Relationship between Growth Traits and Spectral Vegetation Indices in Durum Wheat

Abstract

Destructive sampling for TDM assessment is tedious and time-consuming, and reduces the area available for Future wheat yield improvements may be gained by increasing determining final grain yield in small research plots. total dry matter (TDM) production. Vegetation indices (VI) based on spectral reflectance ratios have been proposed as an appropriate Also, sampling errors often hinder the detection of gemethod to assess TDM and leaf area index (LAI) in wheat. This study notypic differences (Whan et al., 1991). In the last years, was undertaken to determine whether VI could accurately identify VI based on spectral reflectance measurements have TDM and LAI in durum wheat {Triticum turgidum var. durum (Desf.) been proposed as a reliable nondestructive method for Bowden [ϭ T. turgidum subsp. durum (Desf.) Husn.]} and serve as quickly estimating TDM (Tucker, 1979; Asrar et al., indirect selection criteria in breeding programs. Total dry matter and 1984) and LAI in wheat and barley (Elliott and Regan, LAI were determined from destructive sampling from booting to 1993). Total dry matter is mainly determined by two milk-grain in seven field experiments conducted under Mediterranean processes: (i) the interception by the canopy of incident conditions. Each experiment included one of two sets of 20 or 25 solar irradiance, which depends on the photosynthetic genotypes. Field reflectance values were collected using a portable area of the canopy; and (ii) the conversion of the interfield spectroradiometer. Two VI, the normalized difference vegetation index (NDVI) and the simple ratio (SR), were derived from spectral cepted radiant energy to potential chemical energy, measurements and their predictive value for TDM and LAI was evalu-which relies on the overall photosynthetic efficiency of ated. The best stages for growth trait appraisal were Stages 65 and the crop (Hay and Walker, 1989). A rapid, nondestruc-75 of the Zadoks scale. The power of VI for assessing TDM was lower tive simultaneous estimation of both processes may be than their predictive value for LAI. The suitability of VI for the provided by VI based on reflectance values at specific assessment of growth traits depended on the range of variability existwavelengths or formulations using simple operations ing within the experimental data. Vegetation indices accurately between reflectances at given wavelengths (Field et tracked changes in LAI when data were analyzed across a broad range al., 1994). of different growth stages, environments, and genotypes. However,Research to develop applications for VI has focused their value as indirect genotypic selection criteria for TDM or LAI was on wide bandwidths (Blackmer et al., 1996). High speclimited, since they lacked predictive ability for specific environment/ growth stage combinations.

Testing the Temporal Ability of Landsat Imagery and Precision Agriculture Technology to Provide High Resolution Historical Estimates of Wheat Yield at the Farm Scale

“…These findings have also been supported by satellite based studies which indicated good associations between NDVI and wheat grain yield 50 to 110 days after plant emergence [2,15,19,26,49,50]. This wide time period encapsulates critical phenological phases for predicting the final wheat yield, including the formation and organisation of the canopy structure after the emergence of the flag leaf [8,50], at the end of stem elongation and beginning of heading [47] and grain formation [51]. Other studies [11,14] and those undertaken in Australia [37,49,52] suggest that for cereal crops, biomass or LAI measures at the flowering or anthesis stage (September to November) are closely related to final yield.…”

“…After this stage (during the ripening process) there is an asymptotic relationship between NDVI, LAI and yield [14,46,47]. This indicates that the use of NDVI as a surrogate for biomass and yield prediction is best at crop stages where LAI values are less than 3 [45].…”

Using Ridge Regression Models to Estimate Grain Yield from Field Spectral Data in Bread Wheat (Triticum Aestivum L.) Grown under Three Water Regimes

“…Various studies in wheat have associated GY with reflectance data from these zones of the spectral signature [17,21,50].…”

Study on Relationship between Tobacco Canopy Spectra and LAI

“…In wheat study of Aparicio et.al. [14] , the correlation of LAI with vegetation index was not affected by planting measures, species or planting area. But such results on tobacco should be verified through further test.…”