Seleção e divergência genética de pessegueiros e nectarineiras e susceptibilidade a danos causados pelo frio na Estación Experimental de Aula Dei (CSIC)

The peaches and nectarines are highly appreciated by consumer, but it is climacteric fruits, with availability in the market in small time. It is necessary to invest to obtain genotypes with fruit quality and small perishability or that it presente less physiological disorders after storage. The aims of this work were i) to evaluate the genetic divergence among 40 peach and nectarine trees genotypes based on postharvest quality and select posible parents; ii) to evaluate the susceptibility to chilling injury in peaches and nectarines after cold storage; iii) to evaluate divergence of peaches and nectarines on the basis in the susceptibility for chiling injury and select superior genotypes; iv) evaluate the correlations between quality and susceptibility to chilling injury of peaches and nectarines v) select parents with the combination of lower susceptibility to chilling injury and higher quality fruit. The study was carried out in EEAD-CSIC, Zaragoza - Spain, during the production cycle 2013/2014. A total of 40 peaches and nectarines genotypes from germplasm collection were evaluated. The quality characteristics as flesh firmness, total soluble solids, titratable acidity, pH, rippining index and flesh color parameters were evaluated. The fruits were submitted to cold storage at 0 °C and 5 °C, with 95% average relative humidity. The evaluations were after 14 and 28 days, it being observed the presence of symptoms, such as wooliness through mealiness, flesh grainy, leatheriness and flesh color changes, through browning, bleeding and off flavor. As a selection parameter was adopted 20% of genotypes that had a higher frequency of superiority for quality characteristics, susceptibility to chilling injury and the combining of both. For quality characteristic presented greater divergence the ‘Queen Giant’, ‘Sudanel Blanco’ and ‘Borracho de Jarque’. Based on the quality the eight genotypes were selected, ‘Andross’, ‘San Jaime’, ‘San Lorenzo’, ‘Borracho de Jarque’, ‘Sudanell 1’, ‘Carson’, ‘Baby Gold 6’ and ‘Stanford’. All genotypes studied exhibited susceptibility to one or more symptoms caused by cold storage during 28 days, independent of temperature. For 14 days, the ‘Baby Gold 6’, ‘Flavortop’ and ‘Queen Giant’ genotypes did not show any physiological disorder caused by cold. In general, the temperature of 0 °C favored fruit postharvest conservation, it have a lower incidence and severity of symptoms caused by cold storage. The storage for 14 days contributed for the lower incidence of damage in the genotypes fruits studied. For 14 days, with both temperatures, it was observed divergence for ‘Queen Giant’, ‘Sudanell Blanco’, ‘Baby Gold 6’ ‘GF3’, ‘Baby Gold 8’, ‘Campiel’ and ‘Campiel Rojo’ genotypes. For 28 days, in the 5 °C condition, ‘Queen Giant’, ‘Big Top’, ‘Flavortop’ and ‘Redhaven’ genotypes were divergents. Based on susceptibility to chilling injury at 0 °C, the eight genotypes were selected, it being these, ‘Queen Giant’, ‘Keimoes’, ‘Flavortop’, ‘Big Top’, 'Redhaven', 'Sudanell 3', 'Bonet I' and ‘Carson’. The quality parameters as rippining index, soluble solids, firmness and titratable acidity presented correlation among them. These, also it had correlation with woolines and bowning, what it indicate that fruits with more ripening can have this symptoms more easily. The browning, mealiness, flesh grainy and off flavor variables were correlationed with the time period and temperartures, what it confirm that these symptoms are the main disorders caused by cold storage. The quality characteristics together susceptibility to chilling injury allowed selected ‘Baby Gold 6’, ‘Sarell’, ‘Keimoes’, ‘GF3’ ‘San Jaime’, ‘Big Top’, ‘Sudanell 1’, ‘Carson’, ‘Baby Gold 8’, and ‘San Lorenzo’ genotypes.

Desenvolvimento e aplicação de modelo de calibração multivariada para determinação de açúcares e ácidos orgânicos em bebidas comerciais utilizando espectroscopia no infravermelho

The routine analysis for quantization of organic acids and sugars are generally slow methods that involve the use and preparation of several reagents, require trained professional, the availability of special equipment and is expensive. In this context, it has been increasing investment in research whose purpose is the development of substitutive methods to reference, which are faster, cheap and simple, and infrared spectroscopy have been highlighted in this regard. The present study developed multivariate calibration models for the simultaneous and quantitative determination of ascorbic acid, citric, malic and tartaric and sugars sucrose, glucose and fructose, and soluble solids in juices and fruit nectars and classification models for ACP. We used methods of spectroscopy in the near infrared (Near Infrared, NIR) in association with the method regression of partial least squares (PLS). Were used 42 samples between juices and fruit nectars commercially available in local shops. For the construction of the models were performed with reference analysis using high-performance liquid chromatography (HPLC) and refractometry for the analysis of soluble solids. Subsequently, the acquisition of the spectra was done in triplicate, in the spectral range 12500 to 4000 cm-1. The best models were applied to the quantification of analytes in study on natural juices and juice samples produced in the Paraná Southwest Region. The juices used in the application of the models also underwent physical and chemical analysis. Validation of chromatographic methodology has shown satisfactory results, since the external calibration curve obtained R-square value (R2) above 0.98 and coefficient of variation (%CV) for intermediate precision and repeatability below 8.83%. Through the Principal Component Analysis (PCA) was possible to separate samples of juices into two major groups, grape and apple and tangerine and orange, while for nectars groups separated guava and grape, and pineapple and apple. Different validation methods, and pre-processes that were used separately and in combination, were obtained with multivariate calibration models with average forecast square error (RMSEP) and cross validation (RMSECV) errors below 1.33 and 1.53 g.100 mL-1, respectively and R2 above 0.771, except for malic acid. The physicochemical analysis enabled the characterization of drinks, including the pH working range (variation of 2.83 to 5.79) and acidity within the parameters Regulation for each flavor. Regression models have demonstrated the possibility of determining both ascorbic acids, citric, malic and tartaric with successfully, besides sucrose, glucose and fructose by means of only a spectrum, suggesting that the models are economically viable for quality control and product standardization in the fruit juice and nectars processing industry.