Positional differences in nitrogen and sugar concentrations of upper leaves relate to plant N status in rice under different N rates

Wang, Shaohua; Zhu, Yan; Jiang, Haidong; Cao, Weixing

doi:10.1016/j.fcr.2005.07.008

Cited by 74 publications

(52 citation statements)

References 11 publications

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“…The most common method is performed in the laboratory using leaf samples collected in the field [7]. Non-destructive field measurements of N status have been proposed, e.g., using leaf color charts or chlorophyll meters [8,9]. With the availability of remotely sensed data, these measurements enable the indirect determination of the amount of nitrogen available to crops on a large spatial scale.…”

Section: Introductionmentioning

confidence: 99%

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

et al. 2012

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Abstract:The retrieval of nutrient concentration in sugarcane through hyperspectral remote sensing is widely known to be affected by canopy architecture. The goal of this research was to develop an estimation model that could explain the nitrogen variations in sugarcane with combined cultivars. Reflectance spectra were measured over the sugarcane canopy using a field spectroradiometer. The models were calibrated by a vegetation index and multiple linear regression. The original reflectance was transformed into a First-Derivative Spectrum (FDS) and two absorption features. The results indicated that the sensitive spectral wavelengths for quantifying nitrogen content existed mainly in the visible, red edge and far near-infrared regions of the electromagnetic spectrum. Normalized Differential Index (NDI) based on FDS (750/700) and Ratio Spectral Index (RVI) based on FDS (724/700) The strong correlation between measured and estimated nitrogen concentration indicated that the methods proposed in this study could be used for the reliable diagnosis of nitrogen quantity in sugarcane. Finally, the success of the field spectroscopy used for estimating the nutrient quality of sugarcane allowed an additional experiment using the polar orbiting hyperspectral data for the timely determination of crop nutrient status in rangelands without any requirement of prior cultivar information.

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Section: Introductionmentioning

confidence: 99%

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

et al. 2012

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“…The relative SPAD values (RSPAD values) are obtained by dividing the values in the test area by that in an N-saturated plot that has received a high N rate. Wang et al (2006) and Lin et al (2010) utilized the difference, or ratio of SPAD values between different leaf positions to predict rice N status for eliminating the influence of genotypes and developmental stages. Hawkins et al (2007) used RSPAD values to determine N application rates for corn.…”

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confidence: 99%

SPAD Values and Nitrogen Nutrition Index for the Evaluation of Rice Nitrogen Status

Yang

et al. 2014

Plant Production Science

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“…The results from this protocol are relatively reliable, but are weak in the temporal and spatial scales for meeting the needs of rapid, real-time, non-destructive monitoring and effective diagnosis of plant N status. Several improved methods have been proposed for non-destructive estimation of plant N status such as using leaf color charts, chlorophyll meters, leaf positional differences or chlorophyll fluorescence (Turner and Jund 1994;Johnkutty et al 2000;Wang et al 2006). Many studies have indicated that these procedures should be potentially useful for diagnosis of plant N nutrition and recommendation of N fertilization in crop production (Li et al 2003).…”

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confidence: 99%

Monitoring leaf nitrogen in wheat using canopy reflectance spectra

Zhu¹,

Li²,

Feng³

et al. 2006

Can. J. Plant Sci.

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. Monitoring leaf nitrogen in wheat using canopy reflectance spectra. Can. J. Plant Sci. 86: 1037-1046. Non-destructive monitoring of leaf nitrogen (N) status can assist in growth diagnosis, N management and productivity forecast in field crops. The objectives of this study were to determine the relationships of leaf nitrogen concentration on a leaf dry weight basis (LNC) and leaf nitrogen accumulation per unit soil area (LNA) to ground-based canopy reflectance spectra, and to derive regression equations for monitoring N nutrition status in wheat (Triticum aestivum L.). Four field experiments were conducted with different N application rates and wheat cultivars across four growing seasons, and time-course measurements were taken on canopy spectral reflectance, LNC and leaf dry weights under the various treatments. In these studies, LNC and LNA in wheat increased with increasing N fertilization rates. The canopy reflectance differed significantly under varied N rates, and the pattern of response was consistent across the different cultivars and years. Overall, an integrated regression equation of LNC to normalized difference index (NDI) of 1220 and 710 nm of canopy reflectance spectra described the dynamic pattern of change in LNC in wheat. The ratios of several near infrared (NIR) bands to visible light were linearly related to LNA, with the ratio index (RI) of the average reflectance over 760, 810, 870, 950 and 1100 nm to 660 nm having the best index for quantitative estimation of LNA in wheat. When independent data were fit to the derived equations, the average root mean square error (RMSE) values for the predicted LNC and LNA relative to the observed values were no more than 15.1 and 15.2%, respectively, indicating a good fit. Our relationships of leaf N status to spectral indices of canopy reflectance can be potentially used for non-destructive and real-time monitoring of leaf N status in wheat.

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Positional differences in nitrogen and sugar concentrations of upper leaves relate to plant N status in rice under different N rates

Cited by 74 publications

References 11 publications

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

SPAD Values and Nitrogen Nutrition Index for the Evaluation of Rice Nitrogen Status

Monitoring leaf nitrogen in wheat using canopy reflectance spectra

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