Postharvest monitoring of organic potato (cv. Anuschka) during hot‐air drying using visible–NIR hyperspectral imaging

Moscetti, Roberto; Sturm, Barbara; Crichton, Stuart; Amjad, Waseem; Massantini, Riccardo

doi:10.1002/jsfa.8737

Cited by 15 publications

(9 citation statements)

References 37 publications

(74 reference statements)

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“…The larger the b* value, the more obvious the yellow color of the sample. The results were similar to the existing research [27], within the normal range. Since the color change was mainly caused by browning reaction on the surface of potato tuber slices, the browning index was also used to evaluate the surface color in this study.…”

Section: Model Evaluationsupporting

confidence: 92%

“…Amjad et al [26] used HSI to characterize the water content and chromaticity of potato tuber slices during the convective hot air drying process. Moscetti et al [27] further studied the changes of water content and browning of potato tuber slices during hot-air drying by HSI, which both confirmed the feasibility of applying HSI for determination of water content and color in potato tuber slices. However, despite these miscellaneous applications, only few studies have focused on rapid visualization of color and water content of fresh-cut potato chips simultaneously under normal temperature storage conditions using HSI.…”

Section: Introductionmentioning

confidence: 78%

“…The average of these ten measurements was selected as the chromaticity value of the sample. In addition, we used the average value of L*, a* and b* to calculate the browning index (BI) [28] and luminance/yellowness ratio (L*/b* ratio) [27].…”

Section: Color Measurement and Water Content Measurementmentioning

confidence: 99%

“…The greater the browning index, the more pronounced the browning of the surface. In the research of Moscetti et al [27], quality inspection of potato was carried out during hot air drying process, L*/b* was also used as an indicator to evaluate the color of potato tuber slices. L*/b* decreased as the color deepened.…”

Section: Model Evaluationmentioning

confidence: 99%

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Rapid Screen of the Color and Water Content of Fresh-Cut Potato Tuber Slices Using Hyperspectral Imaging Coupled with Multivariate Analysis

Xiao

Bai

2020

Foods

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Color index and water content are important indicators for evaluating the quality of fresh-cut potato tuber slices. In this study, hyperspectral imaging combined with multivariate analysis was used to detect the color parameters (L*, a*, b*, Browning index (BI), L*/b*) and water content of fresh-cut potato tuber slices. The successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) were used to extract characteristic wavelengths, partial least squares (PLS) and least squares support vector machine (LS-SVM) were utilized to establish regression models. For color prediction, R2c, R2p and RPD of all the LSSVM models established for the five color indicators L*, a*, b*, BI, L*/b* were exceeding 0.90, 0.84 and 2.1, respectively. For water content prediction, R2c, R2p, and RPD of the LSSVM models were over 0.80, 0.77 and 1.9, respectively. LS-SVM model based on full spectra was used to reappear the spatial distribution of color and water content in fresh-cut potato tuber slices by pseudo-color imaging since it performed best in most cases. The results illustrated that hyperspectral imaging could be an effective method for color and water content prediction, which could provide solid theoretical basis for subsequent grading and processing of fresh-cut potato tuber slices.

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Section: Model Evaluationsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 78%

Section: Color Measurement and Water Content Measurementmentioning

confidence: 99%

Section: Model Evaluationmentioning

confidence: 99%

See 2 more Smart Citations

Rapid Screen of the Color and Water Content of Fresh-Cut Potato Tuber Slices Using Hyperspectral Imaging Coupled with Multivariate Analysis

Xiao

Bai

2020

Foods

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“…Further studies using hyperspectral imaging on apples [11], meat [12] and potatoes [13,14] show similarly promising results. A reduction of the wavelengths needed for detection of product features will allow for the transfer to simpler systems, e.g.…”

Section: Fig 2: Normalised Moisture Distribution For Apple Slices Befmentioning

confidence: 86%

Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies

Sturm

Moscetti

Crichton

et al. 2018

Proceedings of 21th International Drying Symposium

Self Cite

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Drying is a complex, dynamic, unsteady and nonlinear process that, when not optimized on a system level, may be responsible for (1) significant quality degradation and (2) energy wastage. Consequently, new drying technologies must be designed combining non-invasive at-/on-/in-line advanced measurement and control systems with models cross-linking all relevant aspects of product quality changes and heat and mass transfer phenomena. This paper presents preliminary results on the use of RGB imaging, NIR spectroscopy and Vis-NIR hyperspectral imaging for real-time monitoring of physicochemical changes of apples and carrots during drying. Keywords: chemometrics, artificial intelligence, deep learning

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A Systematized Review on the Applications of Hyperspectral Imaging for Quality Control of Potatoes

Peraza-Alemán,

López-Maestresalas,

Jarén

et al. 2024

Potato Res.

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The application of hyperspectral imaging (HSI) has gained significant importance in the past decade, particulary in the context of food analysis, including potatoes. However, the current literature lacks a comprehensive systematic review of the application of this technique in potato cultivation. Therefore, the aim of this work was to conduct a systematized review by analysing the most relevant compounds, diseases and stress factors in potatoes using hyperspectral imaging. For this purpose, scientific studies were retrieved through a systematic keyword search in Web of Science and Scopus databases. Studies were only included in the review if they provided at least one set of quantitative data. As a result, a total of 52 unique studies were included in the review. Eligible studies were assigned an in-house developed quality scale identifying them as high, medium or low risk. In most cases the studies were rated as low risk. Finally, a comprehensive overview of the HSI applications in potatoes was performed. It has been observed that most of the selected studies obtained better results using linear methods. In addition, a meta-analysis of studies based on regression and classification was attempted but was not possible as not enough studies were found for a specific variable.

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Postharvest monitoring of organic potato (cv. Anuschka) during hot‐air drying using visible–NIR hyperspectral imaging

Cited by 15 publications

References 37 publications

Rapid Screen of the Color and Water Content of Fresh-Cut Potato Tuber Slices Using Hyperspectral Imaging Coupled with Multivariate Analysis

Rapid Screen of the Color and Water Content of Fresh-Cut Potato Tuber Slices Using Hyperspectral Imaging Coupled with Multivariate Analysis

Feasibility of Vis/NIR spectroscopy and image analysis as basis of the development of smart-drying technologies

A Systematized Review on the Applications of Hyperspectral Imaging for Quality Control of Potatoes

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