs of efficacy of miniaturized NIR instruments in food-related scenarios, it is progressively growing the number of end-users, even incentivized by the low-cost of the sensors. While attention is paid to the analytical protocol–from sampling to data collection, up to the data processing, the importance of error investigation in raw data is generally underestimated. Understanding the sources and the structure of uncertainty related to the raw data improves the quality of measurements and suggests the correct planning of the experiments, as well as helps in chemometric model development. The goal of chemometric modeling is to separate information from noise; therefore, a description of the nature of measurement error structure is necessary. Among the different approaches, we present the study of the Error Covariance Matrices (ECMs) and their decomposition in a bilinear structure as a powerful method to study the main sources of variability when using miniaturized NIR sensors in the actual way of use. Granulated and lump sugar samples were chosen as the case study and analyzed with two miniaturized spectrometers working in the NIR regions around 1350–2550 nm and 900–1750 nm, respectively, in dispersive reflectance mode. Results show that having some insights on multivariate measurement errors associated with spectra could be interesting in paving the way for several applications.

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Section: Introductionmentioning

confidence: 99%

On the Importance of Investigating Data Structure in Miniaturized NIR Spectroscopy Measurements of Food: The Case Study of Sugar

Gorla

Taborelli

Alamprese

et al. 2023

Foods

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“…Private companies always more ask for on-site analysis by portable instruments, better if spectroscopic devices. Schoot et al presented a new prediction model from portable NIR data to predict protein content in pig feed ( Schoot et al, 2022 ).…”

Section: Chemometricsmentioning

confidence: 99%

Portable NIR spectroscopy: the route to green analytical chemistry

Gullifa,

Barone,

Papa

et al. 2023

Front. Chem.

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There is a growing interest for cost-effective and nondestructive analytical techniques in both research and application fields. The growing approach by near-infrared spectroscopy (NIRs) pushes to develop handheld devices devoted to be easily applied for in situ determinations. Consequently, portable NIR spectrometers actually result definitively recognized as powerful instruments, able to perform nondestructive, online, or in situ analyses, and useful tools characterized by increasingly smaller size, lower cost, higher robustness, easy-to-use by operator, portable and with ergonomic profile. Chemometrics play a fundamental role to obtain useful and meaningful results from NIR spectra. In this review, portable NIRs applications, published in the period 2019–2022, have been selected to indicate starting references. These publications have been chosen among the many examples of the most recent applications to demonstrate the potential of this analytical approach which, not having the need for extraction processes or any other pre-treatment of the sample under examination, can be considered the “true green analytical chemistry” which allows the analysis where the sample to be characterized is located. In the case of industrial processes or plant or animal samples, it is even possible to follow the variation or evolution of fundamental parameters over time. Publications of specific applications in this field continuously appear in the literature, often in unfamiliar journal or in dedicated special issues. This review aims to give starting references, sometimes not easy to be found.

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“…Near-infrared spectroscopy is widely employed as a rapid and nondestructive technique for characterizing various materials and bulk properties [1,2]. This analytical method provides quantitative information, making it highly suitable for online process monitoring applications.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Standardization Through Score-Augmented Projection-Based Calibration Transfer

Ghaffari,

Abdollahi

2023

Preprint

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Predicting the performance of handheld near-infrared photonic sensors from a master benchtop device

Cited by 7 publications

References 22 publications

On the Importance of Investigating Data Structure in Miniaturized NIR Spectroscopy Measurements of Food: The Case Study of Sugar

On the Importance of Investigating Data Structure in Miniaturized NIR Spectroscopy Measurements of Food: The Case Study of Sugar

Portable NIR spectroscopy: the route to green analytical chemistry

Enhancing Standardization Through Score-Augmented Projection-Based Calibration Transfer

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