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Applied Sciences
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Novel Analysis Techniques for Agri-Food Quality
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Novel Analysis Techniques for Agri-Food Quality

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 3167

Special Issue Editors

Dr. Alessio Tugnolo

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Guest Editor
Department of Agricultural and Environmental Sciences, University of Milan, 20122 Milan, Italy
Interests: biosystems engineering; sensors; agri-food sector; chemometrics; pre- and post-harvest
Dr. Roberto Beghi

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Guest Editor
Department of Agricultural and Environmental Sciences, Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy
Interests: biosystems engineering; optical analyses; agro-food sector; chemometrics; pre-postharvest
Special Issues, Collections and Topics in MDPI journals
Dr. Valentina Giovenzana

E-Mail Website
Guest Editor
Department of Agricultural and Environmental Sciences, University of Milan, 20122 Milan, Italy
Interests: optical analyses; agro-food sector; chemometrics; pre-postharvest
Special Issues, Collections and Topics in MDPI journals
Dr. Hugo M. Oliveira

E-Mail Website
Guest Editor
International Iberian Nanotechnology Laboratory (INL), 4700-004 Braga, Portugal
Interests: optical sensors; analytical chemistry; sample preparation; agri-food applications

Special Issue Information

Dear Colleagues,

The fourth industrial revolution (Industry 4.0) is characterized by, among others, (1) the bridging of the physical and digital world through cyber-physical systems, (2) closed-loop data models and remote-control systems and (3) the personalization/customization of products. The goal is to enable autonomous decision-making processes, to monitor assets and processes in real-time, and to enable real-time connected networks through early involvement of stakeholders, and vertical and horizontal integration of the food chain actors. In this scenario, there is a growing interest and a need for innovation also in the agri-food system (from pre-and post-harvest) through the development of new interconnected sensors (IoT).

Moreover, pre- and post-harvest management practices are critical factors to face the environmental and economic challenges arising from climate change, shortages of labor, and production costs escalation that affect the worldwide agri-food production. However, such a technological revolution is driving the development of smart strategies to support the producers for qualitative monitoring and decision-making processes. Within the technological toolbox already used, optical technologies are among the most suitable to address the current needs in terms of quality and quantity of information and sustainability.

Therefore, the aim of this Special Issue is to collect studies focused on agrifood new green non-invasive sensing techniques, with particular attention paid to automation and integration in field and/or real scale plants. The submitted papers can cover different topics: proximal sensing, product inspection and characterization, pre-harvest field or greenhouse applications, online or inline applications in post-harvest, food process control, monitoring application for food plants, distributed sensors network, new prototypes, multivariate control systems, and automation.

Dr. Alessio Tugnolo
Dr. Roberto Beghi
Dr. Valentina Giovenzana
Dr. Hugo M. Oliveira
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precision agriculture
  • new sensors
  • IoT
  • green technology
  • agri-food
  • Industry 4.0
  • proximal sensing
  • food quality control
  • food process

Published Papers (2 papers)

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Research

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13 pages, 2845 KiB  
Article
Investigating Crude Sesame Oil Sedimentation and Its Monitoring Using Laser Backscattering Imaging (LBI)
by Zhangkai Wu, Sebastian Romuli, Kiatkamjon Intani and Joachim Müller
Appl. Sci. 2023, 13(15), 9013; https://doi.org/10.3390/app13159013 - 07 Aug 2023
Viewed by 1184
Abstract
Sesame oil is a food and energy resource that is not used enough. Sedimentation of crude oil after pressing can remove particles and happens regardless of the producer’s intention. However, sedimentation of crude plant oil and its sensing technology are rarely studied. This [...] Read more.
Sesame oil is a food and energy resource that is not used enough. Sedimentation of crude oil after pressing can remove particles and happens regardless of the producer’s intention. However, sedimentation of crude plant oil and its sensing technology are rarely studied. This research studied crude sesame oil sedimentation and monitored it with low-cost laser backscattering imaging (LBI). In the discontinuous measurement, a 30-day sedimentation was conducted with oil samples sent to the lab LBI system for image capture. A scattering spot and an increasing Tyndall effect along the light path were seen. In the continuous measurement, an LBI system was mounted on a sedimentation tank for 30 days. The sedimentation curve, scattering images, and oil properties were checked. The sedimentation speed was about −7 mm/h, then less than −2 mm/h. The image features correlated well with the sedimentation interface height (R2 = 0.97) when the height was above −100 mm. The oil-particle-related properties (ash content, phosphorus content, carbon residue, and total contamination) dropped by at least 87%, water content decreased by 90%, and the oxidation-related properties (oxidation stability, γ-tocotrienol, δ-tocopherol, γ-tocopherol, and acid value) changed less significantly. The crude sesame oil sedimentation had two stages: diluted and hindered sedimentation. This research can help improve sedimentation tank and LBI system design and prevent unwanted sedimentation. Full article
(This article belongs to the Special Issue Novel Analysis Techniques for Agri-Food Quality)
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Review

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27 pages, 11930 KiB  
Review
Hyperspectral Imaging for Fresh-Cut Fruit and Vegetable Quality Assessment: Basic Concepts and Applications
by Sara Vignati, Alessio Tugnolo, Valentina Giovenzana, Alessia Pampuri, Andrea Casson, Riccardo Guidetti and Roberto Beghi
Appl. Sci. 2023, 13(17), 9740; https://doi.org/10.3390/app13179740 - 28 Aug 2023
Cited by 1 | Viewed by 1617
Abstract
During the last two decades, hyperspectral imaging (HSI) has been one of the most studied and applied techniques in the field of nondestructive monitoring systems for the fruit and vegetable supply chain. This review provides HSI technical aspects (i.e., device features) and data [...] Read more.
During the last two decades, hyperspectral imaging (HSI) has been one of the most studied and applied techniques in the field of nondestructive monitoring systems for the fruit and vegetable supply chain. This review provides HSI technical aspects (i.e., device features) and data analysis approaches (i.e., data processing and qualitative/quantitative modeling) for fresh-cut products, focusing on the different applications which the literature offers and the possible scale-up for process monitoring. Moreover, new frontiers in the development of possible process analytical technologies of cost-effective and hand-held HSI devices are presented and discussed. Even though the performance of these new proximal sensing tools needs to be carefully evaluated, new applicative research perspectives in the development of a proximal sensing approach based on HSI sensor networks are ready to be studied and developed for finding field applications (i.e., precision agriculture, food processing, and more) and enabling faster and more convenient analysis while maintaining the accuracy and capabilities of traditional HSI systems. Full article
(This article belongs to the Special Issue Novel Analysis Techniques for Agri-Food Quality)
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