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| Eyduran,Sadiye Peral; Akin,Meleksen; Ercisli,Sezai; Eyduran,Ecevit; Maghradze,David. |
| BACKGROUND: The Eurasian grapevine (Vitis vinifera L.) is the most widely cultivated and economically important horticultural crop in the world. As a one of the origin area, Anatolia played an important role in the diversification and spread of the cultivated form V. vinifera ssp. vinifera cultivars and also the wild form V. vinifera ssp. sylvestris ecotypes. Although several biodiversity studies have been conducted with local cultivars in different regions of Anatolia, no information has been reported so far on the biochemical (organic acids, sugars, phenolic acids, vitamin C) and antioxidant diversity of local historical table V. vinifera cultivars grown in Igdir province. In this work, we studied these traits in nine local table grape cultivars viz.... |
| Tipo: Journal article |
Palavras-chave: Table grape; Biochemical composition; HPLC; Spectrophotometer; Germplasm characterization. |
| Ano: 2015 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602015000100002 |
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| Orhan,Hikmet; Eyduran,Ecevit; Tatliyer,Adile; Saygici,Hasan. |
| ABSTRACT This study was conducted on 2049 eggs, collected from commercial white layer hybrids, with the purpose of predicting egg weight (EW) from egg quality characteristics such as shell weight (SW), albumen weight (AW), and yolk weight (YW). In the prediction of EW, ridge regression (RR), multiple linear regression (MLR), and regression tree analysis (RTM) methods were used. Predictive performance of RR and MLR methods was evaluated using the determination coefficient (R2) and variance inflation factor (VIF). R2 (%) coefficients for RR and MLR methods were found as 93.15% and 93.4% without multicollinearity problems due to very low VIF values, varying from 1 to 2, respectively. Being a visual, non-parametric analysis technique, regression tree method... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Chaid algorithm; Data mining; Decision tree; Multiple regression. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982016000700380 |
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| Çelik,Şenol; Söğüt,Bünyamin; Şengül,Turgay; Eyduran,Ecevit; Şengül,Ahmet Yusuf. |
| ABSTRACT The objective of this study was to determine the effects of egg quality characteristics (egg weight, egg width, egg height, and shape index) on fertility of eggs of Japanese quail with different colored feathers (yellow, white, grizzled, and normal), which are of economic importance for poultry production. For this purpose, 383 eggs of Japanese quail with various feather colors were used. In the study, usability of classification and regression tree (CART) data-mining algorithm as a classification tree method is necessary for poultry breeders to define proper cut-off values of egg quality characteristics that ensure Japanese quail eggs at good quality in fertility. Fertility as the dependent variable in the study was examined as a binary trait... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data mining algorithm; Quail egg; Hatchability. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982016001100645 |
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| Celik,Senol; Eyduran,Ecevit; Karadas,Koksal; Tariq,Mohammad Masood. |
| ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: ANN; Artificial intelligence; Data mining; Decision tree; MARS algorithm. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017001100863 |
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