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Investigation of the effect of hectoliter and thousand grain weight on variety identification in wheat using deep learning method

Journal of Stored Products Research · Mayıs 2023

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YÖKSİS Kayıtları
Investigation of the effect of hectoliter and thousand grain weight on variety identification in wheat using deep learning method
Journal of Stored Products Research · 2023 SCI-Expanded
DOÇENT MUSTAFA ŞAMİL ARGUN →

Makale Bilgileri

DergiJournal of Stored Products Research
Yayın TarihiMayıs 2023
Cilt / Sayfa102
DOI10.1016/j.jspr.2023.102116
Scopus ID2-s2.0-85152446900
Özet Accurate identification of wheat varieties in the seed and flour industry is extremely important. The success rate of correctly identifying wheat varieties using artificial intelligence methods compared to traditional methods is quite high. Whether hectoliter weight (HLW) and thousand grain weight (TGW) represent the variety in identification studies is a subject to debate. The reason of this debate is these parameters are heavily affected by environmental factors such as soil nutrient levels, amount of rainfall, and number of sunny days. In other words, it is assumed that these parameters are not specific to the variety. In this study, the feature map obtained using the GLCM method was compared with the feature map obtained by adding the HLW and TGW parameters. As a result of the comparison, the accuracy rate was calculated as 78% in the first feature map. However, when standard features were added to the HLW and TGW parameters, the accuracy rate was calculated as 82%. The results show that the HLW and TGW parameters contribute to the identification of the wheat variety when used correctly with artificial intelligence.

Yazarlar (4)

1
Murat Lüy
2
Fuat Türk
ORCID: 0000-0001-8159-360X
3
Mustafa Samil Argun
4
Turgay Polat

Anahtar Kelimeler

Deep learning Gray level Co-Occurrence matrix Hectoliter weight Thousand grain weight Wheat variety identification

Kurumlar

Departmant of Agricultural Machinery and Technologies
Ankara Turkey
Kirikkale Medical University
Kirikkale Turkey
Selçuk Üniversitesi
Selçuklu Turkey
University of Cankiri Karatekin
Cankiri Turkey

Metrikler

2
Atıf
4
Yazar
5
Anahtar Kelime

Sistemimizdeki Yazarlar

MA
MUSTAFA ŞAMİL ARGUN
DOÇENT

Hızlı Erişim

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