Remote sensing of biomass and yield of winter wheat under different nitrogen supplies

By L. Serrano, Iolanda Filella, Josep Peñuelas. 2000

434 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/ce344305626308c4e50453735498fc276a1d84fb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. A. Klatt
2. Muhammad Ali Babar
3. Jose Luis Araus
4. W. Raun
5. Marvin L. Stone
6. Conxita Royo
7. B. Prasad
8. Dolors Villegas

In Environmental Engineering

1. Jose Luis Araus
2. Liangyun Liu
3. W. Cao
4. Jihua Wang
5. Lin-zhang Yang
6. L. Xue
7. Sorin C. Popescu
8. Dar A. Roberts

In Global and Planetary Change

1. Jose Luis Araus
2. Duli Zhao
3. Wenjiang Huang
4. W. Cao
5. Lars Chittka
6. Vijaya Gopal Kakani
7. Lin-zhang Yang
8. Conxita Royo

Citations in the corpus

• Modelo para estimativa do potencial produtivo em trigo e cevada por meio do sensor GreenSeeker (2009, background): “O aumento da concentração de clorofila, em função dos níveis de N, resulta em incremento da área foliar (biomassa) e também da atividade fotossintética (SERRANO et al., 2000).”
• Assessment of plant nitrogen stress in wheat (Triticum aestivum L.) through hyperspectral indices (2012, background): “Nitrogen-stressed plants show significantly lower levels of plant nitrogen and chlorophyll, higher starch content and greater leaf thickness (Serrano et al. 2000).”
• Identification of red and NIR spectral regions and vegetative indices for discrimination of cotton nitrogen stress and growth stage (2005, background): “Research results indicate these VIs have potential applications in agriculture for forecasting and estimating crop productions, monitoring crop conditions, classifying and mapping crops, and directing precision farming activities (Erol and Akdeniz, 1996; Serrano et al., 2000; Plant et al., 2000; Xia”
• Potential Use of Spectral Reflectance Indices as a Selection Tool for Grain Yield in Winter Wheat under Great Plains Conditions (2007, background): “Hence, the common SRI that utilize the red band are insensitive to variation in vegetation fraction or LAI values beyond 3 (Serrano et al., 2000).”
• View angle effects on the discrimination of soybean varieties and on the relationships between vegetation indices and yield using off-nadir Hyperion data (2009, background): “Most often, vegetation indices have been used to either establish empirical relationships with crop yield at local scales (e.g., Ma et al., 2001; Serrano et al., 2000; Shanahan et al., 2001; Shibayama & Akiyama, 1991; Royo et al., 2003) or to estimate a biophysical attribute, such as LeafArea Index ”