Experimental and modeling of potassium diclofenac uptake on activated carbon.

The presence of pharmaceuticals in wastewater resulting from human activities has driven researchers to explore effective treatment methods such as adsorption using activated carbon (AC). While AC shows promise as an adsorbent, further studies are essential to comprehend its entire interaction with pharmaceuticals. This article investigates the adsorption of potassium diclofenac (PD) onto AC using experimental and modeling approaches. Batch adsorption studies coupled with Fourier transform infrared spectroscopy (FTIR) were employed to clarify the adsorption mechanism of PD on AC. Various kinetic and isotherm adsorption models were applied to analyze the adsorbent-adsorbate interaction. The kinetics were best described by Avrami's fractional order (AFO) nonlinear model. Also, the intraparticle diffusion (IP) model reveals a three-stage adsorption process. The experimental equilibrium data fitted well with the three-parameter nonlinear Liu model, indicating a maximum adsorption capacity (Qmax) of 88.45 mg g-1 and suggesting monolayer or multilayer adsorption. Thermodynamic analysis showed favorable adsorption (ΔG° < 0), with an enthalpy change (ΔH° = -30.85 kJ mol-1) characteristic of physisorption involving hydrogen bonds and π-π interactions. The adsorption mechanism was attributed to forming a double layer (adsorbate-adsorbent and adsorbate-adsorbate).

In Vitro Digestibility and Models of Cumulative Gas Production of Forage-Free Diet.

Our objectives were to evaluate the use of cottonseed cake in replacing corn silage in a diet without forage and to identify the model with higher precision and accuracy of adjustment of parameters of ruminal degradation kinetics. A diet containing corn silage and another with cottonseed cake as a fiber source were formulated. Gompertz, Dual-pool Logistic, Brody, and Ørskov models were evaluated for goodness of fit to gas production. There were significant differences in dry matter (DM), organic matter (OM), and neutral detergent fiber (NDF) in the in vitro digestibility for diets and fiber sources. The estimated values of the Gompertz (6.77), Brody (6.72), and Ørskov (6.73) models were similar to the observed mean of gas production in the corn silage diet (6.73 mL/100 mg DM). Similarly, the estimated values of the Brody (5.87) and Ørskov (5.89) models were similar to the observed mean of gas production in the cottonseed cake diet (5.87 mL/100 mg DM). The roughage-free diet containing cottonseed cake as a fiber source stimulated higher gas production. Brody and Ørskov models presented higher precision and accuracy in the fitting of kinetics of degradation independent of the fiber source in the diet.

Strategies for the identification of precocity in zebu beef cattle based on mixed nonlinear models and multivariate approach.

The use of mixed nonlinear models reduces the residual variance by including random effects, thereby improving the estimates in growth curves. Therefore, we tested distinct mixed nonlinear models (Richards, Brody, Gompertz, Logistic, and Von Bertalanffy) to model the growth curves of Zebu cattle herds raised on pasture in Brazil. In addition, we evaluated the diversity among breeds using hierarchical cluster multivariate analysis (full linkage) based on asymptotic weight (A), maturity rate (K), absolute growth rate (AGR), and absolute maturity rate (AMR) adjusted to 205, 365, 550, and 730 days of age. Body weight data from 311,834 males and females of Guzerat, Nellore, Tabapuã, and Polled Nellore breeds provided by the Brazilian Association of Zebu Breeders were used. The Brody model considering breed-sex fixed and animal random effects was the most suitable to describe the growth in the four breeds. The Guzerat and Tabapuã males showed increased precocity (higher K values) when compared to polled Nellore and Nellore males, which were characterized by higher A and AMR values. Females were more precocious than males (high K and low A values), particularly within Tabapuã and Guzerat breeds, respectively. Regardless of sex, the highest AGR values were observed from weaning up to 2 years of age in Tabapuã and Guzerat breeds. The cluster analyses revealed two groups: (1) Polled Nellore and Nellore males with high A, AGR_205, AGR_365, AGR_550, and AGR_730 values, represented by large adult animals, and (2) males and females of Guzerat and Tabapuã, characterized as animals of increased precocity. A subgroup encompassing males of Guzerat and Tabapuã was also observed, with intermediate values ​​for all parameters. This information is useful to help breeders and producers in strategies for feeding management and defining the most precocious beef cattle breed to increase the economic gains in pasture-based raising systems.

Unraveling the effect of temperature and humidity on the life cycle of Diatraea saccharalis (Lepidoptera: Crambidae) and the impact on pest outbreaks.

Temperature and humidity are considered the main abiotic factors that affect both the development and survival of ectothermic organisms. In this study, we estimated the development time as well as the thermal requirements of the sugarcane borer, Diatraea saccharalis (Fabricius, 1794; Lepidoptera: Crambidae), a key insect pest of sugarcane and discussed the influence of temperature and relative humidity and its infestation intensity in a scenario of climate change. The models Brière-1 and Ikemoto-Takai provided the best fit to the data of development rate versus temperature. The average life cycle (from egg to adult) ranged from 39.21 ± 4.84 at 32 °C to 137.10 ± 7.47 at 18 °C days. The thermal constant and average base temperature were 547.69 degree-days and 13.64 °C, respectively. The number of larval instars varied from 4 to 7 depending on the temperature, being higher at lower temperatures. The thermal range comprised the interval from 16.7 °C to 33.9 °C and the optimum temperature was estimated as 27.4 °C. Locations with elevated temperature (≥25 °C) and high relative humidity (≥70%) presented larger populations of D. saccharalis. Our findings show that the infestation pressure of this species is highly influenced by both temperature and humidity, and the studied models allow to forecast pest outbreaks. In the context of climate change, information about the thermal range and the optimum temperature contributes to predicting the spatial-temporal distribution of D. saccharalis and, consequently, aids decision making in pest management.

Modeling hormesis using multivariate nonlinear regression in plant biology: A comprehensive approach to understanding dose-response relationships.

For over a century, ecotoxicological studies have reported the occurrence of hormesis as a significant phenomenon in many areas of science. In plant biology, hormesis research focuses on measuring morphological, physiological, biochemical, and productivity changes in plants exposed to low doses of herbicides. These studies involve multiple features that are often correlated. However, the multivariate aspect and interdependencies among components of a plant system are not considered in the adopted modeling framework. Therefore, a multivariate nonlinear modeling approach for hormesis is proposed, where information regarding correlations among response variables is taken into account through a variance-covariance matrix obtained from univariate residuals. The proposed methodology is evaluated through a Monte Carlo simulation study and an application to experimental data from safflower (Carthamus tinctorius L.) cultivation. In the simulation study, the multivariate model outperformed the univariate models, exhibiting higher precision, lower bias, and greater accuracy in parameter estimation. These results were also confirmed in the analysis of the experimental data. Using the delta method, mean doses of interest can be derived along with their associated standard errors. This is the first study to address hormesis in a multivariate context, allowing for a better understanding of the biphasic dose-response relationships by considering the interrelationships among various measured characteristics in the plant system, leading to more precise parameter estimates.

The Growth Pattern of Brazilian Canela-Preta Chickens with Different Plumages Reared in Two Rearing Systems

Growth pattern is essential for economically efficient poultry production. In this study, we aimed to describe the growth curve of chickens of the Canela-Preta breed reared in two different rearing systems, considering their different plumage colors. Initially, 204 one-day-old male and female chicks were randomly distributed in confinement and semi-confinement (102 animals in each system) without separation by gender. The animals were individually identified by wing and foot plastic brands and were weighted every seven days. The body weight and age records were used to estimate the growth curves of the following factors using the Richards model: plumage color, gender, and rearing system. The likelihood ratio test was used to verify the equality of parameters and identify nonlinear models to compare the growth patterns of the evaluated groups. The growth pattern of Canela-Preta chickens changed as a function of gender, plumage color, and rearing system. Females with black plumage, black and gold hens, and males with black and white plumage showed greater sensitivity to changes in rearing systems. Within-breed selection strategies for specific colors can improve the use of growth pattern differences, improving production efficiency. Semi-confinement is suitable for rearing Canela-Preta chickens with any plumage color, as these animals meet the free-range poultry niche market requirements.(AU)

Growth curves of broilers fed different nutritional relationships using the Gompertz model

The study aimed to evaluate performance and growth curves of broilers fed different nutritional relations. A total of 1,440 Cobb-500 male day-old chicks were assigned to eight treatments in a 2 x 2 x 2 factorial arrangement with six replicates of 30 birds each. The main factors were nutritional density (control and high), lysine source (HCl and sulfate), and calcium pidolate (presence and absence). Analyses were made for body weight gain (BWG), and feed conversion rate (FCR) at 21, and 42 days of age. The growth curves were adjusted by weighing a bird per plot every three days. Data for BWG were tested by ANOVA to evaluatethe effects of treatments and their interactions at 5% significance, and the Gompertz model was adjusted by NLS. Birds fed a high nutritional density had higher BWG and lower FCR. Calcium pidolate and different sources of lysine did not influence the FCR of broilers, however a triple interaction was evidenced for BWG at 1 to 42 days of age. The day with maximum gain adjusted by Gompertz of all treatments was at the 32ndday of age and the maximum weight (A) was around 5.85 kg.(AU)

Productividad y curvas de crecimiento usando modelos no lineales en un cruce de ovino de pelo colombiano x pelibuey

Los ovinos criollos de pelo (OCP) desarrollaron ventajas adaptativas al climática tropical, que le permiten tener resistencia a enfermedades, alta fertilidad y prolificidad; sin embargo, se reportan pocas investigaciones sobre la productividad de los OCP en sistemas asociados al cultivo de la caña, lo que hace necesario realizar investigaciones, que permitan fomentar sus atributos. El objetivo del presente trabajo fue analizar la productividad y el desarrollo corporal de un cruce de OCP, mediante parámetros productivos y curvas de crecimiento. Se utilizaron 180 animales de partos simples y múltiples; se registró el peso al nacimiento (PN), al destete (PD), a los 210 días (PAJ210) y las ganancias diarias predestete (GDPRE) y posdestete (GDPOS). Los datos, se analizaron mediante estadística descriptiva, con un GLM, con los efectos sexo (S), tipo de nacimiento (TN), número de partos (NP) y época de nacimiento (EPONAC). Se emplearon los modelos no lineales Gompertz, Logístico, Brody, Richards y Von Bertalanffy, en 1.455 registros de pesos, a diferentes edades, para realizar las curvas de crecimiento. Los análisis, se efectuaron con el paquete estadístico SAS. Se consideraron los coeficientes R2, AIC y BIC, obtenidos por el método de Gauss-Newton, para seleccionar el modelo de mejor ajuste. Los machos presentaron mayores promedios en las variables PN, PD, PAJ210 y GDPOS. El TN afectó todas las variables; el PN y las GDPOS fueron afectadas por el NP y, la EPONAC, afectó PN, las GDPRE, el PAJ210 y las GDPOS. El modelo de mejor ajuste para las curvas de crecimiento fue la de Richards.

The creole hair sheep (CHS) developed adaptive advantages to the tropical climate, which allow them to have resistance to diseases, high fertility and prolificacy. Currently, there is little research on the productivity of CHS in systems associated with the cultivation of sugarcane, which makes it necessary to carry out research to promote its attributes. The purpose of this research was to analyze the productivity and body development of a crossing of CHS, using production parameters and growth curves.180 animals of single and multiple births were used; the follow weight was recorded: at birth (WB), at weaning (WW); at 210 days (W210), and furthermore, daily gains of pre-weaning (WDPRE) and post-weaning (WPPOS) were recorded. The data were analyzed using descriptive statistics with a GLM with the effects sex (S), type of birth (TB), number of births (NB) and period of birth (PB). The non-linear models Gompertz, Logistic, Brody, Richards and Von Bertalanffy were used in 1455 records of weights at different ages to perform growth curves. All analyzes were performed with the SAS statistical package. The R2, AIC and BIC coefficients obtained by the Gauss-Newton method were considered to select the best fit model. The males presented higher averages in the variables WB, WW, W210) and WPOS. The TB affected all the variables; The WB and the WPPOS were affected by the NB and the PB affected the WB, the WDPRE, the W210 and the WPPOS. The best fit model for the growth curves was of Richards.

Mexican Creole chickens: effect of data collection periods on goodness-of-fit and parameter precision of growth models.

The objective of this study was to estimate the good-of-fitness and precision of parameters of the Gompertz-Laird, Logistic, Richards, and Von Bertalanffy growth models, using different data collection periods (DCP). Two hundred and sixty-two Mexican Creole chicks (116 females and 146 males), were individually weighed to form the following sets of data for each sex: DCP1 (weights recorded weekly from hatching to 63 d, and every 2 wk, from 63 to 133 d of age), DCP2 (weights recorded weekly from hatching to 133 d of age), DCP3 (weights recorded every third day, from hatching to 63 d, and every 14 d, from 63 to 133 d of age), and DCP4 (weights recorded every third day, from hatching to 63 d, and weekly, from 63 to 133 d of age). Data were analyzed using the NLIN procedure of SAS (Marquardt algorithm). For all growth models, the width of confidence interval (CI) of each parameter, was estimated (α = 0.05). The adjusted coefficient of determination (AR2), as well as the Akaike (AIC) and Bayesian information criteria (BIC) were used to select the best model. The higher the AR2, and the lower the width of CI, as well as the AIC and BIC values, the better the model. The Gompertz-Laird model, more frequently showed the highest AR2, and the lowest AIC and BIC values compared to the other models. Moreover, for all models, both sexes and all parameters, most confidence interval widths (all with the Gompertz-Laird model) were the lowest with DCP3 when compared to the other sets of data. In conclusion, the Gompertz-Laird model was the best provided that the chickens are weighed every third day from hatching until 63 d of age, and every 2 wk thereafter.

Estimation of lactation curves of Gyr cattle and some associated production parameters in the Colombian low tropic

Background: The Gyr breed is widely used in Colombian low tropic dairy production systems. During the last 10 years, the Asociación Colombiana de Criadores de Ganado Cebú† ASOCEBU, has been leading a dairy milk control program which led to the creation of a dataset that permits to carry out the first analysis of milk yield in Gyr cattle in the country using records from several herds. Objectives: To study milk production dynamics of Gyr cattle in the Colombian low tropic through the estimation of lactation curves and four derived production parameters: total milk yield between 5 and 305 days (TMY305), peak milk yield (PMY), days at peak (DP) and persistency (P). Methods: 13,798 daily milk yield records from 1,510 cows performing in 103 herds were used; the total number of lactations was 2,480. Four models were considered: Wood, Wiltmink, Papajcsik & Bordero, and a second-degree polynomial. Mean square error, mean absolute error, mean square error of prediction, Akaike and Bayesian information criteria were used to select the model better describing each lactation using the majority rule, that is, the model selected by most criteria was the chosen one. The shape of each fitted lactation curve was checked using basic results from calculus which permitted the classification of the estimated curves into two groups: typical and atypical; only typical functions were used to compute the four aforementioned production parameters. Results: The second-order polynomial was the model most frequently selected, while the Papajcsik & Bordero model had the lowest frequency. Average TMY305, PMY, DP and P were 3,489.86 kg, 17.28 kg, 57.17 days, and 0.83, respectively, with coefficients of variation: 0.27, 0.21, 0.41, and 0.16. Conclusions: This study permitted to identify individuals with outstanding phenotypic performance. To the best of our knowledge, this is the first study of this kind involving thousands of lactations from Gyr cows performing in several regions of Colombian low tropic.

Antecedentes: La raza Gyr es ampliamente utilizada en las lecherías de trópico bajo en Colombia. Durante los últimos 10 años, la Asociación Colombiana de Criadores de Ganado Cebú ASOCEBU, ha liderado un programa de control lechero que generó una base de datos que permite llevar a cabo el primer análisis de producción de leche de la raza Gyr en el país, considerando individuos de varias fincas. Objetivos: Caracterizar la dinámica de producción de leche de ganado Gyr en el trópico bajo colombiano mediante la estimación de curvas de lactancia y cuatro parámetros de producción derivados: producción total entre 5 y 305 días (TMY305), pico de lactancia (PMY), días al pico (DP) y persistencia (P) Métodos: Se utilizaron 13.798 registros de producción diaria de leche de 1.510 vacas provenientes de 103 fincas, el total de lactancias fue 2.480. Se consideraron cuatro modelos: Wood, Wiltmink, Papajcsik & Bordero, y un polinomio de segundo grado. Los criterios usados para elegir el modelo que mejor describió cada lactancia fueron: error cuadrático medio, error absoluto medio, error cuadrático medio de predicción, criterio de información de Akaike y criterio de información Bayesiano. Se utilizó el criterio de mayoría, esto es, el modelo seleccionado fue aquel elegido por más criterios. La forma de cada una de las curvas de lactancia estimadas fue chequeada utilizando resultados básicos del cálculo, esto permitió clasificar las curvas estimadas en dos grupos: típicas y atípicas; solamente las curvas típicas fueron empleadas para calcular los cuatro parámetros antes mencionados. Resultados: El polinomio de segundo grado fue el modelo que se seleccionó con mayor frecuencia, mientras que el modelo Papajcsik & Bordero tuvo la menor frecuencia. Los promedios para TMY305, PMY, DP y P fueron 3.489,86 kg, 17,28 kg, 57,17 días, y 0,83, respectivamente, con coeficientes de variación 0,27, 0,21, 0,41 y 0,16 Conclusiones: Este estudio permitió identificar individuos con desempeño fenotípico sobresaliente. De acuerdo al estado del arte, este es el primer estudio de este tipo que considera miles de lactancias de vacas Gyr provenientes de varias regiones del trópico bajo colombiano.

Antecedentes: Gir é uma raça Bos indicus amplamente utilizada em sistemas de produção leiteira no trópico baixo Colombiano. A Asociación Colombiana de Criadores de Ganado CebúASOCEBU, lidera um programa de controle de leite nos últimos 10 anos, o que permitiu à coleta de um conjunto de dados para realizar a primeira análise de produção de leite em bovinos Gir no país com informações de vários rebanhos. Objetivo: Estudar a dinâmica da produção de leite por meio da estimativa das curvas de lactação e quatro parâmetros de produção derivados: produção total de leite entre 5 e 305 dias (TMY305), produção de leite no pico de lactação (PMY), dias em produção de leite no pico de lactação (DP) e persistência (P). Métodos: Foram utilizados 13.798 registros de produção diária de leite de 1.510 vacas de 103 fazendas , totalizando 2.480 lactações. Foram considerados quatro modelos: Wood, Wiltmink, Papajcsik & Bordero e um polinômio de segundo grau. Para selecionar o modelo que melhor descreve cada lactação foram utilizados os seguintes critérios: erro quadrado médio, erro absoluto médio, e erro quadrado médio de predição. O modelo selecionado pela maioria dos parâmetros, de acordo com os critérios de informação de Akaike e Bayesiano, foi o escolhido. A forma de cada curva de lactação ajustada foi verificada utilizando os resultados básicos do cálculo, isso permitiu classificar as curvas estimadas em dois grupos: típico e atípico, e apenas funções típicas foram utilizadas para calcular os quatro parâmetros de produção acima mencionados Resultados: O polinômio de segunda ordem foi o modelo mais frequentemente selecionado, enquanto o modelo Papajcsik & Bordero apresentou a menor frequência. A média de TMY305, PMY, DP e P foram 3.489,86 kg, 17,28 kg, 57,17 d e 0,83, respectivamente, com coeficientes de variação de 0,27, 0,21, 0,41 e 0,16. Conclusões: Este estudo permitiu identificar indivíduos com excelente desempenho fenotípico. De acordo com a literatura atual, este é o primeiro estudo envolvendo milhares de lactações de vacas Gir em várias regiões do trópico baixo colombiano.

Growth predictability models in Mangalarga marchador horses / Modelos de previsibilidade de crescimento em cavalos Mangalarga marchador

This study evaluated the suitability of the Brody, logistic, and quadratic response plateau models to describe chest and cannon girth data obtained cross-sectionally in Mangalarga Marchador horses, in order to select the best model and predict the growth and maturity of males and females of this breed. Data were collected from 230 horses aged 6 to 176 months, divided by sex and age (16 age classes). The studied models were compared according to each quality evaluator by computing the adjusted coefficient of determination (R²adj) and residual standard deviation (RSD) with R statistical software. The chest girths obtained by the models ranged from 172.06 (males) to 181.50 cm (females) (Brody), 172.51 (males) to 181.89 cm (females) (logistic), and 177.67 (males) to 183.09 cm (females) (plateau). For cannon girth, the values were 18.18 (females) to 19.33 cm (males) (Brody), 18.11 (females) to 19.41 cm (males) (logistic), and 18.70 (females) to 19.40 cm (males) (plateau). The logistic model was best suited to describe the growth in chest girth of male and female Mangalarga Marchador horses. For cannon girth growth, the model best suited for males was the logistic model, and the one best suited for females was the Brody model.

RESUMO: O objetivo deste estudo foi avaliar o ajuste dos modelos Brody, Logístico e Platô de resposta quadrática aos dados de perímetros torácico e de canela em equinos Mangalarga Marchador obtidos pelo método transversal, a fim de selecionar o melhor modelo e predizer sobre o crescimento e a maturidade de machos e fêmeas desta raça. Foram utilizados dados de 230 equinos de seis a 176 meses de idade que foram divididos por sexo e em 16 classes de idade. Os modelos estudados foram comparados segundo os avaliadores de qualidade: coeficiente de determinação ajustado (R²adj) e desvio padrão residual (DPR), utilizando-se o software estatístico R. Os perímetros torácicos obtidos pelos modelos variaram de 172,06 a 181,50 cm (Brody), 172,51 a 181,89 cm (Logístico) e 183,09 a 177,67 cm (Platô) para fêmeas e machos, respectivamente. Para o perímetro de canela os valores variaram de 18,18 a 19,33 cm (Brody), 18,11 a 19,41 cm (Logístico) e 18,70 a 19,40 cm (Platô) para fêmeas e machos, respectivamente. O modelo logístico é mais indicado para expressar o crescimento em perímetro torácico de machos e fêmeas da raça Mangalarga Marchador. Já para a variável perímetro de canela, o modelo mais indicado para os machos foi o modelo Logístico e para as fêmeas o modelo de Brody.

Bayesian modeling of the coffee tree growth curve / Modelagem bayesiana da curva de crescimento do cafeeiro

When modeling growth curves, it should be considered that longitudinal data may show residual autocorrelation, and, if this characteristic is not considered, the results and inferences may be compromised. The Bayesian approach, which considers priori information about studied phenomenon has been shown to be efficient in estimating parameters. However, as it is generally not possible to obtain marginal distributions analytically, it is necessary to use some method, such as the weighted resampling method, to generate samples of these distributions and thus obtain an approximation. Among the advantages of this method, stand out the generation of independent samples and the fact that it is not necessary to evaluate convergence. In this context, the objective of this work research was: to present the Bayesian nonlinear modeling of the coffee tree height growth, irrigated and non-irrigated (NI), considering the residual autocorrelation and the nonlinear Logistic, Brody, von Bertalanffy and Richard models. Among the results, it was found that, for NI plants, the Deviance Information Criterion (DIC) and the Criterion of density Predictive Ordered (CPO), indicated that, among the evaluated models, the Logistic model is the one that best describes the height growth of the coffee tree over time. For irrigated plants, these same criteria indicated the Brody model. Thus, the growth of the non-irrigated and irrigated coffee tree followed different growth patterns, the height of the non-irrigated coffee tree showed sigmoidal growth with maximum growth rate at 726 days after planting and the irrigated coffee tree starts its development with high growth rates that gradually decrease over time.

Na modelagem de curvas de crescimento deve-se considerar que dados longitudinais podem apresentar autocorrelação residual, sendo que, se tal característica não é considerada, os resultados e inferências podem ser comprometidos. A abordagem bayesiana, que considera informações à priori sobre o fenômeno em estudo tem se mostrado eficiente na estimação de parâmetros. No entanto, como geralmente não é possível obter as distribuições marginais de forma analítica, faz-se necessário a utilização de algum método, como o método de reamostragem ponderada, para gerar amostras dessas distribuições e assim obter uma aproximação para as mesmas. Dentre as vantagens desse método, destaca-se a geração de amostras independentes e o fato de não ser necessário avaliar convergência. Diante desse contexto, o objetivo deste trabalho foi apresentar a modelagem não linear bayesiana do crescimento em altura de plantas do cafeeiro, irrigadas e não irrigadas (NI), considerando a autocorrelação residual e os modelos não lineares Logístico, Brody, von Bertalanffy e Richards. Em vista dos resultados, verificou-se que, para as plantas NI, o DIC e CPOc, indicaram que, dentre os modelos avaliados, o modelo Logístico é o que melhor descreve o crescimento em altura do cafeeiro ao longo do tempo. E, para as plantas irrigadas, esses mesmos critérios indicaram o modelo Brody. Assim, o crescimento da planta do cafeeiro não irrigado e irrigado seguiram padrões de crescimento distintos, a altura do cafeeiro não irrigado apresentou crescimento sigmoidal com taxa máxima de crescimento aos 726 dias após o plantio, já o cafeeiro irrigado inicia seu desenvolvimento com altas taxas de crescimento que vão diminuindo aos poucos com o tempo.

Influence of caprine arthritis encephalitis on milk production and quality along the lactation curve in primiparous dairy goats / Influência da artrite encefalite caprina na produção e qualidade do leite ao longo da curva de lactação em cabras leiteiras primíparas

The aim of this study was to examine the influence of caprine arthritis encephalitis (CAE) on the production of milk and its components (protein, fat and total solids) along the lactation curve of primiparous goats. The study was developed using a database from the years 2014 to 2018. Sixty-one animals were subjected to the serological test for CAE, whose result indicated that 42 were seropositive and 19 seronegative, and milk production and quality data were compiled. To adjust the curve for production of milk, fat, protein and total solids during lactation, the following nonlinear model developed by Wood (1967) was used: Y = atb e-ct, where Y represents the observations of milk, fat, protein or total solid production at time t; a is the parameter associated with the initial production; b is the parameter associated with the rate of rise in production until the peak; c is the parameter associated with the rate of decline of the lactation curve; and t is the representative time of the day in milk. The parameters were compared by the confidence interval considering 95% probability. Peak production was calculated using the following formula: a(b/c)b e-b. There was no statistical difference (p > 0.05) between seropositive and seronegative primiparous goats for initial production and the rates of rise and decline of the parameters of milk, fat, protein and total solid production. However, at their peak, these variables were 26, 27, 23 and 23% higher, respectively, in the seronegative goats than in their seropositive counter parts. In conclusion, CAE does not affect milk production or the production of fat, protein and total solids along the lactation curve, but seropositive goats produce less milk and respective components at the peak of the lactation curve than seronegative goats.(AU)

Objetivou-se avaliar a influência da artrite encefalite caprina (CAE) sobre a produção leiteira e seus constituintes (proteína, gordura e sólidos totais) ao longo da curva de lactação de cabras primíparas. O estudo foi realizado a partir do banco de dados dos anos de 2014 a 2018. Foram utilizados um total de 61 animais, todos submetidos ao teste de sorologia para CAE, sendo 42 cabras soropositivas e 19soronegativas, e os dados foram compilados de produção e qualidade do leite. Para o ajuste da curva para a produção de leite, gordura, proteína e sólidos totais ao longo da lactação foi utilizado o modelo não linear de Wood (1967): Y = atb e-ct, no qual: Y representa as observações de produção de leite, gordura, proteína ou sólidos totais no tempo t, a é o parâmetro associado à produção inicial, b é o parâmetro associado à taxa de ascensão da produção até o pico, c é o parâmetro associado à taxa declínio da curva de lactação e t é o tempo representativo do dia em lactação. Os parâmetros foram comparados pelo intervalo de confiança considerando 95% de probabilidade. A produção no pico foi calculada pela fórmula: a(b/c)b e-b. Não houve diferença estatística (p > 0,05) entre cabras primíparas soropositivas e soronegativas para a produção inicial, taxa de ascensão e taxa de declínio dos parâmetros para a produção de leite, de gordura, de proteína e de sólidos totais. Porém a produção no pico das variáveis em cabras soronegativas foi de26%, 27%, 23% e 23%, respectivamente, mais altas que em soropositivas. Conclui-se que a CAE não afeta a produção leiteira, bem como a produção de gordura, proteína e sólidos totais ao longo da curva de lactação, entretanto cabras soropositivas têm menor produção de leite e de seus componentes no pico da curva de lactação em relação às soronegativas.(AU)

Influence of caprine arthritis encephalitis on milk production and quality along the lactation curve in primiparous dairy goats / Influência da artrite encefalite caprina na produção e qualidade do leite ao longo da curva de lactação em cabras leiteiras primíparas

The aim of this study was to examine the influence of caprine arthritis encephalitis (CAE) on the production of milk and its components (protein, fat and total solids) along the lactation curve of primiparous goats. The study was developed using a database from the years 2014 to 2018. Sixty-one animals were subjected to the serological test for CAE, whose result indicated that 42 were seropositive and 19 seronegative, and milk production and quality data were compiled. To adjust the curve for production of milk, fat, protein and total solids during lactation, the following nonlinear model developed by Wood (1967) was used: Y = atb e-ct, where Y represents the observations of milk, fat, protein or total solid production at time t; a is the parameter associated with the initial production; b is the parameter associated with the rate of rise in production until the peak; c is the parameter associated with the rate of decline of the lactation curve; and t is the representative time of the day in milk. The parameters were compared by the confidence interval considering 95% probability. Peak production was calculated using the following formula: a(b/c)b e-b. There was no statistical difference (p > 0.05) between seropositive and seronegative primiparous goats for initial production and the rates of rise and decline of the parameters of milk, fat, protein and total solid production. However, at their peak, these variables were 26, 27, 23 and 23% higher, respectively, in the seronegative goats than in their seropositive counter parts. In conclusion, CAE does not affect milk production or the production of fat, protein and total solids along the lactation curve, but seropositive goats produce less milk and respective components at the peak of the lactation curve than seronegative goats.

Objetivou-se avaliar a influência da artrite encefalite caprina (CAE) sobre a produção leiteira e seus constituintes (proteína, gordura e sólidos totais) ao longo da curva de lactação de cabras primíparas. O estudo foi realizado a partir do banco de dados dos anos de 2014 a 2018. Foram utilizados um total de 61 animais, todos submetidos ao teste de sorologia para CAE, sendo 42 cabras soropositivas e 19soronegativas, e os dados foram compilados de produção e qualidade do leite. Para o ajuste da curva para a produção de leite, gordura, proteína e sólidos totais ao longo da lactação foi utilizado o modelo não linear de Wood (1967): Y = atb e-ct, no qual: Y representa as observações de produção de leite, gordura, proteína ou sólidos totais no tempo t, a é o parâmetro associado à produção inicial, b é o parâmetro associado à taxa de ascensão da produção até o pico, c é o parâmetro associado à taxa declínio da curva de lactação e t é o tempo representativo do dia em lactação. Os parâmetros foram comparados pelo intervalo de confiança considerando 95% de probabilidade. A produção no pico foi calculada pela fórmula: a(b/c)b e-b. Não houve diferença estatística (p > 0,05) entre cabras primíparas soropositivas e soronegativas para a produção inicial, taxa de ascensão e taxa de declínio dos parâmetros para a produção de leite, de gordura, de proteína e de sólidos totais. Porém a produção no pico das variáveis em cabras soronegativas foi de26%, 27%, 23% e 23%, respectivamente, mais altas que em soropositivas. Conclui-se que a CAE não afeta a produção leiteira, bem como a produção de gordura, proteína e sólidos totais ao longo da curva de lactação, entretanto cabras soropositivas têm menor produção de leite e de seus componentes no pico da curva de lactação em relação às soronegativas.

Comparison of nonlinear mathematical models for lamb growth analysis.

With the objective to determine the best mathematical model that could demonstrate the relationship between body weight and age in crossbred sheep, and to evaluate its applicability in different farms, 9985 live weight records of 837 crossbred lambs of Texel, Ile de France, Suffolk, and Hampshire Down breeds were used. Brody, von Bertalanffy, Richards, Logistic, and Gompertz models were fitted to the weight data, which were compared based on adjusted R2, Syx%, chi-square, and Kolmogorov-Smirnov tests, as well as residual analysis. After selecting the model, lambs whose weights at different ages fell within, below, or above ±20% of the values predicted by the model were classified as medium, low, or high performance, respectively. To validate the model, we used a validation dataset comprising 2898 weights of lambs from 6 different farms. Based on statistical analysis and biological characteristics (sigmoid trend of weight over time, weight at birth, and standard deviation), the model that best represented the growth of the lambs was the Richards model. The percentage of lambs classified as below, within, and above the predicted values based on the model was highly similar for the original and validation data, which indicates that this model could be used in different farms. It was concluded that the Richards model best described the live weight growth of crossbred lambs and aided in classifying the lambs as high, medium, or low performance, thereby providing a complementary tool in management decision-making.

Polymorphism in the BIEC2-808543 locus and its association with growth curve in Brasileiro de Hipismo horse breed

Our objective was to evaluate whether the single nucleotide polymorphism (SNP) BIEC2-808543, identified in some horse breeds, also occurs in the Brasileiro de Hipismo (BH) breed. In addition, we verified if this SNP is related to the growth curve profile of these animals for the variables body mass, height at withers, and height at croup, using nonlinear mixed models. For the DNA isolation, we collected blood samples from 167 young BH horses. We obtained the genotypes of these animals using the polymerase chain reaction-restriction fragment length polymorphism technique. For the association studies of this polymorphism with the growth curve in foals, we selected three traits: body mass, height at withers, and height at croup. Polymorphism C/T exists in BH horses and is significantly associated with the evaluated traits. Animals that presented the TT genotype were smaller and lighter when compared with animals of the CT and CC genotypes. By the Akaike information criterion, the model that best described the growth curve for the body mass variable is the Brody model associated with the power of the mean variance function. For the height at withers variable, the best-fit model was von Bertalanffy, adjusted without polymorphism effect in parameter b, associated with the asymptotic variance. For the height at croup trait, the model that best described the growth curve was Brody model, associated with asymptotic variance. This polymorphism represents a good molecular marker. Nonlinear models are promising for describing growth curves in horses, particularly by the possibility of associating SNP effects to model parameters.

Comparison of four nonlinear growth models in Creole chickens of Mexico.

Animal growth is a complex and dynamic process that involves physiological and morphological changes from hatching to maturity. It is defined as the increase in body size per time unit. Mathematical functions, called growth models, have been used to explain growth patterns. The aim of this study was to compare the Gompertz-Laird, logistic, Richards, and Von Bertalanffy growth models to determine which best fits the data of the Creole chickens (CC). Three hundred forty-seven CC were individually weighed from hatching until 177 D of age. Birds were fed a starter diet (0-18 D of age; 19% crude protein (CP) and 3,000 kcal of ME/kg) and grower diet (19-177 D of age; 18% CP and 2,800 kcal of ME/kg). Data were analyzed using PROC NLIN to fit the nonlinear growth curve. The coefficient of determination (R2), Akaike information criteria (AIC), and Bayesian information criteria (BIC) were used to compare the goodness of fit of the models. The Von Bertalanffy (R2: 0.9382, 0.9415; AIC: 2,224.1, 2,424.8; BIC: 2,233.5, 2,434.3, for females and males, respectively) was the model that best explained growth of the birds. On the other hand, both the Gompertz-Laird and logistic models overestimated hatching BW and underestimated the final BW of CC. Females reached age of maximum growth faster than males. The asymptotic weight was higher in males (3,011 g) than in females (2,011 g). Body weight at inflection point was 892 g at 64 D of age for males and 596 g at 54 D for females. In conclusion, the best fit of the data was obtained with the Von Bertalanffy growth model; the information is intended to serve as the basis for utilizing CC.

Application of Artificial Neural Networks for Dengue Fever Outbreak Predictions in the Northwest Coast of Yucatan, Mexico and San Juan, Puerto Rico.

Modelling dengue fever in endemic areas is important to mitigate and improve vector-borne disease control to reduce outbreaks. This study applied artificial neural networks (ANNs) to predict dengue fever outbreak occurrences in San Juan, Puerto Rico (USA), and in several coastal municipalities of the state of Yucatan, Mexico, based on specific thresholds. The models were trained with 19 years of dengue fever data for Puerto Rico and six years for Mexico. Environmental and demographic data included in the predictive models were sea surface temperature (SST), precipitation, air temperature (i.e., minimum, maximum, and average), humidity, previous dengue cases, and population size. Two models were applied for each study area. One predicted dengue incidence rates based on population at risk (i.e., numbers of people younger than 24 years), and the other on the size of the vulnerable population (i.e., number of people younger than five years and older than 65 years). The predictive power was above 70% for all four model runs. The ANNs were able to successfully model dengue fever outbreak occurrences in both study areas. The variables with the most influence on predicting dengue fever outbreak occurrences for San Juan, Puerto Rico, included population size, previous dengue cases, maximum air temperature, and date. In Yucatan, Mexico, the most important variables were population size, previous dengue cases, minimum air temperature, and date. These models have predictive skills and should help dengue fever mitigation and management to aid specific population segments in the Caribbean region and around the Gulf of Mexico.

Comparing Models of Spontaneous Variations, Maneuvers and Indexes to Assess Dynamic Cerebral Autoregulation.

OBJECTIVE: We analyzed the performance of linear and nonlinear models to assess dynamic cerebral autoregulation (dCA) from spontaneous variations in healthy subjects and compared it with the use of two known maneuvers to abruptly change arterial blood pressure (BP): thigh cuffs and sit-to-stand. MATERIALS AND METHODS: Cerebral blood flow velocity and BP were measured simultaneously at rest and while the maneuvers were performed in 20 healthy subjects. To analyze the spontaneous variations, we implemented two types of models using support vector machine (SVM): linear and nonlinear finite impulse response models. The classic autoregulation index (ARI) and the more recently proposed model-free ARI (mfARI) were used as measures of dCA. An ANOVA analysis was applied to compare the different methods and the coefficient of variation was calculated to evaluate their variability. RESULTS: There are differences between indexes, but not between models and maneuvers. The mfARI index with the sit-to-stand maneuver shows the least variability. CONCLUSIONS: Support vector machine modeling of spontaneous variation with the mfARI index could be used for the assessment of dCA as an alternative to maneuvers to introduce large BP fluctuations.

Curva de crescimento em altura na cernelha de equinos da raça Mangalarga Marchador considerando-se heterocedasticidade / Growth curve for height at withers of Mangalarga Marchador horses with heterocedasticity

Objetivou-se, com este estudo, avaliar o ajuste dos modelos de Brody, Gompertz, Logístico e Von Bertalanffy aos dados de altura na cernelha de equinos Mangalarga Marchador, ponderando pelo inverso da variância, a fim de selecionar o melhor modelo e predizer sobre o crescimento e a maturidade dos animais dessa raça. Foram utilizados dados de 230 equinos dos seis aos 176 meses de idade, os quais foram divididos por sexo e em 16 classes de idade. Os modelos estudados foram comparados segundo os avaliadores de qualidade: coeficiente de determinação (R2); desvio padrão residual (DPR) e critério de informação de Akaike (AIC). A estimação dos parâmetros dos modelos foi realizada pelo método de mínimos quadrados ponderado no software R. Todos os modelos avaliados se mostraram adequados para descrever a curva de crescimento em ambos os sexos. Perante os avaliadores utilizados, o modelo Logístico foi o mais adequado para descrever as curvas de crescimento em altura na cernelha nos dois sexos da raça Mangalarga Marchador. Observou-se também um crescimento acelerado nos primeiros meses de idade. Os animais machos atingiram uma altura adulta maior, porém as fêmeas são mais precoces, pois apresentaram maior estimativa para o índice de maturidade.(AU)

This work aimed to evaluate the fit of models Brody, Gompertz, Logistic and Von Bertalanffy to height at the withers of Mangalarga Marchador horses, weighed by the inverse of variance, in order to select the best model and predict growth and maturity of this breed pf animals. We used data of 230 equines from 06 to 176 months of age who were divided by sex and 16 age classes. The models were compared according to the quality assessors: coefficient of determination (R2); residual standard deviation (RSD) and Akaike information criteria (AIC). The estimation of the parameters from models was performed by the weighted least squares method in Software R. All models evaluated were suitable to describe the growth curve in both sexes. In view of the evaluators used, the logistic model was the most suitable to describe the growth curves in withers height in both sexes for the race Mangalarga Marchador. A strong growth at first age was also observed. The males reached a greater adult height, but females did so sooner, because they presented higher estimates for the maturity index.(AU)