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)

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)

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.

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.

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.

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.

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)

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.

Mathematical model for estimating the leaf area of cured dry tobacco using linear measurements / Modelo matemático para estimar a área foliar do tabaco seco curado por meio de medidas lineares

Leaf area of dried Flue-cured tobacco is a reflection of climate and stage of growth of fresh tobacco in field; it also serves as the foundation for calculating a number of significant physical properties of tobacco. So the purpose of this paper was to establish a model to estimate the leaf area of dried Flue-cured tobacco in China from linear dimensions. Three Hundred eight tobacco leaves from different growing area and stalk position were sampled randomly and separated for model selection among linear, proportional and power model type and external evaluation individually. Results showed that there was a significant and strong correlation between leaf area and length×width , The equation LA = 0.495(L×W), where LA is the leaf area and L×W is the product of leaf length and width, was optimum and adequate for the estimation of leaf area of dried tobacco in China examined by Fisher's test, Akaike delta information criterion (AIC) and Bayesian information criterion (BIC). Growing area and stalk position had minor effect on the parameter before (L×W). The equation can sufficiently predict the area of leaf for external evaluation.

A área foliar do tabaco curado pelo Flue seco é um reflexo do clima e do estágio de crescimento do tabaco fresco no campo; também serve como base para o cálculo de várias propriedades físicas significativas do tabaco. Portanto, o objetivo deste artigo foi estabelecer um modelo para estimar a área foliar do tabaco curado por Flue seco na China a partir de dimensões lineares. Foram amostradas aleatoriamente 308 folhas de tabaco de diferentes áreas de cultivo e posição do colmo e separadas para seleção de modelos entre tipo linear, proporcional e de potência e avaliação externa individualmente. Os resultados mostraram que houve uma correlação significativa e forte entre área foliar e comprimento×largura. A equação LA = 0,495 (L×W), em que LA é a área foliar e L×W é o produto do comprimento e largura da folha, ótima e adequada para a estimativa da área foliar de tabaco seco na China examinada pelo teste de Fisher, critério de informação delta de Akaike (AIC) e critério de informação bayesiana (BIC). A área de cultivo e a posição do caule tiveram efeito menor no parâmetro antes (C×L). A equação pode prever suficientemente a área da folha para avaliação externa.

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)

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

ABSTRACT: 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.

RESUMO: 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.

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.

Genome-enabled prediction through quantile random forest for complex traits / Predição genômica por meio do random forest quantílitico para características complexas

ABSTRACT: Quantile Random Forest (QRF) is a non-parametric methodology that combines the advantages of Random Forest (RF) and Quantile Regression (QR). Specifically, this approach can explore non-linear functions, determining the probability distribution of a response variable and extracting information from different quantiles instead of just predicting the mean. This evaluated the performance of the QRF in the genomic prediction for complex traits (epistasis and dominance). In addition, compare the accuracies obtained with those derived from the G-BLUP. The simulation created an F2 population with 1,000 individuals and genotyped for 4,010 SNP markers. Besides, twelve traits were simulated from a model considering additive and non-additive effects, QTL (Quantitative trait loci) numbers ranging from eight to 120, and heritability of 0.3, 0.5, or 0.8. For training and validation, the 5-fold cross-validation approach was used. For each fold, the accuracies of all the proposed models were calculated: QRF in five different quantiles and three G-BLUP models (additive effect, additive and epistatic effects, additive and dominant effects). Finally, the predictive performance of these methodologies was compared. In all scenarios, the QRF accuracies were equal to or greater than the methodologies evaluated and proved to be an alternative tool to predict genetic values in complex traits.

RESUMO: Quantile Random Forest (QRF) é uma metodologia não paramétrica, que combina as vantagens do Random Forest (RF) e da Regressão Quantílica (QR). Especificamente, essa abordagem pode explorar funções não lineares, determinando a distribuição de probabilidade de uma variável resposta e extraindo informações de diferentes quantis em vez de apenas prever a média. O objetivo deste trabalho foi avaliar o desempenho do QRF em predizer o valor genético genômico para características com arquitetura genética não aditiva (epistasia e dominância). Adicionalmente, as acurácias obtidas foram comparadas com aquelas advindas do G-BLUP. A simulação criou uma população F2 com 1.000 indivíduos genotipados para 4.010 marcadores SNP. Além disso, doze características foram simuladas a partir de um modelo considerando efeitos aditivos e não aditivos, com número de QTL (Quantitative trait loci) variando de oito a 120 e herdabilidade de 0,3, 0,5 ou 0,8. Para treinamento e validação foi usada a abordagem da validação cruzada 5-fold. Para cada um dos folds foram calculadas as acurácias de todos os modelos propostos: QRF em cinco quantis diferentes e três modelos do G-BLUP (com efeito aditivo, aditivo e epistático, aditivo e dominante). Por fim, o desempenho preditivo dessas metodologias foi comparado. Em todos os cenários, as acurácias do QRF foram iguais ou superiores às metodologias avaliadas e mostrou ser uma ferramenta alternativa para predizer valores genéticos em características complexas.

Evaluating tree survival and modeling initial growth for Atlantic Forest restoration / Avaliação da sobrevivência e modelagem do desenvolvimento inicial de árvores para restauração da Mata Atlântica

ABSTRACT: Ecological restoration has become an important complementary practice to protect natural resources and preserve biodiversity. However, native species may be used in restoration programs in ways that do not optimize their performance. This research evaluated the survival and to model the initial growth of 15 native tree species planted in "filling" and "diversity" lines in the post-planting phase of a restoration experiment in the subtropics of the Brazilian Atlantic Forest. We measured survival rate (%) one year after planting and collar diameter (mm), total height (m), crown projection area (m²) and crown volume (m³) in the first 48 months after planting. Growth modeling for each variable and species was based on the non-linear mathematical Logistic, Gompertz, and Chapman-Richards models. Model selection for each variable/species was supported by the Akaike Information Criterion, standard error of the estimate, and coefficient of determination. The highest survival rates were reported for Cordia americana, Gochnatia polymorpha, Inga uruguensis, Peltophorum dubium, Prunus sellowii e Zanthoxylum rhoifolium (91.7%) and for Solanum mauritianum (90.3%). The species with faster growth were, by increasing order, Mimosa scabrella, Trema micrantha, Solanum mauritianum and Croton urucurana. With a better understanding of the initial developmental potential of tree species, it is possible to increase the species and functional diversity of the filling group. There was no single model capable of describing the variables analyzed and different models were needed to describe different characteristics and species.

RESUMO: A restauração ecológica tornou-se uma importante atividade complementar para proteger os recursos naturais e conservar a biodiversidade. No entanto, as espécies nativas podem estar a ser utilizadas em programas de restauração de formas que não otimizam as suas características. O objetivo deste trabalho foi avaliar a sobrevivência e modelar o desenvolvimento inicial de 15 espécies arbóreas nativas plantadas em linhas de "preenchimento" e "diversidade" na fase de pós-plantio numa experiência de restauração nos subtrópicos da Mata Atlântica Brasileira. Avaliou-se a taxa de sobrevivência (%) um ano após o plantio e o diâmetro do colo (mm), a altura total (m), a área de projeção de copa (m²) e o volume de copa (m³) nos primeiros 48 meses após o plantio. A modelagem de crescimento para cada variável e espécie foi baseada nos modelos matemáticos não lineares: Logístico, Gompertz e Chapman-Richards. A seleção do modelo para cada variável/espécie teve como base o Critério de Informação de Akaike, erro padrão da estimativa e coeficiente de determinação. Os percentuais de sobrevivência mais altos foram para Cordia americana, Gochnatia polymorpha, Inga uruguensis, Peltophorum dubium, Prunus sellowii e Zanthoxylum rhoifolium (91,7%) e para Solanum mauritianum (90,3%). As espécies de crescimento mais rápido, por ordem crescente, foram: Mimosa scabrella, Trema micrantha, Solanum mauritianum e Croton urucurana. Com o conhecimento do potencial de desenvolvimento inicial das espécies, é possível aumentar a diversidade de espécies e funcional do grupo de preenchimento. Não houve um modelo único capaz de descrever todas as variáveis de desenvolvimento analisadas. Foram necessários diferentes modelos para descrever as diferentes características e as diferentes espécies.

Physical and physiological qualities and productivity of corn seeds fertilized with poultry waste / Avaliação das qualidades física e fisiológica e da produtividade de sementes de milho adubado com resíduo avícola

ABSTRACT: This study evaluated the physical and physiological qualities and productivity of corn seeds, a variety UFVM 100 Native, produced in plots fertilized in top dressing with different levels of poultry waste. The experiment was organized in a randomized block design, with six treatments and four repetitions, totaling 24 plots. The treatments consisted of the application of 0.0, 1.5, 3.0, 4.5, 6.0, and 7.5 t/ha of tanned poultry waste. The seeds were subjected to the following evaluations: uniformity test, thousand seed weight, germination, vigor (first germination count, accelerated aging, soilless cold test, percentage, and emergence rate in sand), and productivity. Linear regression models were used to evaluate the effects of different dosages of poultry waste on the variables considered. The quality of seeds was not influenced by the effects of different levels of fertilization. Among the dosages used, 7.5 t/ha is recommended because it provides a greater increase in productivity, which may result in a greater financial return to the producer.

RESUMO: Este trabalho teve como objetivo avaliar as qualidades física e fisiológica, bem como a produtividade das sementes de milho, variedade UFVM 100 Nativo, produzidas em lavouras adubadas com diferentes níveis de resíduo avícola, em cobertura. O experimento foi instalado no delineamento em blocos casualizados, com seis tratamentos e quatro repetições, totalizando 24 parcelas. Os tratamentos consistiram da aplicação de 0,0; 1,5; 3,0; 4,5; 6,0 e 7,5 t/ha de resíduo avícola curtido. As sementes foram submetidas às seguintes avaliações: Teste de uniformidade, peso de mil sementes, germinação, vigor (primeira contagem de germinação, envelhecimento acelerado, teste de frio sem solo, porcentagem e velocidade de emergência em areia) e produtividade. Para avaliar o efeito das diferentes dosagens de resíduo avícola sobre as variáveis consideradas foram utilizados modelos de regressão linear. A qualidade das sementes não foi influenciada pelo efeito dos diferentes níveis de adubação. Dentre as dosagens utilizadas, recomenda-se a de 7,5 t/ha por proporcionar maior aumento da produtividade, o que poderá resultar em maior retorno financeiro ao produtor.

Relationship between body weight and scrotal circumference in growing Pelibuey sheep raised under tropical conditions / Relação entre o peso corporal e a circunferência escrotal em ovinos Pelibuey em crescimento criados em condições tropicais

The body weight (BW) of an animal is a vital economic trait that might help in decision-making in the handling of animals. The objective of the present study was to develop equations for the prediction of BW in Pelibuey sheep using scrotal circumference (SC). The BW (23.40 ± 6.96 kg) and SC (20.25 ± 6.19 cm) have been recorded in 405 male Pelibuey at the Southeastern Center for Ovine Integration, Mexico. Linear, logarithmic, quadratic, exponential, cubic, and power regression models were used for data analysis. Pearson correlation (R), Coefficient of determination (R2), Adjusted coefficient of determination (Adj.R2) Root mean square error (RMSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to select the best model. Power regression model showed the highest R (0.93), R2 (0.86), Adj.R2 (0.86) and lowest RMSE (0.02), AIC (-989.44) and BIC (-981.44). The current study suggests that SC might be used as the only predictor for BW of growing Pelibuey sheep raised under tropical conditions.

O peso corporal (PC) do animal é uma característica econômica importante, que pode auxiliar na tomada de decisões no manejo dos animais. O objetivo do presente estudo foi desenvolver equações para a predição do PC em ovinos Pelibuey por meio da circunferência escrotal (CE). O PC (23,40±6,96kg) e a CE (20,25±6,19cm) foram registrados em 405 ovinos machos da raça Pelibuey no Centro de Integração Ovina da Região Sudeste do México. Os modelos lineares, logarítmicos, quadráticos, exponenciais, cúbicos e de regressão de potência foram utilizados para a análise dos dados. A correlação de Pearson (R), o coeficiente de determinação (R2), o coeficiente de determinação ajustado (Adj.R2), o erro do quadrado médio (EQM), o critério de informação de Akaike (AIC) e o critério de informação bayesiano (BIC) foram usados para selecionar o melhor modelo. O modelo de regressão de potência apresentou maiores R (0,93), R2 (0,86), Adj.R2 (0,86) e menores EQM (0,02), AIC (-989,44) e BIC (-981,44). O estudo atual sugere que a CE pode ser usada como um único preditor para o PC de ovinos Pelibuey em crescimento criadas em condições tropicais.

Living in the city and producing in the countryside: the growth of a new type of farmer and agriculture in Brazil / Viver na cidade e produzir no campo: o crescimento de um novo tipo de agricultor e de agricultura no Brasil

ABSTRACT: Living in rural neighborhoods has always been a characteristic of small and medium-sized Brazilian farmers. However, when observing the agricultural censuses of 2006 and 2017, carried out in Brazil, there is a tendency to separate the place of work and residence of farmers. This articleanalyzed the double residence and the phenomenon of pendular displacement of farmers in the municipalities of Zona da Mata Mineira (ZMM), an important coffee region in Minas in Brazil, and to discuss its possible causes and impacts in the region. The research used data from the 2006 and 2017 Agricultural Censuses of the Brazilian Institute of Geography and Statistics. The data were analyzed using descriptive statistics and multivariate linear regression models in order to better understand the factors that correlate with the percentage of owners living in cities in the municipalities of region. The results showed that, in the case of the ZMM, the growth of urban residence of farmers more expressive than the other regions of the country is mainly due to the predominance of small coffee producers. Furthermore, living in the city does not mean abandoning agricultural establishments, since living in the city does not prevent daily work in the countryside. It was concluded that the urban residence of the farmers constituted a reproductive strategy that made it possible for them to carry out other activities as well as the receipt of retirement and pensions that complement the agricultural income and, consequently, the maintenance of the agricultural establishment.

RESUMO: Morar em bairros rurais sempre foi uma característica dos pequenos e médios agricultores brasileiros. No entanto, ao se observar os censos agrícolas de 2006 e 2017, realizados no Brasil, nota-se uma tendência de separar o local de trabalho e residência dos agricultores. O objetivo deste artigo é analisar a dupla residência e o fenômeno do deslocamento pendular de agricultores nos municípios da Zona da Mata Mineira (ZMM), importante região cafeeira de Minas no Brasil, e discutir suas possíveis causas e impactos na região. A pesquisa utilizou dados dos Censos Agropecuários de 2006 e 2017 do Instituto Brasileiro de Geografia e Estatística. Os dados foram analisados por meio de estatísticas descritivas e modelos de regressão linear multivariada a fim de compreender melhor os fatores que se correlacionam com o percentual de proprietários residentes em cidades dos municípios da região. Os resultados mostraram que, no caso da ZMM, o crescimento da residência urbana dos agricultores mais expressivo do que as demais regiões do país deve-se, principalmente, ao predomínio de pequenos produtores de café. Além disso, morar na cidade não significa abandonar os estabelecimentos agrícolas uma vez que a moradia na cidade não impede o trabalho diário no campo. Concluiu-se que a residência urbana dos agricultores constituiu uma estratégia reprodutiva que possibilitou que estes realizassem outras atividades (principalmente não-agrícola) assim como o recebimento de aposentadorias e pensões que complementam a renda agrícola e, consequentemente, a manutenção do estabelecimento agrícola.

Physical and physiological qualities and productivity of corn seeds fertilized with poultry waste / Avaliação das qualidades física e fisiológica e da produtividade de sementes de milho adubado com resíduo avícola

This study evaluated the physical and physiological qualities and productivity of corn seeds, a variety UFVM 100 Native, produced in plots fertilized in top dressing with different levels of poultry waste. The experiment was organized in a randomized block design, with six treatments and four repetitions, totaling 24 plots. The treatments consisted of the application of 0.0, 1.5, 3.0, 4.5, 6.0, and 7.5 t/ha of tanned poultry waste. The seeds were subjected to the following evaluations: uniformity test, thousand seed weight, germination, vigor (first germination count, accelerated aging, soilless cold test, percentage, and emergence rate in sand), and productivity. Linear regression models were used to evaluate the effects of different dosages of poultry waste on the variables considered. The quality of seeds was not influenced by the effects of different levels of fertilization. Among the dosages used, 7.5 t/ha is recommended because it provides a greater increase in productivity, which may result in a greater financial return to the producer.

Este trabalho teve como objetivo avaliar as qualidades física e fisiológica, bem como a produtividade das sementes de milho, variedade UFVM 100 Nativo, produzidas em lavouras adubadas com diferentes níveis de resíduo avícola, em cobertura. O experimento foi instalado no delineamento em blocos casualizados, com seis tratamentos e quatro repetições, totalizando 24 parcelas. Os tratamentos consistiram da aplicação de 0,0; 1,5; 3,0; 4,5; 6,0 e 7,5 t/ha de resíduo avícola curtido. As sementes foram submetidas às seguintes avaliações: Teste de uniformidade, peso de mil sementes, germinação, vigor (primeira contagem de germinação, envelhecimento acelerado, teste de frio sem solo, porcentagem e velocidade de emergência em areia) e produtividade. Para avaliar o efeito das diferentes dosagens de resíduo avícola sobre as variáveis consideradas foram utilizados modelos de regressão linear. A qualidade das sementes não foi influenciada pelo efeito dos diferentes níveis de adubação. Dentre as dosagens utilizadas, recomenda-se a de 7,5 t/ha por proporcionar maior aumento da produtividade, o que poderá resultar em maior retorno financeiro ao produtor.