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Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

Guijun Yang, Jiangang Liu, Chunjiang Zhao, Zhenhong Li, Yanbo Huang, Haiyang Yu, Bo Xu, Xiaodong Yang, Dongmei Zhu, Xiaoyan Zhang, Ruyang Zhang, Haikuan Feng (+4 others)
2017 Frontiers in Plant Science  
As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly  ...  reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs  ...  in the field sampling collection. Thanks to all employees of Shandong Shengfeng soybean breeding group. We are grateful to the reviewers for their valuable comments and recommendations.  ... 
doi:10.3389/fpls.2017.01111 pmid:28713402 pmcid:PMC5492853 fatcat:xpfbd7rn7zax5hi6rlrbegfsdy

High-Throughput Field-Phenotyping Tools for Plant Breeding and Precision Agriculture

Aakash Chawade, Joost van Ham, Hanna Blomquist, Oscar Bagge, Erik Alexandersson, Rodomiro Ortiz
2019 Agronomy  
High-throughput field phenotyping has garnered major attention in recent years leading to the development of several new protocols for recording various plant traits of interest.  ...  The aim of this review is to highlight how various high-throughput phenotyping methods are used for plant breeding and farming and the key differences in the applications of such methods.  ...  Conflicts of Interest: The authors declare no conflict of interest. Agronomy 2019, 9, 258  ... 
doi:10.3390/agronomy9050258 fatcat:7y5p7wtvjrgaffn2sbfcnueg3y

Review on unmanned aerial vehicles, remote sensors, imagery processing, and their applications in agriculture

Daniel Olson, James Anderson
2021 Agronomy Journal  
UAV technologies also offers researchers with a non-destructive, objective manner for obtaining phenotypic measurements such as height assessment, biomass estimation, canopy reflectance, and abiotic and  ...  Advances in UAV technologies provides producers with options for assessment of crucial factors impacting crop yield and quality including crop water status and nutrient stress, competition from weeds,  ...  The images are aligned using "key points" of interest such as a rock, plant, or field corner.  ... 
doi:10.1002/agj2.20595 fatcat:pulgc4epnrfezfr23a6z2pvdcu

Field Phenomics: Will It Enable Crop Improvement?

David M Deery, Hamlyn G Jones
2021 Plant Phenomics  
We review recent progress in field phenomics and highlight the importance of targeting breeders' needs, rather than perceived technology needs, through developing and enhancing partnerships between phenomics  ...  Field phenomics has been identified as a promising enabling technology to assist plant breeders with the development of improved cultivars for farmers.  ...  During this Fellowship, staff at CSIRO Agriculture and Food and others in universities and industry spent time in discussions with HGJ about plant phenotyping.  ... 
doi:10.34133/2021/9871989 pmid:34549194 pmcid:PMC8433881 fatcat:67xturvyczhenfhes42qjsbe7y

A Technical Study on UAV Characteristics for Precision Agriculture Applications and Associated Practical Challenges

Nadia Delavarpour, Cengiz Koparan, John Nowatzki, Sreekala Bajwa, Xin Sun
2021 Remote Sensing  
In this paper, a practical guide on technical characterizations of common types of UAVs used in PA is presented.  ...  Over a hundred research studies were reviewed on UAVs applications in PA and practical challenges in monitoring and mapping field crops.  ...  Acknowledgments: The authors would like to thank the US Department of Agriculture, agreement number 58-6064-8-023.  ... 
doi:10.3390/rs13061204 fatcat:wavadzfzjvhajjm7qvdgpf7ux4

Reference Measurements in Developing UAV Systems for Detecting Pests, Weeds, and Diseases

Jere Kaivosoja, Juho Hautsalo, Jaakko Heikkinen, Lea Hiltunen, Pentti Ruuttunen, Roope Näsi, Oiva Niemeläinen, Madis Lemsalu, Eija Honkavaara, Jukka Salonen
2021 Remote Sensing  
The majority of the reviewed studies utilised subjective visual observations of UAV images, and only a few applied in situ measurements.  ...  The development of UAV (unmanned aerial vehicle) imaging technologies for precision farming applications is rapid, and new studies are published frequently.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs13071238 fatcat:xg5o4azqbrh4zdvq4o7wn2ofzq

High-throughput field crop phenotyping: current status and challenges

Seishi Ninomiya
2022 Breeding Science  
, in addition to crop organ detection and counting in the fields.  ...  However, this subsequently shifted to HTP for use in crops in fields.  ...  Guo Wei of the University of Tokyo for his valuable comments and feedback on this work.  ... 
doi:10.1270/jsbbs.21069 pmid:36045897 pmcid:PMC8987842 fatcat:qyabvcv6xngbhc6epjtocob5tq

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

Daoliang Li, Chaoqun Quan, Zhaoyang Song, Xiang Li, Guanghui Yu, Cheng Li, Akhter Muhammad
2021 Frontiers in Bioengineering and Biotechnology  
Food scarcity, population growth, and global climate change have propelled crop yield growth driven by high-throughput phenotyping into the era of big data.  ...  Here, we review these HT3Ps in nearly 7 years from greenhouses and growth chambers to the field, and from ground-based proximal phenotyping to aerial large-scale remote sensing.  ...  ACKNOWLEDGMENTS The authors would like to thank the editors and reviewers for their valuable input, time, and suggestions for improving the overall quality of the manuscript.  ... 
doi:10.3389/fbioe.2020.623705 pmid:33520974 pmcid:PMC7838587 fatcat:5rfrtcrkr5bcphaaemxrvle4ym

The field phenotyping platform's next darling: Dicotyledons

Xiuni Li, Xiangyao Xu, Menggen Chen, Mei Xu, Wenyan Wang, Chunyan Liu, Liang Yu, Weiguo Liu, Wenyu Yang
2022 Frontiers in Plant Science  
Collecting phenotypic data from dicotyledonous crops in the field has been identified as a key factor in the collection of large-scale phenotypic data of crops.  ...  phenotyping of dicotyledonous field crop plants in terms of morphological indicators, physiological and biochemical indicators, biotic/abiotic stress indicators, and yield indicators.  ...  High-throughput phenotyping platforms can be used to obtain crop image traits and conduct modeling to estimate the yield and quality of a crop (Xu et al., 2021) and to analyze the relationship between  ... 
doi:10.3389/fpls.2022.935748 pmid:36092402 pmcid:PMC9449727 fatcat:hgl5mt5aofgzhn5vmxpvp4vz64

The Role of Remote Sensing in Olive Growing Farm Management: A Research Outlook from 2000 to the Present in the Framework of Precision Agriculture Applications

Gaetano Messina, Giuseppe Modica
2022 Remote Sensing  
and phenotyping.  ...  As far as the use of RS platforms such as satellites, aircraft, and unmanned aerial vehicles (UAVs) as olive growing is concerned, a literature review showed the presence of several works devoted to this  ...  - modified Panasonic Lumix DMC-GF1 (MS) Assessment of the performance of low-cost image UAV sensors for the estimation of olive crown parameters [137] UAV - Sony NEX 7 (RGB) Evaluation of UAV data in the  ... 
doi:10.3390/rs14235951 fatcat:c46h5hkrine2llw5364hjry7o4

Quantitative Estimation of Wheat Phenotyping Traits Using Ground and Aerial Imagery

Zohaib Khan, Joshua Chopin, Jinhai Cai, Vahid-Rahimi Eichi, Stephan Haefele, Stanley Miklavcic
2018 Remote Sensing  
While the UAV imaging provides a high-throughput method for canopy-level trait determination, the MGP imaging captures subtle canopy structures, potentially useful for fine-grained analyses of plants.  ...  This study evaluates an aerial and ground imaging platform for assessment of canopy development in a wheat field.  ...  In this paper, we provide such analysis for quantitative estimation of phenotyping traits of wheat in a field trial.  ... 
doi:10.3390/rs10060950 fatcat:fmsfeupuofgvvcke6iwj5hb72q

Large-scale field phenotyping using backpack LiDAR and CropQuant-3D to measure structural variation in wheat

Yulei Zhu, Gang Sun, Guohui Ding, Jie Zhou, Mingxing Wen, Shichao Jin, Qiang Zhao, Joshua Colmer, Yanfeng Ding, Eric S Ober, Ji Zhou
2021 Plant Physiology  
The use of LiDAR can acquire millions of 3D points to represent spatial features of crops, and CropQuant-3D can extract meaningful traits from large, complex point clouds.  ...  We therefore believe that the combined system is easy-to-use and could be used as a reliable research tool in multi-location phenotyping for both crop research and breeding.  ...  Acknowledgements 1028 The authors would like to thank all members of the Zhou laboratory at the Nanjing Agricultural 1029 University (NAU, China) and the Cambridge Crop Research, National Institute of  ... 
doi:10.1093/plphys/kiab324 pmid:34608970 pmcid:PMC8491082 fatcat:4z6di4qwavahdbznun4grwraea

Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature

Gregor Perich, Andreas Hund, Jonas Anderegg, Lukas Roth, Martin P. Boer, Achim Walter, Frank Liebisch, Helge Aasen
2020 Frontiers in Plant Science  
Overall, low-altitude and high-resolution remote sensing proved suitable to assess the CT of crop genotypes in a large number of small field plots as is required in crop breeding and variety testing experiments  ...  Canopy temperature (CT) has been related to water-use and yield formation in crops.  ...  ACKNOWLEDGMENTS We thank Hansueli Zellweger for taking care of the experimental site and the plants throughout the growing season. We thank Pablo Bovy and Delphine Piccot, who suppoted the field work.  ... 
doi:10.3389/fpls.2020.00150 pmid:32158459 pmcid:PMC7052280 fatcat:izop7vlcy5bchl63p4biccl2oy

Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery

Yan Zhao, Bangyou Zheng, Scott C. Chapman, Kenneth Laws, Barbara George-Jaeggli, Graeme L. Hammer, David R. Jordan, Andries B. Potgieter
2021 Plant Phenomics  
Deployment of this pipeline allowed accurate segmentation of crop organs at the canopy level across many diverse field plots with minimal training needed from machine learning approaches.  ...  Using a derived nadir image of each plot, the coefficients of determination were 0.90 and 0.86 for estimates of the number of sorghum plants and heads, respectively.  ...  Infrastructure Grant "Phenotype Sensing Platform to Enhance Plant Breeding" by the University of Queensland.  ... 
doi:10.34133/2021/9874650 pmid:34676373 pmcid:PMC8502246 fatcat:7ogv5wq7srfotdgdlvqof4lglm

The Classification of Farming Progress in Rice–Wheat Rotation Fields Based on UAV RGB Images and the Regional Mean Model

Xiaoxin Song, Fei Wu, Xiaotong Lu, Tianle Yang, Chengxin Ju, Chengming Sun, Tao Liu
2022 Agriculture  
In this study, a new method for the classification of farming progress types using unmanned aerial vehicle (UAV) RGB images and the proposed regional mean (RM) model is presented.  ...  The proposed method was then applied to predict UAV RGB images of unharvested wheat, harvested wheat, and tilled and irrigated fields.  ...  Estimates of Plant Density of Wheat Crops at Emergence from Very Low Altitude UAV Imagery. Remote Sens. Environ. 2017, 198, 105–114. [CrossRef] 21.  ... 
doi:10.3390/agriculture12020124 fatcat:nd5gvcu5wba5jp5lfwdk5dvr6a
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