Yazar "Kahriman, Fatih" seçeneğine göre listele

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    Enhancing near-infrared spectroscopy calibration for accurate protein and gluten determination in wheat flour and intact grains using chemometric techniques
    (Taylor & Francis Inc, 2025) Altay, Mustafa Emre; Kahriman, Fatih
    Rapid and reliable determination of protein and gluten in wheat is crucial for quality assessment and process control. Near-infrared (NIR) spectroscopy provides a nondestructive alternative to conventional chemical analysis; however, its predictive performance depends strongly on preprocessing and modeling strategy. This study evaluated how different combinations of scatter correction, derivative, and wavelength-selection methods influence NIR calibration performance for predicting protein and gluten contents in both wheat flour and intact grain samples, using Partial Least Squares (PLS) and Support Vector Machine (SVM) regression models under identical conditions. The results demonstrated that SVM achieved superior prediction accuracy for both protein and gluten contents, particularly when combined with Standard Normal Variate (SNV) preprocessing and mild smoothing. Among the best-performing models, those developed from flour-based spectra generally achieved higher coefficients of determination (R2, Coefficient of Determination, up to 0.96) than those based on grain spectra (R2 approximate to 0.88-0.90), reflecting reduced scattering and greater compositional uniformity in flour samples. The most successful combinations were SNV + SVM for protein prediction (R2 = 0.99) and smoothing + SNV + Genetic Algorithm-Partial Least Squares (GA-PLS) + SVM for gluten prediction (R2 = 0.93). Overall results revealed that combining NIR spectroscopy with optimized preprocessing and machine-learning algorithms enables rapid and precise quantification of wheat quality traits, supporting its broader application in industrial quality control and breeding programs.
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    EVALUATION DIFFERENCES BETWEEN HAPLOID AND DIPLOID MAIZE SAMPLES AND CUT-OFF POINTS DETERMINATION FOR SEPARATION HAPLOIDS USING DECISION TREE TECHNIQUE
    (Univ Agronomic Sciences & Veterinary Medicine Bucharest - Usamv, 2025) Tunc, Talha; Kahriman, Fatih
    This study aims to assess the discrimination success of these measurements on seeds, germinated seeds, and seedlings of haploid and diploid maize samples, using cytogenetic verification by acetocarmin staining. This study was conducted in the Laboratory of Field Crops, & Ccedil;anakkale Onsekiz Mart University. The decision tree method was used to determine which of the measured traits was effective in differentiating haploid/diploid samples. The results of study showed that the success of visual discrimination according to Navajo marker was 85% for haploid samples and 96% for diploid samples. Differences between haploid and diploid samples varied by donor material, with hybrid donors showing more pronounced disparities. Decision tree analysis revealed that the root length and seed circumference as effective traits to distinguish haploids from diploids. In conclusion, visual differentiation based only seed coloration can be misleading, highlighting the importance of multiple measurements for accurate haploid identification using the in vivo doubled haploid technique.
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    Genetic diversity of Turkish colored maize landraces assessed by simple sequence repeat (SSR) markers
    (Springer, 2025) Yildirim, Ezgi Alaca; Kahriman, Fatih; Matur, Ferhat
    Assessing genetic diversity in maize landraces is critical for conserving genetic resources and unlocking their potential for use in breeding programs. This study investigated the genetic diversity of 34 Turkish colored maize landraces using 28 simple sequence repeat (SSR) markers. Genetic variation was evaluated through gene differentiation and fixation index (Fst) analysis, complemented by Nei's gene diversity index (h), Jaccard similarity index (J), and unweighted pair group method with arithmetic mean (UPGMA) to examine genetic relationships among populations. The SSR markers exhibited high polymorphic informativeness and discrimination power, highlighting their effectiveness in assessing genetic diversity. The analysis revealed expected heterozygosity (He) values ranging from 0.1023 to 0.8832, Nei's gene diversity index (h) of 0.5458, Shannon's diversity index (I) of 1.0338, and Jaccard similarity index (J) values between 0.06 and 0.289, indicating substantial genetic variation among the landraces. These findings demonstrate the significant genetic diversity present in Turkish colored maize landraces and underscore their value as a genetic reservoir for breeding programs focused on agronomic or quality traits. Integrating these results with field performance evaluations may offer valuable insights and contribute to the development of improved maize cultivars.
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    Impact of Kernel Opacity on Protein Content, Some Essential Amino Acids, and Zein Film Properties in Maize
    (Springer, 2025) Gumus, Muhammet; Danisman, Merve; Kibar, Kubra; Yakar, Emin; Oral, Ayhan; Kahriman, Fatih
    Opacity is one of the key indicators of protein quality in maize. Compared to normal maize genotypes, opaque maize contains higher amounts of essential amino acids, contributing to higher levels of lysine and tryptophan, which are limiting in maize diets. These essential amino acids are particularly critical for zeins, the dominant protein fraction in maize, as zeins serve as valuable raw materials with both industrial and nutritional applications. Although zein-based films have been widely studied, there is limited research comparing the properties of zein films derived from maize samples with different kernel opacity levels. In this study, a maize genotype known to possess the opaque trait was used to obtain samples with five different opacity levels. Protein, lysine, and tryptophan content variations were analyzed in flour, raw zein, and zein film samples. Additionally, the dynamic mechanical analysis (DMA) of zein films was performed according to opacity levels. The data obtained were statistically evaluated using one-way analysis of variance (ANOVA), and differences between means were compared using the least significant difference (LSD) test (P < 0.05). The protein content was found to range between 7.6 and 10.14% in flour and 80.6-86.9% in raw zein. Lysine content varied between 1.00 and 1.81% in flour and 0.03-2.28% in raw zein, while tryptophan content ranged from 0.175 to 0.228% in flour to 0.38-2.17% in raw zein. An increase in opacity level led to a decrease in protein content; however, it significantly enhanced the essential amino acid content across all sample types. Furthermore, opacity levels had a substantial impact on the structural properties of zein films. Significant differences were observed among the film samples in terms of color intensity (e.g., L* values ranging from 83.64 in PVA-PEG control to 68.34 in PVA-PEG-Zein100), chroma (2.64 to 40.45), and hue angle (23.30 degrees to 92.43 degrees). Additionally, film thickness varied significantly between 0.028 mm and 0.195 mm across formulations. Mechanical differences were also evident, particularly in storage modulus and flexibility, as quantified through dynamic mechanical analysis (DMA). Although variations in glass transition temperature were modest and appeared to correlate with differences in film opacity-attributable to the lysine-to-tryptophan ratio-a pronounced enhancement in storage modulus was observed. Notably, the formulation exhibiting the highest lysine-tryptophan content showed an increase of up to 1000 times in the storage modulus.The findings suggest that processing and utilizing maize samples separated by opacity level for raw material production could provide important nutritional advantages for food and other applications.
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    Sampling number effects on genetic variation analysis in maize landraces using seed and leaf tissues
    (Springer, 2025) Kahriman, Fatih; Egesel, Cem Omer; Songur, Umut; Yildirim, Ezgi Alaca
    Maize landraces are crucial genetic resources for enhancing genetic diversity within breeding programs and for providing novel alleles that may be absent in registered cultivars. This study evaluates the effects of sample type (leaf vs. seed) and sample size (Single, 10, 20, and 30 individuals) on the outcomes of molecular diversity analysis in maize. DNA was extracted from 11 different maize landraces and two standard genotypes (B73 and Mo17) using optimized protocols. Simple sequence repeat (SSR) marker analysis revealed significant variation in genetic diversity indices between sample types. The analysis of molecular of variance (AMOVA) indicated that 10.98% of the variation in seed samples was explained by the sampling method, while all variation in leaf samples was attributed to differences among genotypes. Dendrogram and graphical analyses demonstrated that seed samples from groups of 10 and 20 exhibited more genetic similarity, while leaf samples showed higher complexity between 10 and 30-sample groups. These findings support the utility of SSR markers in evaluating genetic diversity and emphasize that both tissue type and sample size should be carefully considered in future assesments of genetic variability in maize landraces.