First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes
Yıl: 2022 Cilt: 26 Sayı: 1 Sayfa Aralığı: 1 - 14 Metin Dili: İngilizce DOI: 10.29050/harranziraat.1025087 İndeks Tarihi: 27-09-2022
First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes
Öz: In this study mono and dual ovaries, which belonged to female individuals of different plant parasitic nematode species that were obtained from the quince (Cydonia oblonga Mill.) (Rosales: Rosaceae) cultivated areas in Sakarya Province (Turkey), were classified. The total number of 109 and 121 female nematodes, which were taken from the soil, were used in 2016, July and 2017, July, respectively. Overall body length (L), spear length (Stylet) and tail/distance from vulva to anus (T/VA) parameters belonged to these nematodes were measured and examined. The mono and dual ovary groups were distinguished by using the Linear Discriminate Function (LDF) method (Fisher’s method) and Artificial Neural Networks (ANNs) approach taking correlation between those parameters into consideration. The pair of parameters L and (T/VA) had higher accuracy percentage (as 97% for LDF method and 100% for ANNs approach) than the pair of parameters L and Stylet (as 91% for LDF method and 97% for ANNs approach) for the classification using 2017, July data set. The second approach was more successful than the first method. This research is the first study that was used these method and approach together at the nematology study area in Turkey and the World. The taxonomical studies may be improved using different statistical methods and artificial neural networks approaches together at the nematology.
Anahtar Kelime: İki ayırt etme tekniğinin ilk kez uygulanması: Bazı bitki paraziti nematodların ovary tiplerine göre Doğrusal Ayırt Etme Fonksiyonu Yönteminin ve Yapay Sinir Ağları Yaklaşımının kullanımı
Öz: Bu çalışmada Sakarya ilindeki (Türkiye) ayva (Cydonia oblonga Mill.) (Rosales: Rosaceae) ekiliş alanlarından elde edilen farklı bitki paraziti nematod türlerinin dişi bireylerine ait olan tek ve çift ovarileri sınıflandırılmıştır. Sırasıyla, 2016 Temmuz ve 2017 Temmuz’ da topraktan alınan toplam 109 ve 121 adet dişi nematod kullanılmıştır. Bu nematodlara ait olan tüm vücut uzunluğu (L), stylet uzunluğu (Stylet) ve kuyruk/vulvadan anüse olan mesafe (T/VA) parametreleri ölçülmüş ve incelenmiştir. Tek ve çift ovary grupları, bu parametreler arasındaki ilişki dikkate alınarak Doğrusal Ayırt Etme Fonksiyonu Yöntemi (Fisher Yöntemi) ve Yapay Sinir Ağları Yaklaşımı kullanılarak ayırt edilmiştir. Temmuz 2017 veri seti kullanılarak yapılan sınıflandırmada L ve (T/VA) parametre ikilisi (LDF yöntemi için %97 ve YSA yaklaşımı için %100 olarak), L ve Stylet parametre ikilisinden (LDF yöntemi için %91 ve YSA yaklaşımı için %97 olarak) daha yüksek doğruluk yüzdesine sahiptir. İkinci yaklaşım, birinci yöntemden daha başarılıdır. Bu araştırma Türkiye’de ve Dünya’daki nematoloji çalışma alanında bu yöntemin ve yaklaşımın birlikte kullanıldığı ilk çalışmadır. Taksonomi çalışmaları nematolojide farklı istatistiksel yöntemler ve yapay sinir ağları yaklaşımları birlikte kullanılarak geliştirilebilir.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
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| APA | Tan A, Tan A, SUSURLUK H (2022). First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. , 1 - 14. 10.29050/harranziraat.1025087 |
| Chicago | Tan Ayşe Nur,Tan Aylin,SUSURLUK HİLAL First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. (2022): 1 - 14. 10.29050/harranziraat.1025087 |
| MLA | Tan Ayşe Nur,Tan Aylin,SUSURLUK HİLAL First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. , 2022, ss.1 - 14. 10.29050/harranziraat.1025087 |
| AMA | Tan A,Tan A,SUSURLUK H First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. . 2022; 1 - 14. 10.29050/harranziraat.1025087 |
| Vancouver | Tan A,Tan A,SUSURLUK H First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. . 2022; 1 - 14. 10.29050/harranziraat.1025087 |
| IEEE | Tan A,Tan A,SUSURLUK H "First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes." , ss.1 - 14, 2022. 10.29050/harranziraat.1025087 |
| ISNAD | Tan, Ayşe Nur vd. "First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes". (2022), 1-14. https://doi.org/10.29050/harranziraat.1025087 |
| APA | Tan A, Tan A, SUSURLUK H (2022). First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. Harran Tarım ve Gıda Bilimleri Dergisi, 26(1), 1 - 14. 10.29050/harranziraat.1025087 |
| Chicago | Tan Ayşe Nur,Tan Aylin,SUSURLUK HİLAL First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. Harran Tarım ve Gıda Bilimleri Dergisi 26, no.1 (2022): 1 - 14. 10.29050/harranziraat.1025087 |
| MLA | Tan Ayşe Nur,Tan Aylin,SUSURLUK HİLAL First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. Harran Tarım ve Gıda Bilimleri Dergisi, vol.26, no.1, 2022, ss.1 - 14. 10.29050/harranziraat.1025087 |
| AMA | Tan A,Tan A,SUSURLUK H First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. Harran Tarım ve Gıda Bilimleri Dergisi. 2022; 26(1): 1 - 14. 10.29050/harranziraat.1025087 |
| Vancouver | Tan A,Tan A,SUSURLUK H First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes. Harran Tarım ve Gıda Bilimleri Dergisi. 2022; 26(1): 1 - 14. 10.29050/harranziraat.1025087 |
| IEEE | Tan A,Tan A,SUSURLUK H "First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes." Harran Tarım ve Gıda Bilimleri Dergisi, 26, ss.1 - 14, 2022. 10.29050/harranziraat.1025087 |
| ISNAD | Tan, Ayşe Nur vd. "First application of two distinguishment techniques: Using Linear Discriminate Function method and Artificial Neural Networks approach according to the ovary types for some plant parasitic nematodes". Harran Tarım ve Gıda Bilimleri Dergisi 26/1 (2022), 1-14. https://doi.org/10.29050/harranziraat.1025087 |
