scholarly journals Nonlinear Models for Plant Height of Rye Cultivars at Sowing Times

2018 ◽  
Vol 10 (12) ◽  
pp. 157 ◽  
Author(s):  
Jéssica Andiara Kleinpaul ◽  
Alberto Cargnelutti Filho ◽  
Daniela Lixinski Silveira ◽  
Ismael Mario Marcio Neu ◽  
Cirineu Tolfo Bandeira ◽  
...  
Keyword(s):  
Plant Height ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Maximum Acceleration ◽  
Inflection Points ◽  
Thermal Sum ◽  
Average Plant ◽  
The One

Adjusting nonlinear Gompertz and Logistic models will help in the understanding of the growth pattern of the rye crop and also in the height response of the plant, when planted in different environmental conditions. The the aims of this study were to adjust the nonlinear Gompertz and Logistic models for plant height and indicate the one that best describes growth of two rye cultivars in five sowing times. Ten uniformity trials were conducted with the rye crop in the 2016 harvest. In each trial, ten randomly selected plants were evaluated from the first expanded leaf weekly. In each plant height was measured. The adjustment of the Gompertz and Logistic models as a function of the accumulated thermal sum was performed with the average plant height at each evaluation. The parameters a, b, and c were estimated for each model. The confidence interval for each parameter and the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration were calculated. The quality of fit of the models was verified by the coefficient of determination, Akaike's information criterion and residual standard deviation. Intrinsic non-linearity and non-linearity of the parameter effect were quantified. Both models describe satisfactorily the plant height. The model that best describes the growth of rye cultivars is Logistic.

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 Productive traits of rye cultivars grown under different sowing seasons

2019 ◽  
Vol 23 (12) ◽  
pp. 937-944
Author(s):  
Jéssica A. Kleinpaul ◽  
Alberto Cargnelutti Filho ◽  
Fernanda Carini ◽  
Rafael V. Pezzini ◽  
Gabriela G. Chaves ◽  
...  
Keyword(s):  
Aerial Part ◽  
Dry Matter ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Information Criterion ◽  
Thermal Time ◽  
Coefficient Of Determination ◽  
Maximum Acceleration ◽  
Intrinsic Nonlinearity ◽  
Productive Traits

ABSTRACT This study aimed to adjust the Gompertz and Logistic nonlinear models for the fresh and dry matter of aerial part and indicate the model that best describes the growth of two rye cultivars in five sowing seasons, as well as to characterize the growth of the cultivars regarding the fresh and dry matter of aerial part. Ten uniformity trials were conducted with the rye crop in 2016. A weekly sampling and evaluation of 10 plants per trial was performed from the time the plants presented one expanded leaf. For each plant, the fresh and dry matter of aerial part were weighed. The Gompertz and Logistic models were adjusted to the accumulated thermal time based on the measures of each trait in each assessment. Also the parameters a, b, and c for each model were estimated and calculated the interval of confidence for each parameter, as well as the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration. The quality of the model adjustments was verified using the coefficient of determination, Akaike information criterion, and residual standard deviation. The intrinsic nonlinearity and nonlinearity of the parameter effect was quantified. Both models satisfactorily describe the behavior of the fresh and dry matter of aerial part. The Logistic model best describes the growth of rye cultivars. The growth of the cultivars BRS Progresso and Temprano is distinct between sowing seasons. Cultivar BRS Progresso requires a lower thermal time until reaching 50% of its growth when compared to the Temprano cultivar.

scholarly journals The use of the nonlinear models in the growth of pears of ‘Shinseiki’ cultivar

2017 ◽  
Vol 48 (1) ◽  
Author(s):  
Thais Destefani Ribeiro ◽  
Taciana Villela Savian ◽  
Tales Jesus Fernandes ◽  
Joel Augusto Muniz
Keyword(s):  
Logistic Model ◽  
Least Squares Method ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Information Criterion ◽  
Fruit Weight ◽  
Coefficient Of Determination ◽  
Pear Fruit ◽  
Asian Pear ◽  
Residual Correlations

ABSTRACT: The goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat.

scholarly journals Proposals of non-linear models to adjust in vitro gas production at different incubation times in cassava genotypes

2021 ◽  
Vol 43 ◽  
pp. e22
Author(s):  
André Luiz Pinto dos Santos ◽  
Frank Sinatra Gomes da Silva ◽  
Guilherme Rocha Moreira ◽  
Cícero Carlos Ramos de Brito ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  
Keyword(s):  
Linear Models ◽  
Least Squares Method ◽  
Logistic Models ◽  
Information Criterion ◽  
Gas Production ◽  
Coefficient Of Determination ◽  
Absolute Deviation ◽  
In Vitro Gas Production ◽  
The One

The present study aimed to propose new two-compartment models from the combination of the Gompertz, Logistic and Von Bertalanffy models and to identify between Gompertz and Logistic models, in their uni and two-compartiment versions, the one that presents the highest quality of fit to cumulative gas production curves of five cassava genotypes: Brasília, Engana Ladrão, Dourada, Gema de Ovo e Amansa Burro. The gas production readings were 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 hours after the start of the in vitro fermentation process. The estimation of the parameters for the models was made by the least squares method through the Gauss-Newton iterative process. The selection of the best model to describe the gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion and Bayesian information criterion. Among the adjusted models, the proposed models were the best to describe the accumulation of gases over time according to the methodology and conditions under which this study was developed.

scholarly journals Mathematical models to describe the growth curves of white-egg layers

2018 ◽  
Vol 39 (3) ◽  
pp. 1327
Author(s):  
Cleber Franklin Santos de Oliveira ◽  
João Marcos Novais Tavares ◽  
Gerusa Da Silva Salles Corrêa ◽  
Bruno Serpa Vieira ◽  
Silvana Alves Pedrozo Vitalino Barbosa ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Mean Squared Error ◽  
Computer Software ◽  
Logistic Models ◽  
Growth Curves ◽  
Gompertz Model ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Population Densities

The aim of this study was to compare mathematical models describing growth curves of white-egg layers at different population densities. To fit the models, 4,000 growing white-egg layers were utilized. The experimental design was completely randomized, with population densities of 71, 68, 65, 62, and 59 birds per cage in the starter phase and 19, 17, 15, 13, and 11 birds per cage in the grower phase, with 10 replicates each. Birds were weighed weekly to determine the average body weight and the weight gain. Gompertz and Logistic models were utilized to estimate their growth. The data analysis was carried out using the PROC NLMIXED procedure of the SAS® statistical computer software to estimate the parameters of the equation because mixed models were employed. The mean squared error, the coefficient of determination, and Akaike’s information criterion were used to evaluate the quality of fit of the models. The studied models converged for the description of the growth of the birds at the different densities studied, showing that they were appropriate for estimating the growth of white-egg layers housed at different population densities. The Gompertz model showed a better fit than the Logistic model.

scholarly journals Allometric models to estimate tree height in northern Amazonian ecotone forests

2019 ◽  
Vol 49 (2) ◽  
pp. 81-90 ◽  
Author(s):  
Reinaldo Imbrozio BARBOSA ◽  
Perla Natalia RAMÍREZ-NARVÁEZ ◽  
Philip Martin FEARNSIDE ◽  
Carlos Darwin Angulo VILLACORTA ◽  
Lidiany Camila da Silva CARVALHO
Keyword(s):  
Amazon Basin ◽  
Nonlinear Models ◽  
Tree Height ◽  
Information Criterion ◽  
Specific Model ◽  
Stem Diameter ◽  
Coefficient Of Determination ◽  
Allometric Models ◽  
Peripheral Areas ◽  
Total Tree

ABSTRACT Allometric models defining the relationship between stem diameter and total tree height in the Amazon basin are important because they refine the estimates of tree carbon stocks and flow in the region. This study tests different allometric models to estimate the total tree height from the stem diameter in an ecotone zone between ombrophilous and seasonal forests in the Brazilian state of Roraima, in northern Amazonia. Stem diameter and total height were measured directly in 65 recently fallen trees (live or dead). Linear and nonlinear regressions were tested to represent the D:H relation in this specific ecotone zone. Criteria for model selection were the standard error of the estimate (Syx) and the adjusted coefficient of determination (R²adj), complemented by the Akaike Information Criterion (AIC). Analysis of residuals of the most parsimonious nonlinear models showed a tendency to overestimate the total tree height for trees in the 20-40 cm diameter range. Application of our best fitted model (Michaelis-Menten) indicated that previously published general equations for the tropics that use diameter as the independent variable can either overestimate tree height in the study area by 10-29% (Weibull models) or underestimate it by 8% (climate-based models). We concluded that our site-specific model can be used in the ecotone forests studied in Roraima because it realistically reflects the local biometric relationships between stem diameter and total tree height. Studies need to be expanded in peripheral areas of northern Amazonia in order to reduce uncertainties in biomass and carbon estimates that use the tree height as a variable in general models.

scholarly journals Growth models for morphological traits of sunn hemp

2017 ◽  
Vol 38 (5) ◽  
pp. 2933
Author(s):  
Cláudia Marques de Bem ◽  
Alberto Cargnelutti Filho ◽  
Giovani Facco ◽  
Denison Esequiel Schabarum ◽  
Daniela Lixinski Silveira ◽  
...  
Keyword(s):  
Morphological Traits ◽  
Logistic Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Mean Absolute Deviation ◽  
Absolute Deviation ◽  
Sunn Hemp ◽  
Number Of Leaves ◽  
Second Period

The objective of the present study was to fit Gompertz and Logistic nonlinear to descriptions of morphological traits of sunn hemp. Two uniformity trials were conducted and the crops received identical treatment in all experimental area. Sunn hemp seeds were sown in rows 0.5 m apart with a plant density of 20 plants per row meter in a usable area of 52 m × 50 m. The following morphological traits were evaluated: plant height (PH), number of leaves (NL), stem diameter (SD), and root length (RL). These traits were assessed daily during two sowing periods—seeds were sown on October 22, 2014 (first period) and December 3, 2014 (second period). Four plants were randomly collected daily, beginning 7 days after first period and 13 days after for second period, totaling 94 and 76 evaluation days, respectively. For Gompertz models the equation was used y=a*e^((?-e?^((b-c*xi))and Logistic models the equation was used yi= a/(1+e^((-b-c*xi)). The inflection points of the Gompertz and Logistic models were calculated and the goodness of fit was quantified using the adjusted coefficient of determination, Akaike information criterion, standard deviation of residuals, mean absolute deviation, mean absolute percentage error, and mean prediction error. Differences were observed between the Gompertz and Logistic models and between the experimental periods in the parameter estimate for all morphological traits measured. Satisfactory growth curve fittings were achieved for plant height, number of leaves, and stem diameter in both models using the evaluation criteria: coefficient of determination (R²), Akaike information criterion (AIC), standard deviation of residuals (SDR), mean absolute deviation (MAD), mean absolute percentage error (MAPE), and mean prediction error (MPE).

scholarly journals Nonlinear models for describing lettuce growth in autumn-winter

2020 ◽  
Vol 50 (7) ◽  
Author(s):  
Fernanda Carini ◽  
Alberto Cargnelutti Filho ◽  
Rafael Vieira Pezzini ◽  
Jéssica Maronez de Souza ◽  
Gabriela Görgen Chaves ◽  
...  
Keyword(s):  
Critical Points ◽  
Logistic Model ◽  
Dry Matter ◽  
Nonlinear Models ◽  
Logistic Models ◽  
Intrinsic Curvature ◽  
Dependent Variables ◽  
Thermal Sum ◽  
Lettuce Growth ◽  
Curvature Measures

ABSTRACT: The objectives of this study were to fit the Gompertz and Logistic models for the fresh and dry matter of leaves and the fresh and dry matter of shoots of three lettuce cultivars and indicate the best model to describe their growth in autumn-winter. The lettuce cultivars Gloriosa, Pira Verde, and Stella were evaluated in the autumn-winter of 2016 and 2017, in soilless in a protected environment. After transplantation, the fresh and dry matter of leaves and shoots were weighed every seven days. These dependent variables were fit using the accumulated thermal sum. The parameters of the Gompertz and Logistic models were estimated, the assumptions of the models were verified, the indicators of fit quality and critical points were calculated and the parametric and intrinsic curvature measures quantified. The Logistic and Gompertz models presented a satisfactory adjustment for the fresh and dry matter of leaves and the fresh and dry matter of shoots, for the lettuce cultivars Gloriosa, Pira Verde and Stella, in autumn-winter. The Logistic model best describes the growth of the lettuce cultivars.

scholarly journals Comparative study of some non-linear models for predicting the yield of Gmelina arborea plantation

2014 ◽  
Vol 6 (2) ◽  
pp. 738-743
Author(s):  
F. O. Oboite ◽  
V. D. Ade-Oni
Keyword(s):  
Linear Models ◽  
Logistic Models ◽  
Basal Area ◽  
Weibull Model ◽  
Volume Estimation ◽  
Coefficient Of Determination ◽  
Gmelina Arborea ◽  
Non Linear ◽  
The One ◽  
Log Normal

Yield models are important for effective forest management and as such were developed for the University of Benin Gmelina arborea plantation, Nigeria. The objectives of the study were to develop, evaluate and compare predictions from some non-linear models for timber volume estimation. A total of nine non-linear models comprising of three models each for weibull, logistic and log-normal models were developed using the three independent variables combinations (Basal area and merchantable height, diameter at base and merchantable height, diameter at middle and merchantable height). The assessment criteria (correlation coefficient (R), coefficient of determination (R2), standard error of estimate (SE)) with the validation results (using percentage bias and probability plots of residuals) showed that all categories of weibull and logistic models generated in this study discovered to be very adequate for tree volume estimation. The highest R2 (93.80), lowest SE (0.25) and lowest bias% (1.29) in the study were achieved from Weibull model 1a. The log-normal models were the least adequate for tree volume estimation with the highest bias%. The one way analysis of variance revealed that there were no significant differences in the performance of the non-linear models when varying predictor variables were used. The weibull, logistic models were therefore recommended for further use in this ecosystem and in any other forest ecosystem with similar site condition.

scholarly journals Spatiotemporal Analyses of Tomato Brown Rugose Fruit Virus in Commercial Tomato Greenhouses

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1268
Author(s):  
Luis Felipe González-Concha ◽  
Joaquín Guillermo Ramírez-Gil ◽  
Raymundo Saúl García-Estrada ◽  
Ángel Rebollar-Alviter ◽  
Juan Manuel Tovar-Pedraza
Keyword(s):  
Temporal Dynamics ◽  
Production Systems ◽  
Negative Impact ◽  
Stationary Phases ◽  
Logistic Models ◽  
Information Criterion ◽  
Temporal Analysis ◽  
Coefficient Of Determination ◽  
Tomato Production ◽  
Spatiotemporal Analyses

Tomato brown rugose fruit virus (ToBRFV) is an emerging pathogen affecting tomato-production systems in several countries, including Mexico. This situation involves challenges due to the negative impact on yield and the lack of disease-management measures. This work analyzes the spatiotemporal distribution of ToBRFV in commercial tomato greenhouses. The presence or absence of diseased plants was evaluated weekly, assigning a location in space (x, y). Temporal analysis consisted of fitting the incidence to the monomolecular, logistic, log-logistic, Gompertz, exponential, Weibull, and Richard models, evaluated using the Akaike information criterion, significance, correlation, coefficient of determination, and root mean square error. Spatial analysis consisted of determining spatial aggregation using the Moran, Fisher, and Lloyd indices. In addition, spatial distribution was assessed by sequence observations, point patterns using the inverse distance index, and analysis by SADIE distance indicators. Results indicated that the logistic models (log-logistic and logistic) best described the temporal progress of ToBRFV. This disease also had slightly aggregated patterns in the initial phase, highly aggregated in the exponential phase, and uniform in the deceleration and stationary phases. This study demonstrates that the spatial and temporal dynamics of ToBRFV have important implications for the monitoring, diagnosis, management, and risk prediction of this disease.

Sign in / Sign up

Export Citation Format

Share Document