Mathematical models to describe the growth curves of Vietnamese Ri chicken / Modelos matemáticos para descrever as curvas de crescimento do frango Ri vietnamita

Abstract Ri chicken is the most popular backyard chicken breed in Vietnam, but little is known about the growth curve of this breed. This study compared the performances of models with three parameters (Gompertz, Brody, and Logistic) and models containing four parameters (Richards, Bridges, and Janoschek) for describing the growth of Ri chicken. The bodyweight of Ri chicken was recorded weekly from week 1 to week 19. Growth models were fitted using minpack.lm package in R software and Akaike's information criterion (AIC), Bayesian information criterion (BIC), and root mean square error (RMSE) were used for model comparison. Based on these criteria, the models having four parameters showed better performance than the ones with three parameters, and the Richards model was the best one for males and females. The lowest and highest value of asymmetric weights (α) were obtained by Bridges and Brody models for each of sexes, respectively. Age and weight estimated by the Richard model were 8.46 and 7.51 weeks and 696.88 and 487.58 g for males and for females, respectively. Differences in the growth curves were observed between males and female chicken. Overall, the results suggested using the Richards model for describing the growth curve of Ri chickens. Further studies on the genetics and genomics of the obtained growth parameters are required before using them for the genetic improvement of Ri chickens.

Resumo O frango Ri é a raça de frango de quintal mais popular do Vietnã, mas pouco se sabe sobre a curva de crescimento dessa raça. Este estudo comparou o desempenho de modelos com três parâmetros (Gompertz, Brody e Logistic) e modelos contendo quatro parâmetros (Richards, Bridges e Janoschek) para descrever o crescimento do frango Ri. O peso corporal do frango Ri foi registrado semanalmente da semana 1 à semana 19. Os modelos de crescimento foram ajustados usando o pacote minpack.lm no software R e o critério de informação de Akaike (AIC); critério de informação bayesiano (BIC) e erro quadrático médio (RMSE) foram usados ​​para comparação de modelos. Com base nesses critérios, os modelos com quatro parâmetros apresentaram melhor desempenho do que os com três parâmetros, sendo o modelo de Richards o melhor para homens e mulheres. O menor e o maior valor dos pesos assimétricos (α) foram obtidos pelos modelos Bridges e Brody para cada um dos sexos, respectivamente. A idade e o peso estimados pelo modelo de Richard foram de 8,46 e 7,51 semanas e 696,88 e 487,58 g para homens e mulheres, respectivamente. Diferenças nas curvas de crescimento foram observadas entre frangos machos e fêmeas. No geral, os resultados sugeriram o uso do modelo de Richards para descrever a curva de crescimento de frangos Ri. Mais estudos sobre a genética e genômica dos parâmetros de crescimento obtidos são necessários antes de usá-los para o melhoramento genético de frangos Ri.

Growth Curve of Brazilian Creole Chickens (Canela-Preta Breed) Raised in Two Different Rearing Systems under Tropical Climate

The objective of this study was to describe the growth curve of Brazilian Creole chickens of the Canela-Preta breed raised in two different rearing systems using non-linear growth models. A total of 400 birds were divided into two groups of 200 animals (of both genders), which were kept in confined or semi-confined systems. The confined birds were housed in an experimental masonry shed and the semi-confined animals were housed in another shed with access to pasture from 29 days of age. Birds were individually weighed every seven days during six months for determination of the growth curves of body weight using 10 non-linear models. The parameters of the models were estimated using the Gauss Newton method. The performance of the models was assessed using mean squared error (MSE), coefficient of determination (R2), percentage of convergence, and residual mean absolute deviation (MAD). With the exception of the Inverse Polynomial, all the other models had R2 values close to one. Therefore, the best models were chosen based on the lowest MSE and MAD values, with the Richards model ranking first followed by the Von Bertalanffy model. Gender and rearing system effects significantly influenced (p<0.05) some parameters of the Richards model. In conclusion, the Richards model was the most adequate to describe the growth of Canela-Preta chickens. Gender and rearing system significantly influenced the growth of the birds. The growth rates observed indicated that management strategies can be performed to increase the production efficiency of Canela-Preta chickens.(AU)

Application of statistical process control in mechanized corn seeding / Aplicação do controle estatístico de processo na semeadura mecanizada do milho

Several factors alter the quality of the mechanized sowing process of corn, and the use of the statistical process control (SPC) technique not only allows the identification of process limitation points but also ensures the correct functioningand conduction of the mechanized process, determiningcritical factors. that may decrease their performance. In view of the above, the present study aims to qualitatively evaluate, through this technique, the longitudinal distribution of corn seeds as a function of different stands and operational speeds during the sowing process. The experiment was carried out in a randomized block design (CBD) with three replications and in a split-plot design. Data were submitted to analysis of variance and when significant, analyzed using Tukey's test, with 5% significance. To carry out the statistical process control, mean and amplitude control charts were used to evaluate the effect of operationalspeed, seed distribution, deposition depth and plant germination. The results indicate that the use of statistical process control is an efficient tool to identify the behavior of the corn sowing process. Based on the results, speeds close to 4.5km/hallowed an efficient sowing process, as it presented a higher percentage of normal spaces in the distribution of maize seeds.(AU)

Vários fatores alteram a qualidade do processo de semeadura mecanizada do milho, e o uso da técnica do controle estatístico de processos (CEP) não só permite a identificação de pontos de limitação do processo como asseguram o correto funcionamento e condução do processo mecanizado determinando fatores críticos que possam diminuir seu desempenho. Diante do exposto, o presente estudo visa avaliar qualitativamente por meio desta técnica a distribuição longitudinal das sementes de milho em função de diferentes estandes e velocidades operacionais durante o processo de semeadura. O experimento foi realizado em delineamento de blocos casualizados (DBC) com três repetições e em esquema de parcela subdividida. Os dados foram submetidos a análise de variância e quando significativos analisados por meio do teste de Tukey, com 5% de significância. Para a realização do controle estatístico de processo, foram utilizadas cartas de controle de média e amplitude para avaliar o efeito da velocidade operacional, distribuição das sementes, a profundidade de deposição e a germinação das plantas. Os resultados indicam que o uso do controle estatístico de processo é uma ferramenta eficiente na identificação do comportamento do processo de semeadura do milho. Com base nos resultados, velocidades próximas a 4.5 km/hpermitiram um processo de semeadura eficiente por apresentar maior percentual de espaços normais na distribuição de sementes de milho.(AU)

Mathematical models to describe the growth curves of Vietnamese Ri chicken

Abstract Ri chicken is the most popular backyard chicken breed in Vietnam, but little is known about the growth curve of this breed. This study compared the performances of models with three parameters (Gompertz, Brody, and Logistic) and models containing four parameters (Richards, Bridges, and Janoschek) for describing the growth of Ri chicken. The bodyweight of Ri chicken was recorded weekly from week 1 to week 19. Growth models were fitted using minpack.lm package in R software and Akaikes information criterion (AIC), Bayesian information criterion (BIC), and root mean square error (RMSE) were used for model comparison. Based on these criteria, the models having four parameters showed better performance than the ones with three parameters, and the Richards model was the best one for males and females. The lowest and highest value of asymmetric weights () were obtained by Bridges and Brody models for each of sexes, respectively. Age and weight estimated by the Richard model were 8.46 and 7.51 weeks and 696.88 and 487.58 g for males and for females, respectively. Differences in the growth curves were observed between males and female chicken. Overall, the results suggested using the Richards model for describing the growth curve of Ri chickens. Further studies on the genetics and genomics of the obtained growth parameters are required before using them for the genetic improvement of Ri chickens.

Resumo O frango Ri é a raça de frango de quintal mais popular do Vietnã, mas pouco se sabe sobre a curva de crescimento dessa raça. Este estudo comparou o desempenho de modelos com três parâmetros (Gompertz, Brody e Logistic) e modelos contendo quatro parâmetros (Richards, Bridges e Janoschek) para descrever o crescimento do frango Ri. O peso corporal do frango Ri foi registrado semanalmente da semana 1 à semana 19. Os modelos de crescimento foram ajustados usando o pacote minpack.lm no software R e o critério de informação de Akaike (AIC); critério de informação bayesiano (BIC) e erro quadrático médio (RMSE) foram usados para comparação de modelos. Com base nesses critérios, os modelos com quatro parâmetros apresentaram melhor desempenho do que os com três parâmetros, sendo o modelo de Richards o melhor para homens e mulheres. O menor e o maior valor dos pesos assimétricos () foram obtidos pelos modelos Bridges e Brody para cada um dos sexos, respectivamente. A idade e o peso estimados pelo modelo de Richard foram de 8,46 e 7,51 semanas e 696,88 e 487,58 g para homens e mulheres, respectivamente. Diferenças nas curvas de crescimento foram observadas entre frangos machos e fêmeas. No geral, os resultados sugeriram o uso do modelo de Richards para descrever a curva de crescimento de frangos Ri. Mais estudos sobre a genética e genômica dos parâmetros de crescimento obtidos são necessários antes de usá-los para o melhoramento genético de frangos Ri.

Factors determining farmers' access to agricultural credit in Turkey / Fatores que determinam o acesso dos agricultores ao crédito agrícola na Turquia

This study assessed the parameters determining the access of producers to agricultural credit in Turkey. This research was carried out in the production areas par excellence of the country. A total of 409 producers have been surveyed. The data collected was collected during the first quarter of 2021 and relates to the socio-economic and demographic characteristics of producers as well as the factors likely to influence their access to agricultural credit. The analysis of the results from the logistic regression model produced shows that the access of producers to agricultural credit is determined by their socio-economic and demographic characteristics. These parameters are level of education, degree of involvement in agricultural activities, social security status, household size and whether you own a tractor. Given the importance of agricultural credit for the agricultural sector; it is therefore, imperative to facilitate its access to producers.

O objetivo deste estudo é avaliar os parâmetros que determinam o acesso dos produtores ao crédito agrícola na Turquia. Esta pesquisa foi realizada nas áreas de produção por excelência do país. Foram estudados 409 produtores. Os dados foram recolhidos durante o primeiro trimestre de 2021 e estão relacionados com as características socioeconômicas e demográficas dos produtores, bem como com os fatores que podem influenciar o seu acesso ao crédito agrícola. A análise dos resultados do modelo de regressão logística produzido mostra que o acesso dos produtores ao crédito agrícola é determinado pelas suas características socioeconômicas e demográficas. Esses parâmetros são: nível de escolaridade, grau de envolvimento em atividades agrícolas, situação da previdência social, porte da família e possuir ou não trator. Dada a importância do crédito agrícola para o setor agrícola, torna-se imperativo facilitar o seu acesso aos produtores.

Mapping wood volume in seasonally dry vegetation of Caatinga in Bahia State, Brazil

The Caatinga biome in Brazil comprises the largest and most continuous expanse of the seasonally dry tropical forest (SDTF) worldwide; nevertheless, it is among the most threatened and least studied, despite its ecological and biogeographical importance. The spatial distribution of volumetric wood stocks in the Caatinga and the relationship with environmental factors remain unknown. Therefore, this study intends to quantify and analyze the spatial distribution of wood volume as a function of environmental variables in Caatinga vegetation in Bahia State, Brazil. Volumetric estimates were obtained at the plot and fragment level. The multiple linear regression techniques were adopted, using environmental variables in the area as predictors. Spatial modeling was performed using the geostatistical kriging approach with the model residuals. The model developed presented a reasonable fit for the volume m3 ha with r2 of 0.54 and Root Mean Square Error (RMSE) of 10.9 m3 ha­1. The kriging of ordinary residuals suggested low error estimates in unsampled locations and balance in the under and overestimates of the model. The regression kriging approach provided greater detailing of the global wood volume stock map, yielding volume estimates that ranged from 0.01 to 109 m3 ha­1. Elevation, mean annual temperature, and precipitation of the driest month are strong environmental predictors for volume estimation. This information is necessary to development action plans for sustainable management and use of the Caatinga SDTF in Bahia State, Brazil.(AU)

Estimating the relationship of sugarcane borer larvae and crop damage based on adult captures and climate variables

ABSTRACT: Sugarcane borer Diatraea saccharalis (F.) is the primary sugarcane pest in Brazil. To estimate the relationship between larvae in sugarcane stalks and captures of male adults of D. saccharalis, we collected samples weekly: (1) adults with one delta trap with three virgin females and three female pupae and (2) larvae in 120 stalks per plot of 12.6 hectares (355 × 355 m). The study was conducted in two sites with five plots each, in the municipalities of Nova Ponte and Tupaciguara, Minas Gerais State, Brazil, from July 2016 to May 2017. Relationships between (1) males trapped per week and the number of larvae outside of stalks (LOS) were estimated and (2) we evaluated climate variables, namely average temperature, average relative air humidity, hours with relative air humidity below 30 %, rainfall and number of rainy days, and adults and larvae of D. saccharalis. We obtained generalized linear models for LOS in autumn and for larvae inside the stalks (LIS) in spring and autumn and trapped males in both sites. A significant and direct relationship between LIS and males trapped allows predicting larvae density based on captures of males. In addition, plant damage can be estimated based on accumulated captures of males. There was a negative relationship between hours of air humidity < 30 % and larvae outside of stalks. Densities of LIS can be estimated from male captures and by the humidity variables in the trapping week. Nevertheless, the models require validation in the field.

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)

AgroReg: main regression models in agricultural sciences implemented as an R Package

Regression analysis is highly relevant to agricultural sciences since many of the factors studied are quantitative. Researchers have generally used polynomial models to explain their experimental results, mainly because much of the existing software perform this analysis and a lack of knowledge of other models. On the other hand, many of the natural phenomena do not present such behavior; nevertheless, the use of non-linear models is costly and requires advanced knowledge of language programming such as R. Thus, this work presents several regression models found in scientific studies, implementing them in the form of an R package called AgroReg. The package comprises 44 analysis functions with 66 regression models such as polynomial, non-parametric (loess), segmented, logistic, exponential, and logarithmic, among others. The functions provide the coefficient of determination (R2), model coefficients and the respective p-values from the t-test, root mean square error (RMSE), Akaike's information criterion (AIC), Bayesian information criterion (BIC), maximum and minimum predicted values, and the regression plot. Furthermore, other measures of model quality and graphical analysis of residuals are also included. The package can be downloaded from the CRAN repository using the command: install.packages("AgroReg"). AgroReg is a promising analysis tool in agricultural research on account of its user-friendly and straightforward functions that allow for fast and efficient data processing with greater reliability and relevant information.

Combining deep learning and X-ray imaging technology to assess tomato seed quality

Traditional germination tests which assess seed quality are costly and time-consuming, mainly when performed on a large scale. In this study, we assessed the efficiency of X-ray imaging analyses in predicting the physiological quality of tomato seeds. A convolutional neural network (CNN) called mask region convolutional neural network (MaskRCNN) was also tested for its precision in adequately classifying tomato seeds into four seed quality categories. For this purpose, X-ray images were taken of seeds of 49 tomato genotypes (46 Solanum pennellii introgression lines) from two different growing seasons. Four replicates of 25 seeds for each genotype were analyzed. These seeds were further assessed for germination and seedling vigor-related traits in two independent trials. Correlation analysis revealed significant linear association between germination and image-based variables. Most genotypes differed in terms of germination and seed development performance considering the two independent trials, except LA 4046, LA 4043, and LA4047, which showed similar behavior. Our findings point out that seeds with low opacity and percentage of damaged seed tissue and high values for living tissue opacity have greater physiological quality. In short, our work confirms the reliability of X-ray imaging and deep learning methodologies in predicting the physiological quality of tomato seeds.

Spectrophotometric method for determination of Colossoma macropomum (tambaqui) sperm concentration / Determinação da concentração espermática de tambaqui (Colossoma macropomum) por espectrofotometria

To assist the reproductive management of tambaqui (Colossoma macropomum) males in laboratory and commercial fish farming, a linear regression model was obtained from concentration curves using the spectrophotometric method. Twenty-two tambaqui males with an average age of three years old were selected and divided into two groups containing 11 animals each. Both groups alternately received a single dose of carp pituitary extract (CPE; 2.0 mg/kg body weight, intracoelomic). Sperm was collected 14 h after hormonal treatment and diluted (1:4000; sperm:formaldehyde saline). The concentration was estimated by counting spermatozoa in a Neubauer chamber and by using a spectrophotometer (λ=540 nm). Individual sperm concentration ranged from 11.40 to 71.13 × 109 sperm/mL. The degree of transmittance ranged from 62.1% to 95.0%. There was a significant correlation (r2 = 0.966; p < 0.0001) between sperm concentration analyzed in a Neubauer chamber and transmittance at 540 nm. Analysis by spectrophotometry and the prediction provided by the equation Y=100.293 - 0.509X proved to be an efficient and fast method for estimating sperm concentration in tambaqui and can be used in routine procedures in artificial fish reproduction laboratories.

Visando auxiliar o manejo reprodutivo de machos de tambaqui (Colossoma macropomum) em piscicultura de laboratório e comercial, obteve-se um modelo de regressão linear a partir de curvas de concentração por método espectrofotométrico. Foram selecionados 22 machos de tambaqui com idade média de três anos. Eles foram divididos em dois grupos contendo 11 animais cada. Ambos os grupos receberam alternadamente uma única dose de extrato de hipófise de carpa (EHC; 2,0 mg/kg de peso corporal, intracelomático). O esperma foi coletado 14 horas após o tratamento hormonal e diluído (1:4000; esperma: solução salina formaldeído). A concentração foi estimada por contagem de espermatozoides em câmara de Neubauer e por espectrofotômetro (λ=540 nm). A concentração espermática individual variou de 11,40 a 71,13 × 109 espermatozoides/mL. O grau de transmitância variou de 62,1 a 95,0%. Houve correlação significativa (r2 = 0,966; p < 0,0001) entre a concentração espermática analisada em câmara de Neubauer e a transmitância em 540 nm. A análise por espectrofotometria e a predição pela equação Y=100,293 - 0,509X mostrou ser um método eficiente e rápido para estimar a concentração espermática de tambaqui, podendo ser utilizado em procedimentos de rotina em laboratórios de reprodução artificial de peixes.

Tridimensional models and radiographic study of dorsal laminectomy and thoracolumbar hemilaminectomy in dogs

Purpose: To create three-dimensional anatomical models of the thoracic and lumbar portions of the canine spine that reproduce the vertebral surgical approaches of dorsal laminectomy and hemilaminectomy, and to perform the respective radiographic evaluations of each approach. Methods: In a digital archive of the canine spine, digitally replicate the dorsal laminectomy and hemilaminectomy in the thoracic and lumbar portions and, then, make tridimensional prints of the vertebral models and obtain radiographs in three dorsoventral, ventrodorsal and laterolateral projections. Results: The anatomical models of the surgical spinal canal accesses of the thoracic and lumbar portions showed great fidelity to the natural bones. The created accesses have the proper shape, location and size, and their radiographic images showed similar radiodensities. Conclusions: The replicas of the dorsal laminectomy and hemilaminectomy developed in the anatomical models in the thoracic and lumbar portions are able to represent the technical recommendations of the specialized literature, as well as their respective radiographic images, which have certain radiological properties that allow to make a deep radiological study. Therefore, the models are useful for neurosurgical training.

Analysis of the toxicological and pharmacokinetic profile of Kaempferol-3-O-ß-D-(6"-E-p-coumaryl) glucopyranoside - Tiliroside: in silico, in vitro and ex vivo assay / Análise do perfil toxicológico e farmacocinético de Kaempferol-3-O-ß-D- (6 "-E-p-cumaril) glucopiranosídeo - Tilirosídeo: ensaio in silico, in vitro e ex vivo

Abstract Tiliroside is a glycosidic flavonoid present in many plants species including Helicteres velutina K. Schum (Malvaceae sensu lato), commonly known in Brazil as "pitó". This molecule has been shown to have many biological activities, however no study has been carried out to investigate the toxicity of this substance. The present work aimed to evaluate the possible cellular toxicity in silico, in vitro and ex-vivo of the kaempferol-3-O-β-D-(6"-E-p-coumaroyl) glucopyranoside (tiliroside), through chemical structure analysis, toxicity assessment and predictive bioactive properties, using human samples for in vitro and ex-vivo tests. The in silico analysis suggests that tiliroside exhibited great absorption index when penetrating biological membranes. In addition, it also displayed considerable potential for cellular protection against free radicals, and anticarcinogenic, antioxidant, antineoplastic, anti-inflammatory, anti-hemorrhagic and antithrombotic activities. The assessment of the hemolytic and genotoxic effects of tiliroside showed low hemolysis rates in red blood cells and absence of cellular toxicity in the oral mucosa cells. The data obtained indicate that this molecule could be a promising therapeutic approach as a possible new drug with biotechnological potential.

Resumo O tilirosídeo é um flavonóide glicosídico presente em muitas espécies de plantas, incluindo Helicteres velutina K. Schum (Malvaceae sensu lato), conhecida no Brasil como "pitó". Esta molécula mostrou ter muitas atividades biológicas, porém nenhum estudo foi realizado para investigar a toxicidade dessa substância. O presente trabalho teve como objetivo avaliar a possível toxicidade celular in silico, in vitro e ex-vivo do kaempferol-3-O-β-D- (6 "-Ep-coumaroil) glucopiranosídeo (tilirosídeo), por meio de análises de estrutura química, toxicidade avaliação e propriedades bioativas preditivas, utilizando amostras humanas para testes in vitro e ex-vivo. A análise in silico sugere que o tilirosídeo exibe bom índice de absorção para penetrar nas membranas biológicas. Além disso, apresentou considerável potencial de proteção celular contra os radicais livres e com atividades anticarcinogênica, antioxidante, antineoplásica, antiinflamatória, anti-hemorrágica e antitrombótica. A avaliação dos efeitos hemolíticos e genotóxicos do tilirosídeo mostrou baixas taxas de hemólise nas hemácias e ausência de toxicidade em células da mucosa oral. Os dados obtidos indicam que esta molécula pode possuir uma abordagem terapêutica promissora como uma possível nova droga com potencial biotecnológico.

Estimation of cropland prices in Rio Grande do Sul by multiple linear regression and principal component analysis / Estimação do preço das lavouras no Rio Grande do Sul por meio de regressão linear múltipla e análise de componentes principais

This study aimed to price croplands in Rio Grande do Sul State (southern Brazil) and point which variables had the most significant impact on prices. The main purpose was achieved using multiple linear regression and principal component analysis. The variables used in this study were planted area, production, price, and yield of the commodities soybean, wheat, and corn. The period under analysis was from January 1994 to December 2017 (biannual observations). Multiple linear regression showed that five variables contributed to land pricing, being three related to soybean and two to wheat. Multivariate analysis grouped the investigated variables into clusters and indicated their influence, in addition to providing information on land prices and reducing variable dimensionality from fourteen original variables to three principal components to be analyzed. The two analyses complemented each other so that the croplands' price was explained by three variables, in which two corroborated in constructing the pricing model for croplands.

Este estudo teve como objetivo a precificação de terra para lavouras no Rio Grande do Sul e apresentar quais variáveis possuem maior impacto no preço. O objetivo foi alcançado por meio da aplicação da análise de regressão linear múltipla e de componentes principais. Variáveis relacionadas às commodities soja, trigo e milho, como a área plantada, produção, cotação e rendimento, formaram o banco amostral para as duas metodologias, compreendendo o período de janeiro de 1994 a dezembro de 2017, em observações bianuais. A regressão linear múltipla mostrou que três variáveis relacionadas à soja e duas ao trigo contribuem na precificação das terras. A análise multivariada agrupou as variáveis investigadas, indicando a influência entre as mesmas, fornecendo informações sobre o preço de terras e diminuindo a dimensionalidade do problema de 14 variáveis originais para três componentes a serem analisados. As duas análises se complementaram de forma que o preço de terras foi explicado por três variáveis e duas corroboraram na construção do modelo de precificação das lavouras.

Optimal plot size in white oat with comparison of three methods / Tamanho ótimo de parcela em aveia branca com comparação de três métodos

The objective of this work was to compare three methods for estimating the optimal plot size to evaluate the fresh matter productivity of white oat (Avena sativa L.), IPR Suprema cultivar. Six uniformity trials (blank experiments) were carried out, three trials on the first sowing date (May 3, 2021) and three trials on the second sowing date (May 26, 2021). Fresh matter productivity was evaluated in 216 basic experimental units (BEU) of 1 m × 1 m (36 BEU per trial). The BEU was formed by five rows of 1.0 m in length, spaced 0.20 m apart, totaling 1.0 m2. The optimal plot size was determined using the methods of modified maximum curvature, linear response and plateau model and quadratic response and plateau model. The optimal plot size differs between the methods and decreases in the following order: quadratic response and plateau model (11.09 m2), linear response and plateau model (7.65 m2) and modified maximum curvature (4.00 m2). The optimal plot size to evaluate the fresh matter productivity of white oat is 7.65 m2 and the experimental precision stabilizes from this size on.

O objetivo deste trabalho foi comparar três métodos de estimação do tamanho ótimo de parcela para avaliar a produtividade de matéria fresca de aveia branca (Avena sativa L.), cultivar IPR Suprema. Foram conduzidos seis ensaios de uniformidade (experimentos em branco), sendo três na primeira data de semeadura (03 de maio de 2021) e três na segunda data de semeadura (26 de maio de 2021). Foi avaliada a produtividade de matéria fresca em 216 unidades experimentais básicas (UEB) de 1 m × 1 m (36 UEB por ensaio). A UEB foi formada por cinco fileiras de 1,0 m de comprimento, espaçadas 0,20 m entre fileiras, totalizando 1,0 m2. Foi determinado o tamanho ótimo de parcela por meio dos métodos da curvatura máxima modificado, do modelo linear de resposta com platô e do modelo quadrático de resposta com platô. O tamanho ótimo de parcela difere entre os métodos e decresce na seguinte ordem: modelo quadrático de resposta com platô (11,09 m2), modelo linear de resposta com platô (7,65 m2) e curvatura máxima modificado (4,00 m2). O tamanho ótimo de parcela para avaliar a produtividade de matéria fresca de aveia branca é 7,65 m2 e a precisão experimental estabiliza a partir desse tamanho.

Sampling sufficiency, correlation and path analysis in showy rattlebox / Suficiência amostral, correlação e análise de trilha em crotalária spectabilis

It is important to adequately size the number of plants that should be evaluated to allow precise inferences about the traits under evaluation. The study of the linear relations among traits provides important information, especially in the identification of traits for indirect selection. So, the objectives of this work were to determine the sample size (number of plants) to estimate the mean of Crotalaria spectabilis traits and investigate the relations among traits. Were randomly selected 200 and 110 plants of C. spectabilis in the experiments conducted, respectively, in 2019/2020 and 2020/2021. In these 310 plants, the following traits were evaluated: plant height, stem diameter, number of nodes, number of leaves, leaf fresh matter, stem fresh matter, shoot fresh matter, leaf dry matter, stem dry matter and shoot dry matter. The sample size was calculated to estimate the mean of these traits, based on Student's t-distribution, and the relations among traits were investigated through correlation and path analysis. To estimate the mean of these ten traits of C. spectabilis, with a maximum error of 10% of the mean and 95% confidence level, 64 plants are needed. In an experiment, to estimate the mean of each treatment with 10% precision, 64 plants per treatment must be evaluated. The number of leaves has a positive linear relation with the amount leaf, stem and shoot fresh and dry matter.

É importante dimensionar adequadamente o número de plantas que devem ser avaliadas para possibilitar inferências precisas sobre os caracteres em avaliação. O estudo das relações lineares entre caracteres fornece informações importantes, especialmente, na identificação de caracteres para seleção indireta. Assim, os objetivos deste trabalho foram determinar o tamanho de amostra (número de plantas) necessário para a estimação da média de caracteres de Crotalaria spectabilis e investigar as relações entre os caracteres. Foram selecionadas, aleatoriamente, 200 e 110 plantas de C. spectabilis, nos experimentos conduzidos, respectivamente, em 2019/2020 e 2020/2021. Nessas 310 plantas avaliaram-se os caracteres altura de planta, diâmetro de caule, número de nós, número de folhas, matéria fresca de folhas, matéria fresca de caule, matéria fresca de parte aérea, matéria seca de folhas, matéria seca de caule e matéria seca de parte aérea. Foi calculado o tamanho de amostra para a estimação da média desses caracteres, com base na distribuição t de Student e investigada a relação entre os caracteres por meio de análises de correlação e de trilha. Para a estimação da média, desses dez caracteres de C. spectabilis, com erro máximo de 10% da média e grau de confiança de 95%, são necessárias 64 plantas. Em um experimento, para a estimação da média de cada tratamento com 10% de precisão, devem ser avaliadas 64 plantas por tratamento. O número de folhas tem relação linear positiva com a quantidade de matérias fresca e seca de folhas, do caule e de parte aérea.

Artificial neural networks for the management of poultry industry: a simulation based on the broiler production chain / Redes neurais artificiais para o gerenciamento da indústria avícola: uma simulação baseada na cadeia de produção de frangos de corte

The aim of this study was to predict production indicators and to determine their potential economic impact on a poultry integration system using artificial neural networks (ANN) models. Forty zootechnical and production parameters from broiler breeder farms, one hatchery, broiler production flocks, and one slaughterhouse were selected as variables. The ANN models were established for four output variables: "saleable hatching", "weight at the end of week 5," "partial condemnation," and "total condemnation" and were analyzed in relation to the coefficient of multiple determination (R2), correlation coefficient (R), mean error (E), mean squared error (MSE), and root mean square error (RMSE). The production scenarios were simulated and the economic impacts were estimated. The ANN models were suitable for simulating production scenarios after validation. For "saleable hatching", incubator and egg storage period are likely to increase the financial gains. For "weight at the end of the week 5" the lineage (A) is important to increase revenues. However, broiler weight at the end of the first week may not have a significant influence. Flock sex (female) may influence the "partial condemnation" rates, while chick weight at first day may not. For "total condemnation", flock sex and type of chick may not influence condemnation rates, but mortality rates and broiler weight may have a significant impact.

O objetivo deste trabalho foi predizer os indicadores de produção e determinar o seu potencial impacto econômico em um sistema de integração utilizando as redes neurais artificiais (RNA). Quarenta parâmetros zootécnicos e de produção de granjas de matrizes e de frango de corte, um incubatório e um abatedouro foram selecionados como variáveis. Os modelos de RNA foram estabelecidos para quatro variáveis de saída ("eclosão vendável", "peso ao final da quinta semana", "condenações parciais" e "condenações totais") e foram analisados em relação ao coeficiente de determinação múltipla (R2), coeficiente de correlação (R), erro médio (E), erro quadrático médio (EQM) e raiz do erro quadrático médio (REQM). Os cenários produtivos foram simulados e os impactos foram estimados. Os modelos de RNA gerados foram adequados para simular diferentes cenários produtivos após o treinamento. Para "eclosão vendável", o modelo de incubadora e o período de incubação aumentaram os ganhos financeiros. Para "peso ao final da quinta semana", a linhagem também demonstrou influencia no retorno financeiro, o que não aconteceu com o peso ao final da primeira semana. O sexo do lote possui influência nas taxas de "condenação parcial", ao contrário do peso do frango no primeiro dia. As taxas de mortalidade e o peso do frango apresentaram influência na "condenação total", mas o sexo do lote e o tipo de pinto não tiverem influência.

Components of farm milk price behavior in Brazil from 2005 to 2020

The objective of this study was to assess behavior patterns in Brazilian farm milk prices. We employed a structural time series techniques model, the Unobserved Component Model (UCM), which is part of the family of State Space models, to assess the trend, seasonality, cyclical behavior, and impacts of exogenous regressors on aggregated farm milk price behavior in Brazil from January 2005 to December 2019. We tested five alternative models with different regressors using the monthly national average prices of milk paid to farmers. The fit of the models was assessed with Akaike information criterion and Bayesian information criterion. Predictions were assessed by the root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). All models demonstrated a high degree of accuracy. Trends, seasonality, and two cycles were statistically significant, with the trend and long-period cycle contributing the most to price variation. Exogenous factors such as feed cost and international dairy product prices also had significant positive effects on the level of Brazil's farm milk prices. All models demonstrated a high degree of accuracy, which may indicate their usefulness for price forecasting and policy formulation.(AU)

Retrieval of leaf chlorophyll content in Gannan navel orange based on fusing hyperspectral vegetation indices using machine learning algorithms / Recuperação do teor de clorofila de folhas em laranja do umbigo Gannan com base na fusão de índices de vegetação hiperespectral usando algoritmos de inteligência artificial

ABSTRACT: Estimating leaf chlorophyll contents through leaf reflectance spectra is efficient and nondestructive. The literature base regarding optical indices (particularly chlorophyll indices) is wide ranging and extensive. However, it is without much consensus regarding robust indices for Gannan navel orange. To address this problem, this study investigated the performance of 19 published indices using RDS (raw data spectrum), FDS (first derivative data spectrum) and SDS (second derivative data spectrum) for the estimation of chlorophyll content in navel orange leaves. The single spectral index and combination of multiple spectral indices were compared for their accuracy in predicting chlorophyll a content (Chla), chlorophyll b content (Chlb) and total chlorophyll content (Chltot) content in navel orange leaves by using partial least square regression (PLSR), adaboost regression (AR), random forest regression (RFR), decision tree regression (DTR) and support vector machine regression (SVMR) models. Through the comparison of the above data in three datasets, the optimal modeling data set is RDS data, followed by FDS data, and the worst is SDS data. In modeling with multiple spectral indices, good results were obtained for Chla (NDVI750, NDVI800), Chlb (Datt, DD, Gitelson 2) and Chltot (Datt, DD, Gitelson2) by corresponding index combinations. Overall, we can find that the AR is also the best regression method judging by prediction performance from the results of single spectral index models and multiple spectral indices models. In comparison, result of multiple spectral indices models is better than single spectral index models in predicting Chla and Chltot content using FDS data and SDS data, respectively.

RESUMO: Estimar os teores de clorofila foliar através de espectros de refletância foliar é eficiente e não destrutivo, a base da literatura sobre índices ópticos (principalmente índices de clorofila) é ampla e extensa. No entanto, não há muito consenso sobre índices robustos para a laranja de Gannan. O estudo investigou o desempenho de 19 índices publicados usando RDS (espectro de dados brutos), FDS (espectro de dados de primeira derivada) e SDS (espectro de dados de segunda derivada) para a estimativa do teor de clorofila em folhas de laranja de umbigo. Os índices espectrais foram comparados quanto à sua precisão na previsão do teor de clorofila a (Chla), teor de clorofila b (Chlb) e teor de clorofila total (Chltot) em folhas de laranja de umbigo usando regressão dos mínimos quadrados parcial (PLSR), regressão adaboost (AR), modelos de regressão de floresta aleatória (RFR), regressão de árvore de decisão (DTR) e regressão de máquina de vetor de suporte (SVMR). Através da comparação dos dados acima em três conjuntos de dados, o conjunto de dados de modelagem ideal são os dados RDS, seguidos pelos dados FDS, e o pior são os dados SDS. Na modelagem com vários índices espectrais, bons resultados foram obtidos para Chla (NDVI750, NDVI800), Chlb (Datt, DD, Gitelson 2) e Chltot (Datt, DD, Gitelson2) por combinações de índices correspondentes. No geral, podemos descobrir que o AR também é o melhor método de regressão a julgar pelo desempenho de previsão dos resultados de modelos de índice espectral único e modelos de índices espectrais múltiplos. Em comparação, o resultado de modelos de índices espectrais múltiplos é melhor do que os modelos de índices espectrais únicos na previsão do conteúdo de Chla e Chltot usando dados FDS e dados SDS, respectivamente.

Price trends of Agave Mezcalero in Mexico using multiple linear regression models / Estimativa de tendências de preços de Agave Mezcalero no México usando modelos de regressão linear múltipla

This study developed a multiple linear regression model to estimate the Average rural prices (ARP) in Mexico with information taken from the period 1999-2018. The variables used to generate this model were the supply and demand as represented by planted area, yield, exports and the ARP of Agave Tequilero and Mezcalero. The analysis was carried out through the multiple linear regression model (MLRM) with the least squares method and using the statistical package R. The following variables were identified as having a significant influence on the determination of the ARP: the yield of Agave Mezcalero (YAM), the ARP of Agave Tequilero and the new planted area of Agave Tequilero (NPAATt-6) with an adjustment of 6 periods. Overall, three models were generated: model 2 was considered the most appropriate because it allows carrying out future forecasts with the new planted area with Agave Tequilero with 2 independent variables. YAM and NPAATt-6 were useful in predicting 65.5% of the annual variations in the ARP and helped recognize the negative trend of the Agave price from 2020 to 2024. Therefore, the use of the MLRM to estimate the Agave ARP can be a useful tool in predicting the performance of this crop.

O objetivo deste estudo é desenvolver um modelo de regressão linear múltipla para estimar o Preços médios rurais (PRM) no México com informações retiradas do período 1999-2018. As variáveis ​​utilizadas para gerar este modelo foram a oferta e a demanda representadas pela área plantada, produtividade, exportações e o PRM da Agave Tequilero e Mezcalero. A análise foi realizada através do modelo de regressão linear múltipla (MRLM) com o método dos mínimos quadrados e utilizando o pacote estatístico R. As seguintes variáveis ​​foram identificadas como tendo influência significativa na determinação do PRM: o rendimento da Agave Mezcalero (RAM), o PMR da Agave Tequilero e a nova área plantada da Agave Tequilero (NPAATt-6) com um ajuste de 6 períodos. Ao todo, foram gerados três modelos: o modelo 2 foi considerado o mais adequado porque permite fazer previsões futuras com a nova área plantada com Agave Tequilero com dois variáveis ​​independentes. RAM e NPAATt-6 foram úteis na previsão de 65,5% das variações anuais no ARP e ajudaram a reconhecer a tendência negativa do preço da Agave de 2020 a 2024. Portanto, o uso do MRLM para estimar o PMR da Agave pode ser uma ferramenta útil na previsão do desempenho desta cultura.