BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

124 related articles for article (PubMed ID: 26540057)

  • 1. Active-Optical Sensors Using Red NDVI Compared to Red Edge NDVI for Prediction of Corn Grain Yield in North Dakota, U.S.A.
    Sharma LK; Bu H; Denton A; Franzen DW
    Sensors (Basel); 2015 Nov; 15(11):27832-53. PubMed ID: 26540057
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Case Study of Improving Yield Prediction and Sulfur Deficiency Detection Using Optical Sensors and Relationship of Historical Potato Yield with Weather Data in Maine.
    Sharma LK; Bali SK; Dwyer JD; Plant AB; Bhowmik A
    Sensors (Basel); 2017 May; 17(5):. PubMed ID: 28492476
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Integrating plant morphological traits with remote-sensed multispectral imageries for accurate corn grain yield prediction.
    Jang C; Namoi N; Wolske E; Wasonga D; Behnke G; Bowman ND; Lee DK
    PLoS One; 2024; 19(4):e0297027. PubMed ID: 38564609
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of Crop Yield Using Phenological Information Extracted from Remote Sensing Vegetation Index.
    Ji Z; Pan Y; Zhu X; Wang J; Li Q
    Sensors (Basel); 2021 Feb; 21(4):. PubMed ID: 33671356
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluation of OptRx™ active optical sensor to monitor soybean response to nitrogen inputs.
    Sivarajan S; Maharlooei M; Kandel H; Buetow RR; Nowatzki J; Bajwa SG
    J Sci Food Agric; 2020 Jan; 100(1):154-160. PubMed ID: 31471908
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Unmanned aerial systems-based remote sensing for monitoring sorghum growth and development.
    Shafian S; Rajan N; Schnell R; Bagavathiannan M; Valasek J; Shi Y; Olsenholler J
    PLoS One; 2018; 13(5):e0196605. PubMed ID: 29715311
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting in-season maize (Zea mays L.) yield potential using crop sensors and climatological data.
    Dhillon J; Aula L; Eickhoff E; Raun W
    Sci Rep; 2020 Jul; 10(1):11479. PubMed ID: 32651438
    [TBL] [Abstract][Full Text] [Related]  

  • 8. [Diagnosis of nitrogen content in upper and lower corn leaves based on hyperspectral data].
    Jin L; Hu KL; Tian MM; Wei D; Li H; Bai YL; Zhang JZ
    Guang Pu Xue Yu Guang Pu Fen Xi; 2013 Apr; 33(4):1032-7. PubMed ID: 23841423
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Using of Multi-Source and Multi-Temporal Remote Sensing Data Improves Crop-Type Mapping in the Subtropical Agriculture Region.
    Sun C; Bian Y; Zhou T; Pan J
    Sensors (Basel); 2019 May; 19(10):. PubMed ID: 31130689
    [TBL] [Abstract][Full Text] [Related]  

  • 10. [Study on hyperspectral estimation model of crop vegetation cover percentage].
    Zhu L; Xu JF; Huang JF; Wang FM; Liu ZY; Wang Y
    Guang Pu Xue Yu Guang Pu Fen Xi; 2008 Aug; 28(8):1827-31. PubMed ID: 18975813
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Intercomparison of Same-Day Remote Sensing Data for Measuring Winter Cover Crop Biophysical Traits.
    Thieme A; Prabhakara K; Jennewein J; Lamb BT; McCarty GW; Hively WD
    Sensors (Basel); 2024 Apr; 24(7):. PubMed ID: 38610550
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China).
    Liu X; Ferguson RB; Zheng H; Cao Q; Tian Y; Cao W; Zhu Y
    Sensors (Basel); 2017 Mar; 17(4):. PubMed ID: 28338637
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Yield and leaf area index estimations for sunflower plants using unmanned aerial vehicle images.
    Tunca E; Köksal ES; Çetin S; Ekiz NM; Balde H
    Environ Monit Assess; 2018 Oct; 190(11):682. PubMed ID: 30374821
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Using spatio-temporal fusion of Landsat-8 and MODIS data to derive phenology, biomass and yield estimates for corn and soybean.
    Liao C; Wang J; Dong T; Shang J; Liu J; Song Y
    Sci Total Environ; 2019 Feb; 650(Pt 2):1707-1721. PubMed ID: 30273730
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Canopy reflectance, stalk sugar and juice yields in specialty corn hybrids as affected by nitrogen management strategies.
    Ma B; Zheng ZM
    J Sci Food Agric; 2020 Feb; 100(3):1080-1091. PubMed ID: 31650556
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessment of plant biomass and nitrogen nutrition with plant height in early-to mid-season corn.
    Yin X; Hayes RM; McClure MA; Savoy HJ
    J Sci Food Agric; 2012 Oct; 92(13):2611-7. PubMed ID: 22522386
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe.
    Gracia-Romero A; Kefauver SC; Vergara-Díaz O; Hamadziripi E; Zaman-Allah MA; Thierfelder C; Prassana BM; Cairns JE; Araus JL
    Sci Rep; 2020 Sep; 10(1):16008. PubMed ID: 32994539
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A lysimeter study of nitrate leaching, optimum fertilisation rate and growth responses of corn (Zea mays L.) following soil amendment with water-saving super-absorbent polymer.
    Islam MR; Mao S; Xue X; Eneji AE; Zhao X; Hu Y
    J Sci Food Agric; 2011 Aug; 91(11):1990-7. PubMed ID: 21480276
    [TBL] [Abstract][Full Text] [Related]  

  • 19. [A field-based pushbroom imaging spectrometer for estimating chlorophyll content of maize].
    Zhang DY; Liu RY; Song XY; Xu XG; Huang WJ; Zhu DZ; Wang JH
    Guang Pu Xue Yu Guang Pu Fen Xi; 2011 Mar; 31(3):771-5. PubMed ID: 21595237
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants.
    Wang L; Duan Y; Zhang L; Rehman T; Ma D; Jin J
    Sensors (Basel); 2020 Jun; 20(11):. PubMed ID: 32517003
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.