Assessment of growth, leaf N concentration and chlorophyll content of sweet sorghum using canopy reflectance

被引:26
|
作者
Singh, Shardendu Kumar [1 ]
Houx, James H., III [1 ]
Maw, Michael J. W. [1 ]
Fritschi, Felix B. [1 ]
机构
[1] Univ Missouri, Div Plant Sci, 1-33 Agr Bldg, Columbia, MO 65211 USA
关键词
General purpose model; Near-infrared region; Simple-ratio model; Validation; Visible region; WAVELET DECOMPOSITION; SPECTRAL REFLECTANCE; LIGHT REFLECTANCE; CARBON-DIOXIDE; NITROGEN; YIELD; FERTILIZATION; CAROTENOIDS; EFFICIENCY; PIGMENTS;
D O I
10.1016/j.fcr.2017.04.009
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Remote estimation of leaf nitrogen (N) or pigments through hyperspectral reflectance offers an opportunity to non-destructively diagnose plant N status. Two sweet sorghum (Sorghum bicolor [L.] Moench) cultivars (Top 76-6 and Dale) were grown with 0, 56, 112, 168, and 224 kg N ha(-1) in 2009 and 2010. Reflectance measurements were coupled with plant height, main-stem node number, leaf N concentration, and total chlorophyll content to establish the relationship of these traits with canopy reflectance. Canopy reflectance was most sensitive to N status in the visible region, specifically near green (595 nm) and red (701 nm) wavebands. Simple-ratio spectral models comprised of visible wavebands or wavebands from the visible and near infrared region outperformed models developed using only the most sensitive single-waveband. Based on the cross-validation of spectral models between data from two years and two cultivars, the simple-ratio models comprising the reflectance (R) ratios of 595 nm vs. 1676 nm and 595 nm vs. 508 nm predicted leaf N concentration and chlorophyll content with the greatest accuracy (highest r(2) and lowest relative error, RE). These simple-ratio models were used to develop general-purpose spectral models to derive coefficients to estimate leaf N concentration (-66.63 X R-595/R-1676 + 34.14; r(2) 0.52; RE 16.8%) and chlorophyll content (-49.12 x R-595/R-508 + 107.47; R-2 0.64; RE 17%). The identified spectral models can be used to assess growth, diagnose sweet sorghum N status and may be useful to make N management decisions for site-specific fertilizer applications.
引用
收藏
页码:47 / 57
页数:11
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