Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
2.4
3.1
Journals
Horticulturae
Special Issues
Postharvest Handling and Nondestructive Detection of Fresh Horticulture Crops
share announcement

Postharvest Handling and Nondestructive Detection of Fresh Horticulture Crops

A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Postharvest Biology, Quality, Safety, and Technology".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 4883

Special Issue Editors

Dr. Xiuxiu Sun

E-Mail Website
Guest Editor
United States Department of Agriculture, Agricultural Research Service, Daniel K. Inouye U.S. Pacific Basin Agricultural Research Center, 64 Nowelo St., Hilo, HI 96720, USA
Interests: active packaging; encapsulation; antimicrobial; antioxidant; postharvest preservation
Special Issues, Collections and Topics in MDPI journals
Dr. Sai Xu

E-Mail Website
Guest Editor
Institute of Facility Agriculture of Guangdong Academy of Agricultural Sciences, No. 2 Baishigang Street, Wushan Road, Tianhe District, Guangzhou 510642, China
Interests: food quality; nondestructive detection, intelligent recognition; post harvest technology
Dr. Libin Wang

E-Mail
Guest Editor
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, 40 Dianjiangtai Rd., Nanjing 210031, China
Interests: food quality; postharvest technology; fruit preservation

Special Issue Information

Dear Colleagues,

Fresh fruits and vegetables are an important part of the human diet. They exist in a great variety of flavors and nutritional content. However, many fruits and vegetables have a short shelf life, especially when they are not appropriately handled after harvest. Considerable postharvest loss of fruits and vegetables not only costs time, effort, and money to dispose of or wastes the money of the consumer, but the extra activity can also result in otherwise unnecessary carbon emissions. In addition, intelligent, fast, and nondestructive quality detection is the key to food grading and commercialization, and it is something the industry needs. Therefore, technologies and methods that extend the shelf life, reduce waste, and nondestructively detect fruit and vegetable quality are critical for consumers and society in general.

This Special Issue will focus on “Postharvest Handling and Nondestructive Detection of Fresh Horticulture Crops”. We are open to novel research, reviews, and opinion articles covering all aspects of postharvest research throughout the postharvest supply chain, including storage technologies, postharvest treatments, basic mechanisms, quality evaluation, nondestructive detection, intelligent recognition, packaging, handling, and distribution. Contributions on the physical, chemical, and sensory properties of fresh fruits and vegetables handled by different packaging, sanitation, decontamination, and other novel methods that extend their shelf life and maintain and detect their quality are welcome.

Dr. Xiuxiu Sun
Dr. Sai Xu
Dr. Libin Wang
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. Horticulturae is an international peer-reviewed open access monthly 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 2200 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

  • postharvest
  • packaging
  • food preservation
  • nondestructive detection
  • intelligent recognition

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 7135 KiB  
Article
Early Bruise Detection in Apple Based on an Improved Faster RCNN Model
by Jingli Hou, Yuhang Che, Yanru Fang, Hongyi Bai and Laijun Sun
Horticulturae 2024, 10(1), 100; https://doi.org/10.3390/horticulturae10010100 - 20 Jan 2024
Viewed by 903
Abstract
Bruising is a common occurrence in apples that can lead to gradual fruit decay and substantial economic losses. Due to the lack of visible external features, the detection of early-stage bruising (occurring within 0.5 h) is difficult. Moreover, the identification of stems and [...] Read more.
Bruising is a common occurrence in apples that can lead to gradual fruit decay and substantial economic losses. Due to the lack of visible external features, the detection of early-stage bruising (occurring within 0.5 h) is difficult. Moreover, the identification of stems and calyxes is also important. Here, we studied the use of the short-wave infrared (SWIR) camera and the Faster RCNN model to enable the identification of bruises on apples. To evaluate the effectiveness of early bruise detection by SWIR bands compared to the visible/near-infrared (Vis/NIR) bands, a hybrid dataset with images from two cameras with different bands was used for validation. To improve the accuracy of the model in detecting apple bruises, calyxes, and stems, several improvements are implemented. Firstly, the Feature Pyramid Network (FPN) structure was integrated into the ResNet50 feature extraction network. Additionally, the Normalization-based Attention Module (NAM) was incorporated into the residual network, serving to bolster the attention of model towards detection targets while effectively mitigating the impact of irrelevant features. To reduce false positives and negatives, the Intersection over Union (IoU) metric was replaced with the Complete-IoU (CIoU). Comparison of the detection performance of the Faster RCNN model, YOLOv4P model, YOLOv5s model, and the improved Faster RCNN model, showed that the improved model had the best evaluation indicators. It achieved a mean Average Precision (mAP) of 97.4% and F1 score of 0.87. The results of research indicate that it is possible to accurately and effectively identify early bruises, calyxes, and stems on apples using SWIR cameras and deep learning models. This provides new ideas for real-time online sorting of apples for the presence of bruises. Full article
(This article belongs to the Special Issue Postharvest Handling and Nondestructive Detection of Fresh Horticulture Crops)
►▼ Show Figures

Figure 1

13 pages, 2426 KiB  
Article
Effect of Humidity-Triggered Controlled-Release 1-Methylcyclopropene (1-MCP) on Postharvest Quality of Papaya Fruit
by Chang Shu, Marisa M. Wall, Peter A. Follett, Nobuko Sugimoto, Jinhe Bai and Xiuxiu Sun
Horticulturae 2023, 9(10), 1062; https://doi.org/10.3390/horticulturae9101062 - 22 Sep 2023
Cited by 1 | Viewed by 1050
Abstract
Papaya (Carica papaya L.) is a valuable economic crop that is widely cultivated in tropical and subtropical regions but has a short storage and shelf life. Exploring effective strategies to improve the postharvest quality of papaya is important. This study explored the [...] Read more.
Papaya (Carica papaya L.) is a valuable economic crop that is widely cultivated in tropical and subtropical regions but has a short storage and shelf life. Exploring effective strategies to improve the postharvest quality of papaya is important. This study explored the effect of humidity-triggered controlled-release 1-methylcyclopropene (1-MCP) sheets on the postharvest quality of papaya fruit. ‘Rainbow’ papayas underwent cold storage at 10 ± 0.5 °C, RH 85% ± 2% for 14 days, and then were transferred to 20 ± 0.5 °C, RH 85% ± 2% for 10 days to simulate shelf life. The 1-MCP sheets were cut into different sizes and placed in storage containers in advance to create corresponding concentrations at 0.5, 1.0, 2.0, and 4.0 ppm. Results showed that 1-MCP treatment inhibited fruit softening, and reduced weight loss and peel color deterioration without causing any physiological disorders. The 1.0–2.0 ppm 1-MCP-treated fruit received the highest score for papaya flavor and sweetness respectively and the lowest score for off-flavor. The humidity-triggered controlled-release 1-MCP sheets are effective and convenient, and they can serve as an important tool for regulating postharvest papaya ripening with economic benefits. Full article
(This article belongs to the Special Issue Postharvest Handling and Nondestructive Detection of Fresh Horticulture Crops)
►▼ Show Figures

Figure 1

16 pages, 6219 KiB  
Article
Role of Postharvest Oxalic Acid Treatment on Quality Properties, Phenolic Compounds, and Organic Acid Contents of Nectarine Fruits during Cold Storage
by Deniz Eroğul, Hakan Kibar, Fatih Şen and Muttalip Gundogdu
Horticulturae 2023, 9(9), 1021; https://doi.org/10.3390/horticulturae9091021 - 10 Sep 2023
Cited by 1 | Viewed by 980
Abstract
Due to the soft texture of the nectarine fruit, there are difficulties in long-term storage of this fruit. Therefore, it is of great importance to extend the postharvest storage period of this fruit species. In this study, the effect of postharvest OA (Oxalic [...] Read more.
Due to the soft texture of the nectarine fruit, there are difficulties in long-term storage of this fruit. Therefore, it is of great importance to extend the postharvest storage period of this fruit species. In this study, the effect of postharvest OA (Oxalic acid) applications (0, 0.5, 1 and 1.5 mM) on the quality and biochemical contents of nectarine fruits was investigated. On the 40th day of storage, 1.5 mM OA doses reduced weight loss (1.96%) and fruit flesh firmness (36 N) by approximately 44% and 20%, respectively, compared to the control group. The most effective dose in reducing the respiratory rate was again 1.5 mM OA. The 1 mM OA dose was determined to prevent the decay rate approximately by 16% compared to the control group. Organic acid contents showed a continuous decreasing trend during storage and malic acid was determined to be the dominant acid in nectarine fruits. At the end of storage, it was determined that a 1.5 mM OA dose prevented the decrease in malic acid content approximately 35% more than the control group. Chlorogenic acid and rutin were detected at a higher rate than other phenolics. It was observed that 1.5 mM OA dose prevented the breakdown of chlorogenic acid and rutin compounds more so than other doses during storage. In this study, it was determined that a 1.5 mM OA dose especially protected the quality properties and biochemical contents of nectarine fruits in the cold storage more than the control group. Full article
(This article belongs to the Special Issue Postharvest Handling and Nondestructive Detection of Fresh Horticulture Crops)
►▼ Show Figures

Figure 1

15 pages, 2615 KiB  
Article
Nondestructive Detecting Maturity of Pineapples Based on Visible and Near-Infrared Transmittance Spectroscopy Coupled with Machine Learning Methodologies
by Guangjun Qiu, Huazhong Lu, Xu Wang, Chen Wang, Sai Xu, Xin Liang and Changxiang Fan
Horticulturae 2023, 9(8), 889; https://doi.org/10.3390/horticulturae9080889 - 04 Aug 2023
Cited by 1 | Viewed by 1160
Abstract
Pineapple is mainly grown in tropical regions and consumed fresh worldwide due to its attractive flavor and health benefits. With increasing global production and trade volume, there is an urgent need for nondestructive techniques for accurate and efficient detection of the internal quality [...] Read more.
Pineapple is mainly grown in tropical regions and consumed fresh worldwide due to its attractive flavor and health benefits. With increasing global production and trade volume, there is an urgent need for nondestructive techniques for accurate and efficient detection of the internal quality of pineapples. Therefore, this study is dedicated to developing a nondestructive method for real-time determining the internal quality of pineapples by using VIS/NIR transmittance spectroscopy technique and machine learning methodologies. The VIS/NIR transmittance spectrums ranging in 400–1100 nm of total 195 pineapples were collected from a dynamic experimental platform. The maturity grade and soluble solids content (SSC) of individual pineapples were then measured as indicators of internal quality. The qualitative model for discriminating maturity grades of pineapple achieved a high accuracy of 90.8% by the PLSDA model for unknown samples. Meanwhile, the quantitative model for determining SSC also reached a determination coefficient (RP2) of 0.7596 and a root mean square error of prediction (RMSEP) of 0.7879 °Brix by the ANN-PLS model. Overall, high model performance demonstrated that using VIS/NIR transmittance spectroscopy technique coupled with machine learning methodologies could be a feasible method for nondestructive and real-time detection of the internal quality of pineapples. Full article
(This article belongs to the Special Issue Postharvest Handling and Nondestructive Detection of Fresh Horticulture Crops)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop