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Articles by Mehmet Serhat Odabas
Total Records ( 2 ) for Mehmet Serhat Odabas
  Mehmet Serhat Odabas and Zeki Mut
  The aim of this study was to investigate the possibility to predict by mathematical models seed germination percentage and days to germination on the basis of temperature. Seed from legumes and cereals were used: faba bean (Vicia faba L.), bean (Phaseolus vulgaris L.), pea (Pisum sativum L.), cowpea (Vigna sinensis L.) and some cereals; bread wheat (Triticum aestivum L.), durum wheat (Triticum durum L.), Barleys (Hordeum vulgare conv. distichon and Hordeum vulgare conv. hexastichon), oat (Avena sativa L.), Triticale (Triticale withmack), Rice (Oryza sativa L.), rye (Secale cereale L.), pop corn (Zea mays everta Sturt.), maize (Zea mays indentata Sturt.) and Johnson grass (Sorghum halepense L.) was investigated by mathematical models based on temperature. For this reason a model D = a-(bxT)+(cxT2) produced earlier for predicting the time to emergence in relation to temperature for some vegetable crops was utilized. The final structure of the model did not change for predicting the days to germination of the tried grain legumes while it changed to GP = a+(bxT)-(cxT2) for predicting Germination Percentage (GP) of the crops tried. It was found that the new mathematical models obtained after adapting the present data to the above mentioned model could be applied in terms of the studied parameters. In addition, optimum temperature for seed germination was calculated by using the coefficients T0 = [-b/(2xc)] obtained from the regression models of the days to germination.
  Mehmet Serhat Odabas , Jolita Radusiene , Cuneyt Cırak and Necdet Camas
  In the present study, models for estimation of the content of main secondary metabolites, namely hypericin, pseudohypericin, and hyperforin, were developed for Hypericum origanifolium Willd. (Guttiferae), Hypericum perfoliatum L., and Hypericum montbretii Spach., growing in Northern Turkey. Wild growing plants were harvested at vegetative, floral budding, full flowering, fresh fruiting, and mature fruiting stages and dissected into stem, leaf, and reproductive tissues. Actual secondary metabolite contents of plant materials were measured by a high performance liquid chromatography method. Multiple regression analysis using the Excel 2003 computer package was performed for each species and chemical separately to develop multiple regression models. The equation produced for predicting the content of secondary metabolites in different tissues of the species was formulized as: SMC=[a + (b1x S) + (b2x L) + (b3x RP) + (b4x S2) + (b5x (1/RP))], where SMC is the secondary metabolite content of the whole plant, S is the secondary metabolite content of the stem, L is the secondary metabolite content of the leaf, RP is the secondary metabolite content of the reproductive parts, and a, b1, b2, b3, b4, and b5 are coefficients. The R2 coefficient values between predicted and observed contents of secondary metabolites were determined as 0.99 for H. origanifolium, 0.95-0.98 for H. perfoliatum, and 0.90-0.99 for H. montbretii. All R2 values and standard errors were found to be significant at the p<0.05 level.
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