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Analysis of institutional authors

Collazos-Escobar, GaCorresponding AuthorBarrios-Rodríguez, YfCorresponding Author

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October 11, 2024
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Mid-infrared spectroscopy and machine learning as a complementary tool for sensory quality assessment of roasted cocoa-based products

Publicated to:Infrared Physics & Technology. 141 105482- - 2024-09-01 141(), DOI: 10.1016/j.infrared.2024.105482

Authors: Collazos-Escobar, Gentil A; Barrios-Rodriguez, Yeison Fernando; Bahamon-Monje, Andres F; Gutierrez-Guzman, Nelson

Affiliations

Univ Surcolombiana, Ctr Surcolombiano Invest Cafe CESURCAFE, Dept Ingn Agr - Author

Abstract

Monitoring sensory quality in cocoa-based products is time-consuming and requires expert panelists. Integrating Mid-infrared (MIR) spectroscopy and chemometric models is a promising tool for real-time quality inspection. This study evaluated machine learning (ML) models based on the latent relationship between spectral and sensory information to predict the overall quality of roasted cocoa. Fifty-four roasted cocoa samples were analyzed using ATR-FTIR in the 4000-650 cm(-1) range and sensory evaluated by four trained panelists. Spectral data were preprocessed using Multiplicative Scatter Correction (MSC) and combined with sensory data. Subsequently, the block-scale Principal Component Analysis (PCA) was performed. Secondly, a PCA was calibrated only on the spectral data to obtain uncorrelated regressors as input to the supervised ML techniques. Supported Vector Machine Regression Model (SVMR) and the Random Forest Regression Model (RFR) were used to predict the overall quality of roasted cocoa samples. The training (75 %) and validation (25 %) of the ML techniques were performed 1000 times, and the hyperparameters optimization of each method was assessed via multifactor Analysis of Variance (ANOVA). According to the tasting panel results, the cocoa beans from different growing areas, initially appeared to have similar sensory characteristics. However, using PCA, a distinction was identified in the northern beans. The SVMR and RFR models demonstrated an outstanding ability to describe the overall quality of roasted cocoa samples. Further, the statistical results revealed the potential of MIR coupled with SVMR as a reliable and robust tool for the rapid (CT < 0.02 s) and accurate prediction (MRE < 2 %, R-2 > 99.9 %) of the overall quality of roasted cocoa-based products. This work demonstrates that it is possible to implement artificial intelligence tools to support decisions in cocoa evaluation, ensuring compliance with quality standards and allowing segmentation according to origin and characteristics.

Keywords

Antioxidant capacityArtificial intelligenceBeansChocolateFunctional groupsMachine learningMid-infraredNon-destructive testingOptimizationQuality monitoringSelectionTransform

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Infrared Physics & Technology due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 63/179, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Physics, Applied. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Condensed Matter Physics.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-07-17:

  • WoS: 5
  • Scopus: 3

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-17:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 50 (PlumX).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Colombia.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Collazos Escobar, Gentil Andres) .

the authors responsible for correspondence tasks have been Collazos Escobar, Gentil Andres and Barrios Rodríguez, Yeison Fernando.