scholarly journals Elaboration and validation of diagrammatic scale for lettuce powdery mildew

2018 ◽  
Vol 44 (2) ◽  
pp. 116-121 ◽  
Author(s):  
Guilherme de Resende Camara ◽  
Laedio Magno Busato ◽  
Bárbara Favalessa Almeida ◽  
Willian Bucker Moraes
Keyword(s):  
Powdery Mildew ◽  
Linear Regression ◽  
Leaf Area ◽  
Epidemiological Study ◽  
Logarithmic Scale ◽  
Accuracy And Precision ◽  
Severity Levels ◽  
Hydroponic Systems ◽  
Lettuce Powdery Mildew ◽  
Diagrammatic Scale

ABSTRACT Powdery mildew, caused by Oidium sp., is a disease of great importance in hydroponic crops of lettuce. However, in Brazil, there is scarce research focused on the epidemiological study of this disease, as standardized methods are necessary to quantify the disease severity in hydroponic systems. Thus, a logarithmic scale was developed at levels of 0.37, 1, 2, 4, 8, 16, 32 and 74% injured leaf area, testing the parameters accuracy and precision. The proposed scale was validated by eight evaluators, of whom four were experienced and four were inexperienced, and they used 50 leaves showing symptoms of the disease at different severity levels, previously measured with the aid of QUANT® software. Two evaluations were performed with a 48-h interval, in which the evaluators visually estimated distinct sequences of leaves. Linear regression was used to determine the accuracy and the precision of each evaluator. The proposed scale showed satisfactory results of accuracy and precision, and despite the inexperience of four evaluators, absolute errors were in the range of 8% after training. The proposed scale was adequate to estimate the severity of powdery mildew on lettuce.

scholarly journals Diagrammatic scale to assess downy mildew severity in melon

2009 ◽  
Vol 27 (1) ◽  
pp. 76-79 ◽  
Author(s):  
Sami J Michereff ◽  
Marissônia A Noronha ◽  
Gaus SA Lima ◽  
Ígor CL Albert ◽  
Edilaine A Melo ◽  
...  
Keyword(s):  
Linear Regression ◽  
Leaf Area ◽  
Downy Mildew ◽  
Pseudoperonospora Cubensis ◽  
Northeast Brazil ◽  
Simple Linear Regression ◽  
Standard Methods ◽  
Accuracy And Precision ◽  
Severity Levels ◽  
Diagrammatic Scale

The downy mildew, caused by Pseudoperonospora cubensis, is an important melon disease in Northeast Brazil. Considering the lack of standard methods for its assessment, a diagrammatic scale was developed with 2, 4, 8, 16, 32, 64, 82, and 96% of affected leaf area. The scale was then checked for its accuracy, precision, and reproducibility in estimating downy mildew severity. The diagrammatic scale was validated by eight disease raters; using 50 leaves with different severity levels, previously measured using the software Assess®. Two evaluations were performed on the same set of leaves, but in a different sequence order, by the same raters, within a 15-day interval. The accuracy and precision of each rater was determined by simple linear regression between the actual and the estimated severity. The scale provided good levels of accuracy (means of 87.5%) and excellent levels of precision (means of 94%), with absolute errors concentrated around 10%. Raters showed great repeatability (means of 94%) and reproducibility (>90% in 90.3% of cases) of estimates. Therefore, we could conclude that the diagrammatic scale presented here was suitable for evaluating downy mildew severity in melon.

scholarly journals Development and validation of diagrammatic scales to evaluate damage by the two-spotted spider mite (Tetranychus urticae) in peanut

2021 ◽  
Vol 53 (1) ◽  
pp. 254-261
Author(s):  
Ana Cecilia Crenna ◽  
Claudio Marcelo Oddino ◽  
Santiago Ferrari ◽  
Jorge Antonio Giuggia ◽  
Diego Giovanini ◽  
...  
Keyword(s):  
Linear Regression ◽  
Leaf Area ◽  
Tetranychus Urticae ◽  
Spider Mite ◽  
Mean Values ◽  
Fundamental Parameters ◽  
Peanut Crop ◽  
Two Spotted Spider Mite ◽  
Development And Validation ◽  
Diagrammatic Scale

Argentina is the second largest peanut (Arachis hypogaea L.) exporter in the world. The main peanut pest in our country is the two-spotted spider mite (Tetranychus urticae Koch 1836). To date, there is no validated method to quantify this pest. The aim of this work was to develop and validate a logarithmic diagrammatic scale to assess damage by the two-spotted spider mite in peanut. In 2015-16, 200 leaflets were collected from a plot infested with the pest. Damaged leaf area (DLA) was calculated using SisCob software. Six-, seven-, eight- and nine-class scales were proposed. Mean values for each class and scale were obtained with 2-LOG. Leaflets were analyzed by 13 raters who used the four proposed scales. Precision and accuracy were determined by simple linear regression between the DLA and estimated damaged leaf area. Reproducibility was determined by linear regression between estimates of raters combined in pairs. The seven-class scale was the best validated one for all the parameters. Most raters showed constant deviations and overestimated DLA, whereas only one rater presented systematic deviations. This seven-class scale is the first developed and validated one to evaluate two-spotted spider mite damage to peanut in Argentina. Highlights According to the validation results, the seven-class diagrammatic scale was the best one in terms of accuracy, precision and reproducibility with values above 0.80, 0.75 and 0.75 respectively. The scales are useful tools for pest assessment, fundamental parameters for integrated pest management. The seven-class scale is the first one developed and validated for evaluating damage by the two-spotted spider mite in peanut crop in Argentina. With this scale a loss function will be calculate which will allow the estimation of the EIL of this pest.

scholarly journals Diagrammatic scale for assessment of soybean rust severity

2006 ◽  
Vol 31 (1) ◽  
pp. 63-68 ◽  
Author(s):  
Cláudia V. Godoy ◽  
Lucimara J. Koga ◽  
Marcelo G. Canteri
Keyword(s):  
Glycine Max ◽  
Scale Validation ◽  
Soybean Rust ◽  
Phakopsora Pachyrhizi ◽  
Stimulus Response ◽  
Accuracy And Precision ◽  
Rust Severity ◽  
Severity Levels ◽  
Diagrammatic Scale

A diagrammatic scale to assess soybean (Glycine max) rust severity, caused by the fungus Phakopsora pachyrhizi, was developed in this study. Leaflets showing different severity levels were collected for determination of the minimum and maximum severity limits; intermediate levels were determined according to "Weber-Fechner's stimulus-response law". The proposed scale showed the levels of 0.6; 2; 7; 18; 42, and 78.5%. Scale validation was performed by eight raters (four inexperienced and four experienced), who estimated the severity of 44 soybean leaflets showing rust symptoms, with and without the use of the scale. Except for rater number eight, all showed a tendency to overestimate severity without the aid of the diagrammatic scale. With the scale, the raters obtained better accuracy and precision levels, although the tendency to overestimate was maintained. Experienced raters were more accurate and precise than inexperienced raters, and assessment improvements with the use of the scale were more significant for inexperienced raters.

Does the Modified Arrhenius Model Reliably Predict Area of Tissue Ablation After Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Pediatric Lesional Epilepsy?

2021 ◽  
Author(s):  
Kelsey D Cobourn ◽  
Imazul Qadir ◽  
Islam Fayed ◽  
Hepzibha Alexander ◽  
Chima O Oluigbo
Keyword(s):  
Magnetic Resonance ◽  
Linear Regression ◽  
Magnetic Resonance Images ◽  
Thermal Therapy ◽  
Invasive Technique ◽  
Hypothalamic Hamartoma ◽  
Arrhenius Model ◽  
Laser Interstitial Thermal Therapy ◽  
Accuracy And Precision

Abstract BACKGROUND Commercial magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) systems utilize a generalized Arrhenius model to estimate the area of tissue damage based on the power and time of ablation. However, the reliability of these estimates in Vivo remains unclear. OBJECTIVE To determine the accuracy and precision of the thermal damage estimate (TDE) calculated by commercially available MRgLITT systems using the generalized Arrhenius model. METHODS A single-center retrospective review of pediatric patients undergoing MRgLITT for lesional epilepsy was performed. The area of each lesion was measured on both TDE and intraoperative postablation, postcontrast T1 magnetic resonance images using ImageJ. Lesions requiring multiple ablations were excluded. The strength of the correlation between TDE and postlesioning measurements was assessed via linear regression. RESULTS A total of 32 lesions were identified in 19 patients. After exclusion, 13 pairs were available for analysis. Linear regression demonstrated a strong correlation between estimated and actual ablation areas (R2 = .97, P < .00001). The TDE underestimated the area of ablation by an average of 3.92% overall (standard error (SE) = 4.57%), but this varied depending on the type of pathologic tissue involved. TDE accuracy and precision were highest in tubers (n = 3), with average underestimation of 2.33% (SE = 0.33%). TDE underestimated the lesioning of the single hypothalamic hamartoma in our series by 52%. In periventricular nodular heterotopias, TDE overestimated ablation areas by an average of 13% (n = 2). CONCLUSION TDE reliability is variably consistent across tissue types, particularly in smaller or periventricular lesions. Further investigation is needed to understand the accuracy of this emerging minimally invasive technique.

scholarly journals Making sense of the link between tiller density and pasture production

1995 ◽  
pp. 83-87
Author(s):  
C. Matthew ◽  
A. Hernandez-Garay ◽  
J. Hodgson
Keyword(s):  
Leaf Area ◽  
Shoot Density ◽  
Logarithmic Scale ◽  
Data Set ◽  
Pasture Production ◽  
Density Data ◽  
Density Compensation ◽  
Area Effect ◽  
The Right ◽  
Tiller Density

Interpretation of tiller or shoot density data requires resolution of two independent, confounding effects, namely size/density compensation and what is here called the "leaf area effect". Size/density compensation implies that at higher herbage mass, individual tillers or shoots are larger, but the population density is correspondingly decreased. The leaf area effect represents difference in sward leaf area for two tiller populations. Such leaf area differences may be environmentally or genetically determined, but must of necessity be expressed through change in tiller size and/or tiller density as "yield components" of leaf area. The theoretical basis for distinguishing between size/density compensation and the leaf area effect is to consider tiller or shoot density and herbage yield, respectively, as X,Y co-ordinates in a size/density plot. When such a plot is drawn on a logarithmic scale, points along a line of -l/2 slope show size/ density compensation with respect to each other. Movement of points to the right or left of the size/ density compensation line is evidence of a leaf area effect. It is shown that when the size/density effects are removed from a data set in this way, rankings of experimental treatments for the leaf area effect can often be reversed compared with the ranking of uncorrected tiller density. Tiller density data corrected for size/density compen-. sation in this way appear to be a useful indicator of sward productivity. Keywords: sizeldensity compensation, sward productivity, tiller density

Is the Fluorometric Method for Blood Bilirubin Accurate?

PEDIATRICS ◽  
1980 ◽  
Vol 66 (4) ◽  
pp. 653-654
Author(s):  
George Cembrowski ◽  
Carl C. Garber
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Correlation Coefficient ◽  
Whole Blood ◽  
Total Bilirubin ◽  
Regression Line ◽  
Method Comparison ◽  
Fluorometric Method ◽  
Accuracy And Precision ◽  
Comparison Data

The article by Brown et al1 interested us greatly. Direct fluorometric measurement of whole blood bilirubin, if accurate and precise, will help in the care of the jaundiced neonate. The accuracy and precision of this technique, however, cannot be readily assessed from the authors' data. Consider the comparison of the fluorometric method to the Jendrassik-Grof method for total bilirubin. To assess accuracy, the authors use the correlation coefficient, r, and the slope of the linear regression line through the method comparison data. There are two problems with this data analysis.

scholarly journals Validation of Diagram Scale for Leaf Spot Caused by Pestalotiopsis sp. in Coconut Seedlings

2020 ◽  
Vol 8 (2) ◽  
pp. 32
Author(s):  
Aline Figueiredo Cardoso ◽  
Fernanda Sarmento de Oliveira Louzano ◽  
Cássia Cristina Chaves Pinheiro ◽  
Paulo Manoel Pontes Lins ◽  
Gisele Barata Da Silva
Keyword(s):  
Linear Regression ◽  
Disease Severity ◽  
Cocos Nucifera ◽  
Linear Regression Analysis ◽  
Management Program ◽  
Coefficient Of Determination ◽  
Angular Coefficient ◽  
Linear Coefficient ◽  
Cocos Nucifera L ◽  
Diagrammatic Scale

The absence of a methodology to quantify Pestalotiopsis sp. in coconut plants (Cocos nucifera L.) justified the elaboration and validation of a diagrammatic scale containing seven values (2%, 5%, 10%, 15%, 20%, 40% and 60%) of disease severity, in a sampling under natural conditions of occurrence in the field. To elaborate the diagrammatic scale, 100 leaves of Cocos nucifera L. were obtained from an experimental field of Fazenda Reunidas Sococo in Santa Isabel, Pará. The images of these leaves were obtained with the aid of a digital camera. Subsequently, with the aid of Assess 2.0 APS software, the actual disease severity values were obtained in percentage terms. The validation of the proposed diagrammatic scale was performed by ten inexperienced evaluators who evaluated the projected images without the aid of the suggested scale, and later, with the aid of the scale. From the data obtained from the evaluators with and without scale, linear regression analysis was performed, relating the real severity and the estimated severity. The accuracy of the estimates was evaluated by the regression determination coefficient (R2) and the variance of the absolute errors. The accuracy of each evaluator was determined by the t-test applied to the angular coefficient of line (b) and the linear coefficient of line (a), both obtained by linear regression. Through the coefficient of determination values, It is possible to verify that the use of the scale gave greater accuracy to 100% of the evaluators with an average of 0.94 and 94% repeatability. The use of the diagrammatic spot scale for Pestalotiopsis sp. it enables future work with accuracy and precision, as well as optimizing disease control practices within a coconut tree nursery management program.

scholarly journals Non-destructive linear model for leaf area estimation in Vernonia ferruginea Less

2015 ◽  
Vol 75 (1) ◽  
pp. 152-156 ◽  
Author(s):  
MC. Souza ◽  
CL. Amaral
Keyword(s):  
Linear Regression ◽  
Leaf Area ◽  
Leaf Development ◽  
Linear Equations ◽  
Accurate Estimate ◽  
Area Estimation ◽  
Leaf Dimensions ◽  
Non Destructive ◽  
Linear Regressions ◽  
Very High

Leaf area estimation is an important biometrical trait for evaluating leaf development and plant growth in field and pot experiments. We developed a non-destructive model to estimate the leaf area (LA) of Vernonia ferruginea using the length (L) and width (W) leaf dimensions. Different combinations of linear equations were obtained from L, L2, W, W2, LW and L2W2. The linear regressions using the product of LW dimensions were more efficient to estimate the LA of V. ferruginea than models based on a single dimension (L, W, L2 or W2). Therefore, the linear regression “LA=0.463+0.676WL” provided the most accurate estimate of V. ferruginea leaf area. Validation of the selected model showed that the correlation between real measured leaf area and estimated leaf area was very high.

scholarly journals Assessment of Leaf Area Index Models Using Harmonized Landsat and Sentinel-2 Surface Reflectance Data over a Semi-Arid Irrigated Landscape

2020 ◽  
Vol 12 (19) ◽  
pp. 3121
Author(s):  
Roya Mourad ◽  
Hadi Jaafar ◽  
Martha Anderson ◽  
Feng Gao
Keyword(s):  
Linear Regression ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Above Ground Biomass ◽  
Area Index ◽  
Ground Biomass ◽  
Semi Arid ◽  
Sentinel 2

Leaf area index (LAI) is an essential indicator of crop development and growth. For many agricultural applications, satellite-based LAI estimates at the farm-level often require near-daily imagery at medium to high spatial resolution. The combination of data from different ongoing satellite missions, Sentinel 2 (ESA) and Landsat 8 (NASA), provides this opportunity. In this study, we evaluated the leaf area index generated from three methods, namely, existing vegetation index (VI) relationships applied to Harmonized Landsat-8 and Sentinel-2 (HLS) surface reflectance produced by NASA, the SNAP biophysical model, and the THEIA L2A surface reflectance products from Sentinel-2. The intercomparison was conducted over the agricultural scheme in Bekaa (Lebanon) using a large set of in-field LAIs and other biophysical measurements collected in a wide variety of canopy structures during the 2018 and 2019 growing seasons. The major studied crops include herbs (e.g., cannabis: Cannabis sativa, mint: Mentha, and others), potato (Solanum tuberosum), and vegetables (e.g., bean: Phaseolus vulgaris, cabbage: Brassica oleracea, carrot: Daucus carota subsp. sativus, and others). Additionally, crop-specific height and above-ground biomass relationships with LAIs were investigated. Results show that of the empirical VI relationships tested, the EVI2-based HLS models statistically performed the best, specifically, the LAI models originally developed for wheat (RMSE:1.27), maize (RMSE:1.34), and row crops (RMSE:1.38). LAI derived through European Space Agency’s (ESA) Sentinel Application Platform (SNAP) biophysical processor underestimated LAI and provided less accurate estimates (RMSE of 1.72). Additionally, the S2 SeLI LAI algorithm (from SNAP biophysical processor) produced an acceptable accuracy level compared to HLS-EVI2 models (RMSE of 1.38) but with significant underestimation at high LAI values. Our findings show that the LAI-VI relationship, in general, is crop-specific with both linear and non-linear regression forms. Among the examined indices, EVI2 outperformed other vegetation indices when all crops were combined, and therefore it can be identified as an index that is best suited for a unified algorithm for crops in semi-arid irrigated regions with heterogeneous landscapes. Furthermore, our analysis shows that the observed height-LAI relationship is crop-specific and essentially linear with an R2 value of 0.82 for potato, 0.79 for wheat, and 0.50 for both cannabis and tobacco. The ability of the linear regression to estimate the fresh and dry above-ground biomass of potato from both observed height and LAI was reasonable, yielding R2: ~0.60.

scholarly journals An assessment of the performance of the Monitor for AeRosols and GAses in ambient air (MARGA): a semi-continuous method for soluble compounds

2014 ◽  
Vol 14 (11) ◽  
pp. 5639-5658 ◽  
Author(s):  
I. C. Rumsey ◽  
K. A. Cowen ◽  
J. T. Walker ◽  
T. J. Kelly ◽  
E. A. Hanft ◽  
...  
Keyword(s):  
Linear Regression ◽  
Ambient Air ◽  
Water Soluble ◽  
Performance Goal ◽  
Filter Pack ◽  
Accuracy And Precision ◽  
The Us ◽  
Us Epa ◽  
Best Fit ◽  
A Performance

Abstract. Ambient air monitoring as part of the US Environmental Protection Agency's (US EPA's) Clean Air Status and Trends Network (CASTNet) currently uses filter packs to measure weekly integrated concentrations. The US EPA is interested in supplementing CASTNet with semi-continuous monitoring systems at select sites to characterize atmospheric chemistry and deposition of nitrogen and sulfur compounds at higher time resolution than the filter pack. The Monitor for AeRosols and GAses in ambient air (MARGA) measures water-soluble gases and aerosols at an hourly temporal resolution. The performance of the MARGA was assessed under the US EPA Environmental Technology Verification (ETV) program. The assessment was conducted in Research Triangle Park, North Carolina, from 8 September to 8 October 2010 and focused on gaseous SO2, HNO3, and NH3 and aerosol SO42-, NO3-, and NH4+. Precision of the MARGA was evaluated by calculating the median absolute relative percent difference (MARPD) between paired hourly results from duplicate MARGA units (MUs), with a performance goal of ≤ 25%. The accuracy of the MARGA was evaluated by calculating the MARPD for each MU relative to the average of the duplicate denuder/filter pack concentrations, with a performance goal of ≤ 40%. Accuracy was also evaluated by using linear regression, where MU concentrations were plotted against the average of the duplicate denuder/filter pack concentrations. From this, a linear least squares line of best fit was applied. The goal was for the slope of the line of best fit to be between 0.8 and 1.2. The MARGA performed well in comparison to the denuder/filter pack for SO2, SO42−, and NH4+, with all three compounds passing the accuracy and precision goals by a significant margin. The performance of the MARGA in measuring NO3- could not be evaluated due to the different sampling efficiency of coarse NO3- by the MUs and the filter pack. Estimates of "fine" NO3- were calculated for the MUs and the filter pack. Using this and results from a previous study, it is concluded that if the MUs and the filter pack were sampling the same particle size, the MUs would have good agreement in terms of precision and accuracy. The MARGA performed moderately well in measuring HNO3 and NH3, though neither met the linear regression slope goals. However, recommendations for improving the measurement of HNO3 and NH3 are discussed. It is concluded that SO42-, SO2, NO3-, HNO3, NH4+, and NH3 concentrations can be measured with acceptable accuracy and precision when the MARGA is operated in conjunction with the recommendations outlined in the manuscript.

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