Spectral Reflectance Indices as a Potential Indirect Selection Criteria for Wheat Yield under Irrigation

By Muhammad Ali Babar, Matthew P Reynolds, M. Ginkel, A. Klatt, W. Raun, Marvin L. Stone. 2006

217 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/29ac33fbf8ccd5d4d5187f93c316fa1754bd3314

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Citations in the corpus

Genetic analysis of indirect selection for winter wheat grain yield using spectral reflectance indices (2007, methodology): “ Babar et al. (2006a) reported the effi ciency of the near-infrared indices in estimating spring wheat ( Triticum aestivum L.) grain yield under northwestern Mexico conditions.”
Spectral Reflectance to Estimate Genetic Variation for In-Season Biomass, Leaf Chlorophyll, and Canopy Temperature in Wheat (2006, result): “Babar et al. (2006) found a strong association between grain yield of wheat andWI under the same environmental conditions where the present study was conducted.”
PAPER PRESENTED AT INTERNATIONAL WORKSHOP ON INCREASING WHEAT YIELD POTENTIAL, CIMMYT, OBREGON, MEXICO, 20–24 MARCH 2006 Understanding the physiological basis of yield potential in wheat (2007, background): “For example: frost, which can occur at CIANO in January from time to time, with clear negative effects on RUE; heavy rain events (like 133 mm on 14 Jan 2004) can induce temporary waterlogging, which may be as important as the associated cloudiness ; and perhaps, despite irrigation, the not-infrequen”
Potential Use of Spectral Reflectance Indices as a Selection Tool for Grain Yield in Winter Wheat under Great Plains Conditions (2007, methodology): “However, Babar et al. (2006) established a strong relationship between NIR-based indices and grain yield with irrigated spring wheat genotypes.”
The Potential of Using Spectral Reflectance Indices to Estimate Yield in Wheat Grown Under Reduced Irrigation (2006, background): “Babar et al. (2006a) and GutierrezRodriguez (2004) found significant genotypic variations for SRIs in common wheat under irrigated conditions at the same location as the present research.”
Using UAV Borne, Multi-Spectral Imaging for the Field Phenotyping of Shoot Biomass, Leaf Area Index and Height of West African Sorghum Varieties under Two Contrasted Water Conditions (2021, background): “Higher level of NDVI is associated with faster growth rate, higher biomass accumulation during the vegetative stage and a longer grain filling period by delaying leaf senescence during the ripening phase thereby increasing yield [79].”
Field-based phenomics for plant genetics research (2012, background): “However, to date, most field-based phenotyping systems have focused on rapid assessment of individual suites of traits such as vegetation indices (Babar et al., 2006a,b) or root morphology (Trachsel et al., 2011).”
Identifying traits to improve the nitrogen economy of wheat: Recent advances and future prospects (2009, background): “Spectral reflectance indices, e.g. NDVI = (NIR VIS)/(NIR + VIS), have proved useful in the assessment of early biomass of different wheat genotypes (Eliott and Regan, 1993; Bellairs et al., 1996; Babar et al., 2006).”