scholarly journals Remote Sensing for Assessing Rhizoctonia Crown and Root Rot Severity in Sugar Beet

Plant Disease ◽  
2012 ◽  
Vol 96 (4) ◽  
pp. 497-505 ◽  
Author(s):  
Gregory J. Reynolds ◽  
Carol E. Windels ◽  
Ian V. MacRae ◽  
Soizik Laguette
Keyword(s):  
Remote Sensing ◽  
Sugar Beet ◽  
Root Rot ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Root Surface ◽  
Near Infrared Reflectance ◽  
Initial Appearance ◽  
Crown And Root Rot ◽  
Field Plots

Rhizoctonia crown and root rot (RCRR), caused by Rhizoctonia solani AG-2-2, is an increasingly important disease of sugar beet in Minnesota and North Dakota. Disease ratings are based on subjective, visual estimates of root rot severity (0-to-7 scale, where 0 = healthy and 7 = 100% rotted, foliage dead). Remote sensing was evaluated as an alternative method to assess RCRR. Field plots of sugar beet were inoculated with R. solani AG 2-2 IIIB at different inoculum densities at the 10-leaf stage in 2008 and 2009. Data were collected for (i) hyperspectral reflectance from the sugar beet canopy and (ii) visual ratings of RCRR in 2008 at 2, 4, 6, and 8 weeks after inoculation (WAI) and in 2009 at 2, 3, 5, and 9 WAI. Green, red, and near-infrared reflectance and several calculated narrowband and wideband vegetation indices (VIs) were correlated with visual RCRR ratings, and all resulted in strong nonlinear regressions. Values of VIs were constant until at least 26 to 50% of the root surface was rotted (RCRR = 4, wilting of foliage starting to develop) and then decreased significantly as RCRR ratings increased and plants began dying. RCRR also was detected using airborne, color-infrared imagery at 0.25- and 1-m resolution. Remote sensing can detect RCRR but not before initial appearance of foliar symptoms.

Remote sensing for assessing Rhizoctonia crown and root rot severity in sugar beet

2011 ◽  
Author(s):  
Gregory J. Reynolds ◽  
Carol E. Windels ◽  
Ian V. MacRae ◽  
Soizik Laguette
Keyword(s):  
Remote Sensing ◽  
Sugar Beet ◽  
Root Rot ◽  
Crown And Root Rot

scholarly journals Sensitivity of Rhizoctonia solani AG-2-2 from Sugar Beet to Fungicides

Plant Disease ◽  
2016 ◽  
Vol 100 (12) ◽  
pp. 2427-2433 ◽  
Author(s):  
Sahar Arabiat ◽  
Mohamed F. R. Khan
Keyword(s):  
Sugar Beet ◽  
Rhizoctonia Solani ◽  
Root Rot ◽  
The United States ◽  
Damping Off ◽  
Growth Assay ◽  
The Mean ◽  
Crown And Root Rot ◽  
Mean Concentration

Rhizoctonia damping-off and crown and root rot caused by Rhizoctonia solani are major diseases of sugar beet (Beta vulgaris L.) worldwide, and growers in the United States rely on fungicides for disease management. Sensitivity of R. solani to fungicides was evaluated in vitro using a mycelial radial growth assay and by evaluating disease severity on R. solani AG 2-2 inoculated plants treated with fungicides in the greenhouse. The mean concentration that caused 50% mycelial growth inhibition (EC50) values for baseline isolates (collected before the fungicides were registered for sugar beet) were 49.7, 97.1, 0.3, 0.2, and 0.9 μg ml−1 and for nonbaseline isolates (collected after registration and use of fungicides) were 296.1, 341.7, 0.9, 0.2, and 0.6 μg ml−1 for azoxystrobin, trifloxystrobin, pyraclostrobin, penthiopyrad, and prothioconazole, respectively. The mean EC50 values of azoxystrobin, trifloxystrobin, and pyraclostrobin significantly increased in the nonbaseline isolates compared with baseline isolates, with a resistant factor of 6.0, 3.5, and 3.0, respectively. Frequency of isolates with EC50 values >10 μg ml−1 for azoxystrobin and trifloxystrobin increased from 25% in baseline isolates to 80% in nonbaseline isolates. Although sensitivity of nonbaseline isolates of R. solani to quinone outside inhibitors decreased, these fungicides at labeled rates were still effective at controlling the pathogen under greenhouse conditions.

scholarly journals Integrated Control of Rhizoctonia Crown and Root Rot of Sugar Beet with Fungicides and Antagonistic Bacteria

Plant Disease ◽  
2001 ◽  
Vol 85 (7) ◽  
pp. 718-722 ◽  
Author(s):  
Sebastian Kiewnick ◽  
Barry J. Jacobsen ◽  
Andrea Braun-Kiewnick ◽  
Joyce L. A. Eckhoff ◽  
Jerry W. Bergman
Keyword(s):  
Sugar Beet ◽  
Root Rot ◽  
Integrated Control ◽  
The United States ◽  
Field Trials ◽  
Sugar Yield ◽  
Economic Losses ◽  
Yield Increase ◽  
Leaf Stage ◽  
Crown And Root Rot

Rhizoctonia crown and root rot, caused by the fungus Rhizoctonia solani AG 2-2, is one of the most damaging sugar beet diseases worldwide and causes significant economic losses in more than 25% of the sugar beet production area in the United States. We report on field trials in the years 1996 to 1999 testing both experimental fungicides and antagonistic Bacillus sp. for their potential to reduce disease severity and increase sugar yield in trials inoculated with R. solani AG 2-2. Fungicides were applied as in-furrow sprays at planting or as band sprays directed at the crown at the four-leaf stage, or four- plus eight-leaf stage, while bacteria were applied at the four-leaf stage only. The fungicides azoxystrobin and tebuconazole reduced crown and root rot disease by 50 to 90% over 3 years when used at rates of 76 to 304 g a.i./ha and 250 g a.i./ha, respectively. The disease index at harvest was reduced and the root and sugar yield increased with azoxystrobin compared with tebuconazole. The combination of azoxystrobin applied at 76 g a.i./ha and the Bacillus isolate MSU-127 resulted in best disease reduction and greatest root and sucrose yield increase.

scholarly journals Monitoring the Impact of Environmental Manipulation on Peatland Surface by Simple Remote Sensing Indices

2018 ◽  
Vol 23 ◽  
pp. 00030 ◽  
Author(s):  
Anshu Rastogi ◽  
Subhajit Bandopadhyay ◽  
Marcin Stróżecki ◽  
Radosław Juszczak
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Vegetation Index ◽  
Near Infrared ◽  
Near Infrared Reflectance ◽  
Area Index ◽  
Environmental Manipulation ◽  
Chlorophyll Index ◽  
The Impact ◽  
Remote Sensing Indices

The behaviour of nature depends on the different components of climates. Among these, temperature and rainfall are two of the most important components which are known to change plant productivity. Peatlands are among the most valuable ecosystems on the Earth, which is due to its high biodiversity, huge soil carbon storage, and its sensitivity to different environmental factors. With the rapid growth in industrialization, the climate change is becoming a big concern. Therefore, this work is focused on the behaviour of Sphagnum peatland in Poland, subjected to environment manipulation. Here it has been shown how a simple reflectance based technique can be used to assess the impact of climate change on peatland. The experimental setup consists of four plots with two kind of manipulations (control, warming, reduced precipitation, and a combination of warming and reduced precipitation). Reflectance data were measured twice in August 2017 under a clear sky. Vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), near-infrared reflectance of vegetation (NIRv), MERIS terrestrial chlorophyll index (MTCI), Green chlorophyll index (CIgreen), Simple Ration (SR), and Water Band Index (WBI) were calculated to trace the impact of environmental manipulation on the plant community. Leaf Area Index of vascular plants was also measured for the purpose to correlate it with different VIs. The observation predicts that the global warming of 1°C may cause a significant change in peatland behaviour which can be tracked and monitored by simple remote sensing indices.

scholarly journals Evaluation and Normalization of Topographic Effects on Vegetation Indices

2020 ◽  
Vol 12 (14) ◽  
pp. 2290
Author(s):  
Rui Chen ◽  
Gaofei Yin ◽  
Guoxiang Liu ◽  
Jing Li ◽  
Aleixandre Verger
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Topographic Effects ◽  
Terrestrial Vegetation ◽  
Mountainous Areas ◽  
Near Infrared Reflectance ◽  
Illumination Condition ◽  
Vegetation Monitoring ◽  
Local Illumination

The normalization of topographic effects on vegetation indices (VIs) is a prerequisite for their proper use in mountainous areas. We assessed the topographic effects on the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the soil adjusted vegetation index (SAVI), and the near-infrared reflectance of terrestrial vegetation (NIRv) calculated from Sentinel-2. The evaluation was based on two criteria: the correlation with local illumination condition and the dependence on aspect. Results show that topographic effects can be neglected for the NDVI, while they heavily influence the SAVI, EVI, and NIRv: the local illumination condition explains 19.85%, 25.37%, and 26.69% of the variation of the SAVI, EVI, and NIRv, respectively, and the coefficients of variation across different aspects are, respectively, 8.13%, 10.46%, and 14.07%. We demonstrated the applicability of existing correction methods, including statistical-empirical (SE), sun-canopy-sensor with C-correction (SCS + C), and path length correction (PLC), dedicatedly designed for reflectance, to normalize topographic effects on VIs. Our study will benefit vegetation monitoring with VIs over mountainous areas.

scholarly journals Interaction of Sugar Beet Host Resistance andRhizoctonia solaniAG-2-2 IIIB Strains

Plant Disease ◽  
2013 ◽  
Vol 97 (9) ◽  
pp. 1175-1180 ◽  
Author(s):  
Carl A. Strausbaugh ◽  
Imad A. Eujayl ◽  
Leonard W. Panella
Keyword(s):  
Sugar Beet ◽  
Root Rot ◽  
Weak Interactions ◽  
Block Design ◽  
Field Studies ◽  
Preliminary Evidence ◽  
Economic Losses ◽  
Resistant Lines ◽  
Crown And Root Rot ◽  
Different Strains

Rhizoctonia crown and root rot caused by Rhizoctonia solani can cause serious economic losses in sugar beet fields. Preliminary evidence suggests that there could be interactions between different strains and resistance sources. Thus, field studies were conducted to determine whether nine R. solani AG-2-2 IIIB strains varied for virulence when compared with a noninoculated check and interacted with five sugar beet lines (four resistant lines and a susceptible check). The studies were arranged in a randomized complete block design with six replications. Roots were evaluated for surface rot and internal fungal and bacterial rot in September. All strains were virulent on the susceptible check, FC901/C817, and had a similar ranking (r = 0.80 to 0.97; P = 0.0096 to <0.0001) regardless of disease variable. Line FC709-2 was resistant (response not different from noninoculated check, P ≥ 0.1042) to all strains, while the strain responses resulted in weak interactions with less-resistant lines in 14 of 19 variable-year combinations. Because most commercial sugar beet cultivars contain low to intermediate resistance to Rhizoctonia crown and root rot, the strain used to screen should be considered in order to maintain consistent responses between nurseries and commercial fields.

scholarly journals Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management

2017 ◽  
Vol 52 (11) ◽  
pp. 1072-1079 ◽  
Author(s):  
Elisiane Alba ◽  
Eliziane Pivotto Mello ◽  
Juliana Marchesan ◽  
Emanuel Araújo Silva ◽  
Juliana Tramontina ◽  
...  
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Pinus Elliottii ◽  
Growth Stages ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Infrared Band ◽  
Near Infrared Reflectance ◽  
Planning And Management ◽  
Forest Planning And Management

Abstract: The objective of this work was to evaluate the use of Landsat 8/OLI images to differentiate the age and estimate the total volume of Pinus elliottii, in order to determine the applicability of these data in the planning and management of forest activity. Fifty-three sampling units were installed, and dendrometric variables of 9-and-10-year-old P. elliottii commercial stands were measured. The digital numbers of the image were converted into surface reflectance and, subsequently, vegetation indices were determined. Red and near-infrared reflectance values were used to differentiate the ages of the stands. Regression analysis of the spectral variables was used to estimate the total volume. Increase in age caused an addition in reflectance in the near-infrared band and a decrease in the red band. The general equation for estimating the total volume for P.elliottii had an R2adj of 0.67 with a Syx of 31.46 m3 ha-1. Therefore, the spectral data with medium spatial resolution from the Landsat 8/OLI satellite can be used to distinguish the growth stages of the stands and can, thus, be used in the planning and proper management of forest activity on a spatial and temporal scale.

scholarly journals Monitoring and predicting crop growth and analysing agricultural ecosystems by remote sensing

1996 ◽  
Vol 5 (3) ◽  
pp. 367-376 ◽  
Author(s):  
Tsuyoshi Akiyama ◽  
Y. Inoue ◽  
M. Shibayama ◽  
Y. Awaya ◽  
N. Tanaka
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Nutrient Deficiency ◽  
The Arctic ◽  
Ground Vegetation ◽  
Spectral Vegetation Indices ◽  
Project Monitoring ◽  
Crop Types ◽  
Crop Discrimination

LANDSAT/TM data, which are characterized by high spectral/spatial resolutions, are able to contribute to practical agricultural management. In the first part of the paper, the authors review some recent applications of satellite remote sensing in agriculture. Techniques for crop discrimination and mapping have made such rapid progress that we can classify crop types with more than 80% accuracy. The estimation of crop biomass using satellite data, including leaf area, dry and fresh weights, and the prediction of grain yield, has been attempted using various spectral vegetation indices. Plant stresses caused by nutrient deficiency and water deficit have also been analysed successfully. Such information may be useful for farm management. In the latter half of the paper, we introduce the Arctic Science Project, which was carried out under the Science and Technology Agency of Japan collaborating with Finnish scientists. In this project, monitoring of the boreal forest was carried out using LANDSAT data. Changes in the phenology of subarctic ground vegetation, based on spectral properties, were measured by a boom-mounted, four-band spectroradiometer. The turning point dates of the seasonal near-infrared (NIR) and red (R) reflectance factors might indicate the end of growth and the beginning of autumnal tints, respectively.

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