Valorization of Foods: From Tradition to Innovation

Aquilanti, Lucia; Osimani, Andrea; Cardinali, Federica; Clementi, Francesca; Foligni, Roberta; Garofalo, Cristiana; Loreto, Nino; Mandolesi, Serena; Milanović, Vesna; Mozzon, Massimo; Naspetti, Simona; Pasquini, Marina; Roncolini, Andrea; Ruschioni, Sara; Sabbatini, Riccardo; Solfanelli, Francesco; Trombetta, M. F.; Vairo, Daniela; Zanoli, Raffaele

doi:10.1007/978-3-030-33832-9_36

Cited by 2 publications

(2 citation statements)

References 89 publications

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“…The exploitation of eye-tracking data, as is well known, has proven to be valuable in many domains such as food [21], neuromarketing [22,23] and many more. Its benefits lie in the detection of the eye's movements, which can be collected when users interact with computer interfaces.…”

Section: Related Workmentioning

confidence: 99%

A Visual Attentive Model for Discovering Patterns in Eye-Tracking Data—A Proposal in Cultural Heritage

Pierdicca

Paolanti

Quattrini

et al. 2020

Sensors

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In the Cultural Heritage (CH) context, art galleries and museums employ technology devices to enhance and personalise the museum visit experience. However, the most challenging aspect is to determine what the visitor is interested in. In this work, a novel Visual Attentive Model (VAM) has been proposed that is learned from eye tracking data. In particular, eye-tracking data of adults and children observing five paintings with similar characteristics have been collected. The images are selected by CH experts and are—the three “Ideal Cities” (Urbino, Baltimore and Berlin), the Inlaid chest in the National Gallery of Marche and Wooden panel in the “Studiolo del Duca” with Marche view. These pictures have been recognized by experts as having analogous features thus providing coherent visual stimuli. Our proposed method combines a new coordinates representation from eye sequences by using Geometric Algebra with a deep learning model for automated recognition (to identify, differentiate, or authenticate individuals) of people by the attention focus of distinctive eye movement patterns. The experiments were conducted by comparing five Deep Convolutional Neural Networks (DCNNs), yield high accuracy (more than 80 %), demonstrating the effectiveness and suitability of the proposed approach in identifying adults and children as museums’ visitors.

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Section: Related Workmentioning

confidence: 99%

A Visual Attentive Model for Discovering Patterns in Eye-Tracking Data—A Proposal in Cultural Heritage

Pierdicca

Paolanti

Quattrini

et al. 2020

Sensors

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“…The mistrust about food manufactured at the industrial level using cutting-edge technologies could be one of the reasons for the renewed interest in traditional food. It is undeniable that traditional food, along with typical food, besides being referenced starting blocks for food innovation, represent an invaluable legacy to be protected [1]. European Policy on agri-food quality includes the protection of agricultural and food products through appropriate designations, namely, Protected Designation of Origin (PDO), Protected Geographical Indication (PGI), and Traditional Specialty Guaranteed (TSG).…”

Section: Introductionmentioning

confidence: 99%

Distinctive Traits of Four Apulian Traditional Agri-Food Product (TAP) Cheeses Manufactured at the Same Dairy Plant

Celano

Costantino

Calasso

et al. 2022

Foods

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This study aimed to highlight the distinctive features of four Traditional Agri-food Products (TAP), namely, Caprino, Pecorino, Vaccino, and Cacioricotta cheeses produced at the same dairy plant to reveal any possible relationships between their microbiological and biochemical characteristics. Two distinct natural whey starter (NWS) cultures were used during Caprino and Vaccino cheesemaking, whereas no starter was used for the other cheeses. Cacioricotta retained the highest concentrations of salt and residual carbohydrates. Lactic acid bacteria dominated the microbiota of the cheeses. Furthermore, staphylococci represented an additional dominant microbial population in Cacioricotta. Although culture-dependent analysis showed that the use of NWS cultures only slightly affected the microbial community of cheeses, 16S metagenetic analysis showed that Lactobacillus helveticus dominated both the NWS cultures and the corresponding Caprino and Vaccino cheeses. This analysis indicated that Staphylococcus equorum and Streptococcus thermophilus dominated Cacioricotta and Pecorino cheeses, respectively. The highest peptidase activities were found in either Caprino or Vaccino. Enzymes involved in the catabolism of free amino acids and esterase showed the highest activity in Pecorino cheese. Each cheese showed a distinct profile of volatile organic compounds, with Pecorino being the richest cheese in carboxylic acids, ketones, and esters, related to lipolysis. The results of this study contribute to valorizing and safeguarding these TAP cheeses, sustaining local farming.

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Valorization of Foods: From Tradition to Innovation

Cited by 2 publications

References 89 publications

A Visual Attentive Model for Discovering Patterns in Eye-Tracking Data—A Proposal in Cultural Heritage

A Visual Attentive Model for Discovering Patterns in Eye-Tracking Data—A Proposal in Cultural Heritage

Distinctive Traits of Four Apulian Traditional Agri-Food Product (TAP) Cheeses Manufactured at the Same Dairy Plant

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