Application of Non-destructive Detection Techniques in Horticultural Plants

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: 20 January 2025 | Viewed by 415

Special Issue Editors


E-Mail Website
Guest Editor
Department of Agriculture, Food, Natural Science, Engineering, University of Foggia, Via Napoli 25, 71122 Foggia, Italy
Interests: spectroscopy; image acquisition; digital image processing product packaging; postharvest technique; chemometrics
College of Food Science and Engineering, Tianjin University Science and Technology, State Key Laboratory of Food Nutrition and Safety, Tianjin 300457, China
Interests: postharvest physiology; ripening and senescence; postharvest pathology; immune response of fruits; storage and processing of agriculture products; fruit microbiome
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
Interests: hyperspectral imaging; spectral analysis; chemometrics; nondestructive sensing

Special Issue Information

Dear Colleagues,

Non-destructive detection techniques have recently emerged as a powerful analytical technique with the advantages of fast speed, convenient operation, and easy online inspection of various horticultural products. In recent years, non-destructive detection techniques (such as visible, near- and mid-infrared spectroscopy (VIS-NIRS), fluorescence spectroscopy, hyperspectral imaging (HSI), X-ray imaging, CT scan imaging, electronic nose, machine vision, and thermal imaging) have found numerous successful applications in horticultural product quality detection. These techniques are used to determine quality features and analyze horticultural products in a non-destructive way with minimal sample preparation. The resulting datasets are usually high dimensional and complex, requiring methods of pattern recognition or predictive analysis to extract quality information. This Special Issue aims to focus on the latest research progress of the application and jointly discuss the focus of non-destructive detection techniques in horticultural products.

Dr. Danial Fatchurrahman
Dr. Laifeng Lu
Dr. Anisur Rahman
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

  • non-destructive detection technique
  • visible spectroscopy
  • near-infrared spectroscopy
  • short-infrared spectroscopy
  • fluorescence spectroscopy
  • hyperspectral imaging
  • X-ray imaging
  • thermal imaging
  • machine vision
  • electronic nose

Published Papers

This special issue is now open for submission.
Back to TopTop