Estimation of reference evapotranspiration (ETo) is very relevant for water resource management. The Penman-Monteith (PM) equation was proposed by the Food and Agriculture Organization (FAO) as the standard method for estimation of ETo. However, this method requires various weather data, such as air temperature, wind speed, solar radiation and relative humidity, which are often unavailable. Thus, the objective of this study was to compare the performance of multivariate adaptive regression splines (MARS) and alternative equations, in their original and calibrated forms, to estimate daily ETo with limited weather data. Daily data from 2002 to 2016 from 8 Brazilian weather stations were used. ETo was estimated using empirical equations, PM equation with missing data and MARS. Four data availability scenarios were evaluated as follows: temperature only, temperature and solar radiation, temperature and relative humidity, and temperature and wind speed. The MARS models demonstrated superior performance in all scenarios. The models that used solar radiation showed the best performance, followed by those that used relative humidity and, finally, wind speed. The models based only on air temperature had the worst performance.
The estimation of the reference evapotranspiration is an important factor for hydrological studies, design and management of irrigation systems, among others. The Penman Monteith equation presents high precision and accuracy in the estimation of this variable. However, its use becomes limited due to the large number of required meteorological data. In this context, the Hargreaves-Samani equation could be used as alternative, although, for a better performance a local calibration is required. Thus, the aim was to compare the calibration process of the Hargreaves-Samani equation by linear regression, by adjustment of the coefficients (A and B) and exponent (C) of the equation and by combinations of the two previous alternatives. Daily data from 6 weather stations, located in the state of Minas Gerais, from the period 1997 to 2016 were used. The calibration of the Hargreaves-Samani equation was performed in five ways: calibration by linear regression, adjustment of parameter “A”, adjustment of parameters “A” and “C”, adjustment of parameters “A”, “B” and “C” and adjustment of parameters “A”, “B” and “C” followed by calibration by linear regression. The performances of the models were evaluated based on the statistical indicators mean absolute error, mean bias error, Willmott’s index of agreement, correlation coefficient and performance index. All the studied methodologies promoted better estimations of reference evapotranspiration. The simultaneous adjustment of the empirical parameters “A”, “B” and “C” was the best alternative for calibration of the Hargreaves-Samani equation.
The objective of this study was to characterize banana tree endophytic bacteria at genus and species level and to determine the metabolic reactions associated with the nitrogen transformations. The identification at genus and species levels was performed using the partial sequencing of the rDNA 16S region. The assimbyotic nitrogen fixation, the reduction of nitrate and the production of urease were in vitro evaluated. The DNA of the bacterial isolates was also amplified to verify the presence of the nifH, nirK and nirS regions. Biochemical tests were performed in a complete randomized design; the treatments consisted of 39 bacterial isolates with three replications. Sequence analysis enabled the identification of four genera: Bacillus, Rhizobium, Klebsiella and Enterobacter. The Bacillus genus occurred more frequently, nine species were identified. By evaluating the results of biochemical tests, it was observed that three isolates showed multiple abilities: growth in NFb medium, nitrate reduction and production of urease. The isolates belong to the genus Bacillus and of the species subtilis, thuringienses and amyloliquefaciens. Approximately 12.5% of the isolates amplified the region corresponding to the nifH gene, 7.5% amplified gene nirK and 3.9% amplified the nirS gene. Endophytic bacteria evaluated in the present study showed in vitro activity for urease, nitrate reductase enzymes, however, relevant nitrogenase activity was not observed.
-The aim of this study was to quantify the influence of some environmental and genotypic variables on genotype by environment (GE) interactions in soybean. Mean yield data from eighteen test genotypes in eleven experiments in Goiás State, Brazil, were used and analyzed by AMMI method. To identify environmental and genotypic variables related to the GE interaction, simple linear correlations were estimated between the means of these variables and the scores of the first AMMI principal component of the interactions. Successive simple linear regression analyses were also carried stepwise, in order to relate the GE interaction of each genotype to the observed environmental factors. The environmental factors that influenced the GE interactions most were altitude, maximum temperature, end-of-cycle disease complex, total rainfall and soil fertility.The genotypic variables days to maturity and reaction to end-of-cycle disease complex were most associated with GE interactions.
Methodologies for imposing stress and reproducible results are a bottleneck for breeding programmes, and this is due to the lack of consensus between the existing methodologies. The aim of the present study was to propose and validate a new methodology for imposing water deficit in soybean that allows the identification of water deficit-tolerant genotypes, at different harvest times and phenological stages.The methodology was based on the construction of a water retention curve in the soil to determine the water stresses that indicate the field capacity and the permanent wilt point and, thus, define the water regime in the conditions of control and stress. Seven trials were carried out to validate the methodology. In trials 1, 2, 3, 4, 5 and 6, the water deficit was imposed in the reproductive phase and the components of production were evaluated. In addition to these variables, leaf water potential was evaluated in trial 6. In trial 7, the plants were subjected to water deficit in the vegetative phase and the morphological traits were evaluated. The efficiency of the methodology was confirmed by the distinction between the conditions of control and stress, affirmed by the statistical differences in most of the traits evaluated in the reproductive and vegetative phases.
The umbu (Spondias tuberosa Arruda) is a fruit tree adapted to the Brazilian semiarid region and constitutes an important source of income for many families in Brazil. Due to this, sustainable methods of fruit postharvest conservation should be studied. The objective of this study was to analyze the influence of cassava starch-based biofilm coatings for the postharvest conservation of umbu. The experimental design was completely randomized in a 2x5 factorial arrangement with six replicates. The two treatments, 1% cassava starch coating and no coating, were evaluated during five periods (0, 3, 6, 9, and 12 d of storage). Fresh weight loss (WL), fruit firmness (FIR), pH, total soluble solids (TSS), total titratable acidity (TA), TSS/TA ratio, external color: luminosity (L*), hue angle (H*), and chromaticity (C*) were measured. The coating of fruits with cassava starch-based biofilm improved WL, pH, and TSS. The variables TA, TSS/TA ratio, and L* were not influenced by the use or absence of the cassava starch biofilm coating. The use of 1% cassava starch to coat the fruits ensures better postharvest quality of the umbu and extends its posthavest life.
ABSTRACT:The reference evapotranspiration (ET o ) is an important component for determining the water requirements of the crops. In order to estimate this variable accurately, the Food and Agriculture Organization (FAO) proposed the Penman-Monteith equation, however, this demands a large number of meteorological data, which restricts its use. In this context, this study compares the performance of the Penman-Monteith equation using only measured air temperature (PMT) and the Hargreaves-Samani (HS) equation with the performance of the multivariate adaptive regression splines (MARS) technique for the daily ET o estimation with only air temperature data. For the study, daily meteorological data from 2002 to 2016 were used. The data were collected from weather stations located in Florianópolis-SC, Manaus-AM and Petrolina-PE, being these selected in order to capture different climatic conditions. MARS models were developed for each weather station and the PMT e HS equations were locally calibrated. The performances of the original and calibrated equations and MARS models were evaluated based on the statistical indices root mean square error, mean absolute error, mean bias error and coefficient of determination. The ET o estimated by the Penman-Monteith method with full data was used as reference for the development of the MARS models, calibration of the equations and for the performance evaluation of the models under study. The calibration of the HS and PMT equations promoted better performances in relation to the original equations, improving the methods accuracy. The MARS technique presented good performance, outperforming the original and calibrated PMT and HS equations, with lower error values and higher coefficient of determination, and can be considered as an alternative to empirical methods.
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