BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

141 related articles for article (PubMed ID: 33209290)

  • 1. Field-based individual plant phenotyping of herbaceous species by unmanned aerial vehicle.
    Guo W; Fukano Y; Noshita K; Ninomiya S
    Ecol Evol; 2020 Nov; 10(21):12318-12326. PubMed ID: 33209290
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Improved Accuracy of High-Throughput Phenotyping From Unmanned Aerial Systems by Extracting Traits Directly From Orthorectified Images.
    Wang X; Silva P; Bello NM; Singh D; Evers B; Mondal S; Espinosa FP; Singh RP; Poland J
    Front Plant Sci; 2020; 11():587093. PubMed ID: 33193537
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Erratum: High-Throughput Identification of Resistance to Pseudomonas syringae pv. Tomato in Tomato using Seedling Flood Assay.
    J Vis Exp; 2023 Oct; (200):. PubMed ID: 37851522
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (
    Selvaraj MG; Valderrama M; Guzman D; Valencia M; Ruiz H; Acharjee A
    Plant Methods; 2020; 16():87. PubMed ID: 32549903
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives.
    Yang G; Liu J; Zhao C; Li Z; Huang Y; Yu H; Xu B; Yang X; Zhu D; Zhang X; Zhang R; Feng H; Zhao X; Li Z; Li H; Yang H
    Front Plant Sci; 2017; 8():1111. PubMed ID: 28713402
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Clustering Field-Based Maize Phenotyping of Plant-Height Growth and Canopy Spectral Dynamics Using a UAV Remote-Sensing Approach.
    Han L; Yang G; Yang H; Xu B; Li Z; Yang X
    Front Plant Sci; 2018; 9():1638. PubMed ID: 30483291
    [TBL] [Abstract][Full Text] [Related]  

  • 7. High-Throughput Switchgrass Phenotyping and Biomass Modeling by UAV.
    Li F; Piasecki C; Millwood RJ; Wolfe B; Mazarei M; Stewart CN
    Front Plant Sci; 2020; 11():574073. PubMed ID: 33193511
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development of Multiple UAV Collaborative Driving Systems for Improving Field Phenotyping.
    Lee HS; Shin BS; Thomasson JA; Wang T; Zhang Z; Han X
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214326
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery.
    Zhao Y; Zheng B; Chapman SC; Laws K; George-Jaeggli B; Hammer GL; Jordan DR; Potgieter AB
    Plant Phenomics; 2021; 2021():9874650. PubMed ID: 34676373
    [TBL] [Abstract][Full Text] [Related]  

  • 10. UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought.
    Ludovisi R; Tauro F; Salvati R; Khoury S; Mugnozza Scarascia G; Harfouche A
    Front Plant Sci; 2017; 8():1681. PubMed ID: 29021803
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Unmanned Aerial Vehicle-Based Phenotyping Using Morphometric and Spectral Analysis Can Quantify Responses of Wild Tomato Plants to Salinity Stress.
    Johansen K; Morton MJL; Malbeteau YM; Aragon B; Al-Mashharawi SK; Ziliani MG; Angel Y; Fiene GM; Negrão SSC; Mousa MAA; Tester MA; McCabe MF
    Front Plant Sci; 2019; 10():370. PubMed ID: 30984222
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Rapeseed Seedling Stand Counting and Seeding Performance Evaluation at Two Early Growth Stages Based on Unmanned Aerial Vehicle Imagery.
    Zhao B; Zhang J; Yang C; Zhou G; Ding Y; Shi Y; Zhang D; Xie J; Liao Q
    Front Plant Sci; 2018; 9():1362. PubMed ID: 30298081
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Combining UAV-RGB high-throughput field phenotyping and genome-wide association study to reveal genetic variation of rice germplasms in dynamic response to drought stress.
    Jiang Z; Tu H; Bai B; Yang C; Zhao B; Guo Z; Liu Q; Zhao H; Yang W; Xiong L; Zhang J
    New Phytol; 2021 Oct; 232(1):440-455. PubMed ID: 34165797
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A real-time phenotyping framework using machine learning for plant stress severity rating in soybean.
    Naik HS; Zhang J; Lofquist A; Assefa T; Sarkar S; Ackerman D; Singh A; Singh AK; Ganapathysubramanian B
    Plant Methods; 2017; 13():23. PubMed ID: 28405214
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Easy MPE: Extraction of Quality Microplot Images for UAV-Based High-Throughput Field Phenotyping.
    Tresch L; Mu Y; Itoh A; Kaga A; Taguchi K; Hirafuji M; Ninomiya S; Guo W
    Plant Phenomics; 2019; 2019():2591849. PubMed ID: 33313523
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries.
    Haghighattalab A; González Pérez L; Mondal S; Singh D; Schinstock D; Rutkoski J; Ortiz-Monasterio I; Singh RP; Goodin D; Poland J
    Plant Methods; 2016; 12():35. PubMed ID: 27347001
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture.
    Ogawa D; Sakamoto T; Tsunematsu H; Kanno N; Nonoue Y; Yonemaru JI
    J Exp Bot; 2021 Mar; 72(7):2371-2382. PubMed ID: 33367626
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature.
    Perich G; Hund A; Anderegg J; Roth L; Boer MP; Walter A; Liebisch F; Aasen H
    Front Plant Sci; 2020; 11():150. PubMed ID: 32158459
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrative field scale phenotyping for investigating metabolic components of water stress within a vineyard.
    Gago J; Fernie AR; Nikoloski Z; Tohge T; Martorell S; Escalona JM; Ribas-Carbó M; Flexas J; Medrano H
    Plant Methods; 2017; 13():90. PubMed ID: 29093742
    [TBL] [Abstract][Full Text] [Related]  

  • 20. High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.
    Madec S; Baret F; de Solan B; Thomas S; Dutartre D; Jezequel S; Hemmerlé M; Colombeau G; Comar A
    Front Plant Sci; 2017; 8():2002. PubMed ID: 29230229
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.