scholarly journals Adjusting weight growth curve of male quails Coturnix japonica reared in the semi-arid region of the State of Pernambuco

2018 ◽  
Vol 41 (1) ◽  
pp. 42563 ◽  
Author(s):  
Leandro Ricardo Rodrigues de Lucena ◽  
Marco Aurélio Carneiro de Holanda ◽  
Mônica Calixto Ribeiro de Holanda ◽  
Marcelo Lopes dos Anjos
Keyword(s):  
Growth Curve ◽  
Regression Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Normal Regression ◽  
Weight Growth ◽  
Semi Arid Region ◽  
Log Normal ◽  
Squared Residuals

This study adjusted different regression models to describe the growth pattern of meat quails from birth to 42 days of age. Data of 300 male quails were used. Weight and height information of all quails were collected weekly from the 1st to the 42nd day of age. Body weight of poultry was subjected to the polynomial, logistic, Gompertz, Weibull, and log-normal regression models. The criteria used to choose the best model to explain the growth curve of quails were the coefficient of determination of the model, Akaike’s information criterion, sum of squared residuals and Willmott’s index. For all the models used, the variables age and height were significant to explain the weight of quails. The polynomial (R² = 99.99%, AIC = 24.68, SSR = 27.5, d = 0.9999) and log-normal (R² = 99.60%, AIC = -17.5, SSR = 107.15, d = 0.9989) models presented the best fit criteria and were recommended to explain the growth of quails.

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 Growth curve Nopalea cochenillifera in fractionation function of cladodes using power regression model

2018 ◽  
Vol 36 (3) ◽  
pp. 578
Author(s):  
Leandro Ricardo Rodrigues de LUCENA ◽  
Juliana De Souza PEREIRA ◽  
Maurício Luiz de Mello Vieira LEITE
Keyword(s):  
Plant Growth ◽  
Regression Model ◽  
Pest Control ◽  
Growth Curve ◽  
Regression Models ◽  
Growth Period ◽  
Coefficient Of Determination ◽  
Planting Method ◽  
Nopalea Cochenillifera

In this work we evaluate the growth length of bud of Nopalea cochenillifera using five different forms of crops through power regression model. The adjusted models showed very similar estimates of lengths observed independent using of planting method. The power regression models showed coefficient of determination of model high 99.65% (treatment 1), 99.82% (treatment 2), 99.26% (treatment 3), 99.93% (treatment 4) and 99.34% (treatment 5). The power regression model proved effective to model the growth length of Nopalea cochenillifera of bud can generate strategies and plans for future plantings, as well useful information as: appropriate crop management, increased plant growth period and pest control.

scholarly journals Star Positions from Overlapping Plates in the Cape Zone −40° to −52°

1974 ◽  
Vol 61 ◽  
pp. 305-306
Author(s):  
S. V. M. Clube
Keyword(s):  
Regression Models ◽  
Preliminary Results ◽  
Normal Regression

A modification of the normal regression models used for the determination of star positions is described. Some preliminary results relating to accuracy are given.

Optimizing age at first use of semen for higher fertilityin Sahiwal breeding bulls

2016 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat
Keyword(s):  
Comparative Evaluation ◽  
Regression Models ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
Progeny Testing ◽  
Testing Programme ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

The objective of the study was to optimise the age at first use (AAFU) of semen in Sahiwal breeding bulls which will help in early selection of bulls under progeny testing programme. The data on AAFU, conception rate based on first A.I. (CRFAI), overall conception rate (OCR) and birth weight (B.WT) of 43 Sahiwal bulls during 1987 to 2013 at NDRI centre pertaining to 8 sets of Sahiwal improvement programme at ICAR-NDRI, Karnal, India were adjusted for significant environmental influences and subsequently analyzed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Comparative evaluation of three developed models (I to III) have showed that Model III, having AAFU and B.WT which fulfill the accuracy of model as revealed by high coefficient of determination, low mean sum of square to due error, low conceptual predictive value and low Bayesian information criterion . The results showed that average predicted CRFAI was highest (49.34%) at less than 5 years and lowest (44.79%) at > 6 years of age at first A.I. /use. Similarly average predicted OCR was highest (48.50%) at less than 5 years and lowest (44.56%) at >6 years of age at first A.I. / use of Sahiwal bulls. In organized herd under progeny testing programme, Sahiwal bulls should be used prior to 5 years which is expected to result in 4.45% better CRFAI and 3.94% better OCR in comparison to Sahiwal bulls used after 6 years of age.

scholarly journals Determination of Leaf Nitrogen Concentrations Using Electrical Impedance Spectroscopy in Multiple Crops

2020 ◽  
Vol 12 (3) ◽  
pp. 566 ◽  
Author(s):  
Rinku Basak ◽  
Khan Wahid ◽  
Anh Dinh
Keyword(s):  
Impedance Spectroscopy ◽  
Correlation Coefficient ◽  
Regression Models ◽  
Electrical Impedance ◽  
Leaf Nitrogen ◽  
Electrical Impedance Spectroscopy ◽  
Coefficient Of Determination ◽  
Frequency Range ◽  
Nitrogen Concentrations

In this work, crop leaf nitrogen concentration (LNC) is predicted by leaf impedance measurements made by electrical impedance spectroscopy (EIS). This method uses portable equipment and is noninvasive, as are other available nondestructive methods, such as hyperspectral imaging, near-infrared spectroscopy, and soil-plant analyses development (SPAD). An EVAL-AD5933EBZ evaluation board is used to measure the impedances of four different crop leaves, i.e., canola, wheat, soybeans, and corn, in the frequency range of 5 to 15 kHz. Multiple linear regression using the least square method is employed to obtain a correlation between leaf nitrogen concentrations and leaf impedances. A strong correlation is found between nitrogen concentrations and measured impedances for multiple features using EIS. The results are obtained by PrimaXL Data Analysis ToolPak and validated by analysis of variance (ANOVA) tests. Optimized regression models are determined by selecting features using the backward elimination method. After a comparative analysis among the four different crops, the best multiple regression results are found for canola with an overall correlation coefficient (R) of 0.99, a coefficient of determination (R2) of 0.98, and root mean square (RMSE) of 0.54% in the frequency range of 8.7–12 kHz. The performance of EIS is also compared with an available SPAD reading which is moderately correlated with LNC. A high correlation coefficient of 0.94, a coefficient of determination of 0.89, and RMSE of 1.12% are obtained using EIS, whereas a maximum correlation coefficient of 0.72, a coefficient of determination of 0.53, and RMSE of 1.52% are obtained using SPAD for the same number of combined observations. The proposed multiple linear regression models based on EIS measurements sensitive to LNC can be used on a very local scale to develop a simple, rapid, inexpensive, and effective instrument for determining the leaf nitrogen concentrations in crops.

scholarly journals Nonlinear models in the height description of the Rhino sunflower cultivar

2022 ◽  
Vol 52 (3) ◽  
Author(s):  
Anderson Chuquel Mello ◽  
Marcos Toebe ◽  
Rafael Rodrigues de Souza ◽  
João Antônio Paraginski ◽  
Junior Carvalho Somavilla ◽  
...  
Keyword(s):  
Growth Curve ◽  
Critical Points ◽  
Nonlinear Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Maximum Acceleration ◽  
Inflection Points ◽  
Best Fitting ◽  
Microsoft Office

ABSTRACT: Sunflower produces achenes and oil of good quality, besides serving for production of silage, forage and biodiesel. Growth modeling allows knowing the growth pattern of the crop and optimizing the management. The research characterized the growth of the Rhino sunflower cultivar using the Logistic and Gompertz models and to make considerations regarding management based on critical points. The data used come from three uniformity trials with the Rhino confectionery sunflower cultivar carried out in the experimental area of the Federal University of Santa Maria - Campus Frederico Westphalen in the 2019/2020 agricultural harvest. In the first, second and third trials 14, 12 and 10 weekly height evaluations were performed on 10 plants, respectively. The data were adjusted for the thermal time accumulated. The parameters were estimated by ordinary least square’s method using the Gauss-Newton algorithm. The fitting quality of the models to the data was measured by the adjusted coefficient of determination, Akaike information criterion, Bayesian information criterion, and through intrinsic and parametric nonlinearity. The inflection points (IP), maximum acceleration (MAP), maximum deceleration (MDP) and asymptotic deceleration (ADP) were determined. Statistical analyses were performed with Microsoft Office Excel® and R software. The models satisfactorily described the height growth curve of sunflower, providing parameters with practical interpretations. The Logistics model has the best fitting quality, being the most suitable for characterizing the growth curve. The estimated critical points provide important information for crop management. Weeds must be controlled until the MAP. Covered fertilizer applications must be carried out between the MAP and IP range. ADP is an indicator of maturity, after reaching this point, the plants can be harvested for the production of silage without loss of volume and quality.

scholarly journals THE EFFECT SELF-EFFICACY AND SOCIAL SUPPORT ON WORK STRESS OF TEACHERS

Akademika ◽  
2020 ◽  
Vol 9 (02) ◽  
pp. 177-193
Author(s):  
Masduki Ahmad
Keyword(s):  
Social Support ◽  
Elementary School ◽  
Work Stress ◽  
Self Efficacy ◽  
Regression Models ◽  
Civil Servant ◽  
Coefficient Of Determination ◽  
Analysis Tool ◽  
Linear Regression Models

This study aims to analyze the effects of self-efficacy and social support on work stress for civil servant teachers in Elementary School in Pondok Kelapa Village. This study uses multiple linear regression models as the main analysis tool. This study used a sample of 81 civil servant teachers at Elementary School in Pondok Kelapa Village. The research instrument was a closed questionnaire using a Likert scale and was applied via a google form. Statistical calculations in this study were carried out using SPSS version 25. To test the hypothesis, it was carried out using the t-test and the F test. From the research that has been conducted, it has in several conclusions including 1) self-efficacy has a negative and significant effect on work stress for civil servant teachers at Elementary School in Pondok Kelapa Village, with a significance value of 0.000 (α <0.005); 2) Social support has a negative and significant effect on the work stress of civil servant teachers at Elementary School in Pondok Kelapa Village, with a significance value of 0.000 (α <0.005) and 3) Self-efficacy and social support have a significant effect on work stress for civil servant teachers at Elementary School in Pondok Kelapa Village with a significance value of 0.000 (α <0.005) and a coefficient of determination of 0.597 or 59.7%.

Optimum age at first semen freezing in relation to fertility of Sahiwal breeding bulls

2018 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat ◽  
Ramendra Das ◽  
...  
Keyword(s):  
Birth Weight ◽  
Regression Models ◽  
Dairy Herd ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
National Dairy Research Institute ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

Early selection of bulls having optimum age at first semen freezing play an important role in improving reproductive performance in a dairy herd. Twenty seven years data (1987-2013) on age at first semen freezing (AAFSF), conception rate based on first A.I. (CRFAI) , overall conception rate (OCR) and birth weight (B.WT) of 41 Sahiwal bulls belonging to 8 sets of Sahiwal improvement programme at ICAR-National Dairy Research Institute, Karnal, Haryana, India; were adjusted against environmental effects and subsequently analysed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Among the three developed models (I to III), it was observed that Model III having age at first semen freezing and birth weight fulfil the accuracy of model i.e.; having high coefficient of determination (R2) value (CRFAI = 67% and OCR= 69%), low mean error sum of square (MSSe), low conceptual predictive value (CP value) and low Bayesian information criterion (BIC). The results revealed that optimum age at first semen freezing of Sahiwal bulls should be 2.5 - 3.0 years for 3.10% higher conception rate based on first A.I. (48.86%) and 4.39% higher overall conception rate (48.78%) in comparison to Sahiwal bulls with more than 3.5 years of age (CRFAI :- 45.76% and OCR :- 44.39%).

scholarly journals Mathematical models for metric features extraction from RGB-D sensor

2021 ◽  
Vol 14 (11) ◽  
Author(s):  
Elton Fernandes Dos Santos ◽  
Laurimar Gonçalves Vendrusculo ◽  
Luciano Bastos Lopes ◽  
Scheila Geiele Kamchen ◽  
Isabella C. F. S. Condotta
Keyword(s):  
Regression Models ◽  
Flat Surface ◽  
Average Distance ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Target Area ◽  
Depth Images ◽  
White Cardboard ◽  
Set Up

The use of the RGB-D camera has been applied in several fields of science. That popularization is due to the emergence of technologies such as the Intel® RealSense™ D400 series. However, despite the actual demand from some potential users, few studies concern the characterization of these sensors for object measurements. Our study sought to estimate models dealing with calculating the area and length between targets or points within RGB and depth images.  An experiment was set up with white cardboard fixed on a flat surface with colored pins. We measured the distance between the camera and cardboard by calculating the average distance from the pixels belonging to the target area. The Information Criterion AIC and BIC associated with R2 were performed to select the best models. Polynomial and power regression models reached the highest coefficient of determination and smallest values of AIC and BIC.

scholarly journals 101 Evaluation of Growth Curve Functions for predicted weight in small holder crossbred dairy cattle in Tanzania

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 79-80
Author(s):  
Chinyere Ekine ◽  
Raphael Mrode ◽  
Edwin Oyieng ◽  
Daniel Komwihangilo ◽  
Gilbert Msuta ◽  
...  
Keyword(s):  
Growth Curve ◽  
Model Comparison ◽  
Predictive Ability ◽  
Nonlinear Least Squares ◽  
Information Criterion ◽  
Dairy Farms ◽  
Exponential Model ◽  
Males And Females ◽  
Small Holder ◽  
Two Parameter

Abstract Modelling the growth curve of animals provides information on growth characteristics and is important for optimizing management in different livestock systems. This study evaluated the growth curves of crossbred calves from birth to 30 months of age in small holder dairy farms in Tanzania using a two parameter (exponential), four different three parameters (Logistic, von Bertalanffy, Brody, Gompertz), and three polynomial functions. Predicted weights based on heart girth measurements of 623 male and 846 female calves born between 2016 and 2019 used in this study were from the African Dairy Genetic Gains (ADGG) project in selected milk sheds in Tanzania, namely Tanga, Kilimanjaro, Arusha, Iringa, Njomba and Mbeya. Each function was fitted separately to weight measurement of males and females adjusted for the effect of ward and season of birth using the nonlinear least squares (nls) functions in R statistical software. The Akaike’s information criterion (AIC) and Bayesian information criterion (BIC) were used for model comparison. Based on these criteria, all three polynomial and four parameter functions performed better and did not differ enough from each other in both males and females compared to the two-parameter exponential model. Predicted weight varied among the models and differed between males and females. The highest estimated weight was observed in the Brody model for both males (278.09 kg) and females (264.10 kg). Lowest estimated weight was observed in the exponential model. Estimated growth rate varied among models. For males, it ranged from 0.04 kg-0.08 kg and for females, from 0.05 kg-0.09 kg in the Brody model and logistic model respectively. Predictive ability across all fitted curves was low, ranging from 25% to approximately 29%. This could be due to the huge range of breed compositions in the evaluated crossbred calves which characterizes small holder dairy farms in this system and different levels of farm management.

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