Maraş S., Şahin R., Eminoğlu M. B., Türker U.
Current Agriculture Research Journal, cilt.1, sa.14, ss.90-101, 2026 (Hakemli Dergi)
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Yayın Türü:
Makale / Tam Makale
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Cilt numarası:
1
Sayı:
14
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Basım Tarihi:
2026
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Doi Numarası:
10.12944/carj.14.1.7
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Dergi Adı:
Current Agriculture Research Journal
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Derginin Tarandığı İndeksler:
EBSCO Communication Source, CAB Abstracts, CABI (cabi.org)
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Sayfa Sayıları:
ss.90-101
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Ankara Üniversitesi Adresli:
Evet
Özet
In Türkiye, cereal products are classified according to their quality and then bought by public and private sector organizations. Physical analyses conducted according to standards focus on the definition of besatz in cereals, relying on the analyst's visual skill and expertise. Laboratory and field studies were carried out over a four-year period using the "Cgrain Value ™ Instrument" developed to detect both besatz and sound grains of common wheat, durum wheat, and barley products, utilizing imaging and artificial neural network technology. In these studies, the results of classical method analyses performed by analysts according to national standards and the results obtained from the instrument were evaluated. While an expert analyst can analyze first-class wheat in 15-20 minutes, it takes 25-30 minutes to analyze low-quality wheat. The Cgrain Value ™ Instrument, regardless of the sample's qualities, completes the analysis in 3.5-5 minutes with over 90% accuracy. When the results were examined, it was observed that the instrument achieved its lowest success rate of 91.3% in the nonvitreous grains within the durum wheat sample; the highest success rate was 99.9% in the pest-damaged grains within the red wheat sample. The repeatability rates between the classical analysis result and the instrument analysis result were determined to vary between 82.7% and 99.8%. It is thought that the analysis success demonstrated in this research will increase with the improvement of the instrument's calibration file.