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The aim of this study was to detect the effect of drum-drying parameters on certain physical and chemical properties of apple puree powder. Optimum drying conditions were determined using the Response Surface Methodology (RSM). The qualities of apple puree powder products were investigated in terms of water activity, pH, color, phenolics, antioxidant activity and sensory properties. Apple puree (13 Bx°) and maltodextrin (10 DE) were used as the raw material and carrier agent, respectively. Steam pressure, rotational speed and the puree/maltodextrin ratio were chosen as variable parameters. The effects of three of the parameters mentioned were found to be statistically significant: water activity, pH, and the a* and b* parameters of the powders (P< 0.05). In this study, the results showed that the optimum drying parameters and the highest desirability could be obtained for a treatment using a 60/40 apple puree/malodextrin ratio at 3.5 bar steam pressure and a 1 rpm drum rotation speed.
 

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Association analysis using phenotypic information and molecular markers may provide valuable information for molecular breeding and marker-assisted selection. The objectives of this study were to determine markers associated with sugar parameters and important agronomic traits of watermelon and to estimate the level of genetic diversity. Ninety-six watermelon lines were genotyped by combining SSR (Simple Sequence Repeat), ISSR (Inter-Simple Sequence Repeat) and iPBS (Inter-Priming Binding Sites) marker data. These genotypes were also assessed for population structure, Linkage Disequilibrium (LD), and Association Mapping (AM) of sugar parameters and other important agronomic traits. In the analysis, 583 markers had LD values to a certain degree. A general linear model was developed using only the Q matrix showing the population structure in association mapping, a complex linear model using a kinship matrix, and a complex linear model using both the Q and K matrix linear models. The regression model explanation rates for the 26 characters varied from 11.3 to 81.3%. The highest rates of regression model explanation were measured for fruit firmness (81.3%) and fruit height (78.2%). It might be possible to determine the genes associated with these studied characteristics, to contribute to future genetic and breeding studies, and to be used in Marker-Assisted Selection (MAS) studies.