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)

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.

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.

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)

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.

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.

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.

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

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

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

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

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.

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

ABSTRACT: 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.

RESUMO: 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.

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.

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.

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.

The impact of agricultural comprehensive development on agro-ecological efficiency of China: evidence from perspective of scale and structure / O impacto do desenvolvimento agrícola na eficiência agro-ecológica da China: evidência sob a perspectiva de escala e estrutura

Promoting the agricultural sustainable development is one of the core objectives of agricultural comprehensive development (ACD), and the core of agricultural sustainable development lies in enhancing agro-ecological efficiency (AEE). Based on inter-provincial panel data from 2003-2017, the AEE was measured by a unexpected super-efficient SBM model. From the perspective of investment scale and investment structure, the impact of investment scale in ACD on AEE was examined using a panel econometric model, then characterizing the investment structure by the proportion of government funds in the investment of ACD, examining the non-linear relationship between investment structure of ACD and AEE seeking a reasonable proportion of government expenditure. Finally, a spatial econometric model was constructed to test the spatial spillover effect of the scale and structure of investment in ACD on AEE. Results showed that: (i) AEE of China is on the rise overall, but the efficiency level is still low and there is large scope for improvement. (ii) Due to the inefficient use of funds and the lag in the transformation of agricultural benefits, the scale of investment in ACD has a significant negative impact on AEE in the current period. (iii) The impact of investment structure of ACD on AEE presents a significant "inverted N" relationship, and the optimal proportion of government fund investment structure is 76.71%. The reasonable structure of investment in ACD at different food functional areas shows differences. (iv) After considering the spatial effect, the impact of ACD remains robust, but the spatial spillover effect prolongs the time lag of this impact of investment scale and starts to have a positive impact in the 2nd year after the investment. Guarantee the investment scale in ACD, reduce financial redundancy, establish a cooperation mechanism between ACD and agricultural ecological protection in neighboring areas, and increase the introduction of private capital can achieve sustainable development of agricultural economy.

Promover o desenvolvimento agrícola sustentável é um dos objetivos centrais do desenvolvimento agrícola abrangente (ACD), e o núcleo do desenvolvimento agrícola sustentável está no aumento da eficiência agro-ecológica (AEE). Com base nos dados do painel interprovincial de 2003-2017, o AEE foi medido por um modelo SBM super-eficiente inesperado. Da perspectiva da escala de investimento e da estrutura de investimento, o impacto da escala de investimento da ACD na AEE foi examinado utilizando um modelo econométrico de painel, então caracterizado a estrutura de investimento pela proporção de fundos governamentais no investimento da ACD, examina a relação não linear entre a estrutura de investimento da ACD e da AEE para buscar uma proporção razoável dos gastos governamentais. Finalmente, um modelo econométrico espacial foi construído para testar o efeito de spillover espacial da escala e da estrutura de investimento da TDAA na AEE. Os resultados mostram isso: (i) O AEE da China está em ascensão em geral, mas o nível de eficiência ainda é baixo e há uma grande margem para melhorias. (ii) Devido ao uso ineficiente dos fundos e ao atraso na transformação dos benefícios agrícolas, a escala de investimento na TCAA tem um impacto negativo significativo na TCAA no período atual. (iii) O impacto da estrutura de investimento da DCA na AEE apresenta uma relação "N invertida" significativa, e a proporção ótima da estrutura de investimento dos fundos governamentais é de 76,71%. A estrutura razoável de investimento na TCA em diferentes áreas funcionais de alimentos mostra diferenças. (iv) Depois de considerar o efeito espacial, o impacto da TCA permanece robusto, mas o efeito de spillover espacial prolonga o tempo de atraso deste impacto da escala de investimento e começa a ter um impacto positivo no 2º ano após o investimento. Garantir a escala de investimento na TCA, reduzir a redundância financeira, estabelecer um mecanismo de cooperação entre a TCA e a proteção ecológica agrícola em áreas vizinhas e aumentar a introdução de capital privado pode alcançar o desenvolvimento sustentável da economia agrícola.

Relationship Between Pre-Slaughter Factors and Major Causes of Carcass Condemnation in a Broiler Slaughterhouse under Federal Inspection

This study aimed to investigate the relationship between pre-slaughter factors and major causes of total or partial carcass condemnation in a broiler slaughterhouse under federal inspection. Data on total and partial carcass condemnations between 2018 and 2020 were collected from 10 broiler farms supplying a slaughterhouse located in northern Paraná State, Brazil. The total sample comprised 2,562,642 birds. The pre-slaughter factors analyzed were age at slaughter, stocking density, weight at slaughter, feed conversion, and mortality.Associations between causes of condemnation and pre-slaughter factors were analyzed using a generalized linear model with negative binomial distribution, a generalized linear model with quasi-Poisson distribution, and a generalized linear mixed model with Poisson distribution. Total carcass condemnations were mostly due to repugnant appearance (48.67%) and arthritis (26.56%), whereas partial carcass condemnations were mainly due to arthritis (31.02%), bruising (27.97%), and myopathies (15.18%). Mean age and stocking density were the pre-slaughter factors that most contributed to increasing total and partial condemnation rates, indicating that reducing stocking density and age at slaughter might be important strategies for minimizing economic losses associated with carcass condemnation.(AU)

A relação da agressividade canina com o medo / The relationship of canine aggressiviness with fear / La relación de la agresividad canina con el miedo

A agressividade e o medo são repertórios conhecidos do comportamento canino. Este estudo teve como objetivo principal avaliar a associação entre a agressividade e o medo em cães e como estas características variaram entre diversas raças de cães. Tratou-se de um estudo transversal com dados de 27541 cães, obtidos do Dog Aging Project2020, disponibilizado pela University of Washington, nos Estados Unidos. Dois constructos foram desenvolvidos a partir da teoria de resposta ao item: índice de agressividade e índice de medo. A partir das medianas, as razões de prevalência entre cães com índice de agressividade acima e abaixo da média foram ajustadas pelo modelo de regressão linear generalizada bayesiana. Baseado nos resultados, 43,8% (ICmdp95%: 43,3-44,4) dos cães tinham agressividade acima da média. Após ajuste do modelo regressivo, uma maior prevalência de cães com agressividade acima da média foi associada com os cães machos, castrados e de pequeno porte, especialmente quando o medo acima da média esteve envolvido. O contrário aconteceu para cães idosos e de raça pura com prevalência significativamente menor de cães com agressividade acima da média. Quatro grupos de características comportamentais foram apresentadas entre as raças avaliadas: cães mais agressivos e mais medrosos, menos agressivos e menos medrosos, e as duas discordantes. A principal conclusão deste estudo foi que cães com agressividade acima da média foram associados com o medo acima da média.(AU)

Aggression and fear are known repertoires of canine behavior. This study aimed to evaluate the association between aggressiveness and fear in dogs and how these characteristics varied among different breeds of dogs. This was a cross-sectional study with data from 27541 dogs, obtained from the Dog Aging Project 2020, available by the University of Washington, in the United States. Two constructs were developed fromthe item response theory: aggressiveness and fear index. From the medians, the prevalence ratios between dogs with above and below average aggressiveness index were adjusted by the Bayesian generalized linear regression model. Based on the results, 43.8% (CI 95%: 43.3-44.4) of the dogs had above-average aggressiveness. After adjusting for the regression model, a higher prevalence of dogs with above-average aggressiveness was associated with male, neutered and small dogs, especially when above-average fear was involved. The opposite happened for older and purebred dogs with a significantly lower prevalence of dogs with above-average aggressiveness. Four groups of behavioral characteristics were presented among the evaluated breeds: more aggressive and more fearful dogs, less aggressive and less fearful, and the two discordant ones. The main conclusion of this study was that dogs with above-average aggressiveness were associated with above-average fear.(AU)

La agresión y el miedo son repertorios conocidos del comportamiento canino. Este estudio tuvo como objetivo evaluar la asociación entre la agresión y el miedo en los perros y cómo estas características varían entre las diferentes razas de perros. Este fue un estudio transversal con datos de 27541 perros, obtenidos del Dog Aging Project 2020, puesto a disposición por la University of Washington, en los Estados Unidos. Se desarrollaron dos constructos a partir de la teoría de respuesta al ítem: índice de agresión e índice de miedo. A partir de las medianas, las razones de prevalencia entre perros con un índice de agresión por encima y por debajo del promedio se ajustaron mediante el modelo de regresión linealgeneralizada bayesiana. Según los resultados, el 43,8% (ICmdp95%: 43,3-44,4) de los perros tenían una agresión superior al promedio. Después de ajustar el modelo de regresión, se asoció una mayor prevalencia de perros con agresividad superior a la media con perros machos, castrados y pequeños, especialmente cuando se trataba de un miedo superior a la media. Ocurrió lo contrario para los perros mayores y de raza pura con una prevalencia significativamente menor de perros con agresividad por encima del promedio. Se presentaron cuatro grupos de características comportamentales entre las razas evaluadas: perros más agresivos y más temerosos, menos agresivos y menos temerosos, y los dos discordantes. La principal conclusión de este estudio fue que los perros conagresividad superior al promedio estaban asociados con un miedo superior al promedio.(AU)

Drying of soybean seeds and effect on protein quality and oil extraction efficiency by extruding-expelling process

Soybean seeds (Glycine max) were dried under real scale conditions to different final moisture content (m.c.) (9.1, 9.7, 10.9 %, and control with 16.2 %) and processed through extruding-expelling. Results indicated that soybean seed m.c. affected the composition of the soybean expeller and, thus, the oil extraction efficiency (OEE), which increased as the seed m.c. decreased. A polynomic model was proposed for predicting OEE as a function of soybean m.c., indicating that drying soybean to 10 % resulted in an OEE of approximately 65 %. A thin layer drying experiment of soybean seeds indicated that the protein dispersibility index (PDI) was not affected as regards drying air temperatures up to approximately 69 °C, and a bi-linear model with a non-pre-established break point was fitted. The real scale drying treatment in a rack type dryer (mixed flow) did not show any effect (p > 0.05) on the PDI at 80 °C, while at 115 °C a reduction (p < 0.05) was observed (PDI reduction was 0.8 and 2.1 percentage points, respectively).(AU)