scholarly journals Remote Estimation of Leaf and Canopy Water Content in Winter Wheat with Different Vertical Distribution of Water-Related Properties

2015 ◽  
Vol 7 (4) ◽  
pp. 4626-4650 ◽  
Author(s):  
Shishi Liu ◽  
Yi Peng ◽  
Wei Du ◽  
Yuan Le ◽  
Lu Li
Keyword(s):  
Winter Wheat ◽  
Vertical Distribution ◽  
Water Content ◽  
Remote Estimation ◽  
Canopy Water

Association of biomass production and canopy spectral reflectance indices in winter wheat

2009 ◽  
Vol 89 (3) ◽  
pp. 485-496 ◽  
Author(s):  
B. Prasad ◽  
M. A. Babar ◽  
B. F. Carver ◽  
W. R. Raun ◽  
A. R. Klatt
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Water Content ◽  
Biomass Production ◽  
Spectral Reflectance ◽  
Water Based ◽  
Canopy Spectral Reflectance ◽  
Reflectance Indices ◽  
Canopy Water ◽  
Spectral Reflectance Indices

Increased biomass production could be an important criterion for future grain yield improvement in wheat (Triticum aestivum L.). Quick assessment of genetic variations for biomass production may become a useful tool for wheat breeders. The potential of using canopy spectral reflectance indices (SRI) to assess genetic variation for biomass production in winter wheat was evaluated. Three experiments were conducted for 2 yr (2003-2004 and 2004-2005) at Oklahoma State University, Stillwater, OK. The first experiment consisted of 25 winter wheat cultivars, and the other two experiments contained two sets of 25 F4:6 and F4:7 recombinant inbred lines from two crosses developed by breeding programs in the great plains of the United States of America. Three groups of SRI (vegetation-based, pigment-based, and water-based) were tested for their ability to assess biomass production at three growth stages (booting, heading, and grainfilling). The water index and the normalized water indices gave stronger genetic correlations (P < 0.01) and linear relationship for biomass production compared with the vegetation-based and pigment-based indices. The strong association of water-based indices with biomass was related to the canopy water content of the genotypes. Canopy water content was significantly (P < 0.05) correlated with biomass production. A strong positive association (P < 0.05) of grain yield and dry biomass was observed at the heading and grainfilling stages. Our study demonstrated the potential of using water-based SRI as a breeding tool to estimate genetic variability and identify genotypes with higher biomass production, and could eventually help to achieve higher grain yield in winter wheat. Key words: Wheat; biomass; grain yield; spectral reflectance index

Remote Estimation of Canopy Water Content in Different Crop Types with New Hyperspectral Indices

2018 ◽  
Author(s):  
Nieves Pasqualotto ◽  
Jesus Delegido ◽  
Shari Van Wittenberghe ◽  
Jochem Verrelst ◽  
Juan Pablo Rivera ◽  
...  
Keyword(s):  
Water Content ◽  
Crop Types ◽  
Remote Estimation ◽  
Canopy Water

Retrieving Leaf and Canopy Water Content of Winter Wheat Using Vegetation Water Indices

2018 ◽  
Vol 11 (1) ◽  
pp. 112-126 ◽  
Author(s):  
Chao Zhang ◽  
Elizabeth Pattey ◽  
Jiangui Liu ◽  
Huanjie Cai ◽  
Jiali Shang ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Water Content ◽  
Vegetation Water ◽  
Canopy Water ◽  
Water Indices

Winter Wheat Canopy Water Content Monitoring Based on Spectral Transforms and “Three-edge” Parameters

2020 ◽  
Vol 240 ◽  
pp. 106306 ◽  
Author(s):  
Zhigong Peng ◽  
Shaozhe Lin ◽  
Baozhong Zhang ◽  
Zheng Wei ◽  
Lu Liu ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Water Content ◽  
Spectral Transforms ◽  
Canopy Water

Remote estimation of above ground nitrogen uptake during vegetative growth in winter wheat using hyperspectral red-edge ratio data

2015 ◽  
Vol 180 ◽  
pp. 197-206 ◽  
Author(s):  
Wei Feng ◽  
Bin-Bin Guo ◽  
Hai-Yan Zhang ◽  
Li He ◽  
Yuan-Shuai Zhang ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Nitrogen Uptake ◽  
Vegetative Growth ◽  
Red Edge ◽  
Ratio Data ◽  
Remote Estimation

Soil moisture variation drives canopy water content dynamics across the western U.S.

2021 ◽  
Vol 253 ◽  
pp. 112233
Author(s):  
Drew S. Lyons ◽  
Solomon Z. Dobrowski ◽  
Zachary A. Holden ◽  
Marco P. Maneta ◽  
Anna Sala
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Moisture Variation ◽  
Canopy Water ◽  
Soil Moisture Variation

scholarly journals Energy balance closure on a winter wheat stand: comparing the eddy covariance technique with the soil water balance method

2016 ◽  
Vol 13 (1) ◽  
pp. 63-75 ◽  
Author(s):  
K. Imukova ◽  
J. Ingwersen ◽  
M. Hevart ◽  
T. Streck
Keyword(s):  
Energy Balance ◽  
Water Balance ◽  
Winter Wheat ◽  
Water Content ◽  
Soil Water ◽  
Water Storage ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
Water Balance Method ◽  
Closure Method

Abstract. The energy balance of eddy covariance (EC) flux data is typically not closed. The nature of the gap is usually not known, which hampers using EC data to parameterize and test models. In the present study we cross-checked the evapotranspiration data obtained with the EC method (ETEC) against ET rates measured with the soil water balance method (ETWB) at winter wheat stands in southwest Germany. During the growing seasons 2012 and 2013, we continuously measured, in a half-hourly resolution, latent heat (LE) and sensible (H) heat fluxes using the EC technique. Measured fluxes were adjusted with either the Bowen-ratio (BR), H or LE post-closure method. ETWB was estimated based on rainfall, seepage and soil water storage measurements. The soil water storage term was determined at sixteen locations within the footprint of an EC station, by measuring the soil water content down to a soil depth of 1.5 m. In the second year, the volumetric soil water content was additionally continuously measured in 15 min resolution in 10 cm intervals down to 90 cm depth with sixteen capacitance soil moisture sensors. During the 2012 growing season, the H post-closed LE flux data (ETEC =  3.4 ± 0.6 mm day−1) corresponded closest with the result of the WB method (3.3 ± 0.3 mm day−1). ETEC adjusted by the BR (4.1 ± 0.6 mm day−1) or LE (4.9 ± 0.9 mm day−1) post-closure method were higher than the ETWB by 24 and 48 %, respectively. In 2013, ETWB was in best agreement with ETEC adjusted with the H post-closure method during the periods with low amount of rain and seepage. During these periods the BR and LE post-closure methods overestimated ET by about 46 and 70 %, respectively. During a period with high and frequent rainfalls, ETWB was in-between ETEC adjusted by H and BR post-closure methods. We conclude that, at most observation periods on our site, LE is not a major component of the energy balance gap. Our results indicate that the energy balance gap is made up by other energy fluxes and unconsidered or biased energy storage terms.

scholarly journals Estimating Vertical Distribution of Leaf Water Content within Wheat Canopies after Head Emergence

2021 ◽  
Vol 13 (20) ◽  
pp. 4125
Author(s):  
Weiping Kong ◽  
Wenjiang Huang ◽  
Lingling Ma ◽  
Lingli Tang ◽  
Chuanrong Li ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Water Content ◽  
Near Infrared ◽  
Field Experiments ◽  
Estimation Method ◽  
Middle Layer ◽  
Leaf Water ◽  
Leaf Water Content ◽  
Growth Stages ◽  
Spectral Indices

Monitoring vertical profile of leaf water content (LWC) within wheat canopies after head emergence is vital significant for increasing crop yield. However, the estimation of vertical distribution of LWC from remote sensing data is still challenging due to the effects of wheat spikes and the efficacy of sensor measurement from the nadir direction. Using two-year field experiments with different growth stages after head emergence, N rates, wheat cultivars, we investigated the vertical distribution of LWC within canopies, the changes of canopy reflectance after spikes removal, the relationship between spectral indices and LWC in the upper-, middle- and bottom-layer. The interrelationship among vertical LWC were constructed, and four ratio of reflectance difference (RRD) type of indices were proposed based on the published WI and NDWSI indices to determine vertical distribution of LWC. The results indicated a bell shape distribution of LWC in wheat plants with the highest value appeared at the middle layer, and significant linear correlations between middle-LWC vs. upper-LWC and middle-LWC vs. bottom-LWC (r ≥ 0.92) were identified. The effects of wheat spikes on spectral reflectance mainly occurred in near infrared to shortwave infrared regions, which then decreased the accuracy of LWC estimation. Spectral indices at the middle layer outperformed the other two layers in LWC assessment and were less susceptible to wheat spikes effects, in particular, the newly proposed narrow-band WI-4 and NDWSI-4 indices exhibited great potential in tracking the changes of middle-LWC (R2 = 0.82 and 0.84, respectively). By taking into account the effects of wheat spikes and the interrelationship of vertical LWC within canopies, an indirect induction strategy was developed for modeling the upper-LWC and bottom-LWC. It was found that the indirect induction models based on the WI-4 and NDWSI-4 indices were more effective than the models obtained from conventional direct estimation method, with R2 of 0.78 and 0.81 for the upper-LWC estimation, and 0.75 and 0.74 for the bottom-LWC estimation, respectively.

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