Correlations between canopy reflectance and leaf temperature in irrigated and droughted soybeans

Cure, William W.; Flagler, Richard B.; Heagle, Allen S.

doi:10.1016/0034-4257(89)90006-0

Cited by 14 publications

(12 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such correlations could better refl ect relationships between canopy temperature and severity of wear plus soil compaction. A canopy ratio of R850/R620 was correlated with plant temperature (r from -0.64 to -0.77) in droughted soybean (Cure et al, 1989). Similar results at R849/R622 were found in wear and wear plus soil compaction for turfgrass in our study.…”

Section: Correlations Of Reflectance Indices Canopy Tem Per a Ture Asupporting

confidence: 87%

“…STRESS INDEX (THREE VERSIONS): R695/R420, R695/R760; R706/ R813 (modifi ed from Carter, 1994;Trenholm et al, 1999a). LEAF AREA INDEX (IR/R) (TWO VERSIONS): R850/R620; R935/R661 (modifi ed from Cure et al, 1989;Trenholm et al, 1999a). WATER BAND INDEX (TWO VERSIONS): R900/R970, (R700-R1100)/ R700 (modifi ed from Penuelas et al, 1997a;Rollin and Milton.…”

Section: Normalized Difference Vegetation Index (Three Versions)mentioning

confidence: 99%

“…The fi rst derivative of refl ectance at 939 to 952 nm was correlated with temperature under both stresses at P < 0.01, but not at P < 0.001. Cure et al (1989) found that canopy temperature was cor relat ed with canopy refl ectance at 620 nm and 850 nm in soybean (Glycine max L.) under drought stress. In our study, wear stress mainly affected turfgrass above ground but the wear plus soil compaction operation reduced shoot density and exposed more soil.…”

Section: Turf Quality Density and Percent Can O Py Coveragementioning

confidence: 99%

“…Therefore, the spectral refl ectance data could be incorporated with visual ob ser va tion or other instrumental estimations of turf canopy nature, which would aid in assessing how turfgrass research and man age ment opera-Canopy spectral refl ectance provides an important meth od for plant canopy study under different environmental conditions. Multispectral analysis has been widely used for determining canopy responses to environmental stresses, pri ma ri ly by measur ing variations of canopy refl ectance from visible or/and near infrared wavelengths (Carter et al, 1996;Cure et al, 1989;Huang et al, 1998;Penuelas et al, 1997a;Trenholm et al, 1999a). The changes in canopy refl ectance at a single wave length, a defi ned wavelength band, or various indices have been used to identify a correlation with canopy variables such as pigment content, pho to chem i cal activity, green biomass, and water content (Gamon and Surfus, 1999;Lorenzen and Jensen, 1988;Rollin and Milton, 1998).…”

mentioning

confidence: 99%

See 3 more Smart Citations

Correlation Analysis Procedures for Canopy Spectral Reflectance Data of Seashore Paspalum under Traffic Stress

Jiang¹,

Carrow²,

Duncan³

2003

jashs

View full text Add to dashboard Cite

Traffic stresses often cause a decline in turfgrass quality. Analysis of spectral reflectance is valuable for assessing turfgrass canopy status. The objectives of this study were to determine correlations of narrow band canopy reflectance and selected reflectance indices with canopy temperature and turf quality for seashore paspalum exposed to wear and wear plus soil compaction traffic stresses, and to evaluate the effects of the first derivative of reflectance and degree of data smoothing (spectral manipulations) on such correlations. `Sea Isle 1' seashore paspalum (Paspalum vaginatum Swartz) was established on a simulated sports field during 1999 and used for this study. Compared to original reflectance, the first derivative of reflectance increased the correlation coefficient (r) of certain wavelengths with canopy temperature and turf quality under both traffic stresses. Among 217 wavelengths tested between 400 and 1100 nm, the peak correlations of the first derivative of reflectance occurred at 661 nm and 664 nm for both canopy temperature and turf quality under wear stress, respectively, while the highest correlations were found at 667 nm and 820 to 869 nm for both variables under wear plus soil compaction. Collectively, the first derivative of reflectance at 667 nm was the optimum position to determine correlation with canopy temperature (r > 0.62) and turf quality (r < -0.72) under both traffic stresses. All correlations were not sensitive to degrees of smoothing of reflectance from 400 to 1100 nm. A ratio of R936/R661 (IR/R, Infrared/red) and R693/759 (stress index) had the strongest correlations with canopy temperature for wear (r = -0.63) and wear plus soil compaction (r = 0.66), respectively; and a ratio of R693/R759 had the strongest correlation with turf quality for both wear (r = -0.89) and wear plus soil compaction (r = -0.82). The results suggested that the first derivative of reflectance could be used to estimate any single wavelength simultaneously correlated with multiple turf canopy variables such as turf quality and canopy temperature, and that the stress index (R693/R759) was also a good indicator of canopy stress status.

show abstract

Section: Correlations Of Reflectance Indices Canopy Tem Per a Ture Asupporting

confidence: 87%

Section: Normalized Difference Vegetation Index (Three Versions)mentioning

confidence: 99%

Section: Turf Quality Density and Percent Can O Py Coveragementioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Correlation Analysis Procedures for Canopy Spectral Reflectance Data of Seashore Paspalum under Traffic Stress

Jiang¹,

Carrow²,

Duncan³

2003

jashs

View full text Add to dashboard Cite

show abstract

“…According to these result, estimated values of SWDI through SAVI up to 0.12 indicates non-water stressed conditions. Some previous studies propose estimation of water stress by means of spectral indexes (Pinter 1983;Saha et al 1986;Luquet et al 2003;Cure et al 1989;Cohen 1991;Riggs and Running 1991;Danson et al 1992;Penuelas et al 1993Penuelas et al , 1997.…”

Section: Resultsmentioning

confidence: 99%

Estimation of green bean yield, water deficiency and productivity using spectral indexes during the growing season

Köksal

Kara

Apan

et al. 2008

Irrig Drainage Syst

View full text Add to dashboard Cite

Field experiments were carried out in the 2004 and 2005 growing seasons on drip irrigated dwarf green beans (Phaseolus vulgaris, humilis). Soil water content (SWC), spectral reflectance and yield were monitored. Based on these data crop evapotranspiration (ETc), soil water deficit index (SWDI), water use efficiency (WUE) and four separate spectral indexes were calculated. In order to determine use opportunities of spectral indexes for estimation of yield, SWDI and WUE, some statistical analyzes were made. Results showed that spectral indexes could be used for monitoring of yield, SWDI and WUE. Especially, Soil Adjusted Vegetation Index (SAVI) had the highest correlations with all three of the parameters. The estimation procedure which was given in this study has a potential use either during, or at the end of the growing season. Estimated values of WUE and SWDI were 3.2 (kg m −3 ) and 0.12, respectively, through SAVI and the given procedure, indicates the optimal water use and yield conditions for dwarf green beans. At this situation, probably ETc was 580 mm and yield was 25.5 t ha −1 .

show abstract

Time‐series multispectral imaging in soybean for improving biomass and genomic prediction accuracy

et al. 2022

View full text Add to dashboard Cite

Multispectral (MS) imaging enables the measurement of characteristics important for increasing the prediction accuracy of genotypic and phenotypic values for yieldrelated traits. In this study, we evaluated the potential application of temporal MS imaging for the prediction of aboveground biomass (AGB) in soybean [Glycine max (L.) Merr.]. Field experiments with 198 accessions of soybean were conducted with four different irrigation levels. Five vegetation indices (VIs) were calculated using MS images from soybean canopies from early vegetative to early reproductive stage. To predict the genotypic values of AGB, VIs at the different growth stages were used as secondary traits in a multitrait genomic prediction. The prediction accuracy of the genotypic values of AGB from MS and genomic data largely outperformed that of the genomic data alone before the flowering stage (90% of accessions did not flower), suggesting that it would be possible to determine cross-combinations based on the predicted genotypic values of AGB. We compared the prediction accuracy of a model using the five VIs and a model using only one VI to predict the phenotypic values of AGB and found that the difference in prediction accuracy decreased over time at all irrigation levels except for the most severe drought. The difference in the most severe drought was not as small as that in the other treatments. Only the prediction accuracy of a model using the five VIs in the most severe droughts gradually increased over time. Therefore, the optimal timing for MS imaging may depend on the irrigation levels.Abbreviations: AGB, aboveground biomass; DTF, days to flowering; GEI, genotype × environment interaction; GRVI, green-red vegetation index; MS, multispectral; MT, multitrait; NDI red , normalized difference index using red-edge and red spectral reflectance; NDRE, normalized difference red-edge index; NDVI, normalized difference vegetation index; PCA, principal component analysis; RTVI, red-edge triangular vegetation index; SNP, single-nucleotide polymorphism; UAV, unmanned aerial vehicle; VI, vegetation index.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Correlations between canopy reflectance and leaf temperature in irrigated and droughted soybeans

Cited by 14 publications

References 20 publications

Correlation Analysis Procedures for Canopy Spectral Reflectance Data of Seashore Paspalum under Traffic Stress

Correlation Analysis Procedures for Canopy Spectral Reflectance Data of Seashore Paspalum under Traffic Stress

Estimation of green bean yield, water deficiency and productivity using spectral indexes during the growing season

Time‐series multispectral imaging in soybean for improving biomass and genomic prediction accuracy

Contact Info

Product

Resources

About