scholarly journals Estimation of leaf area of Erythroxylum citrifolium from linear leaf dimensions

2019 ◽  
Vol 35 (6) ◽  
Author(s):  
João Everthon da Silva Ribeiro ◽  
Ester dos Santos Coêlho ◽  
Francisco Romário Andrade Figueiredo ◽  
Sérgio de Faria Lopes ◽  
Manoel Bandeira de Albuquerque
Keyword(s):  
Leaf Area ◽  
Leaf Blade ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Concordance Index ◽  
R And D ◽  
Linear Dimensions ◽  
Bias Index ◽  
Linear Leaf ◽  
Leaf Dimensions

Erythroxylum citrifolium is a neotropical plant species recorded in all regions of Brazil. Determining leaf area is of fundamental importance to studies related to plant propagation and growth. The objective was to obtain an equation to estimate the leaf area of E. citrifolium from linear dimensions of the leaf blade (length and width). A total of 200 leaf blades were collected in Parque Estadual Mata do Pau-Ferro in the municipality of Areia, state of Paraíba, Northeast Brazil. The models evaluated were: linear, linear without intercept, quadratic, cubic, power and exponential. The best model was determined by the criteria of: high coefficient of determination (R²), low root mean square error (RMSE), low Akaike information criterion (AIC), high Willmott concordance index (d) and a BIAS index close to zero. All of the models constructed satisfactorily estimated the leaf area of E. citrifolium, with coefficients of determination above 0.9050, but the power model using the product between length and width (L*W) ŷ = 0.5966 * LW1.0181 was the best, with the highest values of R² and d, low values of RMSE and AIC, and a BIAS index closest to zero.

scholarly journals Allometric equations to estimate the leaf area of Psychotria colorata (Willd. Ex Schult.) Müll.Arg.

2021 ◽  
Vol 37 ◽  
pp. e37076
Author(s):  
João Everthon da Silva Ribeiro ◽  
Francisco Romário Andrade Figueiredo ◽  
Ester Dos Santos Coêlho ◽  
Marlenildo Ferreira Melo
Keyword(s):  
Leaf Area ◽  
Leaf Blade ◽  
Mean Squared Error ◽  
Information Criterion ◽  
Absolute Error ◽  
Allometric Equation ◽  
Coefficient Of Determination ◽  
Regression Equations ◽  
Linear Leaf ◽  
Leaf Dimensions

Estimating leaf area using non-destructive methods from regression equations has become a more efficient, quick, and accurate way. Thus, this study aimed to propose an equation that significantly estimates the leaf area of Psychotria colorata (Rubiaceae) through linear leaf dimensions. For this purpose, 200 leaves of different shapes were collected, and length (L), width (W), product of length by width (L.W), and real leaf area (LA) of each leaf blade were determined. Then, equations were adjusted for predicting leaf area using simple linear, linear (0.0), quadratic, cubic, power, and exponential regression models. The proposed equation was selected according to the coefficient of determination (R²), Willmott's agreement index (d), Akaike's information criterion (AIC), mean absolute error (MAE), mean squared error (RMSE) and BIAS index. It was noted that the equations adjusted using L.W met the best criteria for estimating leaf area, but the equation LA = 0.59 * L.W from linear regression without intercept was the most suitable. This equation predicts that 59% of leaf area is explained by L.W. Concluding, the leaf area of P. colorata can be estimated using an allometric equation that uses linear leaf blade dimensions.

scholarly journals A NON-DESTRUCTIVE METHOD FOR ESTIMATING LEAF AREA OF Ceiba glaziovii (Kuntze) K. Schum.

FLORESTA ◽  
2019 ◽  
Vol 50 (1) ◽  
pp. 1063
Author(s):  
João Everthon da Silva Ribeiro ◽  
Francisco Romário Andrade Figueiredo ◽  
Ester Dos Santos Coêlho ◽  
Walter Esfrain Pereira ◽  
Manoel Bandeira de Albuquerque
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Linear Measurements ◽  
Maximum Width ◽  
Bias Index ◽  
Different Shapes ◽  
Non Destructive

The determination of leaf area is of fundamental importance in studies involving ecological and ecophysiological aspects of forest species. The objective of this research was to adjust an equation to determine the leaf area of Ceiba glaziovii as a function of linear measurements of leaves. Six hundred healthy leaf limbs were collected in different matrices, with different shapes and sizes, in the Mata do Pau-Ferro State Park, Areia, Paraíba state, Northeast Brazil. The maximum length (L), maximum width (W), product between length and width (L.W), and leaf area of the leaf limbs were calculated. The regression models used to construct equations were: linear, linear without intercept, quadratic, cubic, power and exponential. The criteria for choosing the best equation were based on the coefficient of determination (R²), Akaike information criterion (AIC), root mean square error (RMSE), Willmott concordance index (d) and BIAS index. All the proposed equations satisfactorily estimate the leaf area of C. glaziovii, due to their high determination coefficients (R² ≥ 0.851). The linear model without intercept, using the product between length and width (L.W), presented the best criteria to estimate the leaf area of the species, using the equation 0.4549*LW.

scholarly journals Non-destructive method for estimating leaf area of Erythroxylum pauferrense (Erythroxylaceae) from linear dimensions of leaf blades

2020 ◽  
Author(s):  
João Everthon da Silva Ribeiro ◽  
Ester dos Santos Coêlho ◽  
Francisco Romário Andrade Figueiredo ◽  
Marlenildo Ferreira Melo
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Information Criterion ◽  
Mean Square ◽  
Forest Species ◽  
Exponential Regression ◽  
Linear Dimensions ◽  
Bias Index ◽  
Lower Akaike Information Criterion ◽  
Non Destructive

Background and Aims: Determining the leaf area is essential for studies on growth, propagation, and ecophysiology of forest species. Developing quick, practical, and accurate methods is needed to estimate leaf area without destroying leaves. Therefore, this research aimed to obtain an equation from regression models that meaningfully estimate the leaf area of Erythroxylum pauferrense using linear dimensions of its leaf blades.Methods: For this purpose, 1200 leaves were randomly collected from different plants in the Mata do Pau-Ferro, a state park located in Areia city, Paraíba state, Brazil. Equations were fitted from simple linear, linear without intercept, quadratic, cubic, power, and exponential regression models. Next, the best equation was selected by checking the following assumptions: higher determination coefficient (R²) and Willmott's index (d), lower Akaike information criterion (AIC) and root mean square error (RMSE), as well as the BIAS index closest to zero.Key results: Based on the criteria used, all equations fitted using the product of length by width (L.W) can estimate the leaf area of E. pauferrense.Conclusions: The equation ŷ=0.6740*LW from the linear model without intercept significantly estimates the leaf area of E. pauferrense in a quick and practical way (R²=0.9960; d=0.9953; AIC=1231.61; RMSE=0.4255; BIAS=-0.0130).

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 Mathematical Modeling for Leaf Area Estimation From Papaya Seedlings ‘Golden THB’

2019 ◽  
Vol 11 (5) ◽  
pp. 496
Author(s):  
Vinicius de Souza Oliveira ◽  
Karina Tiemi Hassuda dos Santos ◽  
Thainá de Jesus Ambrósio ◽  
Jéssica Sayuri Hassuda Santos ◽  
Weslley do Rosário Santana ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Leaf Area ◽  
Regression Models ◽  
Leaf Blade ◽  
Coefficient Of Determination ◽  
Suitable Model ◽  
Linear Regression Models ◽  
Maximum Width ◽  
Area Estimation ◽  
Linear Dimensions

The aim of this study was to select the most suitable model for leaf area estimation from papaya seedlings cv. ‘Golden THB’ using linear dimensions of leaves with unilobular and trilobular morphology. It was used leaves of 60 seedlings with 30 days after sowing produced in nursery of the Fazenda Santa Teresinha which belongs to company Caliman Agrícola S.A., in the municipality of Linhares, state of Espírito Santo, in March 2016. The measurement of the length (L) was performed along the midrib, the maximum width (W) of the leaf blade, the product of the length by the width (LW) and the observed leaf area (OLA). From these results, first degree and power linear regression models was adjusted. From the proposed regression models, the validation was performed with a leaves sample of 60 seedlings produced in June 2016, obtaining, thus, the estimated leaf area (ELA). The following criteria were used to choose the best model: the highest coefficient of determination (R2), the values do not significant of the comparison of means of OLA and ELA and values of MAE and RMSE closer to zero. The leaf area estimation from papaya seedlings cv. ‘Golden THB’ can be represented through equation ELA = -0.402619 + 0.612525(LW) for trilobular leaves and through equation ELA = 0.623355 + 0.610552(LW) for unilobular leaves.

scholarly journals Alometric Model for Estimation of Leaf Area of Garcinia brasiliensis Mart. Through Non-destructive Method

2019 ◽  
Vol 11 (10) ◽  
pp. 154
Author(s):  
Vinicius de Souza Oliveira ◽  
Cássio Francisco Moreira de Carvalho ◽  
Juliany Morosini França ◽  
Flávia Barreto Pinto ◽  
Karina Tiemi Hassuda dos Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Linear Equations ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Maximum Width ◽  
Linear Dimensions ◽  
Length Width ◽  
Independent Variable ◽  
The Mean ◽  
Non Destructive

The objective of the present study was to test and establish mathematical models to estimate the leaf area of Garcinia brasiliensis Mart. through linear dimensions of the length, width and product of both measurements. In this way, 500 leaves of trees with age between 4 and 6 years were collected from all the cardinal points of the plant in the municipality of São Mateus, North of the State of Espírito Santo, Brazil. The length (L) along the main midrib, the maximum width (W), the product of the length with the width (LW) and the observed leaf area (OLA) were obtained for all leaves. From these measurements were adjusted linear equations of first degree, quadratic and power, in which OLA was used as dependent variable as function of L, W and LW as independent variable. For the validation, the values of L, W and LW of 100 random leaves were substituted in the equations generated in the modeling, thus obtaining the estimated leaf area (ELA). The values of the means of ELA and OLA were tested by Student’s t test 5% of probability. The mean absolute error (MAE), root mean square error (RMSE) and Willmott’s index d for all proposed models were also determined. The choice of the best model was based on the non significant values in the comparison of the means of ELA and OLA, values of MAE and RMSE closer to zero and value of the index d and coefficient of determination (R2) close to unity. The equation that best estimates leaf area of Garcinia brasiliensis Mart. in a way non-destructive is the power model represented by por ELA = 0.7470(LW)0.9842 and R2 = 0.9949.

scholarly journals Estimation of buckwheat leaf area by leaf dimensions

2021 ◽  
Vol 42 (3Supl1) ◽  
pp. 1529-1548
Author(s):  
Alberto Cargnelutti Filho ◽  
◽  
Rafael Vieira Pezzini ◽  
Ismael Mario Márcio Neu ◽  
Gabriel Elias Dumke ◽  
...  
Keyword(s):  
Leaf Area ◽  
Linear Model ◽  
Leaf Blade ◽  
Sowing Date ◽  
Quadratic Model ◽  
Digital Photo ◽  
Sowing Dates ◽  
Leaf Dimensions ◽  
Fagopyrum Esculentum Moench ◽  
Uniformity Trials

The objective of this work was to model and identify the best models for estimating the leaf area, determined by digital photos, of buckwheat (Fagopyrum esculentum Moench) of the cultivars IPR91-Baili and IPR92-Altar, as a function of length (L), width (W) or length x width product (LW) of the leaf blade. Ten uniformity trials (blank experiments) were carried out, five with IPR91-Baili cultivar and five with IPR92-Altar cultivar. The trials were performed on five sowing dates. In each trial and cultivar, expanded leaves were collected at random from the lower, middle and upper segments of the plants, totaling 1,815 leaves. In these 1,815 leaves, L and W were measured and the LW of the leaf blade was calculated, which were used as independent variables in the model. The leaf area of each leaf was determined using the digital photo method (Y), which was used as a dependent variable of the model. For each sowing date, cultivar and thirds of the plant, 80% of the leaves (1,452 leaves) were randomly separated for the generation of the models and 20% of the leaves (363 leaves) for the validation of the models of leaf area estimation as a function of linear dimensions. For buckwheat, IPR91-Baili and IPR92-Altar cultivars, the quadratic model (Ŷ = 0.5217 + 0.6581LW + 0.0004LW2, R2 = 0.9590), power model (Ŷ = 0.6809LW1.0037, R2 = 0.9587), linear model (Ŷ = 0.0653 + 0.6892LW, R2 = 0.9587) and linear model without intercept (Ŷ = 0.6907LW, R2 = 0.9587) are indicated for the estimation of leaf area determined by digital photos (Y) based on the LW of the leaf blade (x), and, preferably, the linear model without intercept can be used, due to its greater simplicity.

scholarly journals Estimative of Black Pepper leaf area with basis on the leaf blade linear dimension

2007 ◽  
Vol 37 (5) ◽  
pp. 1458-1461 ◽  
Author(s):  
Fábio Luiz Partelli ◽  
Henrique Duarte Vieira ◽  
Alexandre Pio Viana
Keyword(s):  
Leaf Area ◽  
Leaf Blade ◽  
Correlation Coefficients ◽  
Black Pepper ◽  
Regression Equation ◽  
Piper Nigrum ◽  
Regression Equations ◽  
Linear Regression Equation ◽  
Linear Leaf ◽  
Predicted Values

This research was aimed at establishing regression equations to estimate black pepper (Piper nigrum) leaf area based on linear leaf measures. Different black pepper varieties where growth on the field, four different size leaves were collected per plant with a total of 52 leaves to establish the regression equation and 28 to validate the equation for each variety (Bragantina, Laçará, Guajarina e Cingapura). Leaf midrib length (LML), maximum leaf broad width (MLBW) and leaf area (LA) were measured. Pearson's linear correlation coefficients were determined between observed and predicted measures with the observed LA, besides estimating the linear regression equation for each variety. The equations best-fitted to estimate LA based on circumscript rectangle were: 1) LA = 2.2689 + 0.6900 x LML x MLBW; 2) LA = 1.6402 + 0.6816 x LML x MLBW; 3) LA = 1.4942 + 0.6215 x LML x MLBW and 4) LA = 0.7467 + 0.6735 x LML x MLBW, for Bragantina, Laçará, Guajarina and Cingapura varieties respectively. For all equations predicted values had high correlation coefficient with observed values thus showing that these equations must be variety specific and that they are appropriate for black pepper leaf area estimative.

scholarly journals Leaf area estimation for Psychotria carthagenensis and Psychotria hoffmannseggiana as a function of linear leaf dimensions

2019 ◽  
Vol 41 (1) ◽  
pp. 43494
Author(s):  
João Everthon da Silva Ribeiro ◽  
Ester Dos Santos Coêlho ◽  
Francisco Romário Andrade Figueiredo ◽  
Walter Esfrain Pereira ◽  
Manoel Bandeira de Albuquerque
Keyword(s):  
Leaf Area ◽  
Area Estimation ◽  
Linear Leaf ◽  
Leaf Dimensions

scholarly journals Non-destructive measurement of leaf area and leaf pigments in feijoa trees

2019 ◽  
Vol 23 (1) ◽  
pp. 16-20
Author(s):  
Marcos R. Sachet ◽  
Idemir Citadin ◽  
Marieli T. Guerrezi ◽  
Rafael H. Pertille ◽  
Joel Donazzolo ◽  
...  
Keyword(s):  
Leaf Area ◽  
Chlorophyll A ◽  
Leaf Blade ◽  
Leaf Pigment ◽  
Leaf Dimensions ◽  
Chlorophyll Index ◽  
Acca Sellowiana ◽  
Old Trees ◽  
Destructive Measurement ◽  
Non Destructive

ABSTRACT Leaf area (cm2 per leaf) and leaf pigment content are important traits that can be used to better understand a plants physiology. In this study, empirical non-destructive models for leaf area and leaf pigment based on the leaf dimensions, length (L) and width (W) in centimeters, and chlorophyll meter readings were developed for feijoa (Acca sellowiana). The experiment was carried out during January 2016 using five-year-old trees of 60 genotypes, grown under field conditions in the state of Paraná, Brazil. The proposed leaf area (LA) model was L A = 0 . 0022 L 3 + 0 . 1482 W 2 + 0 . 6159 L W + 0 . 1076 (R2 = 0.99). Three current leaf area models found in the literature were also assessed. All of the already created models were less accurate than the model proposed in this article. The proposed leaf pigment models were based on the Falker Chlorophyll Index for Chlorophyll a (A) and b (B), these were C h l a = 2 . 564 A + 13 . 098 B - 42 . 605 (R2 = 0.94), C h l b = 1 . 538 A + 3 . 287 B + 8 . 847 (R2 = 0.86) and C a r o t e n o i d s = 0 . 947 B + 8 . 943 (R2 = 0.88) expressed as µmol m-2 of leaf blade. In conclusion, the proposed models in this study were shown to be a reliable non-destructivel way of estimating A. sellowiana leaf area and leaf pigment.

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