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Journal Abstract Search

304 related items for PubMed ID: 31534277

  • 1.
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  • 2. Hyperspectral Leaf Reflectance as Proxy for Photosynthetic Capacities: An Ensemble Approach Based on Multiple Machine Learning Algorithms.
    Fu P, Meacham-Hensold K, Guan K, Bernacchi CJ.
    Front Plant Sci; 2019; 10():730. PubMed ID: 31214235
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  • 4. Estimating photosynthetic traits from reflectance spectra: A synthesis of spectral indices, numerical inversion, and partial least square regression.
    Fu P, Meacham-Hensold K, Guan K, Wu J, Bernacchi C.
    Plant Cell Environ; 2020 May; 43(5):1241-1258. PubMed ID: 31922609
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  • 6. Unique contributions of chlorophyll and nitrogen to predict crop photosynthetic capacity from leaf spectroscopy.
    Wang S, Guan K, Wang Z, Ainsworth EA, Zheng T, Townsend PA, Li K, Moller C, Wu G, Jiang C.
    J Exp Bot; 2021 Feb 02; 72(2):341-354. PubMed ID: 32937655
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  • 7. Selecting informative bands for partial least squares regressions improves their goodness-of-fits to estimate leaf photosynthetic parameters from hyperspectral data.
    Jin J, Wang Q, Song G.
    Photosynth Res; 2022 Jan 02; 151(1):71-82. PubMed ID: 34491493
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  • 9. Plot-level rapid screening for photosynthetic parameters using proximal hyperspectral imaging.
    Meacham-Hensold K, Fu P, Wu J, Serbin S, Montes CM, Ainsworth E, Guan K, Dracup E, Pederson T, Driever S, Bernacchi C.
    J Exp Bot; 2020 Apr 06; 71(7):2312-2328. PubMed ID: 32092145
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  • 10. Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum.
    Zhi X, Massey-Reed SR, Wu A, Potgieter A, Borrell A, Hunt C, Jordan D, Zhao Y, Chapman S, Hammer G, George-Jaeggli B.
    Plant Phenomics; 2022 Apr 06; 2022():9768502. PubMed ID: 35498954
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  • 13. Beyond greenness: Detecting temporal changes in photosynthetic capacity with hyperspectral reflectance data.
    Barnes ML, Breshears DD, Law DJ, van Leeuwen WJD, Monson RK, Fojtik AC, Barron-Gafford GA, Moore DJP.
    PLoS One; 2017 Apr 06; 12(12):e0189539. PubMed ID: 29281709
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  • 14. Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature.
    Serbin SP, Dillaway DN, Kruger EL, Townsend PA.
    J Exp Bot; 2012 Jan 06; 63(1):489-502. PubMed ID: 21984647
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  • 15. A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression.
    Burnett AC, Anderson J, Davidson KJ, Ely KS, Lamour J, Li Q, Morrison BD, Yang D, Rogers A, Serbin SP.
    J Exp Bot; 2021 Sep 30; 72(18):6175-6189. PubMed ID: 34131723
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  • 16. Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models.
    Buchaillot ML, Soba D, Shu T, Liu J, Aranjuelo I, Araus JL, Runion GB, Prior SA, Kefauver SC, Sanz-Saez A.
    Planta; 2022 Mar 24; 255(4):93. PubMed ID: 35325309
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  • 17. Predicting photosynthetic capacity in tobacco using shortwave infrared spectral reflectance.
    Sexton T, Sankaran S, Cousins AB.
    J Exp Bot; 2021 May 28; 72(12):4373-4383. PubMed ID: 33735372
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  • 18. Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning.
    Furbank RT, Silva-Perez V, Evans JR, Condon AG, Estavillo GM, He W, Newman S, Poiré R, Hall A, He Z.
    Plant Methods; 2021 Oct 19; 17(1):108. PubMed ID: 34666801
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  • 19. Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy.
    Lamour J, Davidson KJ, Ely KS, Anderson JA, Rogers A, Wu J, Serbin SP.
    PLoS One; 2021 Oct 19; 16(10):e0258791. PubMed ID: 34665822
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  • 20. Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat.
    Silva-Perez V, Molero G, Serbin SP, Condon AG, Reynolds MP, Furbank RT, Evans JR.
    J Exp Bot; 2018 Jan 23; 69(3):483-496. PubMed ID: 29309611
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