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A BIG DATA-BASED ANALYSIS: COLOR AS A PREDICTOR OF SILAGE QUALITY   
Yazarlar (3)
Ömer Mermer
Türkiye
Dr. Öğr. Üyesi Ayşe Gül FİLİK Dr. Öğr. Üyesi Ayşe Gül FİLİK
Kırşehir Ahi Evran Üniversitesi, Türkiye
Doç. Dr. Gökhan FİLİK Doç. Dr. Gökhan FİLİK
Kırşehir Ahi Evran Üniversitesi, Türkiye
Devamını Göster
Özet
In this study, the relationship between color parameters and nutrient composition was examined using silage trial data conducted on 10 different plant species or mixtures by the Filik Research Lab. The dataset, comprising a total of 6,254 observations, was analyzed using big data analytics and statistical modeling techniques. Significant associations were identified between color parameters (L*, a*, b*, C*, h°, ΔE, saturation, and hue) and the physical, chemical, and sensory characteristics of the silage (crude protein, NDF, ADF, TDN, NFC). Initially, exploratory data analysis (EDA) and correlation matrices were employed to observe preliminary relationships between color and nutritional components. These were followed by classical and machine learning methods, such as multiple linear regression and Random Forest, to assess the strength and direction of these associations. The analysis revealed a* negative correlation (r = -0.45) between L* (lightness) and crude protein (CP, %), while a strong positive relationship (r = 0.52) was found between b* (yellowness) and NDF. Additionally, a meaningful correlation (r = 0.41) was observed between color saturation and TDN. Random Forest analysis confirmed these findings and highlighted L*, b*, and saturation as the most influential color parameters. These results suggest that color parameters are not only indicators of visual quality but also provide indirect insights into the chemical and nutritional content of silage. This study, conducted within the scope of big data analytics, demonstrates that color data can serve as a* rapid predictive tool, either as an alternative or complement to traditional chemical …
Anahtar Kelimeler
Makale Türü Özgün Makale
Makale Alt Türü Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayınlanan tam makale
Dergi Adı Black Sea Journal of Agriculture
Dergi ISSN 2618 – 6578
Dergi Tarandığı Indeksler TR DİZİN
Makale Dili İngilizce
Basım Tarihi 09-2025
Cilt No 8
Sayı 5
Sayfalar 725 / 735
Doi Numarası 10.47115/bsagriculture.1721520
Makale Linki https://dergipark.org.tr/en/pub/bsagriculture/issue/94614/1721520