Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study

Han, Qing; Peller, Joseph; Erasmus, Sara W.; Elliott, Christopher T.; Ruth, Saskia M. van

doi:10.1016/j.foodres.2023.113023

Cited by 4 publications

(1 citation statement)

References 49 publications

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“…Specifically, the incorporation of not only natural (e.g., seasonal, cultivar, environmental, food varieties or types, etc.) and processing (production parameters and storage) variability into a food sample but also other secondary types of real-world experimental variation (instrumental, sampling, and human factors) is necessary for the creation of universal and robust chemometric models and their transition to industrial online applications [ 25 ].…”

Section: Challenges and Sources Of Error In Current Research Studiesmentioning

confidence: 99%

Challenges in the Use of AI-Driven Non-Destructive Spectroscopic Tools for Rapid Food Analysis

Jia,

Georgouli,

Martinez-Del Rincon

et al. 2024

Foods

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Routine, remote, and process analysis for foodstuffs is gaining attention and can provide more confidence for the food supply chain. A new generation of rapid methods is emerging both in the literature and in industry based on spectroscopy coupled with AI-driven modelling methods. Current published studies using these advanced methods are plagued by weaknesses, including sample size, abuse of advanced modelling techniques, and the process of validation for both the acquisition method and modelling. This paper aims to give a comprehensive overview of the analytical challenges faced in research and industrial settings where screening analysis is performed while providing practical solutions in the form of guidelines for a range of scenarios. After extended literature analysis, we conclude that there is no easy way to enhance the accuracy of the methods by using state-of-the-art modelling methods and the key remains that capturing good quality raw data from authentic samples in sufficient volume is very important along with robust validation. A comprehensive methodology involving suitable analytical techniques and interpretive modelling methods needs to be considered under a tailored experimental design whenever conducting rapid food analysis.

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Section: Challenges and Sources Of Error In Current Research Studiesmentioning

confidence: 99%

Challenges in the Use of AI-Driven Non-Destructive Spectroscopic Tools for Rapid Food Analysis

Jia,

Georgouli,

Martinez-Del Rincon

et al. 2024

Foods

View full text Add to dashboard Cite

show abstract

Fluorescence lifetime imaging microscopy as a tool to characterize spice powder variations for quality and authenticity purposes: A ginger case study

Han,

Erasmus,

Bader

et al. 2024

Food Research International

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Spice authentication by near-infrared spectroscopy: Current advances, limitations, and future perspectives

Shawky,

Nahar,

Nassief

et al. 2024

Trends in Food Science & Technology

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Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study

Cited by 4 publications

References 49 publications

Challenges in the Use of AI-Driven Non-Destructive Spectroscopic Tools for Rapid Food Analysis

Challenges in the Use of AI-Driven Non-Destructive Spectroscopic Tools for Rapid Food Analysis

Fluorescence lifetime imaging microscopy as a tool to characterize spice powder variations for quality and authenticity purposes: A ginger case study

Spice authentication by near-infrared spectroscopy: Current advances, limitations, and future perspectives

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