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The Key Technology of Fresh Fruit and Vegetable Logistics Preservation
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The Key Technology of Fresh Fruit and Vegetable Logistics Preservation

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Packaging and Preservation".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 14460

Special Issue Editors

Prof. Dr. Zisheng Luo

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Guest Editor
College of Biosystems Engineering and Food Science, Key Laboratory of Agro-Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang Key Laboratory for Agro-Food Processing, National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment, Zhejiang University, Hangzhou 310058, China
Interests: food quality and safety control; food nutrition evaluation; environment-friendly food preservation; postharvest physiology; logistics technology
Special Issues, Collections and Topics in MDPI journals
Dr. Yanqun Xu

E-Mail Website
Guest Editor
College of Biosystems Engineering and Food Science, Key Laboratory of Agro-Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang Key Laboratory for Agro-Food Processing, National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment, Zhejiang University, Hangzhou 310058, China
Interests: food preservation; postharvest disease; biocontrol; plant disease resistance; fungi pathogen
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Fresh fruits and vegetables are perishable food, susceptible to microbial decay, and with a short shelf life. The distant transportation from fresh produce to markets means large quality loss during the logistics stage if suitable preservation technologies are not used. In addition, due to the increasing consumer awareness and rapidly changing lifestyles, there has been a global, exponential increase in the demand for healthy, fresh food products, especially fresh fruits and vegetables. It is necessary to adopt proper postharvest logistics technologies in order to preserve the initial quality and limit microbial decay in the fresh-keeping industry.

Therefore, this Special Issue on “The Key Technology of Fresh Fruit and Vegetable Logistics Preservation” is inviting researchers to submit their latest findings in this area in the form of original research papers, review articles, and short communications.

Topics covered in this Special Issue include (but are not limited to)

  1. Physiological and biochemical changes of fresh fruits and vegetables during postharvest storage and transportation;
  2. Advances in postharvest strategies to maintain fruit quality and nutrition;
  3. Systematic and in-depth studies about postharvest preservation mechanisms;
  4. Novel packaging materials applied to the fresh-keeping industry for quality and safety;
  5. Advances in cold chain logistics for the fruit and vegetable industry;
  6. Developments in the handling and distribution technology of fresh fruits and vegetables.

Prof. Dr. Zisheng Luo
Dr. Yanqun Xu
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. Foods 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 2900 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

  • fruit and vegetables
  • logistics preservation
  • postharvest physiology
  • postharvest treatment
  • novel packaging materials
  • handling and distribution technology

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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18 pages, 4526 KiB  
Article
Classification of Strawberry Maturity Stages and Varieties Using Neural Networks Based on Volatile Organic Compounds
by Jing Huang, Xuenan Zhang, Hang Yang, Zhenbiao Li, Zhengfang Xue, Qingqing Wang, Xinyuan Zhang, Shenghua Ding, Zisheng Luo and Yanqun Xu
Foods 2025, 14(2), 169; https://doi.org/10.3390/foods14020169 - 8 Jan 2025
Viewed by 1244
Abstract
Volatile organic compounds (VOCs) are closely associated with the maturity and variety of strawberries. However, the complexity of VOCs hinders their potential application in strawberry classification. This study developed a novel classification workflow using strawberry VOC profiles and machine learning (ML) models for [...] Read more.
Volatile organic compounds (VOCs) are closely associated with the maturity and variety of strawberries. However, the complexity of VOCs hinders their potential application in strawberry classification. This study developed a novel classification workflow using strawberry VOC profiles and machine learning (ML) models for precise fruit classification. A comprehensive VOC dataset was rapidly collected using gas chromatography-ion mobility spectrometry (GC-IMS) from five strawberry varieties at four maturity stages (n = 300) and visualized through principal component analysis (PCA). Five ML models were developed, including partial least squares discriminant analysis (PLS-DA), decision trees, support vector machines (SVM), Xgboost and neural networks (NN). The accuracy of all models ranged from 90.00% to 98.33%, with the NN model demonstrating the best performance. Specifically, it achieved 96.67% accuracy for single-maturity classification, 98.33% for single-variety classification, and 96.67% for dual maturity and variety classification, along with 98.09% precision, 97.92% recall, and 97.91% F1 score. Feature importance analysis indicated that the NN model exhibited the most balanced reliance on various VOCs, contributing to its optimal performance with the broad-spectrum VOC detection method, GC-IMS. Overall, these findings underscore the potential of NN modeling for accurate and efficient fruit classification based on integrated VOC profiles. Full article
(This article belongs to the Special Issue The Key Technology of Fresh Fruit and Vegetable Logistics Preservation)
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20 pages, 5392 KiB  
Article
Early Discrimination and Prediction of C. fimbriata-Infected Sweetpotatoes during the Asymptomatic Period Using Electronic Nose
by Jiawen Wu, Linjiang Pang, Xiaoqiong Zhang, Xinghua Lu, Liqing Yin, Guoquan Lu and Jiyu Cheng
Foods 2022, 11(13), 1919; https://doi.org/10.3390/foods11131919 - 28 Jun 2022
Cited by 19 | Viewed by 2728
Abstract
Sweetpotato is prone to disease caused by C. fimbriata without obvious lesions on the surface in the early period of infection. Therefore, it is necessary to explore the possibility of developing an efficient early disease detection method for sweetpotatoes that can be used [...] Read more.
Sweetpotato is prone to disease caused by C. fimbriata without obvious lesions on the surface in the early period of infection. Therefore, it is necessary to explore the possibility of developing an efficient early disease detection method for sweetpotatoes that can be used before symptoms are observed. In this study, sweetpotatoes were inoculated with C. fimbriata and stored for different lengths of time. The total colony count was detected every 8 h; HS-SPME/GC–MS and E-nose were used simultaneously to detect volatile compounds. The results indicated that the growth of C. fimbriata entered the exponential phase at 48 h, resulting in significant differences in concentrations of volatile compounds in infected sweetpotatoes at different times, especially toxic ipomeamarone in ketones. The contents of volatile compounds were related to the responses of the sensors. E-nose was combined with multiple chemometrics methods to discriminate and predict infected sweetpotatoes at 0 h, 48 h, 64 h, and 72 h. Among the methods used, linear discriminant analysis (LDA) had the best discriminant effect, with sensitivity, specificity, precision, and accuracy scores of 100%. E-nose combined with K-nearest neighbours (KNN) achieved the best predictions for ipomeamarone contents and total colony counts. This study illustrates that E-nose is a feasible and promising technology for the early detection of C. fimbriata infection in sweetpotatoes during the asymptomatic period. Full article
(This article belongs to the Special Issue The Key Technology of Fresh Fruit and Vegetable Logistics Preservation)
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11 pages, 2547 KiB  
Article
ε-Poly-l-Lysine Enhances Fruit Disease Resistance in Postharvest Longans (Dimocarpus longan Lour.) by Modulating Energy Status and ATPase Activity
by Junzheng Sun, Hongbin Chen, Yihui Chen, Mengshi Lin, Yen-Con Hung, Yuji Jiang and Hetong Lin
Foods 2022, 11(5), 773; https://doi.org/10.3390/foods11050773 - 7 Mar 2022
Cited by 20 | Viewed by 3162
Abstract
ε-poly-l-lysine (ε-PL) holds a strong antibacterial property and is widely used for food preservation. However, the application of ε-PL to enhance fruit disease resistance in postharvest longans (Dimocarpus longan Lour.) has not been explored. The objective of this study was [...] Read more.
ε-poly-l-lysine (ε-PL) holds a strong antibacterial property and is widely used for food preservation. However, the application of ε-PL to enhance fruit disease resistance in postharvest longans (Dimocarpus longan Lour.) has not been explored. The objective of this study was to explore the impact of ε-PL treatment on disease occurrence and energy metabolism of longans infected with Phomopsis longanae Chi (P. longanae). It was found that, in comparison with P. longanae-inoculated longans, ε-PL could decrease the fruit disease index and adenosine monophosphate (AMP) content, increase the amounts of adenosine triphosphate (ATP), adenosine diphosphate (ADP), and energy charge, and enhance the activities of adenosine triphosphatase (ATPase) (such as H+-, Mg2+-, and Ca2+-ATPase) in the mitochondria, protoplasm, and vacuole. The results suggest that the higher levels of ATPase activity and energy status played essential roles in disease resistance of postharvest longan fruit. Therefore, the ε-PL treatment can be used as a safe and efficient postharvest method to inhibit the disease occurrence of longan fruit during storage at room temperature. Full article
(This article belongs to the Special Issue The Key Technology of Fresh Fruit and Vegetable Logistics Preservation)
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Review

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21 pages, 371 KiB  
Review
Ambient Parameter Monitoring in Fresh Fruit and Vegetable Supply Chains Using Internet of Things-Enabled Sensor and Communication Technology
by Anna Lamberty and Judith Kreyenschmidt
Foods 2022, 11(12), 1777; https://doi.org/10.3390/foods11121777 - 16 Jun 2022
Cited by 33 | Viewed by 6072
Abstract
Up to half of the global fruit and vegetable production is wasted or lost along the supply chain, causing wastage of resources and economic losses. Ambient parameters strongly influence quality and shelf life of fresh fruit and vegetables. Monitoring these parameters by using [...] Read more.
Up to half of the global fruit and vegetable production is wasted or lost along the supply chain, causing wastage of resources and economic losses. Ambient parameters strongly influence quality and shelf life of fresh fruit and vegetables. Monitoring these parameters by using Internet of Things (IoT)-enabled sensor and communication technology in supply chains can help to optimize product qualities and hence reduce product rejections and losses. Various corresponding technical solutions are available, but the diverse characteristics of fresh plant-based produce impede establishing valuable applications. Therefore, the aim of this review is to give an overview of IoT-enabled sensor and communication technology in relation to the specific quality and spoilage characteristics of fresh fruit and vegetables. Temperature, relative humidity (RH), O2, CO2 and vibration/shock are ambient parameters that provide most added value regarding product quality optimization, and can be monitored by current IoT-enabled sensor technology. Several wireless communication technologies are available for real-time data exchange and subsequent data processing and usage. Although many studies investigate the general possibility of monitoring systems using IoT-enabled technology, large-scale implementation in fresh fruit and vegetable supply chains is still hindered by unsolved challenges. Full article
(This article belongs to the Special Issue The Key Technology of Fresh Fruit and Vegetable Logistics Preservation)
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