Collection
Development of New Sensing Technology in Sustainable Farming and Smart Environmental Monitoring
- Submission status
- Closed
In recent years, new sensing technology and instruments, artificial intelligence, big data and Internet of Things have developed rapidly. The application of such technology and instruments has permeated almost all scientific research and production practices in all walks of life. Not unexpectedly, it has already had a profound impact on plant science. Almost all kinds of monitoring and culture instruments used in cell biology, molecular biology and plant physiology involve sensors (for example Electron microscope, artificial climate chamber, automatic time controller, PCR instrument, electrophoresis instrument, etc.). In macro scale, remote sensing technology for large-scale ecological and agricultural monitoring is the mainstream trend. It has been widely used in forest fire, soil moisture, pest and disease monitoring. In addition, Nondestructive sensing techniques was used to measure seeding and plant growth. Emerging Internet of Things (IoT) technological developments allowed for more effective and efficient management of land and agricultural products, opening up the possibility of a new paradigm for smart agriculture.
Although significant progress has been made in the field of new sensing technology in plant science, there is still insufficient scientific research and application and some technical difficulties still need to be resolved. Hence, it is urgent to combining new sensing technology in plant science.
Here, we propose a research topic that focuses on recent advances and research on theory and application of new sensing technology, such as deep learning, artificial intelligence, and big data by sensor technologies in agricultural and environmental monitoring. Our goal is to focus on new sensing technology in plant science. Besides, we also welcome studies which introduce some unconventional instruments and equipment for obtaining data in plant science research. Because they are also the original scientific technologies. In this topic, we welcome all article types published by Frontiers in Plant Science that show the recent research on sustainable farming, ecological and environmental monitoring. This topic will collect the relevant research papers including, but not limited to the below potential topics:
Potential topics include but are not limited to the following:
New sensing technology in sustainable farming
Plant growth estimation using optical remote sensing data
Sensors and applications in molecular biology related to plant
Sensors and applications under abiotic and biotic stresses
Sensors for nutrient and water use efficiency
IoT-based, AI or big data to facilitate the above
Editors
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Yuan Li ,
Yuan Li
Shaanxi Normal University, Xi'an, China
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Zhenxing Zhang
Northeast Normal University, Changchun, China
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Huiwen Yu
University of Copenhagen, Copenhagen, Denmark
Articles (22 in this collection)
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Improving the prediction performance of leaf water content by coupling multi-source data with machine learning in rice (Oryza sativa L.)
Authors (first, second and last of 11)
- Xuenan Zhang
- Haocong Xu
- Haibing He
- Content type: Research
- Open Access
- Published: 23 March 2024
- Article: 48
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LysipheN: a gravimetric IoT device for near real-time high-frequency crop phenotyping: a case study on common beans
Authors (first, second and last of 4)
- Duvan Pineda-Castro
- Harold Diaz
- Milan Oldřich Urban
- Content type: Research
- Open Access
- Published: 14 March 2024
- Article: 39
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Small- and medium-sized rice fields identification in hilly areas using all available sentinel-1/2 images
Authors (first, second and last of 8)
- Lihua Wang
- Hao Ma
- Yumiao Wang
- Content type: Research
- Open Access
- Published: 04 February 2024
- Article: 25
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A method for small-sized wheat seedlings detection: from annotation mode to model construction
Authors (first, second and last of 11)
- Suwan Wang
- Jianqing Zhao
- Xiaohu Zhang
- Content type: Methodology
- Open Access
- Published: 29 January 2024
- Article: 15
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A deep learning model for predicting risks of crop pests and diseases from sequential environmental data
Authors
- Sangyeon Lee
- Choa Mun Yun
- Content type: Research
- Open Access
- Published: 14 December 2023
- Article: 145
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Ripening dynamics revisited: an automated method to track the development of asynchronous berries on time-lapse images
Authors (first, second and last of 6)
- Benoit Daviet
- Christian Fournier
- Charles Romieu
- Content type: Methodology
- Open Access
- Published: 14 December 2023
- Article: 146
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Tensor methods in data analysis of chromatography/mass spectroscopy-based plant metabolomics
Authors (first, second and last of 5)
- Lili Guo
- Huiwen Yu
- Mourad Kharbach
- Content type: Review
- Open Access
- Published: 21 November 2023
- Article: 130
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Free and open-source software for object detection, size, and colour determination for use in plant phenotyping
Authors (first, second and last of 4)
- Harry Charles Wright
- Frederick Antonio Lawrence
- Duncan Drummond Cameron
- Content type: Methodology
- Open Access
- Published: 15 November 2023
- Article: 126
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Machine learning provides specific detection of salt and drought stresses in cucumber based on miRNA characteristics
Authors
- Parvin Mohammadi
- Keyvan Asefpour Vakilian
- Content type: Research
- Open Access
- Published: 08 November 2023
- Article: 123
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Detection and characterization of spike architecture based on deep learning and X-ray computed tomography in barley
Authors (first, second and last of 7)
- Yimin Ling
- Qinlong Zhao
- Xiaojun Nie
- Content type: Research
- Open Access
- Published: 27 October 2023
- Article: 115
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Evaluating potential of leaf reflectance spectra to monitor plant genetic variation
Authors (first, second and last of 6)
- Cheng Li
- Ewa A. Czyż
- Meredith C. Schuman
- Content type: Research
- Open Access
- Published: 14 October 2023
- Article: 108
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In vivo characterisation of field pea stem wall thickness using optical coherence tomography
Authors (first, second and last of 7)
- Qi Fang
- Felipe A. Castro-Urrea
- Brendan F. Kennedy
- Content type: Methodology
- Open Access
- Published: 11 October 2023
- Article: 105
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WheatLFANet: in-field detection and counting of wheat heads with high-real-time global regression network
Authors (first, second and last of 5)
- Jianxiong Ye
- Zhenghong Yu
- Huabing Zhou
- Content type: Research
- Open Access
- Published: 04 October 2023
- Article: 103
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Establishment of an NPK nutrient monitor system in yield-graded cotton petioles under drip irrigation
Authors (first, second and last of 9)
- Zhiqiang Dong
- Yang Liu
- Fuyu Ma
- Content type: Methodology
- Open Access
- Published: 04 September 2023
- Article: 97
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High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data
Authors (first, second and last of 6)
- Predrag Ranđelović
- Vuk Đorđević
- Johann Vollmann
- Content type: Research
- Open Access
- Published: 26 August 2023
- Article: 89
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RGB image-based method for phenotyping rust disease progress in pea leaves using R
Authors (first, second and last of 5)
- Salvador Osuna-Caballero
- Tiago Olivoto
- Nicolas Rispail
- Content type: Methodology
- Open Access
- Published: 21 August 2023
- Article: 86
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Atmospheric correction of vegetation reflectance with simulation-trained deep learning for ground-based hyperspectral remote sensing
Authors
- Farid Qamar
- Gregory Dobler
- Content type: Methodology
- Open Access
- Published: 29 July 2023
- Article: 74
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Non-destructive pre-symptomatic detection of gray mold infection in kiwifruit using hyperspectral data and chemometrics
Authors (first, second and last of 4)
- Najmeh Haghbin
- Adel Bakhshipour
- Sedigheh Mousanejad
- Content type: Research
- Open Access
- Published: 02 June 2023
- Article: 53
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The impact of variable illumination on vegetation indices and evaluation of illumination correction methods on chlorophyll content estimation using UAV imagery
Authors (first, second and last of 4)
- Yuxiang Wang
- Zengling Yang
- Haris Ahmad Khan
- Content type: Research
- Open Access
- Published: 27 May 2023
- Article: 51
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Mapping the forage nitrogen, phosphorus, and potassium contents of alpine grasslands by integrating Sentinel-2 and Tiangong-2 data
Authors (first, second and last of 8)
- Xuanfan Zhang
- Tiangang Liang
- Zhiwei Wang
- Content type: Research
- Open Access
- Published: 15 May 2023
- Article: 48
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A vector-free gene interference system using delaminated Mg–Al-lactate layered double hydroxide nanosheets as molecular carriers to intact plant cells
Authors (first, second and last of 8)
- He Zhang
- Xinyu Li
- Yinglang Wan
- Content type: Methodology
- Open Access
- Published: 08 May 2023
- Article: 44