The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Remote Sensing of Biomass and Yield of Winter Wheat under Different Nitrogen Supplies
Abstract
Vegetation indices derived from reflectance data are related to canopy variables such as aboveground biomass, leaf area index (LAI), and the fraction of intercepted photosynthetically active radiation (fIPAR). However, under N stress the relationships between vegetation indices (VI) and these canopy variables might be confounded due to plant chlorosis. We studied the relationships between reflectance‐based VI and canopy variables (aboveground biomass, LAI canopy chlorophyll A content [LAI × Chl A], and fIPAR) for a wheat (Triticum aestivum L.) crop growing under different N supplies. Nitrogen fertilization promoted significant increases in radiation interception (plant growth) and, to a lesser extent, in radiation use efficiency (RUE). The VI vs. LAI relationships varied significantly among treatments, rendering the VI‐based equations unreliable to estimate LAI under contrasting N conditions. However, a single relationship emerged when LAI × Chl A was considered. Moreover, VI were robust indicators of fIPAR by green canopy components independently of N treatment and phenology. Aboveground biomass was poorly correlated with grain yield, whereas cumulative VI simple ratio (SR) was a good predictor of grain yield, probably because cumulative SR closely tracked the duration and intensity of the canopy photosynthetic capacity.
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Remote sensing of regional crop production in the Yaqui Valley, Mexico: estimates and uncertainties
Lobell, D. B., Asner, G. P., Ortiz-Monasterio, J. I., & Benning, T. L. (2003) · Agriculture, Ecosystems & Environment · doi:10.1016/s0167-8809(02)00021-x · Cited by 328
A review of remote sensing methods for biomass feedstock production
Ahamed, T., Tian, L., Zhang, Y., & Ting, K. C. (2011) · Biomass and Bioenergy · doi:10.1016/j.biombioe.2011.02.028 · Cited by 261
MODIS-based corn grain yield estimation model incorporating crop phenology information
Sakamoto, T., Gitelson, A. A., & Arkebauer, T. J. (2013) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.12.017 · Cited by 254
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Metadata
- Authors
- Serrano, L., Filella, I., & Peñuelas, J.
- Venue
- Crop Science
- Publisher
- Wiley
- Published
- 2000-05
- Volume
- 40
- Issue
- 3
- Pages
- 723-731
- ISSN
- 0011-183X (ISSN-L)
- 1435-0653
- OpenAlex
- W2070559755
- Cited by
- 428
- References
- 21
- FWCI
- 5.92
- Type
- journal article
- Language
- en
- Open access
- closed
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