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Sensing and Imaging for the Monitoring of Seeds and Plants

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 3137

Special Issue Editors

School of Molecular and Life Sciences, Curtin University, Perth 6845, Australia
Interests: ecological restoration; seed biology; community ecology and phytosociology; freshwater aquatic ecosystems; conservation biology
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Guest Editor
School of Spatial Sciences, Curtin University, Perth, Australia
Interests: photogrammetry; remote sensing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Laboratory of Rehabilitation and Ecological Restoration of Arid and Semiarid Ecosystems (LARREA), National University of Comahue, CP 8300 Neuquén, Argentina
Interests: ecological restoration; seed ecology

Special Issue Information

Dear Colleagues,

Sensors of all kinds, and mounted on a variety of platforms, are increasingly being used to monitor natural and human-influenced landscapes right around the world. However, recently there has been an increased focus upon the use of sensors to monitor plants and vegetation, whether this be in urban areas, agricultural systems, or natural ecosystems. Such monitoring occurs for a great variety of purposes, from assessment of crop yield and phenology to plant health or the assessment of ecosystem trajectory in landscapes undergoing rehabilitation or ecological restoration. This Special Issue welcomes empirical research of all kinds, in all ecosystems, that expands or improves the use of sensors to monitor plants at every life cycle stage, including as seeds, and enhances our mechanistic understanding of how sensor data can be examined or analysed to provide meaningful information about the ecology, physiology or growth of plants and vegetation.

Dr. Adam T. Cross
Dr. David Belton
Dr. Daniel Roberto Perez
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. Sensors 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 2600 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

  • remote sensing (including all sub-keywords such as drone, UAV, RPAS, satellite, LiDAR, multispectral, hyperspectral, and thermal)
  • ecology
  • vegetation
  • ecosystem trajectory
  • monitoring

Published Papers (1 paper)

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Research

13 pages, 1757 KiB  
Article
High-Throughput Phenotyping Approach for the Evaluation of Heat Stress in Korean Ginseng (Panax ginseng Meyer) Using a Hyperspectral Reflectance Image
by Eunsoo Park, Yun-Soo Kim, Mohammad Kamran Omari, Hyun-Kwon Suh, Mohammad Akbar Faqeerzada, Moon S. Kim, Insuck Baek and Byoung-Kwan Cho
Sensors 2021, 21(16), 5634; https://0-doi-org.brum.beds.ac.uk/10.3390/s21165634 - 21 Aug 2021
Cited by 15 | Viewed by 2126
Abstract
Panax ginseng has been used as a traditional medicine to strengthen human health for centuries. Over the last decade, significant agronomical progress has been made in the development of elite ginseng cultivars, increasing their production and quality. However, as one of the significant [...] Read more.
Panax ginseng has been used as a traditional medicine to strengthen human health for centuries. Over the last decade, significant agronomical progress has been made in the development of elite ginseng cultivars, increasing their production and quality. However, as one of the significant environmental factors, heat stress remains a challenge and poses a significant threat to ginseng plants’ growth and sustainable production. This study was conducted to investigate the phenotype of ginseng leaves under heat stress using hyperspectral imaging (HSI). A visible/near-infrared (Vis/NIR) and short-wave infrared (SWIR) HSI system were used to acquire hyperspectral images for normal and heat stress-exposed plants, showing their susceptibility (Chunpoong) and resistibility (Sunmyoung and Sunil). The acquired hyperspectral images were analyzed using the partial least squares-discriminant analysis (PLS-DA) technique, combining the variable importance in projection and successive projection algorithm methods. The correlation of each group was verified using linear discriminant analysis. The developed models showed 12 bands over 79.2% accuracy in Vis/NIR and 18 bands with over 98.9% accuracy at SWIR in validation data. The constructed beta-coefficient allowed the observation of the key wavebands and peaks linked to the chlorophyll, nitrogen, fatty acid, sugar and protein content regions, which differentiated normal and stressed plants. This result shows that the HSI with the PLS-DA technique significantly differentiated between the heat-stressed susceptibility and resistibility of ginseng plants with high accuracy. Full article
(This article belongs to the Special Issue Sensing and Imaging for the Monitoring of Seeds and Plants)
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