2 resultados para Nonlinear correlation coefficients

em Repositório Institucional da Universidade Tecnológica Federal do Paraná (RIUT)


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The instability of environment between years in climates of subtropical regions difficult to obtain peach trees genotypes with wide adaptation and stable production, contributing to poor crop. The climate instability can affect development stages as flower bud and vegetative bud formation. The factors understanding that control the bud formation, presents elementary importance for effective solutions search to these problems. The objective this work is verify the temperature effect, relative humidity and rainfall on bud density and length shoot (Brindilas) and identify genotypes with more adaptability and stability for this character. Was used 12 peach trees genotypes growing in experimental orchard in the Technology Federal of Paraná State University, Campus Pato Branco with Cfa Köppen climate according to the classification. Data of rainfall, hourly temperature were collected by the weather station of Simepar. They were used three plants for genotype (rehearsal), identify five shoots per tree, in May of each year. Were carried analyzes of length shoot CR (cm), count number of flower bud (GF) and vegetative bud (GV). Also calculated the relationship between GF/GV and flower bud density and vegetative bud density. Evaluations were performer annual 2007-2014. With these data adaptability and stability analyzes were performed using Biplot methodology and correlations analyzes (Pearson) with climates variables. They used the weather data to calculate the sums of hours with temperatures below 20 °C, temperatures between 20-25 °C, temperature between 25-30 °C and temperature above 30 °C, considering the period of August 1fst of the previous period to February 28 of the following year. Pearson correlation coefficients were used for path analysis, GF and DGF as basic variables. For CR, GV and GF the highest average occurred in 2009/10 period. The genotypes ‘BRS Kampai’ and ‘BRS Libra’ highest CR. They are considered stable and adapted as the CR genotypes ‘Casc. 967’ and ‘BRS Kampai’. There was negative correlation between CR and GV for Σh <20 ° C, Σh> 30 °C and Σh with URA <50% and positive correlation between these variables and Σh 25-30 °C and Σh with URA> 70%. The evaluation of GV ‘Cons. 681’ and ‘Casc. 1055’ can be considered adapted and stable. The lowest average was presented by the genotype ‘Sta. Áurea’ though the genotype is also stable. In GF evaluation genotypes are considered adapted ‘BRS Bonão’, ‘Casc. 1055’, ‘Cons. 681’ with adaptability to all evaluated period. In path analysis was direct effect Σh 25-30 °C on flower bud density. In evaluating DGV and DGF and the variations are due to genetic effect. The most adapted and stable genotypes for DGV were ‘T. Beauty’, ‘T. Snow’, ‘Casc. 1055’ and ‘Cons. 681’. CR and GV variables are strongly affected by environment. GF is strongly affected by genetic conditions and moderately affected by environment. DGV and DGF are affected basically by genetic conditions.

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Considering the social and economic importance that the milk has, the objective of this study was to evaluate the incidence and quantifying antimicrobial residues in the food. The samples were collected in dairy industry of southwestern Paraná state and thus they were able to cover all ten municipalities in the region of Pato Branco. The work focused on the development of appropriate models for the identification and quantification of analytes: tetracycline, sulfamethazine, sulfadimethoxine, chloramphenicol and ampicillin, all antimicrobials with health interest. For the calibration procedure and validation of the models was used the Infrared Spectroscopy Fourier Transform associated with chemometric method based on Partial Least Squares regression (PLS - Partial Least Squares). To prepare a work solution antimicrobials, the five analytes of interest were used in increasing doses, namely tetracycline from 0 to 0.60 ppm, sulfamethazine 0 to 0.12 ppm, sulfadimethoxine 0 to 2.40 ppm chloramphenicol 0 1.20 ppm and ampicillin 0 to 1.80 ppm to perform the work with the interest in multiresidues analysis. The performance of the models constructed was evaluated through the figures of merit: mean square error of calibration and cross-validation, correlation coefficients and offset performance ratio. For the purposes of applicability in this work, it is considered that the models generated for Tetracycline, Sulfadimethoxine and Chloramphenicol were considered viable, with the greatest predictive power and efficiency, then were employed to evaluate the quality of raw milk from the region of Pato Branco . Among the analyzed samples by NIR, 70% were in conformity with sanitary legislation, and 5% of these samples had concentrations below the Maximum Residue permitted, and is also satisfactory. However 30% of the sample set showed unsatisfactory results when evaluating the contamination with antimicrobials residues, which is non conformity related to the presence of antimicrobial unauthorized use or concentrations above the permitted limits. With the development of this work can be said that laboratory tests in the food area, using infrared spectroscopy with multivariate calibration was also good, fast in analysis, reduced costs and with minimum generation of laboratory waste. Thus, the alternative method proposed meets the quality concerns and desired efficiency by industrial sectors and society in general.