Stability of soybean yield through different sowing periods

Soybean yield is highly affected by sowing period and there are significant productivity losses when sowings are done outward a relatively restricted period in many regions of Brazil. Breeding cultivars less sensitive to photoperiod and to temperature variations is desirable for adaptation to wider sowing period and wider latitude range and also make irrigated soybean cultivation possible during the fall-winter seasons in frost free regions. The possibility of selecting high yielding and stable lines for yield during various sowing periods was studied by analyzing the behavior of 100 non-selected advanced lines (F9 and F10), from each one of all possible biparental crosses involving the genotypes BR85-29009, OCEPAR 8, FT-2, and BR-13. Experiments were set up in a completely randomized design with single-plant hill plots and received supplementary irrigation. Sowing was on Sept 27, Oct 20, Nov 17, and Dec 17 in 1993/94 and Sept 20, Oct 20, Nov 17, and Dec 14 in 1994/95 at Londrina, PR, Brazil. Procedures of regression analysis and minimum variance among planting date means were efficient for selecting stable lines during the four sowing seasons. It was possible to select stable and high yielding genotypes through the four sowing periods in all the crosses. No specific cross was clearly better to produce a greater number of stable genotypes.

Appraisal of Phlebotomus argentipes habitat suitability using a remotely sensed index in the kala-azar endemic focus of Bihar, India

Visceral leishmaniasis, or kala-azar, is recognised as a serious emerging public health problem in India. In this study, environmental parameters, such as land surface temperature (LST) and renormalised difference vegetation indices (RDVI), were used to delineate the association between environmental variables and Phlebotomus argentipes abundance in a representative endemic region of Bihar, India. The adult P. argentipes were collected between September 2009-February 2010 using the hand-held aspirator technique. The distribution of P. argentipes was analysed with the LST and RDVI of the peak and lean seasons. The association between environmental covariates and P. argentipes density was analysed a multivariate linear regression model. The sandfly density at its maximum in September, whereas the minimum density was recorded in January. The regression model indicated that the season, minimum LST, mean LST and mean RDVI were the best environmental covariates for the P. argentipes distribution. The final model indicated that nearly 74% of the variance of sandfly density could be explained by these environmental covariates. This approach might be useful for mapping and predicting the distribution of P. argentipes, which may help the health agencies that are involved in the kala-azar control programme focus on high-risk areas.

Use of the swat model for hydro-sedimentologic simulation in a small rural watershed

Mathematical models have great potential to support land use planning, with the goal of improving water and land quality. Before using a model, however, the model must demonstrate that it can correctly simulate the hydrological and erosive processes of a given site. The SWAT model (Soil and Water Assessment Tool) was developed in the United States to evaluate the effects of conservation agriculture on hydrological processes and water quality at the watershed scale. This model was initially proposed for use without calibration, which would eliminate the need for measured hydro-sedimentologic data. In this study, the SWAT model was evaluated in a small rural watershed (1.19 km²) located on the basalt slopes of the state of Rio Grande do Sul in southern Brazil, where farmers have been using cover crops associated with minimum tillage to control soil erosion. Values simulated by the model were compared with measured hydro-sedimentological data. Results for surface and total runoff on a daily basis were considered unsatisfactory (Nash-Sutcliffe efficiency coefficient - NSE < 0.5). However simulation results on monthly and annual scales were significantly better. With regard to the erosion process, the simulated sediment yields for all years of the study were unsatisfactory in comparison with the observed values on a daily and monthly basis (NSE values < -6), and overestimated the annual sediment yield by more than 100 %.

Analysis of variance of primary data on plant growth analysis

Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.

Biometrical analysis and selection of tetraploid progenies of Panicum maximum using mixed model methods

The objectives of this work were to estimate the genetic and phenotypic parameters and to predict the genetic and genotypic values of the selection candidates obtained from intraspecific crosses in Panicum maximum as well as the performance of the hybrid progeny of the existing and projected crosses. Seventy-nine intraspecific hybrids obtained from artificial crosses among five apomictic and three sexual autotetraploid individuals were evaluated in a clonal test with two replications and ten plants per plot. Green matter yield, total and leaf dry matter yields and leaf percentage were evaluated in five cuts per year during three years. Genetic parameters were estimated and breeding and genotypic values were predicted using the restricted maximum likelihood/best linear unbiased prediction procedure (REML/BLUP). The dominant genetic variance was estimated by adjusting the effect of full-sib families. Low magnitude individual narrow sense heritabilities (0.02-0.05), individual broad sense heritabilities (0.14-0.20) and repeatability measured on an individual basis (0.15-0.21) were obtained. Dominance effects for all evaluated characteristics indicated that breeding strategies that explore heterosis must be adopted. Less than 5% increase in the parameter repeatability was obtained for a three-year evaluation period and may be the criterion to determine the maximum number of years of evaluation to be adopted, without compromising gain per cycle of selection. The identification of hybrid candidates for future cultivars and of those that can be incorporated into the breeding program was based on the genotypic and breeding values, respectively. The prediction of the performance of the hybrid progeny, based on the breeding values of the progenitors, permitted the identification of the best crosses and indicated the best parents to use in crosses.

Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

The objective of this study was to assess genotype by environment interaction for seed yield per plant in rapeseed cultivars grown in Northern Serbia by the AMMI (additive main effects and multiplicative interaction) model. The study comprised 19 rapeseed genotypes, analyzed in seven years through field trials arranged in a randomized complete block design, with three replicates. Seed yield per plant of the tested cultivars varied from 1.82 to 19.47 g throughout the seven seasons, with an average of 7.41 g. In the variance analysis, 72.49% of the total yield variation was explained by environment, 7.71% by differences between genotypes, and 19.09% by genotype by environment interaction. On the biplot, cultivars with high yield genetic potential had positive correlation with the seasons with optimal growing conditions, while the cultivars with lower yield potential were correlated to the years with unfavorable conditions. Seed yield per plant is highly influenced by environmental factors, which indicates the adaptability of specific genotypes to specific seasons.

Base temperature and simulation model for nodes appearance in cape gooseberry (Physalis peruviana L.)

Data was analyzed on development of the solanaceen fruit crop Cape gooseberry to evaluate how well a classical thermal time model could describe node appearance in different environments. The data used in the analysis were obtained from experiments conducted in Colombia in open fields and greenhouse condition at two locations with different climate. An empirical, non linear segmented model was used to estimate the base temperature and to parameterize the model for simulation of node appearance vs. time. The base temperature (Tb) used to calculate the thermal time (TT, ºCd) for node appearance was estimated to be 6.29 ºC. The slope of the first linear segment was 0.023 nodes per TT and 0.008 for the second linear segment. The time at which the slope of node apperance changed was 1039.5 ºCd after transplanting, determined from a statistical analysis of model for the first segment. When these coefficients were used to predict node appearance at all locations, the model successfully fit the observed data (RSME=2.1), especially for the first segment where node appearance was more homogeneous than the second segment. More nodes were produced by plants grown under greenhouse conditions and minimum and maximum rates of node appearance rates were also higher.

Hydrological simulation using SWAT model in headwater basin in Southeast Brazil

Hydrological models are important tools that have been used in water resource planning and management. Thus, the aim of this work was to calibrate and validate in a daily time scale, the SWAT model (Soil and Water Assessment Tool) to the watershed of the Galo creek , located in Espírito Santo State. To conduct the study we used georeferenced maps of relief, soil type and use, in addition to historical daily time series of basin climate and flow. In modeling were used time series corresponding to the periods Jan 1, 1995 to Dec 31, 2000 and Jan 1, 2001 to Dec 20, 2003 for calibration and validation, respectively. Model performance evaluation was done using the Nash-Sutcliffe coefficient (E NS) and the percentage of bias (P BIAS). SWAT evaluation was also done in the simulation of the following hydrological variables: maximum and minimum annual daily flowsand minimum reference flows, Q90 and Q95, based on mean absolute error. E NS and P BIAS were, respectively, 0.65 and 7.2% and 0.70 and 14.1%, for calibration and validation, indicating a satisfactory performance for the model. SWAT adequately simulated minimum annual daily flow and the reference flows, Q90 and Q95; it was not suitable in the simulation of maximum annual daily flows.

Bartlett-Lewis of rectangular pulse modified model: estimate of parameters for simulation of precipitation in sub-hourly duration

The Bartlett-Lewis Rectangular Pulse Modified (BLPRM) model simulates the precipitous slide in the hourly and sub-hourly and has six parameters for each of the twelve months of the year. This study aimed to evaluate the behavior of precipitation series in the duration of 15 min, obtained by simulation using the model BLPRM in situations: (a) where the parameters are estimated from a combination of statistics, creating five different sets; (b) suitability of the model to generate rain. To adjust the parameters were used rain gauge records of Pelotas/RS/Brazil, which statistics were estimated - mean, variance, covariance, autocorrelation coefficient of lag 1, the proportion of dry days in the period considered. The results showed that the parameters related to the time of onset of precipitation (λ) and intensities (μx) were the most stable and the most unstable were ν parameter, related to rain duration. The BLPRM model adequately represented the mean, variance, and proportion of the dry period of the series of precipitation lasting 15 min and, the time dependence of the heights of rain, represented autocorrelation coefficient of the first retardation was statistically less simulated series suitability for the duration of 15 min.

Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil

ABSTRACTChanges in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data.

The terrestrial Gastropoda Megalobulimus abbreviatus as a useful model for nociceptive experiments: effects of morphine and naloxone on thermal avoidance behavior

We describe the behavior of the snail Megalobulimus abbreviatus upon receiving thermal stimuli and the effects of pretreatment with morphine and naloxone on behavior after a thermal stimulus, in order to establish a useful model for nociceptive experiments. Snails submitted to non-functional (22ºC) and non-thermal hot-plate stress (30ºC) only displayed exploratory behavior. However, the animals submitted to a thermal stimulus (50ºC) displayed biphasic avoidance behavior. Latency was measured from the time the animal was placed on the hot plate to the time when the animal lifted the head-foot complex 1 cm from the substrate, indicating aversive thermal behavior. Other animals were pretreated with morphine (5, 10, 20 mg/kg) or naloxone (2.5, 5.0, 7.5 mg/kg) 15 min prior to receiving a thermal stimulus (50ºC; N = 9 in each group). The results (means ± SD) showed an extremely significant difference in response latency between the group treated with 20 mg/kg morphine (63.18 ± 14.47 s) and the other experimental groups (P < 0.001). With 2.5 mg/kg (16.26 ± 3.19 s), 5.0 mg/kg (11.53 ± 1.64 s) and 7.5 mg/kg naloxone (7.38 ± 1.6 s), there was a significant, not dose-dependent decrease in latency compared to the control (33.44 ± 8.53 s) and saline groups (29.1 ± 9.91 s). No statistically significant difference was found between the naloxone-treated groups. With naloxone plus morphine, there was a significant decrease in latency when compared to all other groups (minimum 64% in the saline group and maximum 83.2% decrease in the morphine group). These results provide evidence of the involvement of endogenous opioid peptides in the control of thermal withdrawal behavior in this snail, and reveal a stereotyped and reproducible avoidance behavior for this snail species, which could be studied in other pharmacological and neurophysiological studies.

Exercise training prevents increased intraocular pressure and sympathetic vascular modulation in an experimental model of metabolic syndrome

The present study aimed to study the effects of exercise training (ET) performed by rats on a 10-week high-fructose diet on metabolic, hemodynamic, and autonomic changes, as well as intraocular pressure (IOP). Male Wistar rats receiving fructose overload in drinking water (100 g/L) were concomitantly trained on a treadmill for 10 weeks (FT group) or kept sedentary (F group), and a control group (C) was kept in normal laboratory conditions. The metabolic evaluation comprised the Lee index, glycemia, and insulin tolerance test (KITT). Arterial pressure (AP) was measured directly, and systolic AP variability was performed to determine peripheral autonomic modulation. ET attenuated impaired metabolic parameters, AP, IOP, and ocular perfusion pressure (OPP) induced by fructose overload (FT vs F). The increase in peripheral sympathetic modulation in F rats, demonstrated by systolic AP variance and low frequency (LF) band (F: 37±2, 6.6±0.3 vs C: 26±3, 3.6±0.5 mmHg2), was prevented by ET (FT: 29±3, 3.4±0.7 mmHg2). Positive correlations were found between the LF band and right IOP (r=0.57, P=0.01) and left IOP (r=0.64, P=0.003). Negative correlations were noted between KITT values and right IOP (r=-0.55, P=0.01) and left IOP (r=-0.62, P=0.005). ET in rats effectively prevented metabolic abnormalities and AP and IOP increases promoted by a high-fructose diet. In addition, ocular benefits triggered by exercise training were associated with peripheral autonomic improvement.