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Applied Sciences
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Applications of Remote Image Capture Systems in Agriculture Ⅱ
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Applications of Remote Image Capture Systems in Agriculture Ⅱ

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

Deadline for manuscript submissions: closed (20 March 2023) | Viewed by 6620
Related Special Issue: Applications of Remote Image Capture System in Agriculture

Special Issue Editors

Prof. Dr. José Miguel Molina Martínez

E-Mail Website
Guest Editor
Department of Agricultural Engineering, Technical University of Cartagena, 30202 Cartagena, Murcia, Spain
Interests: water resources management; irrigation; energy efficiency; smart agriculture; agriculture automation and control; computers and electronics in agriculture
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ginés García-Mateos

E-Mail Website
Guest Editor
Department of Computer Science and Systems, University of Murcia, 30100 Murcia, Spain
Interests: computer vision; image processing in agriculture; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Dr. Dolores Parras-Burgos

E-Mail Website
Guest Editor
Department of Structures, Construction and Graphic Expression, Universidad Politécnica de Cartagena, 30202 Cartagena, Murcia, Spain
Interests: industrial design in agriculture; augmented/virtual reality; CAD
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, image capture systems are increasingly being used in agricultural engineering as a means to obtain information of interest from crops, the soil, and the environment. Remote imaging systems are especially relevant, since they allow acquiring frequent and high-resolution information of great extensions. This Special Issue aims to address the applications of digital photography for the management of water resources, energy, pest and disease control, etc. in agriculture. The concept of remote image capture systems includes different types of devices (from satellites and drones, to digital cameras on the ground integrated in wireless sensor networks), different types of spectral information (from standard RGB images, to multispectral and hyperspectral images), different types of applications (water management, pest detection, yield estimation, plant monitoring, etc.), and different types of techniques (in the fields of image capture systems, image processing and analysis, computer vision and pattern recognition, decision support systems, etc.). Manuscripts covering these topics are invited to the present Special Issue.

In addition, there are some related publications free to be viewed in the old Special Issue:

https://www.mdpi.com/journal/applsci/special_issues/RICS_Agriculture

Prof. Dr. José Miguel Molina Martínez
Prof. Dr. Ginés García-Mateos
Dr. Dolores Parras-Burgos
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

  • Computer vision in agriculture
  • Digital photography
  • Agricultural engineering
  • Mathematical models
  • Hydrology
  • Energy efficiency
  • Multispectral and hyperspectral imaging systems
  • Drones and satellites in agriculture

Published Papers (3 papers)

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Research

15 pages, 2526 KiB  
Article
Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage
by Geonwoo Kim, Hoonsoo Lee, Seung Hwan Wi and Byoung-Kwan Cho
Appl. Sci. 2022, 12(18), 9340; https://doi.org/10.3390/app12189340 - 18 Sep 2022
Cited by 3 | Viewed by 1636
Abstract
Heat stress in particular can damage physiological processes, adaptation, cellular homeostasis, and yield of higher plants. Early detection of heat stress in leafy crops is critical for preventing extensive loss of crop productivity for global food security. Thus, this study aimed to evaluate [...] Read more.
Heat stress in particular can damage physiological processes, adaptation, cellular homeostasis, and yield of higher plants. Early detection of heat stress in leafy crops is critical for preventing extensive loss of crop productivity for global food security. Thus, this study aimed to evaluate the potential of a snapshot-based visible-near infrared multispectral imaging system for detecting the early stage of heat injury during the growth of Chinese cabbage. Two classification models based on partial least squares-discriminant analysis (PLS-DA) and least-squares support vector machine (LS-SVM) were developed to identify heat stress. Various vegetation indices (VIs), including the normalized difference vegetation index (NDVI), red-edge ratio (RE/R), and photochemical reflectance index (PRI), which are closely related to plant heat stress, were acquired from sample images, and their values were compared with the developed models for the evaluation of their discriminant performance of developed models. The highest classification accuracies for LS-SVM, PLS-DA, NDVI, RE/R, and PRI were 93.6%, 92.4%, 72.5%, 69.6%, and 58.1%, respectively, without false-positive errors. Among these methods for identifying plant heat stress, the developed LS-SVM and PLS-DA models showed more reliable discriminant performance than the traditional VIs. This clearly demonstrates that the developed models are much more effective and efficient predictive tools for detecting heat stress in Chinese cabbage in the early stages compared to conventional methods. The developed technique shows promise as an accurate and cost-effective screening tool for rapid identification of heat stress in Chinese cabbage. Full article
(This article belongs to the Special Issue Applications of Remote Image Capture Systems in Agriculture Ⅱ)
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18 pages, 5251 KiB  
Article
Non-Invasive Monitoring of the Thermal and Morphometric Characteristics of Lettuce Grown in an Aeroponic System through Multispectral Image System
by Coral Martinez-Nolasco, José A. Padilla-Medina, Juan J. Martinez Nolasco, Ramon Gerardo Guevara-Gonzalez, Alejandro I. Barranco-Gutiérrez and José J. Diaz-Carmona
Appl. Sci. 2022, 12(13), 6540; https://doi.org/10.3390/app12136540 - 28 Jun 2022
Cited by 6 | Viewed by 2780
Abstract
Aeroponics is a soilless cultivation technology integrating plant nutrition, physiology, ecological environment, agricultural automation and horticulture. One of the soilless advantages is that a non-invasive observation of the root system growth development is possible. This paper presents a vegetative growth evaluation of lettuce [...] Read more.
Aeroponics is a soilless cultivation technology integrating plant nutrition, physiology, ecological environment, agricultural automation and horticulture. One of the soilless advantages is that a non-invasive observation of the root system growth development is possible. This paper presents a vegetative growth evaluation of lettuce plants in an aeroponic chamber, where root and leaf development parameters were measured in three lettuce crops through plant images captured in the visible (VIS), near infrared (NIR) and far infrared (IR) spectra. A total of ninety lettuce plants was transplanted for this research, thirty for each experimental crop. The three lettuce crops were grown for thirty days in an aeroponic growth plant chamber inside a greenhouse under favorable conditions. The morphometric and thermal parameters of the lettuce roots (perimeter, area, length and average temperature) and leaves (perimeter, area and average temperature) were evaluated for each crop along ten image-capturing sessions through an implemented multispectral vision system. The average values of the root and leaf morphometric parameters obtained with the implemented imaging system along the lettuce growing period were statistically analyzed with Tukey testing. The obtained analysis results show no significant difference for a value of p ≤ 0.05 in 86.67%. Hence, the morphometric parameters can be used to characterize the vegetative lettuce growth in aeroponic crops. On the other hand, a correlation analysis was conducted between the thermal parameters computed with the root and leaf thermal image processing and the measured ambient temperature. The results were: R = 0.945 for correlation between ambient and leaf temperature, R = 0.963 for correlation between ambient and root temperature and R = 0.977 for leaf and root temperature. According to these results, the plant temperature is highly correlated with the ambient temperature in an aeroponic crop. The obtained study results suggest that multispectral image processing is a useful non-invasive tool to estimate the vegetative root and leaf growth parameters of aeroponic lettuce plants in a greenhouse. Full article
(This article belongs to the Special Issue Applications of Remote Image Capture Systems in Agriculture Ⅱ)
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16 pages, 17752 KiB  
Article
Effects of Cropland Expansion on the Regional Land Surface Radiative Energy Balance and Heat Fluxes in Northern China
by Jia Ning
Appl. Sci. 2021, 11(4), 1556; https://doi.org/10.3390/app11041556 - 9 Feb 2021
Cited by 4 | Viewed by 1404
Abstract
Land use change can impact the land surface radiation budget and energy balance by changing surface biophysical processes. Based on satellite remote sensing data and land use data from 2000 to 2015, we quantitatively estimated radiative forcing induced by cropland expansion during the [...] Read more.
Land use change can impact the land surface radiation budget and energy balance by changing surface biophysical processes. Based on satellite remote sensing data and land use data from 2000 to 2015, we quantitatively estimated radiative forcing induced by cropland expansion during the early 21st century in northern China. The results showed that heat flux from the land surface to the atmosphere due to cropland expansion was quite variable in different climate zones. The heat flux increased in humid North China, whereas it decreased in arid Northwest China, semiarid Inner Mongolia, and humid Northeast China. Cropland expansion from woodland areas led to a general decline in the land surface heat flux to the atmosphere, which led to a cooling effect on the climate. The surface heat flux to the atmosphere due to cropland expansion in grassland areas displayed significant variations in different climate zones. The surface heat flux decreased only in humid Northeast China and arid Northwest China. The net surface radiation and latent heat flux both increased when grasslands were changed into cropland, but to different extents, which produced the differences in the surface heat flux to the atmosphere between different zones. Full article
(This article belongs to the Special Issue Applications of Remote Image Capture Systems in Agriculture Ⅱ)
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