Literature DB >> 12371160

Narrow-waveband reflectance ratios for remote estimation of nitrogen status in cotton.

J J Read1, L Tarpley, J M McKinion, K R Reddy.   

Abstract

Tailoring nitrogen (N) fertilizer applications to cotton (Gossypium hirsutum L.) in response to leaf N status may optimize N use efficiency and reduce off-site effects of excessive fertilizer use. This study compared leaf and canopy reflectance within the 350 to 950 nm range in order to identify reflectance ratios sensitive to leaf chlorophyll (Chl), and hence N status, in cotton. Plants were grown outdoors in large pots using half-strength Hoagland's (control) solution until some three-row plots received a restricted supply of N. Treatments comprised control, 20% of control N at first flower bud (square) onward; 0 and 20% of control N at first flower onward; and 0% of control N at fruit-filling onward. Despite leaf N values ranging from 51 to 19 g kg-1 across treatments and sampling dates, a weak correlation was obtained between Chl and N (r2 = 0.32, df = 70). In general, N stress led to increased reflectance at 695 +/- 2.5 nm (R695) and decreased reflectance at R410, and changes in leaf N were best correlated with either R695 or R755 in leaves and either R410 or R700 in canopies. The strongest associations between leaf constituent and canopy reflectance ratio were Chl vs. R415/R695 (r2 = 0.72), carotenoids vs. R415/R685 (r2 = 0.79), and N vs. R415/R710 (r2 = 0.70). The R415 measure appears to be a more stable spectral feature under N stress, as compared with more pronounced changes along the reflectance red edge (690-730 nm). Multiple regression identified a three-waveband canopy reflectance model that explained 80% of the variability in leaf N. Results indicate that remote sensing of N status in cotton is feasible using narrow-waveband reflectance ratios that involve the violet or blue region of the spectrum (400 to 450 nm) and the more commonly featured red-edge region.

Entities:  

Mesh:

Substances:

Year:  2002        PMID: 12371160     DOI: 10.2134/jeq2002.1442

Source DB:  PubMed          Journal:  J Environ Qual        ISSN: 0047-2425            Impact factor:   2.751


  8 in total

1.  ASPIS, A Flexible Multispectral System for Airborne Remote Sensing Environmental Applications.

Authors:  Dario Papale; Claudio Belli; Beniamino Gioli; Franco Miglietta; Cesare Ronchi; Francesco Primo Vaccari; Riccardo Valentini
Journal:  Sensors (Basel)       Date:  2008-05-16       Impact factor: 3.576

2.  Reflectance variation within the in-chlorophyll centre waveband for robust retrieval of leaf chlorophyll content.

Authors:  Jing Zhang; Wenjiang Huang; Qifa Zhou
Journal:  PLoS One       Date:  2014-11-03       Impact factor: 3.240

3.  Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding.

Authors:  Gustavo A Lobos; Carlos Poblete-Echeverría
Journal:  Front Plant Sci       Date:  2017-01-09       Impact factor: 5.753

Review 4.  Proximal Optical Sensors for Nitrogen Management of Vegetable Crops: A Review.

Authors:  Francisco M Padilla; Marisa Gallardo; M Teresa Peña-Fleitas; Romina de Souza; Rodney B Thompson
Journal:  Sensors (Basel)       Date:  2018-06-28       Impact factor: 3.576

Review 5.  Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography.

Authors:  Angelica Galieni; Nicola D'Ascenzo; Fabio Stagnari; Giancarlo Pagnani; Qingguo Xie; Michele Pisante
Journal:  Front Plant Sci       Date:  2021-01-27       Impact factor: 5.753

6.  Remotely Assessing Fraction of Photosynthetically Active Radiation (FPAR) for Wheat Canopies Based on Hyperspectral Vegetation Indexes.

Authors:  Changwei Tan; Dunliang Wang; Jian Zhou; Ying Du; Ming Luo; Yongjian Zhang; Wenshan Guo
Journal:  Front Plant Sci       Date:  2018-06-07       Impact factor: 5.753

7.  Detection of Stress in Cotton (Gossypium hirsutum L.) Caused by Aphids Using Leaf Level Hyperspectral Measurements.

Authors:  Tingting Chen; Ruier Zeng; Wenxuan Guo; Xueying Hou; Yubin Lan; Lei Zhang
Journal:  Sensors (Basel)       Date:  2018-08-24       Impact factor: 3.576

8.  Assessment of Fv/Fm absorbed by wheat canopies employing in-situ hyperspectral vegetation indexes.

Authors:  Chang-Wei Tan; Dun-Liang Wang; Jian Zhou; Ying Du; Ming Luo; Yong-Jian Zhang; Wen-Shan Guo
Journal:  Sci Rep       Date:  2018-06-22       Impact factor: 4.379

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.