scholarly journals Estimating Leaf Chlorophyll Content of Buffaloberry Using Normalized Difference Vegetation Index Sensors

2021 ◽  
pp. 1-7
Author(s):  
Ji-Jhong Chen ◽  
Shuyang Zhen ◽  
Youping Sun
Keyword(s):  
Chlorophyll Content ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Red Light ◽  
Leaf Chlorophyll Content ◽  
Nir Light ◽  
Leaf Chlorophyll ◽  
Chlorophyll Extraction ◽  
Relative Chlorophyll Content

Commercial optical chlorophyll meters estimate relative chlorophyll content using the ratio of transmitted red light and near-infrared (NIR) light emitted from a red light-emitting diode (LED) and an NIR LED. Normalized difference vegetation index (NDVI) sensors have red and NIR light detectors and may be used to estimate chlorophyll content by detecting the transmitted red and NIR light through leaves. In this study, leaf chlorophyll content of ‘Torrey’ buffaloberry (Shepherdia ×utahensis) plants treated with 0 mm [zero nitrogen (N)], 2 mm (medium N), or 4 mm (ample N) ammonium nitrate for 3 weeks were evaluated using two commercial chlorophyll meters and NDVI sensors. The absolute chlorophyll content was determined using chlorophyll extraction. Our results showed that plants receiving ample N and medium N had decreased transmitted red light (i.e., greater absorption in red light). Measurements of optical chlorophyll meters, NDVI sensors, and chlorophyll extraction similarly showed that plants receiving medium N and ample N had greater leaf chlorophyll content than those receiving zero N. Relative leaf chlorophyll content estimated using NDVI sensors correlated positively with those from the chlorophyll meters (P < 0.0001; r2 range, 0.56–0.82). Therefore, our results indicate that NDVI measurements are sensitive to leaf chlorophyll content. These NDVI sensors, or specialized sensors developed using similar principles, can be used to estimate the relative chlorophyll content of nursery crops and help growers adjust fertilization to improve plant growth and nutrient status.

scholarly journals Leaf Chlorophyll Content Estimation of Winter Wheat Based on Visible and Near-Infrared Sensors

Sensors ◽  
2016 ◽  
Vol 16 (4) ◽  
pp. 437 ◽  
Author(s):  
Jianfeng Zhang ◽  
Wenting Han ◽  
Lvwen Huang ◽  
Zhiyong Zhang ◽  
Yimian Ma ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Chlorophyll Content ◽  
Near Infrared ◽  
Infrared Sensors ◽  
Leaf Chlorophyll Content ◽  
Leaf Chlorophyll

scholarly journals Effects of Crop Leaf Angle on LAI-Sensitive Narrow-Band Vegetation Indices Derived from Imaging Spectroscopy

2018 ◽  
Vol 8 (9) ◽  
pp. 1435 ◽  
Author(s):  
Xiaochen Zou ◽  
Iina Haikarainen ◽  
Iikka Haikarainen ◽  
Pirjo Mäkelä ◽  
Matti Mõttus ◽  
...  
Keyword(s):  
Chlorophyll Content ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Imaging Spectroscopy ◽  
Leaf Angle ◽  
Field Crops ◽  
Leaf Chlorophyll ◽  
Simple Ratio ◽  
The Relationship

Leaf area index (LAI) is an important biophysical variable for understanding the radiation use efficiency of field crops and their potential yield. On a large scale, LAI can be estimated with the help of imaging spectroscopy. However, recent studies have revealed that the leaf angle greatly affects the spectral reflectance of the canopy and hence imaging spectroscopy data. To investigate the effects of the leaf angle on LAI-sensitive narrowband vegetation indices, we used both empirical measurements from field crops and model-simulated data generated by the PROSAIL canopy reflectance model. We found the relationship between vegetation indices and LAI to be notably affected, especially when the leaf mean tilt angle (MTA) exceeded 70 degrees. Of the indices used in the study, the modified soil-adjusted vegetation index (MSAVI) was most strongly affected by leaf angles, while the blue normalized difference vegetation index (BNDVI), the green normalized difference vegetation index (GNDVI), the modified simple ratio using the wavelength of 705 nm (MSR705), the normalized difference vegetation index (NDVI), and the soil-adjusted vegetation index (SAVI) were only affected for sparse canopies (LAI < 3) and MTA exceeding 60°. Generally, the effect of MTA on the vegetation indices increased as a function of decreasing LAI. The leaf chlorophyll content did not affect the relationship between BNDVI, MSAVI, NDVI, and LAI, while the green atmospherically resistant index (GARI), GNDVI, and MSR705 were the most strongly affected indices. While the relationship between SR and LAI was somewhat affected by both MTA and the leaf chlorophyll content, the simple ratio (SR) displayed only slight saturation with LAI, regardless of MTA and the chlorophyll content. The best index found in the study for LAI estimation was BNDVI, although it performed robustly only for LAI > 3 and showed considerable nonlinearity. Thus, none of the studied indices were well suited for across-species LAI estimation: information on the leaf angle would be required for remote LAI measurement, especially at low LAI values. Nevertheless, narrowband indices can be used to monitor the LAI of crops with a constant leaf angle distribution.

Airborne detection of southern pine beetle damage using key spectral bands

1998 ◽  
Vol 28 (7) ◽  
pp. 1040-1045 ◽  
Author(s):  
Gregory A Carter ◽  
Michael R Seal ◽  
Tim Haley
Keyword(s):  
Chlorophyll Content ◽  
Vegetation Index ◽  
Dendroctonus Frontalis ◽  
Southern Pine Beetle ◽  
Pinus Echinata ◽  
Shortleaf Pine ◽  
Southern Pine ◽  
Leaf Chlorophyll Content ◽  
Leaf Chlorophyll ◽  
Pine Beetle

Damage by the southern pine beetle (SPB) (Dendroctonus frontalis Zimm.) occurs frequently in the southeastern United States and can result in tree death over large areas. A new technique for detection of SPB activity was tested for shortleaf pine (Pinus echinata Mill.) in the Caney Creek Wilderness, Ouachita National Forest, Arkansas. Digital images with 1-m pixel resolution were acquired from a light aircraft in 6- to 10-nm bandwidths centered at wavelengths of 675, 698, and 840 nm. The 675-nm band was selected to yield a maximum contrast between yellow or brown versus green foliage. The 698-nm band was selected based on its high sensitivity to leaf chlorophyll content to enable detection of less severe chlorosis in more recently damaged trees. The 840-nm band was used as a reference band that is not sensitive to chlorophyll. Images acquired within each band were calibrated to percent reflectance based on the known reflectances of a gray scale placard located on the ground. Individual trees with yellow to brown foliage were easily located in the 675- and 698-nm images. Milder chlorosis in more recently damaged pines was detected by a normalized difference vegetation index (NDVI) that was derived from 698- and 840-nm reflectances. Although statistically significant, the contrast of recently infested trees versus undamaged trees was generally visually poor in NDVI or color composite images. This was apparently a result of the inherent variability in leaf chlorophyll content throughout the forest. The increased reflectance near 700 nm characteristic of recent damage likely would be resolved more easily in pine plantations of low species diversity. Images of a NDVI that was based on 675- and 840-nm reflectances produced the strongest contrast between heavily damaged and undamaged trees.

Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach

2019 ◽  
Vol 224 ◽  
pp. 60-73 ◽  
Author(s):  
Mingzhu Xu ◽  
Ronggao Liu ◽  
Jing M. Chen ◽  
Yang Liu ◽  
Rong Shang ◽  
...  
Keyword(s):  
Chlorophyll Content ◽  
Vegetation Index ◽  
Leaf Chlorophyll Content ◽  
Leaf Chlorophyll ◽  
Combination Approach ◽  
Index Combination

scholarly journals Mapping within-field leaf chlorophyll content in agricultural crops for nitrogen management using Landsat-8 imagery

2019 ◽  
Vol 21 (4) ◽  
pp. 856-880 ◽  
Author(s):  
Holly Croft ◽  
Joyce Arabian ◽  
Jing M. Chen ◽  
Jiali Shang ◽  
Jiangui Liu
Keyword(s):  
Chlorophyll Content ◽  
Satellite Data ◽  
Nitrogen Fertilizer ◽  
Vegetation Index ◽  
Growing Season ◽  
Fertilizer Application ◽  
Landsat 8 ◽  
Leaf Chlorophyll Content ◽  
Leaf Chlorophyll ◽  
Normalised Difference Vegetation Index

AbstractSpatial information on crop nutrient status is central for monitoring vegetation health, plant productivity and managing nutrient optimization programs in agricultural systems. This study maps the spatial variability of leaf chlorophyll content within fields with differing quantities of nitrogen fertilizer application, using multispectral Landsat-8 OLI data (30 m). Leaf chlorophyll content and leaf area index measurements were collected at 15 wheat (Triticum aestivum) sites and 13 corn (Zea mays) sites approximately every 10 days during the growing season between May and September 2013 near Stratford, Ontario. Of the 28 sites, 9 sites were within controlled areas of zero nitrogen fertilizer application. Hyperspectral leaf reflectance measurements were also sampled using an Analytical Spectral Devices FieldSpecPro spectroradiometer (400–2500 nm). A two-step inversion process was developed to estimate leaf chlorophyll content from Landsat-8 satellite data at the sub-field scale, using linked canopy and leaf radiative transfer models. Firstly, at the leaf-level, leaf chlorophyll content was modelled using the PROSPECT model, using both hyperspectral and simulated mulitspectral Landsat-8 bands from the same leaf sample. Hyperspectral and multispectral validation results were both strong (R2 = 0.79, RMSE = 13.62 μg/cm2 and R2 = 0.81, RMSE = 9.45 μg/cm2, respectively). Secondly, leaf chlorophyll content was estimated from Landsat-8 satellite imagery for 7 dates within the growing season, using PROSPECT linked to the 4-Scale canopy model. The Landsat-8 derived estimates of leaf chlorophyll content demonstrated a strong relationship with measured leaf chlorophyll values (R2 = 0.64, RMSE = 16.18 μg/cm2), and compared favourably to correlations between leaf chlorophyll and the best performing tested spectral vegetation index (Green Normalised Difference Vegetation Index, GNDVI; R2 = 0.59). This research provides an operational basis for modelling within-field variations in leaf chlorophyll content as an indicator of plant nitrogen stress, using a physically-based modelling approach, and opens up the possibility of exploiting a wealth of multispectral satellite data and UAV-mounted multispectral imaging systems.

scholarly journals Spectral Reflectance in Silver Birch Genotypes from Three Provenances in Finland

2020 ◽  
Vol 12 (17) ◽  
pp. 2677
Author(s):  
Maya Deepak ◽  
Sarita Keski-Saari ◽  
Laure Fauch ◽  
Lars Granlund ◽  
Elina Oksanen ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Chlorophyll Content ◽  
Spectral Reflectance ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Leaf Traits ◽  
Silver Birch ◽  
Red Edge

The goal of this study was to investigate the variation in the leaf spectral reflectance and its association with other leaf traits from 12 genotypes among three provenances of origin (populations) in a common garden for Finnish silver birch trees in 2015 and 2016. The spectral reflectance was measured in the laboratory from the detached leaves in the wavelength range of visible and near-infrared (VNIR, 400–1000 nm) and shortwave infrared (SWIR, 1000–2500 nm). The variation among the provenance was initially visualized with principal component analysis (PCA) and a clear separation among the provenances was detected with the discriminant analysis of principal components (DAPC) and partial least squares discriminant analysis (PLS-DA) depicting a less strong variation among the genotypes within the provenances. Wavelengths contributing to the separation of the genotypes and provenances were identified from the contribution plot of DAPC and the red edge was strongly related to the differences. Chlorophyll content showed clear provenance variation and was associated with the separation among the genotypes and provenances in the DAPC space. The normalized difference vegetation index (NDVI705,750) and chlorophyll reflectance index (CRI) showed clear significance among the provenances, whereas NDVI670,780 showed no variation. The variation in the chlorophyll content and the CRI and red edge-based NDVI indices indicated seasonal variation as the chlorophyll content starts increasing in early June. The correlation of foliar chlorophyll content and the chlorophyll-related spectral indices for the discrimination of provenances and genotypes are reported for the first time in a naturally occurring tree species consecutively for two years.

scholarly journals The Preferences of Different Cultivars of Lettuce Seedlings (Lactuca sativa L.) for the Spectral Composition of Light

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1211
Author(s):  
Barbara Frąszczak ◽  
Monika Kula-Maximenko
Keyword(s):  
Chlorophyll Content ◽  
Blue Light ◽  
White Light ◽  
Leaf Shape ◽  
Red Light ◽  
Spectral Composition ◽  
Fresh Weight ◽  
Light Spectrum ◽  
Dark Green ◽  
Relative Chlorophyll Content

The spectrum of light significantly influences the growth of plants cultivated in closed systems. Five lettuce cultivars with different leaf colours were grown under white light (W, 170 μmol m−2 s−1) and under white light with the addition of red (W + R) or blue light (W + B) (230 μmol m−2 s−1). The plants were grown until they reached the seedling phase (30 days). Each cultivar reacted differently to the light spectrum applied. The red-leaved cultivar exhibited the strongest plasticity in response to the spectrum. The blue light stimulated the growth of the leaf surface in all the plants. The red light negatively influenced the length of leaves in the cultivars, but it positively affected their number in red and dark-green lettuce. It also increased the relative chlorophyll content and fresh weight gain in the cultivars containing anthocyanins. When the cultivars were grown under white light, they had longer leaves and higher value of the leaf shape index. The light-green cultivars had a greater fresh weight. Both the addition of blue and red light significantly increased the relative chlorophyll content in the dark-green cultivar. The spectrum enhanced with blue light had positive influence on most of the parameters under analysis in butter lettuce cultivars. These cultivars were also characterised by the highest absorbance of blue light.

Sign in / Sign up

Export Citation Format

Share Document