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Convolutional Neural Networks for Image-Based High-Throughput plant Phenotyping:A Review

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plant phenomics 2020年第1期2卷 73-94页

作者： Yu Jiang Changying Li Horticulture Section School of Integrative Plant ScienceCornell AgriTechCornell UniversityUSA School of Electrical and Computer Engineering College of EngineeringThe University of GeorgiaUSA phenomics and plant robotics center The University of GeorgiaUSA

plant phenotyping has been recognized as a bottleneck for improving the efficiency of breeding programs,understanding plantenvironment interactions,and managing agricultural *** the past five years,imaging approaches have shown great potential for high-throughput plant phenotyping,resulting in more attention paid to imaging-based plant *** this increased amount of image data,it has become urgent to develop robust analytical tools that can extract phenotypic traits accurately and *** goal of this review is to provide a comprehensive overview of the latest studies using deep convolutional neural networks(CNNs)in plant phenotyping *** specifically review the use of various CNN architecture for plant stress evaluation,plant development,and postharvest quality *** systematically organize the studies based on technical developments resulting from imaging classification,object detection,and image segmentation,thereby identifying state-of-the-art solutions for certain phenotyping ***,we provide several directions for future research in the use of CNN architecture for plant phenotyping purposes.

关键词： plant image thereby

Digital imaging approaches for phenotyping whole plant nitrogen and phosphorus response in Brachypodium distachyon

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Journal of Integrative plant Biology 2014年第8期56卷 781-796页

作者： Richard Poiré Vincent Chochois Xavier R.R.Sirault John P.Vogel Michelle Watt Robert T.Furbank CSIRO plant Industry High Resolution plant phenomics Centre CSIRO Plant Industry USDA-ARS Western Regional Research center

This work evaluates the phenotypic response of the model grass （Brachypodium distacbyon （L.） P. Beauv.） to nitrogen and phosphorus nutrition using a combination of imaging techniques and destructive harvest of shoots and roots. Reference line Bd21-3 was grown in pots using 11 phosphorus and 11 nitrogen concentrations to establish a dose-response curve. Shoot biovolume and biomass, root length and biomass, and tissue phosphorus and nitrogen concentrations increased with nutrient concentration. Shoot biovolume, estimated by imaging, was highly correlated with dry weight （R2 〉 0.92） and both biovolume and growth rate responded strongly to nutrient availability. Higher nutrient supply increased nodal root length more than other root types. Photochemical efficiency was strongly reduced by low phosphorus concentrations as early as 1 week after germination, suggesting that this measurement may be suitable for high throughput screening of phosphorus response. In contrast, nitrogen concentration had little effect on photochemical efficiency. Changes in biovolume over time were used to compare growth rates of four accessions in response tonitrogen and phosphorus supply. We demonstrate that a time series image-based approach coupled with mathematical modeling provides higher resolution of genotypic response to nutrient supply than traditional destructive techniques and shows promise for high throughput screening and determina- tion of genomic regions associated with superior nutrient use efficiency.

关键词： Nutrients uptake phenomics photosynthesis root shootCitation: Poire R, Chochois V, Sirault XRR, Vogel JP, Watt M, Furbank RT(2o14) Digital imaging approaches for phenotyping whole plantnitrogen and phosphorus response in Brachypodium distachyon.

An Exploration of Deep-Learning Based Phenotypic Analysis to Detect Spike Regions in Field Conditions for UK Bread Wheat

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plant phenomics 2019年第1期1卷 162-178页

作者： Tahani Alkhudaydi Daniel Reynolds Simon Griffiths Ji Zhou Beatriz de la Iglesia University of East Anglia Norwich Research ParkNorwich NR47TJUK University of Tabuk Faculty of Computers&ITTabuk 71491Saudi Arabia Earlham Institute Norwich Research ParkNorwich NR47UZUK John Innes Centre Norwich Research ParkNorwich NR47UHUK plant phenomics Research center China-UK Plant Phenomics Research CentreNanjing Agricultural UniversityNanjing 210095China

Wheat is one of the major crops in the world,with a global demand expected to reach 850 million tons by 2050 that is clearly outpacing current *** continual pressure to sustain wheat yield due to the world’s growing population under fluctuating climate conditions requires breeders to increase yield and yield stability across *** are working to integrate deep learning into field-based phenotypic analysis to assist breeders in this *** have utilised wheat images collected by distributed CropQuant phenotyping workstations deployed for multiyear field experiments of UK bread wheat *** on these image series,we have developed a deep-learning based analysis pipeline to segment spike regions from complicated *** a first step towards robust measurement of key yield traits in the field,we present a promising approach that employ Fully Convolutional Network(FCN)to performsemantic segmentation of images to segment wheat spike *** also demonstrate the benefits of transfer learning through the use of parameters obtained from other image *** found that the FCN architecture had achieved a Mean classification Accuracy(MA)>82%on validation data and>76%on test data and Mean Intersection over Union value(MIoU)>73%on validation data and and>64%on test *** this phenomics research,we trust our attempt is likely to form a sound foundation for extracting key yield-related traits such as spikes per unit area and spikelet number per spike,which can be used to assist yield-focused wheat breeding objectives in near future.

关键词： Wheat breeding crops

Transition from a maternal to external nitrogen source in maize seedlings

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Journal of Integrative plant Biology 2017年第4期59卷 261-274页

作者： Kasra Sabermanesh Luke R. Holtham Jessey George Ute Roessner Berin A. Boughton Sigrid Heuer Mark Tester Darren C. Plett Trevor P. Garnett Australian Centre for plant Functional Genomics Waite Research Institute University of Adelaide Adelaide SA 5064 Australia School of Agriculture Food and Wine Waite Research Institute University of Adelaide Adelaide SA 5064 Australia Australian Centre for plant Functional Genomics School of BioSciences University of Melbourne Parkville Vic. 3010 Australia Metabolomics Australia School of BioSciences University of Melbourne Vic. 3010 Australia King Abdullah University of Science and Technology Center for Desert Agriculture Thuwal 23955-6900 Kingdom of Saudi Arabia6. The Australian Plant Phenomics Facility The Plant Accelerator Waite Campus The University of Adelaide Adelaide SA 5064 Australia The Australian plant phenomics Facility The Plant Accelerator Waite Campus The University of Adelaide Adelaide SA 5064 Australia

Maximizing NO3 uptake during seedling development is important as it has a major influence on plant growth and yield. However, little is known about the processes leading to, and involved in, the initiation of root NO3 uptake capacity in developing seedlings. This study examines the physiological processes involved in root NO3 uptake and metabolism, to gain an understanding of how the NO3 uptake system responds to meet demand as maize seedlings transition from seed N use to external N capture. The concentrations of seedderived free amino acids within root and shoot tissues are initially high, but decrease rapidly until stabilizing eight days after imbibition （DAI）. Similarly, shoot N% decreases, but does not stabilize until 12-13 DAI. Following the decrease in free amino acid concentrations, root NO3- uptake capacity increases until shoot N% stabilizes. The increase in root NO3 uptake capacity corresponds with a rapid rise in transcript levels of putative NO3 transporters, ZmNRT2.1 and ZmNRT2.2. The processes underlying the increase in root NO3- uptake capacity to meet N demand provide an insight into the processes controlling N uptake.

关键词： NRT Transition from a maternal to external nitrogen source in maize seedlings NO

OsBRXL4 Regulates Shoot Gravitropism and Rice Tiller Angle through Affecting LAZY1 Nuclear Localization

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Molecular plant 2019年第8期12卷 1143-1156页

作者： Zhen Li Yan Liang Yundong Yuan Lei Wang Xiangbing Meng Guosheng Xiong Jie Zhou Yueyue Cai Ningpei Han Lekai Hua Guifu Liu Jiayang Li Yonghong Wang State Key Laboratory of plant Genomics and National center for plant Gene Research (Beijing) Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100039China CAS center for Excellence in Molecular plant Sciences Chinese Academy of SciencesShanghai 200032China Institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural SciencesBeijing 100081China plant phenomics Research center Nanjing Agriculture UniversityNanjing 210095China Root Biology center College of Resources and EnvironmentFujian Agriculture and Forestry UniversityFuzhou 350002China

Rice tiller angle is a key agronomic trait that contributes to ideal plant architecture and grain ***1 (LA1) was previously shown to control tiller angle via affecting shoot gravitropism,but the underlying molecular mechanism remains largely *** this study,we identified an LA1-interacting protein named Brevis Radix Like 4 (OsBRXL4).We showed that the interaction between OsBRXL4 and LA1 occurs at the plasma membrane and that their interaction determines nuclear localization of *** found that nuclear localization of LA1 is essential for its function,which is different from AtLA1,its Arabidopsis *** of OsBRXL4 leads to a prostrate growth phenotype,whereas OsBRXLs RNAi plants,in which the expression levels of OsBRXLI,OsBRXL4,and OsBRXL5 were decreased,display a compact *** genetic analysis also supported that OsBRXL4 controls rice tiller angle by affecting nuclear localization of ***,we demonstrated that OsBRXL4 regulates the shoot gravitropism through affecting polar auxin transport as did *** together,our study not only identifies OsBRXL4 as a regulatory component of rice tiller angle but also provides new insights into genetic regulation of rice plant architecture.

关键词： OsBRXL4 LA1 nuclear localization shoot gravitropism tiller angle rice

Easy MPE:Extraction of Quality Microplot Images for UAV-Based High-Throughput Field Phenotyping

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plant phenomics 2019年第1期1卷 30-38页

作者： Léa Tresch Yue Mu Atsushi Itoh Akito Kaga Kazunori Taguchi Masayuki Hirafuji Seishi Ninomiya Wei Guo International Field phenomics Research Laboratory Institute for Sustainable Agro-Ecosystem ServicesGraduate School of Agricultural and Life SciencesThe University of TokyoTokyoJapan 2Montpellier SupAgroMontpellierFrance 3Plant Phenomics Research CenterNanjing Agricultural UniversityNanjingChina 4Memuro Upland Farming Research StationHokkaido Agricultural Research CenterNational Agriculture and Food Research OrganizationHokkaidoJapan 5Institute of Crop ScienceNational Agriculture and Food Research OrganizationTsukuba CityIbarakiJapan

Microplot extraction(PE)is a necessary image processing step in unmanned aerial vehicle-(UAV-)based research on breeding *** present,it is manually using ArcGIS,QGIS,or other GIS-based software,but achieving the desired accuracy is *** therefore developed an intuitive,easy-to-use semiautomatic program for MPE called Easy MPE to enable researchers and others to access reliable plot data UAV images of whole fields under variable field *** program uses four major steps:(1)binary segmentation,(2)microplot extraction,(3)production of∗.shp files to enable further file manipulation,and(4)projection of individual microplots generated from the orthomosaic back onto the raw aerial UAV images to preserve the image *** rows were successfully identified in all trial *** performance of the proposed method was evaluated by calculating the intersection-over-union(IOU)ratio between microplots determined manually and by Easy MPE:the average IOU(±SD)of all trials was 91%(±3).

关键词： enable image union

A deep learning-integrated micro-CT image analysis pipeline for quantifying rice lodging resistance-related traits

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plant Communications 2021年第2期2卷 51-62页

作者： Di Wu Dan Wu Hui Feng Lingfeng Duan Guoxing Dai Xiao Liu Kang Wang Peng Yang Guoxing Chen Alan P.Gay John H.Doonan Zhiyou Niu Lizhong Xiong Wanneng Yang National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene ResearchHubei Key Laboratory of Agricultural Bioinformatics and College of EngineeringHuazhong Agricultural UniversityWuhan 430070PR China School of Information Engineering Wuhan Technology and Business UniversityWuhan 430065PR China The National plant phenomics Centre Institute of BiologicalEnvironmental and Rural SciencesAberystwyth UniversityAberystwythUK

Lodging is a common problemin rice,reducing its yield andmechanical harvesting *** architecture is a key aspect of its domestication and a major factor that limits its high *** ideal rice culm structure,includingmajor_axis_culm,minor axis_culm,andwall thickness_culm,is critical for improving lodging ***,the traditionalmethod ofmeasuring rice culms is destructive,time consuming,and labor *** this study,we used a high-throughput micro-CT-RGB imaging system and deep learning(SegNet)todevelopa high-throughputmicro-CTimageanalysis pipelinethatcanextract 24 riceculmmorphological traits and lodging resistance-related *** manual and automatic measurements were compared at themature stage,the mean absolute percentage errors for major_axis_culm,minor_axis_culm,andwall_thickness_culmin 104 indica rice accessionswere 6.03%,5.60%,and 9.85%,respectively,and the R^(2) valueswere 0.799,0.818,and *** also builtmodels of bending stress using culmtraits at the mature and tillering stages,and the R^(2) values were 0.722 and 0.544,*** modeling results indicated that this method can quantify lodging resistance nondestructively,even at an early growth *** addition,we also evaluated the relationships of bending stress toshoot dryweight,culm density,and drought-related traits and found that plants with greater resistance to bending stress had slightly higher biomass,culm density,and culm area but poorer drought *** conclusion,we developed a deep learning-integrated micro-CT image analysis pipeline to accurately quantify the phenotypic traits of rice culms in4.6 min per plant;this pipeline will assist in future high-throughput screening of large rice populations for lodging resistance.

关键词： rice culm micro-CT lodging resistance SegNet high-throughput deep learning

Combining computer vision and deep learning to enable ultra-scale aerial phenotyping and precision agriculture:A case study of lettuce production

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Horticulture Research 2019年第1期6卷 906-917页

作者： Alan Bauer Aaron George Bostrom Joshua Ball Christopher Applegate Tao Cheng Stephen Laycock Sergio Moreno Rojas Jacob Kirwan Ji Zhou Earlham Institute Norwich Research ParkNorwich NR47UZUK plant phenomics Research center China-UK Plant Phenomics Research CentreNanjing Agricultural UniversityNanjing 210095 JiangsuChina School of Computing Sciences University of East AngliaNorwich Research ParkNorwich NR47TJUK National Engineering and Technology center for Information Agriculture MARA Key Laboratory for Crop System Analysis and Decision MakingJiangsu Key Laboratory for Information AgricultureNanjing Agricultural UniversityNanjing 210095 JiangsuChina G’s Growers Limited ElyCambridgeshire CB75TZUK

Aerial imagery is regularly used by crop researchers,growers and farmers to monitor crops during the growing *** extract meaningful information from large-scale aerial images collected from the field,high-throughput phenotypic analysis solutions are required,which not only produce high-quality measures of key crop traits,but also support professionals to make prompt and reliable crop management ***,we report AirSurf,an automated and open-source analytic platform that combines modern computer vision,up-to-date machine learning,and modular software engineering in order to measure yield-related phenotypes from ultra-large aerial *** quantify millions of in-field lettuces acquired by fixed-wing light aircrafts equipped with normalised difference vegetation index(NDVI)sensors,we customised AirSurf by combining computer vision algorithms and a deep-learning classifier trained with over 100,000 labelled lettuce *** tailored platform,AirSurf-Lettuce,is capable of scoring and categorising iceberg lettuces with high accuracy(>98%).Furthermore,novel analysis functions have been developed to map lettuce size distribution across the field,based on which associated global positioning system(GPS)tagged harvest regions have been identified to enable growers and farmers to conduct precision agricultural practises in order to improve the actual yield as well as crop marketability before the harvest.

关键词： computer analysis equipped

A Strigolactone Biosynthesis Gene Contributed to the Green Revolution in Rice

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Molecular plant 2020年第6期13卷 923-932页

作者： Yuexing Wang Lianguang Shang Hong Yu Longjun Zeng Jiang Hu Shen Ni Yuchun Rao Sanfeng Li Jinfang Chu Xiangbing Meng Lei Wang Ping Hu Jijun Yan Shujing Kang Minghao Qu Hai Lin Tao Wang Quan Wang Xingming Hu Hongqi Chen Bing Wang Zhenyu Gao Longbiao Guo Dali Zeng Xudong Zhu Guosheng Xiong Jiayang Li Qian Qian State Key Laboratory of Rice Biology China National Rice Research InstituteHangzhou 310006China Shenzhen Branch Guangdong Laboratory for Lingnan Modern AgricultureGenome Analysis Laboratory of the Ministry of AgricultureAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhen 518120China State Key Laboratory of plant Genomics and National Center for Plant Gene Research(Beijing)Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijing 100101China plant phenomics Research center Nanjing Agricultural UniversityNanjing 210095China College of Chemistry and Life Sciences Zhejiang Normal UniversityJinhua 321004China

plant architecture is a complex agronomic trait and a major factor of crop yield,which is affected by several important ***(SLs)are identified as a new class hormoneinhibiting branching in many plant species and have been shown to be involved in various developmental *** and chemical modulation of the SL pathway is recognized as a promising approach to modify plant ***,whether and how the genes involved in the SL pathway could be utilized in breeding still remain ***,we demonstrate that a partial loss-of-function allele of the SL biosynthesis gene,HIGH TILLERING AND DWARF 1/DWARF17(HTD1/D17),which encodes CAROTENOID CLEAVAGE DIOXYGENASE 7(CCD7),increases tiller number and improves grain yield in *** found that the HTD1 gene had been widely utilized and co-selected with Semidwarf 1(SD1),both contributing to the improvement of plant architecture in modern rice varieties since the Green Revolution in the *** how phytohormone pathway genes regulate plant architecture and how they have been utilized and selected in breeding will lay the foundation for developing the rational approaches toward improving crop yield.

关键词： rice strigolactones tiller number Green Revolution