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The aim of this study was to develop and validate qualitative and quantitative models to discriminate different types of maize and also estimate biochemical constituents. Spectral data were taken from the central leaf of randomly-chosen plants grown in field trials in 2011 and 2012. Leaf chlorophyll and protein content and stalk protein content were determined in the same plants. Four different Support Vector Machine (SVM) models were generated and validated in this study. In qualitative models, maize type was designated as dependent variable while Full Spectral (FS) data (400-1,000 nm) and Spectral Indices (SI) data (34 indices/bands) were independent variables. In the two quantitative models (SVMR-FS and SVMR-SI), independent variables were the same, whereas dependent variables were assigned as the quantitatively measured traits. Results showed the qualitative models to be a robust method of classification for distinguishing different maize types, such as High Oil Maize (HOM), High Protein Maize (HPM) and standard (NORMAL) maize genotypes. The SVMC-FS model was superior to SVMC-SI in terms of the genotypic classification of maize plants. Quantitative models with full spectral data gave more robust prediction than the others. The best prediction result (RMSEC= 222.4 µg g^-1, R² for Cal= 0.739, SEP= 213.3 µg g^-1; RPD= 2.04 and r= 0.877) was obtained from the SVMR-FS model developed for chlorophyll content. Indirect estimation models, based on relationships between leaf-based spectral measurements and leaf and stalk protein content, were less satisfactory.

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The concentration of heavy metals (Hg, Cd, As, Cu, Pb, Cr, and Zn) in the water, sediment and fish (Mugil cephalus) were investigated from different sites on Köyceğiz Lagoon System. Potential ecological risk analysis of heavy metal concentrations in sediments underlined considerable ecological risk for two sites of the lagoon during winter and spring. The ratio of transfer factors of Hg, Cr, Cu, Zn, and As in fish from water was higher than 1, which means that fish undergo bioaccumulation of these elements from lagoon water. The determination of individual Target Hazard Quotients (THQs) in fish tissue indicated safe levels for the local people, but there is a possible risk in terms of total THQ because the highest THQ value of As suggests that they may experience a certain degree of adverse health effect.

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 The aim of this study was to determine Total Phenolic Compound (TPC) and antioxidant activity changes depending on the ripening in Rosa canina, R. dumalis, R. dumalis ssp. boissieri and R. villosa rosehip species. Rosehip fruits were harvested in 6 different times from July to September. TPC content and antioxidant activities were determined by spectrophotometric methods. TPC and antioxidant activities of the studied species increased during ripening. TPC (1510.57 mg GAE 100 g^-1/H-6) and antioxidant activities (TEAC: 364.12 µmol trolox equivalent g^-1/H-6 and FRAP: 286.79 µmol trolox equivalent g^-1/H-6) were higher in R. dumalis (MR-15) than the other studied species. There was a high correlation between the TPC and the antioxidant activity. Also, there was a positive correlation between maturation, phenolics and antioxidant activities. This correlation was high in R. dumalis and low in R. canina. However, it was not possible to express the existence of a relationship between temperature, TPC, and antioxidant activity. It was possible to express the existence of correlations between the color of fruits and some studied characteristics. The correlations between the colors of the fruits and TPC and antioxidant activity of R. dumalis were found higher than the other species.