scholarly journals Non-destructive equations to estimate the leaf area of Styrax pohlii and Styrax ferrugineus

2014 ◽  
Vol 74 (1) ◽  
pp. 222-225 ◽  
Author(s):  
MC Souza ◽  
G Habermann
Keyword(s):  
Linear Regression ◽  
Leaf Area ◽  
Linear Equations ◽  
Independent Variables ◽  
Leaf Dimensions ◽  
Independent Variable ◽  
Non Destructive ◽  
Linear Regressions

We developed linear equations to predict the leaf area (LA) of the species Styrax pohlii and Styrax ferrugineus using the width (W) and length (L) leaf dimensions. For both species the linear regression (Y=α+bX) using LA as a dependent variable vs. W × L as an independent variable was more efficient than linear regressions using L, W, L2 and W2 as independent variables. Therefore, the LA of S. pohlii can be estimated with the equation LA=0.582+0.683WL, while the LA of S. ferrugineus follows the equation LA=−0.666+0.704WL.

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 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 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 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 Non-destructive models for leaf area determination in canola

2016 ◽  
Vol 20 (6) ◽  
pp. 551-556 ◽  
Author(s):  
Francilene de L. Tartaglia ◽  
Evandro Z. Righi ◽  
Leidiana da Rocha ◽  
Luis H. Loose ◽  
Ivan C. Maldaner ◽  
...  
Keyword(s):  
Leaf Area ◽  
Leaf Length ◽  
Phenological Stages ◽  
Gas Exchanges ◽  
Independent Variables ◽  
Length Width ◽  
Leaf Dimensions ◽  
Non Destructive ◽  
Important Structure ◽  
Area Determination

ABSTRACT The leaf is a very important structure of the plants, since it allows gas exchanges and the transformation of light energy into chemical energy. This study aimed to generate and test mathematical models for leaf area estimation in canola based on leaf dimensions. Two experiments were conducted with canola in 2014, in which leaves were collected in different phenological stages with different sizes and shapes. Subsequently, leaf length, width and area were measured (with automatic meter) in 606 leaves, which included 371 ovate and 235 lanceolate leaves. The models were generated using length, width and length versus width as independent variables and leaf area as dependent variable. The models were validated using a group of leaves different from those used to generate the models. A total of 27 models were obtained and those with best statistics and higher simplicity were selected. The polynomial model LA = 0.88735 W2 + 0.93503 W and the power model LA = 1.1282 W1.9396 can be used for both types of leaves and have high accuracy in the estimation of canola leaf area.

scholarly journals Models for estimating yacon leaf area

2016 ◽  
Vol 34 (3) ◽  
pp. 422-427 ◽  
Author(s):  
Wellington A Erlacher ◽  
Fábio L Oliveira ◽  
Gustavo S Fialho ◽  
Diego MN Silva ◽  
Arnaldo HO Carvalho
Keyword(s):  
Leaf Area ◽  
Crop Production ◽  
Scientific Information ◽  
Leaf Size ◽  
Leaf Length ◽  
Logarithmic Model ◽  
Area Estimate ◽  
Independent Variable ◽  
Precision And Accuracy ◽  
Non Destructive

ABSTRACT The recent exploration of yacon demands scientific information for improving the crop production technology. This study aimed to set a leaf area estimate model for yacon plants, using non-destructive measurements of leaf length (L) and/or width (W). Sixty-four representative yacon plants were randomly selected in an experimental field during the full vegetative growth. One thousand leaves of various sizes were taken from those plants for setting and validating a model. The logarithmic model best fitted this purpose, the result of multiplying length by width being used as independent variable. Yacon leaf area can be determined with high precision and accuracy by LALW = (-27.7418 + (3.9812LW / ln LW ) , disregarding the leaf size.

scholarly journals Pendugaan Produktivitas Bagan Perahu dengan Regresi Gulud, LASSO dan Elastic-net

2018 ◽  
Vol 2 (2) ◽  
pp. 7-14
Author(s):  
Resty Fanny ◽  
Anik Djuraidah ◽  
Aam Alamudi
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Ridge Regression ◽  
Penalized Regression ◽  
Statistical Technique ◽  
Elastic Net ◽  
Least Square ◽  
Productivity Change ◽  
Independent Variables ◽  
Independent Variable

Regression analysis is a statistical technique to examine and model the relationship between dependent variable and independent variable. Multiple linear regression includes more than one independent variable. Multicollinearity in multiple linear regression occurs when the independent variables has correlations. Multicolinearity causes the estimator by ordinary least square to be unstable and produce a large variety. Multicollinearity can be overcome by the addition of penalized regression coefficient. The purpose of this research is modeling ridge regression, LASSO, and elastic-net. Data which is data of fisherman catch at Carocok Beach of Tarusan Sumatera Barat as dependent variable and amount of labor, amount of fuel, volume of fishing/waring boat, number of catches, ship size, number of boat wattage, sea experience, education and age of fisher as independent variables. The best model provided by LASSO that has a RMSEP value of validated regression model is minimum than ridge regression and elastic-net. LASSO shrinked amount of labor, amount of fuel and number of wattage equal zero. There can be influence (productivity change) that is volume of fishing/waring boat and boat size that used by fisher.

scholarly journals PENGARUH RASIO PROFITABILITAS, RASIO SOLVABILITAS DAN RASIO NILAI PASAR TERHADAP RETURN SAHAM PERUSAHAAN REAL ESTATE DAN PROPERTI

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Desy Dwi Nestanti
Keyword(s):  
Real Estate ◽  
Stock Returns ◽  
Linear Equations ◽  
Financial Ratios ◽  
Analysis Tool ◽  
Linear Regression Equation ◽  
Return On Equity ◽  
Book Value ◽  
Independent Variables ◽  
Independent Variable

The purpose of this study was to analyze the influence of financial ratios, as measured by the ratio of profitability, solvability ratio and the ratio of the market value of the stock returns of real estate companies and property and to determine which variables are the most significant effect on stock returns. The analysis tool used is multiple linear equations with multiple regresion method for the analysis of the influence of the independent variable on the dependent variable. This model was chosen because the study was designed to determine the independent variables that have an influence on the dependent variable. The result of F test (simultaneous) shows that the financial ratios of return on equity and price to book value have a significant effect on stock returns and partial results showed that the variable return on equity have a significant effect on the analysis tehadap return saham. Berdasarkan diterdapat variables have a significant influence on stock returns. The variable that has no significant effect on stock returns are removed from the multiple linear regression equation. So the result shows that the return on equity and price to book value have a significant effect on stock returns.

scholarly journals Pengaruh Karakteristik Wirausahawan Design Grafis Terhadap Tingkat Keberhasilan Usaha

2019 ◽  
Vol 3 (1) ◽  
pp. 45
Author(s):  
Afiff Yudha Tripariyanto ◽  
Ana Komari ◽  
Heribertus Budi Santoso
Keyword(s):  
Graphic Design ◽  
Rapid Development ◽  
Business Success ◽  
Independent Variables ◽  
Simultaneous Test ◽  
Test Models ◽  
Regression Test ◽  
Saturated Sample ◽  
Independent Variable ◽  
Linear Regressions

The rapid development of graphic design raises many people who want to become graphic design entrepreneurs. In this study aims to determine the effect of the characteristics of graphic design entrepreneurs on the level of business success. Used 8 independent variables, namely hard work, cooperation, appearance, confidence, good at making decisions, want to increase knowledge, ambition to move forward and good at communicating to the level of business success. The sample used was of the saturated sample because the respondents were less than 100 people, as many as 40 respondents. The method used is multiple linear regressions. The results of the study are in the partial test, the independent variable that is not able to influence the level of success of graphic design business is a good performance variable, confident of pioneered business, want to increase knowledge, ambition to move forward, while in the simultaneous test the characteristics of entrepreneurial design are not influence the success of the business. In the multiple linear regression test models are obtained namely: Y = 4,140 + 0,957X1 + 0,904X2-0,149X3-0,071X4 + 0.029X5 + -1,070X6-0,914X7 + 0,257X8Keyword : Characteristics, Graphic design, T-Test, F-TestPerkembangan desain grafis yang pesat menimbulkan banyak orang yang ingin menjadi pengusaha desain grafis.Pada penelitian ini bertujuan untuk mengetahui pengaruh karakteristik wirausahawan desain grafis terhadap tingkat keberhasilan usaha. Digunakan 8 variabel bebas yaitu kerja keras, kerja sama, penampilan, yakin, pandai membuat keputusan, mau menambah pengetahuan, ambisi untuk maju dan pandai berkomunikasi terhadap tingkat keberhasilan usaha. Sampel yang digunakan berjenis sampel jenuh karena responden kurang dari 100 orang, yaitu sebanyak 40 responden. Metode yang digunakan adalah regres linier berganda. Hasil dari penelitian yaitu pada uji T, variabel bebas yang tidak mampu memberikan pengaruh terhadap tingkat keberhasilan usaha desain grafis adalah variabel penampilan yang baik, yakin akan usaha yang dirintis, mau menambah pengetahuan, ambisi untuk maju, sedangkan pada uji F wirausaha desain grafis tidak memberikan pengaruh terhadap keberhasilan usaha. Pada uji regreli linier berganda didapatkan model yaitu : Y=4,140+0,957X1+0,904X2-0,149X3-0,071X4+0,029X5+-1,070X6-0,914X7+0,257X8..Kata Kunci: Karakteristik,Desain grafis,Uji T, Uji F

scholarly journals PENGARUH MANAJEMEN MODAL KERJA TERHADAP PROFITABILITAS PADA CONSUMER GOODS SECTOR

2021 ◽  
Vol 29 (1) ◽  
pp. 43-56
Author(s):  
Prafidhya Dwi Yulianto ◽  
Lilik Ambarwati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Consumer Goods ◽  
Annual Report ◽  
T Test ◽  
Purposive Sampling ◽  
Independent Variables ◽  
Regression Methods ◽  
Inventory Turnover ◽  
Independent Variable

The purpose of this research is to know the influence of Working CapitalManagement on Profitabilty in Consumers Goods listed on the Bursa EfekIndonesia (BEI) aims to analyze the influence of woring capital in the from of:Cash Turnover, Account Receivable Turnover, and Inventory Turnover toProfitability (Return On Asset) at Consumers Goods Sector. This research methoduses multiple linear regression analysys with the help of SPSS 23.00 softwarewhich is used to see the inflyence between the independent variables in the fromCash Turnover, Account Recevaible Turnover, and Inventory Turnover to ReturnOn Asset (ROA)). The sample of this research is 31 consumer goods sector in2015-2018, so there are 124 annual report obtained through purposive sampling,then analyzed using multiple linear regression methods. The result showed thadbased on the F test, the independent variable had an effect on the ROA, it isindicated of 6.765 and significance of 0.000, overall the independent variable wasable to eaplain the effect 59,60%. While based on the partial t test, shows that thevariable Cash Turnover, Account Recevaible Turnover, and Inventory Turnoverhas a positive and siginificant effect on Profitability.

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