Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions

By Conxita Royo, Nieves Aparicio, Dolors Villegas, J. Casadesús, P. Monneveux, Jose Luis Araus. 2003

144 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/e961cd52eb4b5d0234a14b27748ef1be06cff9c1

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Citations in the corpus

The Potential of Using Spectral Reflectance Indices to Estimate Yield in Wheat Grown Under Reduced Irrigation (2006, background): “, 2006a), under moisture stressed conditions in durum wheat (Aparicio et al., 2000; Royo et al., 2003), and in soybean (Ma et al.”
Spectral Reflectance to Estimate Genetic Variation for In-Season Biomass, Leaf Chlorophyll, and Canopy Temperature in Wheat (2006, background): “Moreover, WI is influenced by leaf area index, and therefore by the total biomass (Royo et al., 2003).”
Comprehending crystalline β-carotene accumulation by comparing engineered cell models and the natural carotenoid-rich system of citrus (2011, unknown): “, 2005), and yield in wheat and other cereals (Filella et al., 1995; Aparicio et al., 2000; Royo et al., 2003).”
Data fusion of spectral, thermal and canopy height parameters for improved yield prediction of drought stressed spring barley (2016, background): “Royo et al. (2003) found that 17.3% to 65.2% of durum wheat yield could be accounted for with multiple linear regression models based on varying spectral indices.”
Prediction of grain yield using reflectance spectra of canopy and leaves in maize plants grown under different water regimes (2012, methodology): “The weaker association between canopy reflectance and grain yield may be related to environmental background noise while measuring the canopy reflectance as discussed above, and the fact that the canopy reflectance is saturated for values of leaf area index higher than 3 (Royo et al., 2003).”
Genetic analysis of indirect selection for winter wheat grain yield using spectral reflectance indices (2007, background): “Similar observations were reported in irrigated spring wheat (Babar et al., 2006a), in durum wheat (Aparicio et al., 2000; Royo et al., 2003 ), and in winter wheat (Prasad et al., 2007).”
Predicting Grain Yield and Protein Content in Winter Wheat at Different N Supply Levels Using Canopy Reflectance Spectra (2007, background): “Royo et al. (2003) also found that when nine field experiments, each including 20 or 25 durum wheat genotypes, were analyzed together, the milk ripe stage (mid-filling) was the most appropriate developmental stage for wheat yield assessment, with reflectance at 550 nm (R550) explaining 92% of the…”
Breeding for Yield Potential and Stress Adaptation in Cereals (2008, methodology): “The scarce use of spectral reflectance measurements as tools for screening in breeding programs can be attributed to several reasons: i) a wide range of variability for the trait of interest must occur within the set of genotypes in order to be detected by the apparatus (Royo et al., 2003); ii) the ”
Potential Use of Spectral Reflectance Indices as a Selection Tool for Grain Yield in Winter Wheat under Great Plains Conditions (2007, background): “This indicates genotypes were ranked diff erently for indices value in diff erent growth stages, which is similar to observations reported by Babar et al. (2006) and Royo et al. (2003) .”
Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions (2004, background): “This is consistent with the asymptotic relationship observed between NDVI and leaf area index in durum wheat genotypes (Royo et al. 2003).”
The early explanatory power of NDVI in crop yield modelling (2008, background): “Under Mediterranean conditions, Royo et al. (2003) related NDVI to durum wheat, and Vicente-Serrano et al. (2006) predicted wheat and barley yields 4 months before harvest.”
Promising eco-physiological traits for genetic improvement of cereal yields in Mediterranean environments (2005, methodology): “, 2001), as it can determine the surface temperature of a field plot within a few seconds (Royo et al., 2003).”
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 ”
Spectral Reflectance Indices as a Potential Indirect Selection Criteria for Wheat Yield under Irrigation (2006, background): “…Performance In this study, we observed a wide range of genetic variation for different spectral indices, as was also shown in earlier studies under irrigated conditions (Ball and Konzak, 1993; Aparicio et al., 2000) and moisturestressed conditions (Aparicio et al., 2000; Royo et al., 2003).”