These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

130 related articles for article (PubMed ID: 37693634)

  • 1. SPOT: Scanning plant IoT facility for high-throughput plant phenotyping.
    Lantin S; McCourt K; Butcher N; Puri V; Esposito M; Sanchez S; Ramirez-Loza F; McLamore E; Correll M; Singh A
    HardwareX; 2023 Sep; 15():e00468. PubMed ID: 37693634
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.
    Guo Q; Wu F; Pang S; Zhao X; Chen L; Liu J; Xue B; Xu G; Li L; Jing H; Chu C
    Sci China Life Sci; 2018 Mar; 61(3):328-339. PubMed ID: 28616808
    [TBL] [Abstract][Full Text] [Related]  

  • 3. CropSight: a scalable and open-source information management system for distributed plant phenotyping and IoT-based crop management.
    Reynolds D; Ball J; Bauer A; Davey R; Griffiths S; Zhou J
    Gigascience; 2019 Mar; 8(3):. PubMed ID: 30715329
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Improving High-Throughput Phenotyping Using Fusion of Close-Range Hyperspectral Camera and Low-Cost Depth Sensor.
    Huang P; Luo X; Jin J; Wang L; Zhang L; Liu J; Zhang Z
    Sensors (Basel); 2018 Aug; 18(8):. PubMed ID: 30126148
    [TBL] [Abstract][Full Text] [Related]  

  • 5. CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements.
    Banerjee BP; Spangenberg G; Kant S
    Biosensors (Basel); 2021 Dec; 12(1):. PubMed ID: 35049643
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Assessing plant performance in the Enviratron.
    Bao Y; Zarecor S; Shah D; Tuel T; Campbell DA; Chapman AVE; Imberti D; Kiekhaefer D; Imberti H; Lübberstedt T; Yin Y; Nettleton D; Lawrence-Dill CJ; Whitham SA; Tang L; Howell SH
    Plant Methods; 2019; 15():117. PubMed ID: 31660060
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping.
    Bagley SA; Atkinson JA; Hunt H; Wilson MH; Pridmore TP; Wells DM
    Sensors (Basel); 2020 Jun; 20(11):. PubMed ID: 32545168
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application of Internet of Things to Agriculture-The LQ-FieldPheno Platform: A High-Throughput Platform for Obtaining Crop Phenotypes in Field.
    Fan J; Li Y; Yu S; Gou W; Guo X; Zhao C
    Research (Wash D C); 2023; 6():0059. PubMed ID: 36951796
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Image-Based High-Throughput Phenotyping in Horticultural Crops.
    Abebe AM; Kim Y; Kim J; Kim SL; Baek J
    Plants (Basel); 2023 May; 12(10):. PubMed ID: 37653978
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Applying high-throughput phenotyping to plant-insect interactions: picturing more resistant crops.
    Goggin FL; Lorence A; Topp CN
    Curr Opin Insect Sci; 2015 Jun; 9():69-76. PubMed ID: 32846711
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Multi-Source Data Fusion Improves Time-Series Phenotype Accuracy in Maize under a Field High-Throughput Phenotyping Platform.
    Li Y; Wen W; Fan J; Gou W; Gu S; Lu X; Yu Z; Wang X; Guo X
    Plant Phenomics; 2023; 5():0043. PubMed ID: 37223316
    [TBL] [Abstract][Full Text] [Related]  

  • 12. High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field.
    Li D; Quan C; Song Z; Li X; Yu G; Li C; Muhammad A
    Front Bioeng Biotechnol; 2020; 8():623705. PubMed ID: 33520974
    [TBL] [Abstract][Full Text] [Related]  

  • 13. PhenoApp: A mobile tool for plant phenotyping to record field and greenhouse observations.
    Röckel F; Schreiber T; Schüler D; Braun U; Krukenberg I; Schwander F; Peil A; Brandt C; Willner E; Gransow D; Scholz U; Kecke S; Maul E; Lange M; Töpfer R
    F1000Res; 2022; 11():12. PubMed ID: 36636476
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Field-based high-throughput phenotyping of plant height in sorghum using different sensing technologies.
    Wang X; Singh D; Marla S; Morris G; Poland J
    Plant Methods; 2018; 14():53. PubMed ID: 29997682
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Field-Based High-Throughput Phenotyping for Maize Plant Using 3D LiDAR Point Cloud Generated With a "Phenomobile".
    Qiu Q; Sun N; Bai H; Wang N; Fan Z; Wang Y; Meng Z; Li B; Cong Y
    Front Plant Sci; 2019; 10():554. PubMed ID: 31134110
    [TBL] [Abstract][Full Text] [Related]  

  • 16. UAV Multisensory Data Fusion and Multi-Task Deep Learning for High-Throughput Maize Phenotyping.
    Nguyen C; Sagan V; Bhadra S; Moose S
    Sensors (Basel); 2023 Feb; 23(4):. PubMed ID: 36850425
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.
    Hakkenberg CR; Zhu K; Peet RK; Song C
    Ecology; 2018 Feb; 99(2):474-487. PubMed ID: 29231965
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Development of a Target-to-Sensor Mode Multispectral Imaging Device for High-Throughput and High-Precision Touch-Based Leaf-Scale Soybean Phenotyping.
    Li X; Chen Z; Wei X; Zhao T; Jin J
    Sensors (Basel); 2023 Apr; 23(7):. PubMed ID: 37050815
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses - a review.
    Humplík JF; Lazár D; Husičková A; Spíchal L
    Plant Methods; 2015; 11():29. PubMed ID: 25904970
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Design Considerations for In-Field Measurement of Plant Architecture Traits Using Ground-Based Platforms.
    Pandey P; Young S
    Methods Mol Biol; 2022; 2539():171-190. PubMed ID: 35895204
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.