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Several studies have reported the relationship of deforestation with increased incidence of infectious diseases, mainly due to the deregulation caused in these environments. The purpose of this study was to answer the following questions: a) is increased loss of vegetation related to dengue cases in the Brazilian Cerrado? b) how do different regions of the tropical savanna biome present distinct patterns for total dengue cases and vegetation loss? c) what is the projection of a future scenario of deforestation and an increased number of dengue cases in 2030? Thus, this study aimed to assess the relationship between loss of native vegetation in the Cerrado and dengue infection. In this paper, we quantify the entire deforested area and dengue infection cases from 2001 to 2019. For data analyses, we used Poisson generalized linear model, descriptive statistics, cluster analysis, non-parametric statistics, and autoregressive integrated moving average (ARIMA) models to predict loss of vegetation and fever dengue cases for the next decade. Cluster analysis revealed the formation of four clusters among the states. Our results showed significant increases in loss of native vegetation in all states, with the exception of Piauí. As for dengue cases, there were increases in the states of Minas Gerais, São Paulo, and Mato Grosso. Based on projections for 2030, Minas Gerais will register about 4,000 dengue cases per 100,000 inhabitants, São Paulo 750 dengue cases per 100,000 inhabitants, and Mato Grosso 500 dengue cases per 100,000 inhabitants. To reduce these projections, Brazil will need to control deforestation and implement public health, environmental and social policies, requiring a joint effort from all spheres of society. [ABSTRACT FROM AUTHOR]

Different regions have different environmental conditions, which may be unfavorable for the preservation of the quality of stored soybean seeds over time. Thus, it is necessary to adopt specific technologies to control the storage environment conditions. Big raffia bags are widely used for the storage of soybean seeds, however these consist of a porous, permeable material that allows the exchange of gases between the packaging and the storage environment. In an effort to find a solution to this problem, in this study we evaluated low cost big bag coating alternatives, in order to minimize the effects of temperature and intergranular humidity on stored seeds. Thus, the aim of this work was to evaluate the quality of soybean cultivars subjected to different temperature and storage duration conditions and stored in raffia bags with or without internal coating. We used a completely randomized, three-factor (10 × 6 × 5) experimental design. We assessed 10 soybean cultivars, six storage environments, and five evaluation periods. Our results showed that seeds of the M-SOY 8866, M7110 IPRO, CD 2737 RR, and BMX DESAFIO 8473 RSF soybean cultivars preserved their physiological quality better in different storage environments. The storage duration had a cumulative effect on the negative factors that favor the deterioration of the quality of the stored seeds. The storage temperature was the main factor that affected the physiological quality of the stored seeds. The use of coated packaging was beneficial in preserving the physiological quality of stored soybean seeds; however, its effect was greater at ambient temperature than in a cold environment. The best storage environment for the preservation of the quality of the seeds was characterized by 10°C temperature conditions and the use of coated packaging, while the worst storage environment was characterized by ambient temperature conditions without the use of coated packaging. Thus, it was concluded that the use of coatings in raffia big bags can be an alternative for maintaining the quality of seeds of different soybean cultivars during storage in seed processing units. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the quality of seeds of RR and RR2 PRO soybean cultivars stored in ambient air with raffia packaging (ANER), ambient air with laminated packaging (ANEL), modified atmosphere with polyethylene packaging (AMEP), refrigerated atmosphere (1 to 3°C) with raffia packaging (ARER), refrigerated atmosphere (1 to 3°C) with laminated packaging (AREL), and modified (-14 PSI) and refrigerated (1 to 3°C) atmosphere with polyethylene packaging (AMREP), over 6 months of storage. Results showed that the seeds of cultivar RR2 were preserved with better physiological quality. Raffia and polyethylene packaging under natural storage conditions, in a refrigerated and modified atmosphere, did not preserve the seed quality over the storage period. The conditions of storage in ambient air with laminated packaging (ANEL) and in a refrigerated atmosphere with laminated packaging (AREL) reduced the environmental effects of temperature and relative humidity, leading to better results of physiological quality of the seeds. Storage time negatively influenced the physiological quality of seeds, except for AREL and ANEL, which maintained the quality close to that of the initial conditions, over the 6 months of storage. The best alternatives for soybean seeds storage over 6 months are the laminated packaging in a natural environment, matching the refrigerated conditions. The technological laminated packaging can be used as a new alternative for conserving soybean seeds in processing and storage units. [ABSTRACT FROM AUTHOR]

The stem volume of commercial trees is an important variable that assists in decision making and economic analysis in forest management. Wood from forest plantations can be used for several purposes, which makes estimating multi-volumes for the same tree a necessary task. Defining its exploitation and use potential, such as the total and merchantable volumes (up to a minimum diameter of interest), with or without bark, is a possible work. The goal of this study was to use different strategies to model multi-volumes of the stem of eucalyptus trees. The data came from rigorous scaling of 460 felled trees stems from four eucalyptus clones in high forest and coppice regimes. The diameters were measured at different heights, with the volume of the sections obtained by the Smalian method. Data were randomly separated into fit and validation data. The single multi-volume model, volume-specific models, and the training of artificial neural networks (ANNs) were fitted. The evaluation criteria of the models were: coefficient of determination, root mean square error, mean absolute error, mean bias error, as well as graphical analysis of observed and estimated values and distribution of residuals. Additionally, the t-test (α = 0.05) was performed between the volume obtained in the rigorous scaling and estimated by each strategy with the validation data. Results showed that the strategies used to model different tree stem volumes are efficient. The actual and estimated volumes showed no differences. The multi-volume model had the most considerable advantage in volume estimation practicality, while the volume-specific models were more efficient in the accuracy of estimates. Given the conditions of this study, the ANNs are more suitable than the regression models in the estimation of multi-volumes of eucalyptus trees, revealing greater accuracy and practicality. [ABSTRACT FROM AUTHOR]

Nutritional deficiencies limit the growth of snap bean plants, therefore knowing the biological mechanisms involved in it is fundamental. This study is aimed to evaluate the damage caused by a deficiency of macronutrients in physiological variables that cause decreased growth and the appearance of visual symptoms in snap bean. Thus, we design a hydroponic system of snap bean cultivation in order to test the effect of macronutrient deficiencies in a controlled environment. The treatments consisted in evaluate the effects of lack of one macronutrient in time. To perform this, we used Hoagland and Arnon solution in its complete formulation (control) or without N, P; K; Mg, Ca or S in each treatment. Physiological, nutritional, and growth analyses were performed when visual deficiency symptoms of each omitted nutrient appeared. Thus, the omissions of N and P in the nutrient solution led to lower accumulations of all macronutrients in the shoot. And the K, Ca, Mg, and S omissions decreased the amounts of K, Ca, Mg, P, and S in the shoot of the snap bean plants when compared with the plants grown in the complete nutrient solution. With the lowest accumulation of macronutrients, the content of photosynthetic pigments and the photosynthetic rate were reduced, with harmful effects on plant growth. Thus, from the losses in dry matter production of the shoot, the order of limiting of macronutrients in bean plants was N < P < Ca < S < Mg < K, with a decrease of up to 86.2%, 80.1%, 51.2%, 46.5%, 25.6%, and 19.3%, respectively. The nitrogen deficiency is more evident, proven by symptoms such as chlorosis in the lower and upper third leaves and necrosis of the lower third leaves. [ABSTRACT FROM AUTHOR]

Photosynthetic efficiency has become the target of several breeding programs since the positive correlation between photosynthetic rate and yield in soybean suggests that the improvement of photosynthetic efficiency may be a promising target for new yield gains. However, studies on combining ability of soybean genotypes for physiological traits are still scarce in the literature. The objective of this study was to estimate the combining ability of soybean genotypes based on F2 generation aiming to identify superior parents and segregating populations for physiological traits. Twenty-eight F2 populations resulting from partial diallel crossings between eleven lines were evaluated in two crop seasons for the physiological traits: photosynthesis, stomatal conductance, internal CO2 concentration, and transpiration. General combining ability (GCA) of the parents and specific combining ability (SCA) of the F2 populations were estimated. Our findings reveal the predominance of additive effects in controlling the traits. The genotype TMG 7062 IPRO is the most promising parent for programs aiming at photosynthetic efficiency. We have also identified other promising parents and proposed cross-breeding with higher potential for obtaining superior lines for photosynthetic efficiency. [ABSTRACT FROM AUTHOR]

This study describes the use of X-ray fluorescence spectroscopy in Crotalaria ochroleuca seed technology. This work evaluated X-ray fluorescence techniques to estimate the physiological performance of different C. ochroleuca seed coat colours based on the concentration and distribution of Ca, P, K, and S in seed structures. The treatments consisted of seeds separated by coat colours (yellow, green, and red) and a control treatment (colour mix according to their natural occurrence in commercial lots), and was carried out in a completely randomized design, with four replications. The physiological performance was evaluated by analyzing the water content, germination, first germination count, germination speed index, electrical conductivity, seedling emergence, and seedling length and dry mass. X-ray fluorescence spectroscopy techniques were carried out with quantitative analyses (Ca, P, K, and S concentration in the seed coat and the whole seed) and qualitative analyses (macronutrient mapping). The EDXRF and μ-XRF techniques are efficient and promising to differentiate the physiological performance of C. ochroleuca seeds, based on the concentration and distribution of Ca, P, K, and S in different structures. Ca is predominant in the seed coat, and K, S, and P are found throughout the embryonic axis. Seeds of yellow and green coats have higher nutrients concentration and distribution in the embryonic axis, revealing high germinative capacity and physiological performance. Seeds of red coat have higher nutrients concentration in the seed coat and lower assimilation, showing less vigour, which interferes directly in the quality of commercial lots. [ABSTRACT FROM AUTHOR]

At present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; ) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of . Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny. [ABSTRACT FROM AUTHOR]

Pesticides aerial application may results in the drift to neighboring areas if some application technology is not well executed. This phenomenon should be minimized to reduce environmental risks and agricultural production costs. This work aimed to investigate the interaction of environmental conditions, surrounding distance, and application conditions influencing spray drift in aerial applications. Sampling data from aerial sprays were collected during three agricultural years (from 2012 to 2014) in fields cultivated with sorghum, millet, soybean, corn, and cotton. The following variables were evaluated: application swath width, application rate, distance from the applied field, wind speed, relative humidity, and temperature. The estimated Pearson’s correlations and path analysis identified that application rate and distance from the applied field and application were the variables that most influenced drift. Equations relating spray drift in function of distance from the applied field and application rate were adjusted in function of the variable, and a response surface model was constructed to estimate drift. The major pesticide class sprayed with aircraft in the Brazilian Cerrado was insecticide, followed by fungicide. This scenario shows the potential hazard risk of spray drift over the environment. The concentration of the drift deposits decreased as surrounding distance and application rate were increased. A mathematical equation of drift prediction was established, where the variables that contributed most to drift deposits were surrounding distance and wind speed. Thus, it is very important to monitor and respect the wind speed limits during the aerial spraying, mainly when there is any risk potential associated with pesticide exposure over the downwind direction. [ABSTRACT FROM AUTHOR]

Jatropha (Jatropha curcas) has become one of the most important species for producing biofuels. Currently, Genotype x Environment (GxE) interaction is the biggest challenge that breeders should solve to increase the section accuracy in the plant breeding. Therefore, the objectives in this study were to estimate the parameters in the 180 half-sib families in Jatropha evaluated for five production years, to verify the significance of the GxE interaction variance, to evaluate the adaptability and stability for each family based on three prediction methods, to select superior half-sib families based on the adaptability and stability analyses, and to predict the accuracy for the sixth production year. Jatropha half-sib families were classified and selected using the follow adaptability and stability methods: linear regression, bi-segmented linear regression and mixed models concepts called harmonic mean of the relative performance of genetic values (HMRPGV). The prediction accuracy was estimated by the Pearson correlation between the predicted genetic values by adaptability and stability methods and the phenotypic value in the sixth production year. In result, most half-sib families were classified as general adaptability and general stability for the evaluated traits. The selection gain obtained via HMRPGV was higher than other methods. The prediction accuracy for the sixth production year was 0.45. Therefore, HMRPGV is efficient to maximize the genetic gain, and it can be a useful strategy to select genotype with high adaptability and stability in Jatropha breeding as well as other species that should be evaluated for many years to take a suitable selection accuracy. [ABSTRACT FROM AUTHOR]

Asian rust affects the physiology of soybean plants and causes losses in yield. Repeatability coefficients may help breeders to know how many measurements are needed to obtain a suitable reliability for a target trait. Therefore, the objectives of this study were to determine the repeatability coefficients of 14 traits in soybean plants inoculated with Phakopsora pachyrhizi and to establish the minimum number of measurements needed to predict the breeding value with high accuracy. Experiments were performed in a 3x2 factorial arrangement with three treatments and two inoculations in a random block design. Repeatability coefficients, coefficients of determination and number of measurements needed to obtain a certain reliability were estimated using ANOVA, principal component analysis based on the covariance matrix and the correlation matrix, structural analysis and mixed model. It was observed that the principal component analysis based on the covariance matrix out-performed other methods for almost all traits. Significant differences were observed for all traits except internal CO2 concentration for the treatment effects. For the measurement effects, all traits were significantly different. In addition, significant differences were found for all Treatment x Measurement interaction traits except coumestrol, chitinase and chlorophyll content. Six measurements were suitable to obtain a coefficient of determination higher than 0.7 for all traits based on principal component analysis. The information obtained from this research will help breeders and physiologists determine exactly how many measurements are needed to evaluate each trait in soybean plants infected by P. pachyrhizi with a desirable reliability. [ABSTRACT FROM AUTHOR]

[This corrects the article DOI: 10.1371/journal.pone.0192189.].

Asian rust affects the physiology of soybean plants and causes losses in yield. Repeatability coefficients may help breeders to know how many measurements are needed to obtain a suitable reliability for a target trait. Therefore, the objectives of this study were to determine the repeatability coefficients of 14 traits in soybean plants inoculated with Phakopsora pachyrhizi and to establish the minimum number of measurements needed to predict the breeding value with high accuracy. Experiments were performed in a 3x2 factorial arrangement with three treatments and two inoculations in a random block design. Repeatability coefficients, coefficients of determination and number of measurements needed to obtain a certain reliability were estimated using ANOVA, principal component analysis based on the covariance matrix and the correlation matrix, structural analysis and mixed model. It was observed that the principal component analysis based on the covariance matrix out-performed other methods for almost all traits. Significant differences were observed for all traits except internal CO2 concentration for the treatment effects. For the measurement effects, all traits were significantly different. In addition, significant differences were found for all Treatment x Measurement interaction traits except coumestrol, chitinase and chlorophyll content. Six measurements were suitable to obtain a coefficient of determination higher than 0.7 for all traits based on principal component analysis. The information obtained from this research will help breeders and physiologists determine exactly how many measurements are needed to evaluate each trait in soybean plants infected by P. pachyrhizi with a desirable reliability.