scholarly journals Estimation of Leaf Area by Linear Dimensions in Coffea dewevrei

2019 ◽  
pp. 1-8
Author(s):  
Omar Schmildt ◽  
Enilton Nascimento de Santana ◽  
Vinicius de Souza Oliveira ◽  
Rafael Ruy Gouvea ◽  
Lucas Corrêa Souza ◽  
...  
Keyword(s):  
Leaf Area ◽  
Technical Assistance ◽  
Absolute Error ◽  
Equation Model ◽  
Quadratic Model ◽  
Linear Dimensions ◽  
Independent Variable ◽  
Student’S T ◽  
Simple Linear Equation ◽  
The City

The objective of this research was to select the equation that best estimates the leaf area of the coffee tree Coffea dewevrei, from the linear dimensions of the leaves. For this purpose, 140 leaves of adult plants were collected from the Capixaba Institute for Research, Technical Assistance and Rural Extension, in the city of Linhares, North of the State of Espírito Santo, Brazil. The length (L), the width (W), the product of the multiplication between the length and width (LW) and the leaf area observed (OLA) were determined from all leaves. For the modeling, a 100 leaves sample was used, where OLA was used as a dependent variable in function of L, W and LW as independent variable, being obtained the following models: linear first degree, quadratic and power. For the validation, a sample of 40 leaves was used, where the values of L, W LW were substituted in the equations generated in the modeling, thus obtaining the estimated leaf area (ELA). A simple linear equation model was fitted for each modeling equation relating ELA in function of OLA. The hypotheses H0: β0 = 0 versus Ha: β0 ≠ 0 and H0: β1 = 1 versus Ha: β1 ≠ 1, were tested using Student's t test at 5% probability. The mean absolute error (MAE), root mean square error (RMSE) and Willmott's index d for all equations were also determined. The best model that estimates the area of Coffea dewevrei was chosen through the following criteria: β0 not different from zero, β1 not different from one, MAE and RMSE values closer to zero and index d closer to the unit. The area of the leaves can be determined by its greater width (W), through the quadratic model equation ELA=-10.255+1.020(W)+1.293(W)2.

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 Single Leaf Area of Acacia mangium Willd

2019 ◽  
pp. 1-7
Author(s):  
Vinicius De Souza Oliveira ◽  
Jean Karlos Barros Galote ◽  
Ivani Vieira Damaceno ◽  
Natália de Souza Furtado ◽  
Karina Tiemi Hassuda Dos Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Linear Models ◽  
Acacia Mangium ◽  
Absolute Error ◽  
Single Leaf ◽  
The North ◽  
Independent Variable ◽  
Student’S T ◽  
Non Destructive ◽  
Student’S T Test

The objective of this study was to determine the best equation for estimating the leaf area of ​​Acacia mangium Willd. from the linear dimensions of the leaflets of non-destructive form. For this, 476 leaflets of plants belonging to Lajeado farm were collected in the municipality of Ecoporanga, in the north of the State of Espírito Santo, Brazil. From each leaflet was determined the length (L) along the main midrib, the largest width (W), the product of the multiplication between the length and the width (LW) the observed leaf area (OLA). For the modeling, we used 382 leaflets in which OLA was the dependent variable in function of L, W or LW as independent variable, being adjusted the linear models of first degree, quadratic and power. For the validation, the values ​​of L, W and LW of 94 leaflets were replaced in the equations obtained in the modeling thus obtaining the estimated leaf area (ELA). The means of ELA and OLA were compared by Student's t test at 5% probability. . It was also determined the mean absolute error (MAE), the root mean square error (RMSE) and Willmott's index d. In order to select the best equation, the following criteria were used: : not significant of the comparison of the means of ELA and OLA, values ​​of MAE and RMSE with closer to zero and index d closer to one. The power model equation represented by is the most adequate to predict the leaf area of ​​Acacia mangium Willd. quickly and non-destructively.

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 Leaf Area of Jackfruit Through Non-destructive Method

2019 ◽  
Vol 11 (6) ◽  
pp. 77
Author(s):  
Vinicius de Souza Oliveira ◽  
Leonardo Raasch Hell ◽  
Karina Tiemi Hassuda dos Santos ◽  
Hugo Rebonato Pelegrini ◽  
Jéssica Sayuri Hassuda Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Linear Equations ◽  
Absolute Error ◽  
Order Model ◽  
Sanitary Condition ◽  
Federal Institute ◽  
Independent Variable ◽  
Mathematical Equations ◽  
The Mean ◽  
Non Destructive

The objective of this study was to determine mathematical equations that estimate the leaf area of jackfruit (Artocarpus heterophyllus) in an easy and non-destructive way based on linear dimensions. In this way, 300 leaves of different sizes and in good sanitary condition of adult plants were collected at the Federal Institute of Espírito Santo, Campus Itapina, located in Colatina, municipality north of the State of Espírito Santo, Brazil. Were measured The length (L) along the midrib and the maximum leaf width (W), observed leaf area (OLA), besides the product of the multiplication of length with width (LW), length with length (LL) and width with width (WW). The models of linear equations of first degree, quadratic and power and their respective R2 were adjusted using OLA as dependent variable in function of L, W and LW, LL and WW as independent variable. The data were validated and the estimated leaf area (ELA) was obtained. The means of ELA and OLA were compared by Student’s t test (5% probability) and were evaluated by the mean absolute error (MAE) and root mean square error (RMSE) criteria. The choice of the best model was based on non-significant comparative values of ELA and OLA, in addition to the closest values of zero of EAM and RQME. The jackfruit leaf area estimate can be determined quickly, accurately and non-destructively by the linear first-order model with LW as the independent variable by equation ELA = 1.07451 + 0.71181(LW).

scholarly journals Non-destructive Method for Estimating the Leaf Area of Pear cv. ‘Triunfo’

2019 ◽  
Vol 11 (7) ◽  
pp. 14
Author(s):  
Vinicius de Souza Oliveira ◽  
Karina Tiemi Hassuda dos Santos ◽  
Andréia Lopes de Morais ◽  
Gleyce Pereira Santos ◽  
Jéssica Sayuri Hassuda Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Mean Squared Error ◽  
Linear Equations ◽  
Absolute Error ◽  
Equation Model ◽  
Maximum Width ◽  
Northern Side ◽  
Mathematical Equations ◽  
The Mean ◽  
High Degree

The present study had as objective to determine mathematical equations to estimate the leaf area of pear cv. ‘Triunfo’ using linear dimensions of the leaves. For that, 300 healthy leaves of different sizes from each quadrant of plants from the small farm of Boa Vista located in the city of Montanha, at the northern side of the State of Espírito Santo, Brazil were used. The length (L) along the main vein was measured, along with the maximum width (W) of the leaf blade and observed leaf area (OLA), in addition to the product of the length and width (LW) of each leaf. From these measurements models of linear equations of first degree, quadratic and power were adjusted and their respective R2, using OLA as dependent variable and L, W and LW as independent variable. Based on the proposed equations, the data were validated obtaining the estimated leaf area (ELA). The mean of the ELA and OLA were compared by Student t test 5% probability. The mean error (E), the mean absolute error (MAE) and the root mean squared error (RMSE) was also used as validation criterion. The best equation model was defined based on the non-significant values from the comparison of means of ELA and OLA, E, MAE and RMSE values closer to zero and highest R2. The leaf area of pear cv. ‘Triunfo’ can be estimated by the equation ELA = -0.432338 + 0.712862(LW) non-destructively and with a high degree of precision.

scholarly journals Mathematical Modeling to Estimation Leaf Area of Pimenta dioica from Linear Dimensions

2019 ◽  
pp. 1-8
Author(s):  
Vinicius De Souza Oliveira ◽  
Lucas Caetano Gonçalves ◽  
Amanda Costa ◽  
Karina Tiemi Hassuda dos Santos ◽  
Jéssica Sayuri Hassuda Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Linear Equations ◽  
Selection Criterion ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Regression Equations ◽  
Maximum Width ◽  
Independent Variable ◽  
Pimenta Dioica ◽  
Non Destructive

The objective of this work was to obtain regression equations and to indicate the most appropriate from different mathematical models for the estimation of the leaf area of ​​ Allspice (Pimenta dioica) by non - destructive method. 500 leaves of plants located in the municipality of São Mateus, North of Espírito Santo State, Brazil, were collected, 400 of which were used to adjust the equations and 100 for validation. 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 measured from all leaves. We fitted models of linear equations of first degree, quadratic and power, where OLA was the dependent variable in function of L, W and LW. From the 100 sheets intended for validation, and using the adjusted equations for each mathematical model, the estimated leaf area (ELA) was obtained. Subsequently, a simple linear regression was fitted for each model of the proposed equation in which ELA was the dependent variable and OLA the independent variable. The mean absolute error (MAE), the root mean square error (RMSE) and Willmott's index d also determined. The best fit had as selection criterion the non-significance of the comparative means of ELA and OLA, MAE and RMSE values ​​closer to zero and value of the coefficient of determination coefficient (R2) close to one. Thus, the power model (ELA = 0.7605(LW)0.9926, R2 = 0.9764, MAE = 1.0066, RMSE = 1.7759 and d = 0.9950) based on the product of length and width (LW) is the most appropriate for estimating the leaf area of ​​Pimenta dioica.

scholarly journals Determination of the Leaflet Area of Schinus terebinthifolius Raddi in Function of Linear Dimensions

2019 ◽  
Vol 11 (14) ◽  
pp. 198
Author(s):  
Vinicius de Souza Oliveira ◽  
André Monzoli Covre ◽  
Drielly Stephania Gouvea ◽  
Luciano Canal ◽  
Karina Tiemi Hassuda dos Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Absolute Error ◽  
T Test ◽  
Quadratic Model ◽  
Angular Coefficient ◽  
Schinus Terebinthifolius ◽  
Linear Coefficient ◽  
Mean Values ◽  
Mathematical Equations ◽  
The Mean

The objective of this study was to select mathematical equations that best fit the estimation of the leaf area of pink pepper (Schinus terebinthifolius Raddi) from the linear leaflet dimensions. 500 leaflets with different physiological ages of a commercial plantation were collected, located in the region of Gameleira, municipality of São Mateus, North of the State of Espírito Santo, Brazil. Was measured the length (L) along the main midrib, the largest width (W) and the observed leaf area (OLA) of each sheet. The product of the multiplication between L and W of the leaflets (LW) was determined. For the modeling the measurements of 400 leaflets were used, where OLA was used in function of L, W or LW. Based on the models found, we obtained the estimated leaf area (ELA). A simple linear regression was fitted for each proposed model of OLA in function of ELA. We tested the hypotheses H0: β0 = 0 versus Ha: β0 ≠ 0 and H0: β1 = 1 versus Ha: β1 ≠ 1, using Student’s t test at 5% probability. The mean values of ELA and OLA were compared by Student’s t test 5% probability. It was determined the mean error (E), mean absolute error (MAE), root mean square error (RMSE) and Willmott d index. The best adjusted equation was chosen by linear coefficient (β0) not different from zero, angular coefficient (β1) not unlike one, non-significant values of ELA and OLA, E, EAM and RQME closer to zero and Willmott’s index d closer to one. In this way, the leaf area of leaflets of Schinus terebinthifolius Raddi can be estimated by the quadratic model equation ELA = -2.6646 + 2.2124W + 1.3953(W)2 , using only the width of the leaves as a measure.

PENGARUH PEMANFAATAN TEKNOLOGI INFORMASI TERHADAP KEPUASAN END USER COMPUTING DENGAN KETIDAKPASTIAN TUGAS SEBAGAI VARIABEL MODERATING

2013 ◽  
Author(s):  
Herawati M
Keyword(s):  
Information Technology ◽  
Primary Data ◽  
End User ◽  
Moderating Variables ◽  
The Third ◽  
Use Of Technology ◽  
Task Uncertainty ◽  
Independent Variable ◽  
The City ◽  
End User Computing

This study aims to use information technology, uncertainty or moderation duties and interactions between task uncertainty with the use of information technology to end user computing satisfaction. In this study used 70 respondents who actively use computers and working with several companies banking on the city of Padang. The data used are the primary data obtained through questionnaires. The study used three types of variables, the first is the independent variable, namely the utilization of information technology, both moderating variables, namely the uncertainty of the task, the third is the dependent variable is satisfaction of end user computing. The stages of hypothesis testing is done by using a regression model of moderating and statistical t-test. Based on the results of testing the first hypothesis (HI) was found to significantly influence the utilization of information technology to the satisfaction of end user computing. The second hypothesis (H2) testing results found that task uncertainty did not significantly influence the end user computing satisfaction. The third hypothesis (H3) testing found that the interaction or moderation between the use of technology with task uncertainty no significant effect on end user computing satisfaction.

scholarly journals City library network knowledge management for social cohesion: The case of Santa Coloma de Gramenet, Barcelona, Spain

IFLA Journal ◽  
2020 ◽  
Vol 46 (1) ◽  
pp. 52-63
Author(s):  
Daniel García Giménez ◽  
Lluis Soler Alsina
Keyword(s):  
Knowledge Management ◽  
Social Cohesion ◽  
Technical Assistance ◽  
Public Libraries ◽  
Provincial Government ◽  
Strategic Orientation ◽  
Equal Opportunities ◽  
Library Network ◽  
The City ◽  
Historical Periods

In Santa Coloma de Gramenet (Catalonia, Spain) there is a network of four public libraries. They belong to the City, with technical assistance, strategic orientation and financial support from the provincial government, Diputació de Barcelona. These four libraries have been built in different historical periods and located in neighbourhoods with very unequal social backgrounds. They have been working on adapting their services to their neighbourhoods and as a network they have been moving on along the differences. Even so, the current information society challenges require a city library project in order to guarantee social cohesion and equal opportunities. This article tries to explain the strategy to achieve those goals, based on knowledge management and networking, transversal workshops and a shared communication circuit that so far has allowed this urban library network to extend and to renew services as well as to empower vulnerable sectors in accordance with the United Nations 2030 Agenda.

scholarly journals Quadratic Model-Based Dynamically Updated PID Control of CSTR System with Varying Parameters

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 31
Author(s):  
Dushko Stavrov ◽  
Gorjan Nadzinski ◽  
Stojche Deskovski ◽  
Mile Stankovski
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Absolute Error ◽  
Error Model ◽  
Quadratic Model ◽  
Control Performance ◽  
Continuous Stirred Tank Reactor ◽  
Quadratic Error ◽  
Varying Parameters ◽  
Cstr System

In this paper, we discuss an improved version of the conventional PID (Proportional–Integral–Derivative) controller, the Dynamically Updated PID (DUPID) controller. The DUPID is a control solution which preserves the advantages of the PID controller and tends to improve them by introducing a quadratic error model in the PID control structure. The quadratic error model is constructed over a window of past error points. The objective is to use the model to give the conventional PID controller the awareness needed to battle the effects caused by the variation of the parameters. The quality of the predictions that the model is able to deliver depends on the appropriate selection of data used for its construction. In this regard, the paper discusses two algorithms, named 1D (one dimensional) and 2D (two dimensional) DUPID. Appropriate to their names, the former selects data based on one coordinate, whereas the latter selects the data based on two coordinates. Both these versions of the DUPID controller are compared to the conventional PID controller with respect to their capabilities of controlling a Continuous Stirred Tank Reactor (CSTR) system with varying parameters in three different scenarios. As a quantifying measure of the control performance, the integral of absolute error (IAE) metric is used. The results from the performed simulations indicated that the two versions of the DUPID controller improved the control performance of the conventional PID controller in all scenarios.

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