scholarly journals Mathematical Models for Leaf Area Estimates of Guava

2018 ◽  
Vol 10 (12) ◽  
pp. 272
Author(s):  
Edney L. da Vitória ◽  
Ismael L. de J. Freitas ◽  
Tamara Locatelli ◽  
Elcio das G. Lacerda ◽  
Juliana M. Valle ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Leaf Area ◽  
Digital Imaging ◽  
Linear Regression Analysis ◽  
Linear Quadratic ◽  
Leaf Discs ◽  
Linear Dimensions ◽  
Power Models ◽  
Scanned Images ◽  
Guava Leaf

The aim of this work was to compare methods of determining the leaf area of guava (leaf discs and scanned images) and to model leaf area as a function of linear dimensions. Four areas of guava ‘Paluma’ were selected (12, 15, 20 and 24 months of age) for the experiment in the municipality of Pedro Canário, ES, Brazil. We randomly collected samples from 15 plants in each area. Ten leaves were chosen among the lower, middle and upper thirds of each plant to ensure that leaves of all sizes were collected, for a total of 600 leaves. Subsequently, we determined the leaf area by the methods of digital imaging and leaf discs. Linear regression analysis and correlation analysis were used to compare the methods. Linear, quadratic and power models of leaf area, as a function of the length or width and/or the product of length and width were adjusted. The methods of leaf discs and scanned images are discordant. The method of digitised images was a better fit to the width of the leaf, while the method of leaf discs was a better fit for length.

scholarly journals LEAF AREA ESTIMATION IN LITCHI BY MEANS OF ALLOMETRIC RELATIONSHIPS

2017 ◽  
Vol 39 (spe) ◽  
Author(s):  
PABLO SOUTO OLIVEIRA ◽  
WILTON SILVA ◽  
ADRIANA APARECIDA MATTA COSTA ◽  
EDILSON ROMAIS SCHMILDT ◽  
EDNEY LEANDRO DA VITÓRIA
Keyword(s):  
Linear Regression ◽  
Leaf Area ◽  
Linear Regression Equation ◽  
Allometric Relationships ◽  
Linear Quadratic ◽  
Maximum Width ◽  
Quadratic Potential ◽  
Area Estimation ◽  
Linear Dimensions ◽  
The One

ABSTRACT Obtaining leaf area is critical in several agronomic studies, being one of the important instruments to assess plant growth. The aim of this study was to estimate equations and select the most appropriate in determining leaf area in litchi (Litchi chinensis Sonn.). From the linear dimensions of length (L) and maximum width (W) of leaf limb, equations were estimated using linear, quadratic, potential and exponential models. The linear regression equation using the product of the length by maximum width, given by Y = 0.2885 + 0.662 (L.W) is the one that best expresses the leaf area estimation of litchi tree.

scholarly journals Leaf Area Estimation of Garden Boldo From Linear Dimensions

2019 ◽  
Vol 11 (5) ◽  
pp. 461
Author(s):  
Ana Maria Alves de Souza Ribeiro ◽  
Daniel Alves Mundim ◽  
Daisy Cristina Martins Mendonça ◽  
Karina Tiemi Hassuda dos Santos ◽  
Jéssica Sayuri Hassuda Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Leaf Blade ◽  
Coefficient Of Determination ◽  
Angular Coefficient ◽  
Simple Linear Regression ◽  
Linear Quadratic ◽  
Maximum Width ◽  
Quadratic Potential ◽  
Linear Dimensions ◽  
Medicinal Properties

The objective of this work was to determine a mathematical equation using linear measures that allows estimating a leaf area of the specie Plectranthus barbatus Andrews, a plant with medicinal properties popularly known as garden boldo. For this was performed a direct measurement of the leaf blade considering the length (L) along the midrib and the maximum width (W) perpendicular to the midrib of 500 leaves of different specimens and the observed foliar area (OLA), which were obtained by digitized images. A regression study with linear, quadratic, potential and exponential models was performed using a random sample of 400 from the evaluated leaves using OLA as a function of L, W or LW and then obtaining the estimated leaf area (ELA) of each model. From the remaining 100 leaves a validation of the tested models was performed using ELA as a function of OLA in a simple linear regression. From the residues between ELA and OLA the root-square-mean error and Willmot index (d) was obtained and the normality was verified. The parameters used for validation were: statistically linear and angular coefficient equal to zero and one respectively; coefficient of determination closest to the unit; RQME closer to zero; d index closest to the unit; normal distribution of residues. The equation that best represents the estimated leaf area of the garden boldo is ELA = 0.1389 + 0.6779 (LW).

scholarly journals Estimation Leaf Area by Composite Leaves of Canavalia rosea Seedlings Through Linear Dimensions From Last Leaflet

2019 ◽  
Vol 11 (9) ◽  
pp. 299
Author(s):  
Ana Paula Braido Pinheiro ◽  
Vinicius de Souza Oliveira ◽  
Karina Tiemi Hassuda dos Santos ◽  
Jéssica Sayuri Hassuda Santos ◽  
Gleyce Pereira Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Mean Absolute Error ◽  
Linear Equations ◽  
Absolute Error ◽  
Mean Values ◽  
Linear Dimensions ◽  
Power Models ◽  
Independent Variable ◽  
The Mean ◽  
Non Linear Equations

The objective of this work was to propose models of equations from measurements of the linear dimensions of the last leaflet for the estimation of the leaf area of the composite leaves of Canavalia rosea. For this purpose, 441 composite leaves of 198 seedlings were used, 45 days after sowing, produced in nursery and belonging to the Federal University of Espírito Santo, Campus São Mateus, located in the municipality of São Mateus, North of the State of Espírito Santo, Brazil. The length (L) along the main midrib and the maximum leaf width (W) of the last leaflet of each composite leaf, as well as the leaf area of all leaflets, were measured. Subsequently, it was determined the product of the multiplication of the length with the width (LW) and leaf area observed (OLA) from the sum of leaf area of leaflets in front of these measures were adjusted linear and non-linear equations of linear first degree, quadratic and power models, where, OLA was used as a dependent variable in function of L, W and LW as independent variable. Based on the models tested, we obtained equations for the estimated leaf area (ELA). The mean values of ELA and OLA were compared by Student's t test 5% probability. The mean absolute error (MAE), the root mean square error (RMSE) and the Willmott d index, were determined as criteria for validation. The best adjusted equation was chosen through the non-significant values in the comparison of the means of ELA and OLA, values of MAE and RMSE closer to zero, value of the index d near the unitary and higher values of R2. Thus, the leaf area of the composite leaf of C. rosea seedlings can be estimated by the power model represented by equation ELA = 2.2951 (LW)0.9474 quickly, easily and non-destructively.

scholarly journals Estimation of common bean (Phaseolus vulgaris) leaf area by a non-destructive method

2021 ◽  
Vol 42 (4) ◽  
pp. 2163-2180
Author(s):  
Valeria Pohlmann ◽  
◽  
Isabel Lago ◽  
Sidinei José Lopes ◽  
Jéssica Taynara da Silva Martins ◽  
...  
Keyword(s):  
Phaseolus Vulgaris ◽  
Common Bean ◽  
Leaf Area ◽  
Absolute Error ◽  
Linear Quadratic ◽  
Linear Measurements ◽  
Predictive Capacity ◽  
Water Regimes ◽  
Randomized Design ◽  
Power Models

The aim of this study was to develop mathematical models to estimate the leaf area of common bean (Phaseolus vulgaris) in irrigated and non-irrigated water regimes from linear dimensions. An experiment was carried out in a completely randomized design with a 3×2 factorial arrangement (three cultivars: Triunfo, Garapiá and FC 104; two water regimes: irrigated and non-irrigated) with 25 replicates each. A total of 523 trifoliates were collected throughout the crop cycle. The length (L, cm) and width (W, cm) of the central leaflet of the trifoliate were measured and their product (LW) (cm²) calculated. Then, the leaf area of these trifoliates was determined by digital photography methods using ImageJ® software, and using leaf discs. The number of samples required to estimate the leaf area of a trifoliate was determined to define which method is the most accurate to be used as the real leaf area in generating equations to estimate the leaf area in common bean. The relationship between area by digital photographs and the dimensions of the central leaflet of the trifoliate (L, W and LW) was fitted by linear, quadratic and power models. Subsequently, the predictive capacity of the equations was assessed by the root mean square error (cm2 trifoliate-1), mean absolute error (cm2 trifoliate-1), index of agreement and Pearson’s correlation coefficient. Sample size varied between cultivars, water regimes and evaluation methods. It is more appropriate to use the leaf area provided by ImageJ® as real for comparison purposes in generating models to estimate leaf area from linear measurements, in common bean. The general equation LA = 1.092L1.945 can be used in the tested regimes without accuracy losses.

Choroidal luminal and stromal areas and choriocapillaris perfusion are characterised by a non-linear quadratic relation in healthy eyes

2020 ◽  
pp. bjophthalmol-2020-316479 ◽  
Author(s):  
Enrico Borrelli ◽  
Maria Cristina Gabela ◽  
Riccardo Sacconi ◽  
Lea Querques ◽  
Giovanna Vella ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Healthy Subjects ◽  
Linear Models ◽  
Linear Regression Analysis ◽  
Quadratic Function ◽  
Initial Increase ◽  
Linear Quadratic ◽  
Cross Sectional ◽  
Non Linear

PurposeTo assess the associations among different optical coherence tomography (OCT) structural and angiography quantitative metrics used to characterise the choroid in healthy subjects.MethodsIn this cross-sectional study, macular structural OCT and OCT angiography (OCTA) images were acquired from healthy subjects. The main outcome measures were: (i) choriocapillaris (CC) flow deficits percentage (FD%), (ii) choroidal luminal (LA) and stromal (SA) areas and (iii) choroidal vascularity index (CVI), which was calculated as the LA divided by the total choroidal area. These measurements were generated using previously published algorithms and were separately computed in the foveal and extrafoveal regions.ResultsEighty-five eyes from 85 subjects (44 males, 41 females) were included in the analysis. Mean±SD age was 47.9±22.4 years (range: 19.0 to 85.0 years). Linear regression analysis displayed no significant associations between CC FD% and other parameters (LA, SA and CVI). Importantly, non-linear regression analysis showed that the relations of LA and SA to CC FD% were all best fitted by a quadratic function. Compared with the linear models, the use of the quadratic function allowed a relative increase in the R2 coefficients. No significant non-linear associations were found between CC FD% and CVI.ConclusionBased on our models, changes in the luminal and stromal areas in the choroid lead to an initial increase in CC perfusion. Subsequently, further increases in LA and SA amounts are accompanied by a progressive increment in CC FD%.

Prevalence and Predictors of Fruit Intake Among Community College Women in the Extended Opportunity Program and Services

2003 ◽  
Vol 1 (1) ◽  
pp. 91-102 ◽  
Author(s):  
Steve E. Shive ◽  
Michelle R. Neyman
Keyword(s):  
Community College ◽  
Weight Loss ◽  
Regression Analysis ◽  
College Women ◽  
Linear Regression Analysis ◽  
Good Health ◽  
Fruit Intake ◽  
Attitudes And Behaviors ◽  
Eating Fruit ◽  
Opportunity Program

This study examined fruit intake among 276 female Extended Opportunity Program and Services (EOPS) community college students. Knowledge, attitudes, and behaviors associated with fruit intake were determined. The attitudes which are potential predictors of daily fruit intake were also examined. Analysis showed that 33% ate fewer than the minimum recommended two daily servings of fruit. Students reported that fruit gave them energy, taste and cost were not barriers to consumption and that it would not be difficult to increase daily fruit consumption. A linear regression analysis revealed that beliefs that eating fruit leads to good health, having a habit of eating fruit, feeling energy, and weight loss accounted for 30% of the variance in fruit intake.

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

Struktur Organisasi, Desain Kerja, Budaya Organisasi Dan Pengaruhnya Terhadap Produktivitas Karyawan Studi Kasus Pada PT. XX Di Jakarta

Liquidity ◽  
2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Yanti Budiasih
Keyword(s):  
Organizational Culture ◽  
Regression Analysis ◽  
Linear Regression ◽  
Organizational Structure ◽  
Research Method ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Job Design ◽  
Employee Productivity ◽  
Dominant Influence

The objectives of this study are to analyze changes in organizational structure, job design, organizational culture and its influence on employee productivity at PT. XX in Jakarta and to identify variables that have a dominant influence on the productivity of employees. The research method used is using multiple linear regression analysis. The results show that the all variables simultaneously and partially change the organizational structure, job design, and organizational culture has a significant impact on employee productivity at PT. XXin Jakarta.

The Contribution of Sexual Identity Towards the Students’ Perception of Lesbian, Gay, Bisexual, and Transgender

10.32698/0642 ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 120
Author(s):  
Wiwi Delfita ◽  
Neviyarni S. ◽  
Riska Ahmad
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Sexual Identity ◽  
Student Perceptions ◽  
Undergraduate Students ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Simple Linear Regression ◽  
Simple Linear Regression Analysis ◽  
Bisexual And Transgender

Some students perceive lesbian, gay, bisexual, and transgender (LGBT) positively, even though LGBT is a sexual deviation that is not appropriate with values and norms. There are several factors that influence an individual's perception of LGBT, including sexual identity. This study aims at looking at the contribution of sexual identity to student perceptions about LGBT. This research used a quantitative approach with a descriptive method and a simple linear regression analysis. The sample of this research was 385 taken from 15.752 undergraduate students of Universitas Negeri Padang which the sample was drawn by using the Slovin formula and continued with a Proportional Random Sampling technique. The instrument used was the Guttman model's sexual identity scale and the scale of students' perceptions of the LGBT Likert model. After analyzing the data with the descriptive technique and the simple linear regression analysis, the results showed that sexual identity significantly contributed to the students' perceptions of LGBT. This research has implications as a basis for counselors to help students avoid sexual identity mismatches and prevent the emergence of positive perceptions of LGBT.

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