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Development of New Sensing Technology in Sustainable Farming and Smart Environmental Monitoring

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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

Submission Status: Closed | Submission Deadline: Closed

Guest Editors:
Yuan Li, PhD, Shaanxi Normal University, Xi'an, China
Zhenxing Zhang, PhD, Northeast Normal University, China
Huiwen Yu, PhD, University of Copenhagen, Denmark

Collection articles

  1. Leaf water content (LWC) significantly affects rice growth and development. Real-time monitoring of rice leaf water status is essential to obtain high yield and water use efficiency of rice plants with precise...

    Authors: Xuenan Zhang, Haocong Xu, Yehong She, Chao Hu, Tiezhong Zhu, Lele Wang, Liquan Wu, Cuicui You, Jian Ke, Qiangqiang Zhang and Haibing He
    Citation: Plant Methods 2024 20:48
  2. Climate instability directly affects agro-environments. Water scarcity, high air temperature, and changes in soil biota are some factors caused by environmental changes. Verified and precise phenotypic traits ...

    Authors: Duvan Pineda-Castro, Harold Diaz, Jonatan Soto and Milan Oldřich Urban
    Citation: Plant Methods 2024 20:39
  3. Mastering the spatial distribution and planting area of paddy can provide a scientific basis for monitoring rice production, and planning grain production layout. Previous remote sensing studies on paddy conce...

    Authors: Lihua Wang, Hao Ma, Yanghua Gao, Shengbo Chen, Songling Yang, Peng Lu, Li Fan and Yumiao Wang
    Citation: Plant Methods 2024 20:25
  4. Grapevine berries undergo asynchronous growth and ripening dynamics within the same bunch. Due to the lack of efficient methods to perform sequential non-destructive measurements on a representative number of ...

    Authors: Benoit Daviet, Christian Fournier, Llorenç Cabrera-Bosquet, Thierry Simonneau, Maxence Cafier and Charles Romieu
    Citation: Plant Methods 2023 19:146
  5. Crop pests reduce productivity, so managing them through early detection and prevention is essential. Data from various modalities are being used to predict crop diseases by applying machine learning methodolo...

    Authors: Sangyeon Lee and Choa Mun Yun
    Citation: Plant Methods 2023 19:145

    The Correction to this article has been published in Plant Methods 2024 20:24

  6. Object detection, size determination, and colour detection of images are tools commonly used in plant science. Key examples of this include identification of ripening stages of fruit such as tomatoes and the d...

    Authors: Harry Charles Wright, Frederick Antonio Lawrence, Anthony John Ryan and Duncan Drummond Cameron
    Citation: Plant Methods 2023 19:126
  7. Remote sensing of vegetation by spectroscopy is increasingly used to characterize trait distributions in plant communities. How leaves interact with electromagnetic radiation is determined by their structure a...

    Authors: Cheng Li, Ewa A. Czyż, Rayko Halitschke, Ian T. Baldwin, Michael E. Schaepman and Meredith C. Schuman
    Citation: Plant Methods 2023 19:108
  8. Detection and counting of wheat heads are of crucial importance in the field of plant science, as they can be used for crop field management, yield prediction, and phenotype analysis. With the widespread appli...

    Authors: Jianxiong Ye, Zhenghong Yu, Yangxu Wang, Dunlu Lu and Huabing Zhou
    Citation: Plant Methods 2023 19:103
  9. The determination of nutrient content in the petiole is one of the important methods for achieving cotton fertilization management. The establishment of a monitoring system for the nutrient content of cotton p...

    Authors: Zhiqiang Dong, Yang Liu, Minghua Li, Baoxia Ci, Xiaokang Feng, Shuai Wen, Xi Lu, Zheng He and Fuyu Ma
    Citation: Plant Methods 2023 19:97
  10. Biomass accumulation as a growth indicator can be significant in achieving high and stable soybean yields. More robust genotypes have a better potential for exploiting available resources such as water or sunl...

    Authors: Predrag Ranđelović, Vuk Đorđević, Jegor Miladinović, Slaven Prodanović, Marina Ćeran and Johann Vollmann
    Citation: Plant Methods 2023 19:89
  11. Rust is a damaging disease affecting vital crops, including pea, and identifying highly resistant genotypes remains a challenge. Accurate measurement of infection levels in large germplasm collections is cruci...

    Authors: Salvador Osuna-Caballero, Tiago Olivoto, Manuel A. Jiménez-Vaquero, Diego Rubiales and Nicolas Rispail
    Citation: Plant Methods 2023 19:86
  12. Application of hyperspectral imaging (HSI) and data analysis algorithms was investigated for early and non-destructive detection of Botrytis cinerea infection. Hyperspectral images were collected from laboratory-...

    Authors: Najmeh Haghbin, Adel Bakhshipour, Hemad Zareiforoush and Sedigheh Mousanejad
    Citation: Plant Methods 2023 19:53
  13. The advancements in unmanned aerial vehicle (UAV) technology have recently emerged as an effective, cost-efficient, and versatile solution for monitoring crop growth with high spatial and temporal precision. T...

    Authors: Yuxiang Wang, Zengling Yang, Gert Kootstra and Haris Ahmad Khan
    Citation: Plant Methods 2023 19:51

    The Correction to this article has been published in Plant Methods 2023 19:62

  14. Nitrogen (N), phosphorus (P), and potassium (K) contents are crucial quality indicators for forage in alpine natural grasslands and are closely related to plant growth and reproduction. One of the greatest cha...

    Authors: Xuanfan Zhang, Tiangang Liang, Jinlong Gao, Dongmei Zhang, Jie Liu, Qisheng Feng, Caixia Wu and Zhiwei Wang
    Citation: Plant Methods 2023 19:48
  15. The Mg–Al-lactate layered double hydroxide nanosheet (LDH-NS) has shown great potential as an optimal nanocarrier for extensive use in plants. However, previous studies in plant sciences have not provided a cl...

    Authors: He Zhang, Xinyu Li, Dong Yu, Junqi Guan, Hao Ding, Hongyang Wu, Qiang Wang and Yinglang Wan
    Citation: Plant Methods 2023 19:44