Relationship between Growth Traits and Spectral Vegetation Indices in Durum Wheat

By Nieves Aparicio, Dolors Villegas, Jose Luis Araus, J. Casadesús, Conxita Royo. 2002

198 citations recorded by the source corpus.

Subfields: Agronomy and Crop Science, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/7582e7be75db59a4320f8990efc3c66db914a200

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Citations in the corpus

Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions (2003, methodology): “Similarly, Aparicio et al. (2002) found that NDVI and SR properly tracked changes in LAI when a wide range of variability existed in the experimental data, but their predictive value was reduced on specific locations.”
The Potential of Using Spectral Reflectance Indices to Estimate Yield in Wheat Grown Under Reduced Irrigation (2006, methodology): “The use of SRIs to follow physiological changes during different growth stages was documented in durum wheat under rainfed conditions ( Aparicio et al., 2000; 2002 ), and in common wheat under irrigated conditions (Leamer et al., 1980; Hatfield, 1981).”
Spectral Reflectance Indices as a Potential Indirect Selection Criteria for Wheat Yield under Irrigation (2006, background): “Aparicio et al. (2002) also reported a significant interaction between growth stages and spectral indices (NDVI and SR) in durum wheat.”
Breeding for increased nitrogen‐use efficiency: a review for wheat (T. aestivum L.) (2016, background): “Using ground-based spectroradiometers, SRI have been developed to estimate crop biomass (Babar et al. 2006), green canopy area (Aparicio et al. 2002), leaf chlorophyll (Babar et al. 2006), ‘stay-green’ (Lopes and Reynolds 2012), grain yield (Gutierrez-Rodriguez et al. 2004, Gutierrez et al.…”
Potential Use of Spectral Reflectance Indices as a Selection Tool for Grain Yield in Winter Wheat under Great Plains Conditions (2007, background): “Several researchers have suggested that grain yield can be estimated using spectral refl ectance during diff erent crop growth stages (Araus et al., 2001; Aparicio et al., 2002; Osborne et al., 2002; Babar et al., 2006).”
Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat (2011, background): “…productivity potential, and potential yield (Peñuelas et al. 1994; Thenkabail et al. 2000; Ma et al. 2001; Raun et al. 2001; Báez-González et al. 2002) and have been found to be sensitive to leaf area index, green biomass (Peñuelas et al. 1994), and photosynthetic efficiency (Aparicio et al. 2002).”
Spectral Reflectance to Estimate Genetic Variation for In-Season Biomass, Leaf Chlorophyll, and Canopy Temperature in Wheat (2006, methodology): “The most widely used SRI, the NDVI and the SR, were not able to predict the variations in biomass successfully when estimated at later growth stages in durum wheat (Aparicio et al., 2000, 2002).”
Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions (2004, background): “For example, Aparicio et al. (2000) found that NDVI combined with the simple ratio (R900/R680) and photochemical reflectance index (R531 –R570/R531+R570) measured at any crop stage was positively correlated with yield in rainfed conditions (yield 1650–2960 kg/ha) and irrigated conditions (yield 3370”
Large‐Area Maize Yield Forecasting Using Leaf Area Index Based Yield Model (2005, methodology): “…active radiation (IPAR), biomass, photosynthetic size of canopy, and LAI (OchiYield forecasting, or determining yield in advance et al., 2000; Aparicio et al., 2002; Lobell et al., 2002).of harvest, has been used in many parts of the world Leaf area index, a quantitative measure of foliageto…”
LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands (2011, methodology): “The better LAI prediction ability of NDVI for wheat in comparison with potato (Tables 4 and 5) is in agreement with Aparicio et al. (2002) resulting in better LAI prediction by NDVI for a wider range of LAI values.”