Monitoring leaf pigment status with hyperspectral remote sensing in wheat

2008 ◽  
Vol 59 (8) ◽  
pp. 748 ◽  
Author(s):  
Wei Feng ◽  
Xia Yao ◽  
Yongchao Tian ◽  
Weixing Cao ◽  
Yan Zhu
Keyword(s):  
Protein Concentration ◽  
Grain Protein ◽  
Growth Stages ◽  
Hyperspectral Reflectance ◽  
Red Edge ◽  
Leaf Pigment ◽  
Lower Estimation ◽  
Pigment Concentrations ◽  
Highly Correlated ◽  
Red Edge Position

Leaf pigment status within a canopy is a key index for evaluating photosynthetic efficiency and nutritional stress in crop plants. Non-destructive and quick assessment of leaf pigment status is needed for growth diagnosis, yield prediction, and nitrogen (N) management in crop production. The objectives of this study were to analyse quantitative relationships of leaf pigment concentration on a dry weight basis and leaf pigment density per unit soil area to ground-based canopy hyperspectral reflectance and derivative parameters, and to establish estimation models for real-time monitoring of leaf pigment status with key hyperspectral bands and indices in wheat (Triticum aestivum L.). Two field experiments were conducted with different N application rates and wheat cultivars across two growing seasons, and time-course measurements were taken on canopy hyperspectral reflectance over 350−2500 nm, leaf pigment concentrations, and leaf dry weights under the various treatments at different growth stages. The results showed that different pigment concentrations and densities of chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophyll (Chla+b), and carotenoids (Car) in two cultivars, Ningmai 9 (low grain protein concentration) and Yumai 34 (high grain protein concentration), tended to increase with increasing N rates, and differed with genotypes and growth stages. The analyses on the relationships between vegetation indices and leaf pigment concentrations and densities indicated that the pigment concentrations and pigment densities, respectively, were highly correlated with eight spectral parameters selected. The leaf chlorophyll concentrations were highly correlated with red edge position, with highest coefficients of determination (R2) for REPLE, while R2 between Car and spectral indices decreased. The chlorophyll densities were highly correlated with VOG2, VOG3, RVI(810,560), Dr/Db, and SDr/SDb, but the correlation was also reduced for carotenoids. Testing of the monitoring equations with independent datasets indicated that the red edge position was the best hyperspectral parameter to estimate leaf pigment concentrations, with no significant difference between REPLE and REPIG for Chla, Chla+b, and Car, although better performance with REPIG than with REPIE for estimation of Chlb. The VOG2, VOG3, Dr/Db, and SDr/SDb were the best hyperspectral parameters to estimate leaf pigment densities, but with lower estimation accuracy for Chlb and lower estimation precision for Car. The overall results suggested that the pigment concentrations and densities in wheat leaves, especially for Chla and Chla+b, could be reliably estimated with the hyperspectral parameters established in this study.

scholarly journals LEAF CHLOROPHYLL CONTENT ESTIMATION IN THE MONARCH BUTTERFLY BIOSPHERE RESERVE

2010 ◽  
Vol 33 (2) ◽  
pp. 175
Author(s):  
Ma. Luisa España-Boquera ◽  
Philippe Lobit ◽  
Vilma Castellanos-Morales
Keyword(s):  
Chlorophyll Content ◽  
Vegetation Indices ◽  
Biosphere Reserve ◽  
Monarch Butterfly ◽  
Hyperspectral Reflectance ◽  
Plant Leaves ◽  
Red Edge ◽  
Monarch Butterfly Biosphere Reserve ◽  
Leaf Composition ◽  
Red Edge Position

Chlorophyll is an essential element of photosynthesis and its content in plant leaves indicates their photosynthetic capacity as well as the presence of stress or diseases. The purpose of this work was to evaluate the feasibility of estimating chlorophyll content in the Monarch Butterfly Biosphere Reserve forest (Sierra Chincua sanctuary, México) based on vegetation indices calculated by using hyperspectral reflectance measurements of plant leaves. This study focused on oyamel (Abies religiosa L.) which is the main tree specie of this area. Leaf samples were taken on 140 trees and analyzed for chlorophyll a and b, nitrogen and carbon content. The hyperspectral reflectance spectra were measured on each sample and different vegetation indices were calculated. Results showed that the indices best correlated with chlorophyll content were the red edge position index (r = 0.531) and the red edge position chlorophyll reflectance index (r = 0.506), followed by the MERIS terrestrial chlorophyll index (r = 0.497) and the green chlorophyll reflectance index (r = 0.472). Although there was a significant correlation between nitrogen and chlorophyll content, none of the indices studied here correlated with nitrogen content. The influence of various environmental factors (altitude, slope, vegetation density and aspect) on leaf composition (nitrogen, carbon chlorophyll content and chlorophyll a/b ratio) and on the vegetation indices was studied. Environmental factors had an influence on both leaf composition and vegetation indices. Chlorophyll and nitrogen content were influenced mostly by the altitude and slope of the site while vegetation indices were affected mostly by its orientation.

scholarly journals Estimation of Crop Growth Parameters Using UAV-Based Hyperspectral Remote Sensing Data

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1296 ◽  
Author(s):  
Huilin Tao ◽  
Haikuan Feng ◽  
Liangji Xu ◽  
Mengke Miao ◽  
Huiling Long ◽  
...  
Keyword(s):  
Growth Parameters ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Crop Growth ◽  
Growth Stages ◽  
Complex Data ◽  
Least Squares Regression ◽  
Area Index ◽  
Red Edge ◽  
Highly Correlated

Above-ground biomass (AGB) and the leaf area index (LAI) are important indicators for the assessment of crop growth, and are therefore important for agricultural management. Although improvements have been made in the monitoring of crop growth parameters using ground- and satellite-based sensors, the application of these technologies is limited by imaging difficulties, complex data processing, and low spatial resolution. Therefore, this study evaluated the use of hyperspectral indices, red-edge parameters, and their combination to estimate and map the distributions of AGB and LAI for various growth stages of winter wheat. A hyperspectral sensor mounted on an unmanned aerial vehicle was used to obtain vegetation indices and red-edge parameters, and stepwise regression (SWR) and partial least squares regression (PLSR) methods were used to accurately estimate the AGB and LAI based on these vegetation indices, red-edge parameters, and their combination. The results show that: (i) most of the studied vegetation indices and red-edge parameters are significantly highly correlated with AGB and LAI; (ii) overall, the correlations between vegetation indices and AGB and LAI, respectively, are stronger than those between red-edge parameters and AGB and LAI, respectively; (iii) Compared with the estimations using only vegetation indices or red-edge parameters, the estimation of AGB and LAI using a combination of vegetation indices and red-edge parameters is more accurate; and (iv) The estimations of AGB and LAI obtained using the PLSR method are superior to those obtained using the SWR method. Therefore, combining vegetation indices with red-edge parameters and using the PLSR method can improve the estimation of AGB and LAI.

scholarly journals Deviation from the grain protein concentration–grain yield negative relationship is highly correlated to post-anthesis N uptake in winter wheat

2010 ◽  
Vol 61 (15) ◽  
pp. 4303-4312 ◽  
Author(s):  
Matthieu Bogard ◽  
Vincent Allard ◽  
Maryse Brancourt-Hulmel ◽  
Emmanuel Heumez ◽  
Jean-Marie Machet ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Protein Concentration ◽  
N Uptake ◽  
Negative Relationship ◽  
Grain Protein ◽  
Grain Protein Concentration ◽  
Highly Correlated

scholarly journals Modelling durum wheat (Triticum turgidum L. var. durum) grain protein concentration

2016 ◽  
Vol 155 (6) ◽  
pp. 930-938 ◽  
Author(s):  
F. ORLANDO ◽  
M. MANCINI ◽  
R. MOTHA ◽  
J.J. QU ◽  
S. ORLANDINI ◽  
...  
Keyword(s):  
Durum Wheat ◽  
Leaf Area ◽  
Protein Concentration ◽  
Triticum Turgidum ◽  
Model Simulation ◽  
Ground Surface ◽  
Grain Protein ◽  
Growth Stages ◽  
Area Index ◽  
Grain Protein Concentration

SUMMARYThe goal of the present study was to improve the CERES-wheat model simulation of grain protein concentration (GPC) for winter durum wheat and to use the model as a basis for the development of a GPC Simplified Forecasting Index (SFIpro). The performances of CERES-wheat, which is one of the most widespread crop simulation models, with (i) its standard GPC routine and (ii) a novel equation developed to improve the model GPC simulation for durum wheat, were assessed through comparison with field data. Subsequently, CERES-wheat was run for a 56-year period in order to identify the most important status and forcing variables affecting GPC simulation. The number of dry days during the early growth stages and the leaf area index (LAI; green leaf area per unit ground surface area) at heading stage (LAI5) were identified as the main variables positively correlated with CERES-wheat predicted GPC, and so included in the SFIpro. At validation against observed data SFIpro was found to perform differently on the basis of observed plant LAI. In fact, SFIpro was able to forecast GPC variability for intermediate values of LAI5 ranging from 1 to 2, while it totally failed when LAI5 was outside this range (LAI5 < 1 or LAI5 > 2). The results suggest that the relationship between LAI and GPC is not linear and that the model assumptions for GPC simulation in CERES-wheat are only partially confirmed, being valid for an intermediate range of LAI.

Genetic Relationship between Kernel Discoloration and Grain Protein Concentration in Barley

Crop Science ◽  
2003 ◽  
Vol 43 (5) ◽  
pp. 1671-1679 ◽  
Author(s):  
Paulo C. Canci ◽  
Lexingtons M. Nduulu ◽  
Ruth Dill‐Macky ◽  
Gary J. Muehlbauer ◽  
Donald C. Rasmusson ◽  
...  
Keyword(s):  
Genetic Relationship ◽  
Protein Concentration ◽  
Grain Protein ◽  
Grain Protein Concentration ◽  
Kernel Discoloration

Crop and soil nitrogen status of tilled and no-tillage systems in semiarid regions of Saskatchewan

2002 ◽  
Vol 82 (4) ◽  
pp. 489-498 ◽  
Author(s):  
B G McConkey ◽  
D. Curtin ◽  
C A Campbell ◽  
S A Brandt ◽  
F. Selles
Keyword(s):  
Grain Yield ◽  
Protein Concentration ◽  
Grain Protein ◽  
Soil N ◽  
Grain Protein Concentration ◽  
Brown Soil ◽  
Semiarid Regions ◽  
Soil Zone ◽  
Tillage System ◽  
Loam Soil

We examined 1990-1996 crop and soil N data for no-tillage (NT), minimum tillage (MT) and conventional tillage (CT) systems from four long-term tillage studies in semiarid regions of Saskatchewan for evidence that the N status was affected by tillage system. On a silt loam and clay soil in the Brown soil zone, spring what (Triticum aestivum L.) grain yield and protein concentration were lower for NT compared with tilled (CT or MT) systems for a fallow-wheat (F-WM) rotation. Grain protein concentration for continuous wheat (Cont W) was also lower for NT than for MT. For a sandy loam soil in the Brown soil zone, durum (Triticum durum L.) grain protein concentration was similar for MT and NT for both Cont W and F-W, but NT had higher grain yield than MT (P < 0.05 for F-W only). For a loam soil in the Dark Brown soil zone, wheat grain yield for NT was increased by about 7% for fallow-oilseed-wheat (F-O-W) and wheat-oilseed-wheat (W-O-W) rotations. The higher grain yields for NT reduced grain protein concentration by dilution effect as indicated by similar grain N yield. However, at this site, about 23 kg ha-1 more fertilizer N was required for NT than for CT. Elimination of tillage increased total organic N in the upper 7.5 cm of soil and N in surface residues. Our results suggest that a contributing factor to decreased availability of soil N in medium- and fine-textured soils under NT was a slower rate of net N mineralization from organic matter. Soil nitrates to 2.4 m depth did not indicate that nitrate leaching was affected by tillage system. Current fertilizer N recommendations developed for tilled systems may be inadequate for optimum production of wheat with acceptable grain protein under NT is semiarid regions of Saskatchewan. Key words: Tillage intensity, N availability, soil N fractions, N mineralization, crop residue decomposition, grain protein

Effect of leaf spotting diseases on grain yield and seed traits of wheat in southern Saskatchewan

2002 ◽  
Vol 82 (3) ◽  
pp. 507-512 ◽  
Author(s):  
H. Wang ◽  
M. R. Fernandez ◽  
F. R. Clarke ◽  
R. M. DePauw ◽  
J. M. Clarke
Keyword(s):  
Grain Yield ◽  
Protein Concentration ◽  
Flag Leaf ◽  
Kernel Weight ◽  
Test Weight ◽  
Grain Protein ◽  
Seed Traits ◽  
Grain Protein Concentration ◽  
Leaf Emergence ◽  
Weight Test

Although leaf spotting diseases have been reported to have a negative effect on grain yield and seed characteristics of wheat (Triticum spp.), the magnitude of such effects on wheat grown on dryland in southern Saskatchewan is not known. A fungicide experiment was conducted at Swift Current (Brown soil) and Indian Head (Black soil) from 1997 to 1999 to determine the effect of leaf spotting diseases on yield and seed traits of wheat. Two fungicides, Folicur 3.6F and Bravo 500, were applied at different growth stages on three common wheat (Triticum aestivum L.) and three durum wheat (T. turgidum L. var durum) genotypes. Fungicide treatments generally did not affect yield, kernel weight, test weight or grain protein concentration, and these effects were relatively consistent among genotypes. Folicur applied at head emergence in 1997 and at flag leaf emergence and/or head emergence in 1998 increased yield at Indian Head (P < 0.05). Fungicides applied at and before flag leaf emergence tended to increase kernel weight. Grain protein concentration increased only in treatments of Bravo applications at Indian Head in 1998. These results suggested that under the dryland environment and management in southern Saskatchewan leaf spotting diseases generally have a small effect on yield, kernel weight, test weight and protein concentration. Key words: Wheat, leaf spotting diseases, fungicide, yield

Effect of weeds and nitrogen fertiliser on yield and grain protein concentration of wheat

1996 ◽  
Vol 36 (4) ◽  
pp. 443 ◽  
Author(s):  
MG Mason ◽  
RW Madin
Keyword(s):  
Grain Yield ◽  
Weed Control ◽  
Dry Matter ◽  
Protein Concentration ◽  
The Other ◽  
Grain Protein ◽  
Dry Matter Yield ◽  
Wheat Grain ◽  
Grain Protein Concentration ◽  
Nitrogen Fertiliser

Field trials at Beverley (19911, Salmon Gums (1991; 2 sites) and Merredin (1992; 2 sites), each with 5 rates of nitrogen (N) and 3 levels of weed control, were used to investigate the effect of weeds and N on wheat grain yield and protein concentration during 1991 and 1992. Weeds in the study were grasses (G) and broadleaf (BL). Weeds reduced both vegetative dry matter yield and grain yield of wheat at all sites except for dry matter at Merredin (BL). Nitrogen fertiliser increased wheat dry matter yield at all sites. Nitrogen increased wheat grain yield at Beverley and Merredin (BL), but decreased yield at both Salmon Gums sites in 1991. Nitrogen fertiliser increased grain protein concentration at all 5 sites-at all rates for 3 sites [Salmon Gums (G) and (BL) and Merredin (G)] and at rates of 69 kg N/ha or more at the other 2 sites [Beverley and Merredin (BL)]. However, the effect of weeds on grain protein varied across sites. At Merredin (G) protein concentration was higher where there was no weed control, possibly due to competition for soil moisture by the greater weed burden. At Salmon Gums (G), grain protein concentration was greater when weeds were controlled than in the presence of weeds, probably due to competition for N between crop and weeds. In the other 3 trials, there was no effect of weeds on grain protein. The effect of weeds on grain protein appears complex and depends on competition between crop and weeds for N and for water at the end of the season, and the interaction between the two.

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