Field Measurements of Canopy Spectra for Biomass Assessment of Small-Grain Cereals

Royo, C.; Villegas, D.

doi:10.5772/17745

Cited by 20 publications

(16 citation statements)

References 114 publications

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“…The commonalities of Δ 13 C and the spectral indices catching genotypic differences in GY only at the two least stressed growing conditions indicate that these SRI capture the genotypic variability in Δ 13 C just through the same physiological principles as they do capturing in GY. In fact, when pooling data from different trials, NWI3 assessed a similarly large proportion of green biomass (around 80%) as vegetation indices like NDVI (Royo and Villegas ). In the same sense, when GY data from the three growing environments were combined in this study, the strength of the determination coefficients of the relationships of NWI3, NDMI2, and SWWI were very high and comparable to that of NDVI.…”

Section: Discussionmentioning

confidence: 99%

Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance

Lobos

Matus²,

Rodríguez³

et al. 2014

JIPB

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A collection of 368 advanced lines and cultivars of spring wheat (Triticum aestivum L.) from Chile, Uruguay, and CIMMYT (Centro Internacional de Mejoramiento de Maíz y Trigo), with good agronomic characteristics were evaluated under the Mediterranean conditions of central Chile. Three different water regimes were assayed: severe water stress (SWS, rain fed), mild water stress (MWS; one irrigation around booting), and full irrigation (FI; four irrigations: at tillering, flag leaf appearance, heading, and middle grain filling). Traits evaluated were grain yield (GY), agronomical yield components, days from sowing to heading, carbon isotope discrimination (D 13 C) in kernels, and canopy spectral reflectance. Correlation analyses were performed for 70 spectral reflectance indices (SRI) and the other traits evaluated in the three trials. GY and D 13C were the traits best correlated with SRI, particularly when these indices were measured during grain filling. However, only GY could be predicted using a single regression, with NIR-based SRI proved to be better predictors than those that combine visible and NIR wavelengths.Keywords: Breeding; drought; dry matter index; normalized difference moisture index; vegetative index; water index Citation: Lobos GA, Matus I, Rodriguez A, Romero-Bravo S, Araus JL, del Pozo A (2014) Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance.

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Section: Discussionmentioning

confidence: 99%

Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance

Lobos

Matus²,

Rodríguez³

et al. 2014

JIPB

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“…As the field of view for the NDVI measurements was smaller than the gaps between the slats (~17.5 cm), we selected the maximum NDVI measurement for each sensor during a given day to avoid the effects of shelter artefacts and clouds. Greenness was calculated using the following equation based on Royo & Villegas ():

Greenness (NDVI) = \frac{ρ NIR - ρ red}{ρ NIR + ρ red}

where ρNIR is the percentage reflectance of the near infrared (the ratio of the reflected NIR from the vegetation to the incident NIR) and ρred is percentage reflectance of the red (the ratio of reflected red of the vegetation to the incident red). Daily greenness data were smoothed across the whole time period using local regression (PROC LOESS, span = 0.1; sas v9.3, SAS Institute, Raleigh, NC, USA), which is a nonparametric method that estimates local regression surfaces (Cleveland & Loader ).…”

Section: Methodsmentioning

confidence: 99%

Testing the apparent resistance of three dominant plants to chronic drought on the Colorado Plateau

2016

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Summary Many drylands, including the south‐western United States, are projected to become more water‐limited as these regions become warmer and drier with climate change. Such chronic drought may push individual species or plant functional types beyond key thresholds leading to reduced growth or even mortality. Indeed, recent observational and experimental evidence from the Colorado Plateau suggests that C3 grasses are the most vulnerable to chronic drought, while C4 grasses and C3 shrubs appear to have greater resistance. The effects of chronic, or press‐drought are predicted to begin at the physiological level and translate up to higher hierarchical levels. To date, the drought resistance of C4 grasses and C3 shrubs in this region has been only evaluated at the community level and thus we lack information on whether there are sensitivities to drought at lower hierarchical levels. In this study, we tested the apparent drought resistance of three dominant species (Pleuraphis jamesii, a C4 rhizomatous grass; Coleogyne ramosissima, a C3 drought‐deciduous shrub; and Ephedra viridis, a C3 evergreen shrub) to an ongoing experimental press‐drought (‐35% precipitation) by comparing individual‐level responses (ecophysiology and growth dynamics) to community‐level responses (plant cover). For all three species, we observed consistent responses across all hierarchical levels: P. jamesii was sensitive to drought across all measured variables, while the shrubs C. ramosissima and E. viridis had little to no responses to the experimental press‐drought at any given level. Synthesis. Our findings suggest that the apparent drought resistance at higher hierarchical levels, such as cover, may serve as good proxies for lower‐level responses. Furthermore, it appears the shrubs are avoiding drought, possibly by utilizing moisture at deeper soil layers, while the grasses are limited to shallower layers and must endure the drought conditions. Give this differential sensitivity to drought, a future with less precipitation and higher temperatures may increase the dominance of shrubs on the Colorado Plateau, as grasses succumb to chronic water stress.

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“…The assessment of AB is important for monitoring crop growth because it could reflect the effect of stresses on crop growth and senescence (Araus et al, 2008;Royo and Villegas, 2011). Larger green AB represents higher potential canopy photosynthesis and thus more yield.…”

Section: Introductionmentioning

confidence: 99%

The combined use of vegetation indices and stable isotopes to predict durum wheat grain yield under contrasting water conditions

Elazab

Bort

Zhou

et al. 2015

Agricultural Water Management

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Field Measurements of Canopy Spectra for Biomass Assessment of Small-Grain Cereals

Cited by 20 publications

References 114 publications

Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance

Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance

Testing the apparent resistance of three dominant plants to chronic drought on the Colorado Plateau

The combined use of vegetation indices and stable isotopes to predict durum wheat grain yield under contrasting water conditions

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