Evaluation of susceptibility of Amaranthus species to the herbicide trifloxysulfuron-sodium using nonlinear models
Edilene Cristina Pedroso Azarias,
Natiele de Almeida Gonzaga,
Rafaela de Carvalho Salvador
et al.
Abstract:Various elements have the potential to negatively impact crops in the agricultural sector, such as the presence of weeds that compete for essential resources, hindering growth and production and resulting in financial losses. There are several methods employed for weed control, among which herbicides stand out for requiring less labor and lower costs compared to others, especially in large-scale cultivation. The objective of this study was to use nonlinear models to assess the dose-response curve of the herbic… Show more
Objective: To use the non-linear regression models (Lewis, Overhults, Page, Midilli, and Three-parameter simple Exponential) to describe the drying kinetics of bean seeds as a function of time (hours).
Theoretical Structure: The research project shows the steps taken to conduct and analyze data.
Method: The model parameters were estimated using the least squares method and the Gauss-Newton convergence algorithm. The assumptions of normality, homoscedasticity, and independence of residuals were tested using the Shapiro-Wilk, Breuch-Pagan, and Durbin-Watson tests, respectively. If the assumption of independence of residuals was violated, this dependence was modeled with an autoregressive error structure AR(1). The adjusted coefficient of determination (Raj2), Akaike information criterion (AIC), residual standard deviation (RSD), and Bates and Watts curvature measure were used to assess the goodness of fit of the models.
Results and conclusion: The results showed that the Midilli model presented a good quality fit to the data, and is the most suitable for describing the drying kinetics of bean seeds, with the drying rate averaging 0.4681 g of water/hour.
Research Implications: The research contributes to the literature with practical information about the drying process.
Originality/value: Highlights the importance of adjusting non-linear regression models to the drying kinetics of biological products. These models are used to represent the decrease in the amount of water in a given food over time.
Objective: To use the non-linear regression models (Lewis, Overhults, Page, Midilli, and Three-parameter simple Exponential) to describe the drying kinetics of bean seeds as a function of time (hours).
Theoretical Structure: The research project shows the steps taken to conduct and analyze data.
Method: The model parameters were estimated using the least squares method and the Gauss-Newton convergence algorithm. The assumptions of normality, homoscedasticity, and independence of residuals were tested using the Shapiro-Wilk, Breuch-Pagan, and Durbin-Watson tests, respectively. If the assumption of independence of residuals was violated, this dependence was modeled with an autoregressive error structure AR(1). The adjusted coefficient of determination (Raj2), Akaike information criterion (AIC), residual standard deviation (RSD), and Bates and Watts curvature measure were used to assess the goodness of fit of the models.
Results and conclusion: The results showed that the Midilli model presented a good quality fit to the data, and is the most suitable for describing the drying kinetics of bean seeds, with the drying rate averaging 0.4681 g of water/hour.
Research Implications: The research contributes to the literature with practical information about the drying process.
Originality/value: Highlights the importance of adjusting non-linear regression models to the drying kinetics of biological products. These models are used to represent the decrease in the amount of water in a given food over time.
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