A CHEAPLY NON-DESTRUCTIVE TECHNIQUE TO ESTIMATE HONEY QUALITY: THERMAL IMAGING AND MACHINE LEARNING

Year 2024, Volume: 24 Issue: 1, 79 - 92, 29.05.2024

Mustafa Kibar

https://doi.org/10.31467/uluaricilik.1429971

Abstract

The aim of this study was to estimate honey quality based on proline and Brix content using a thermal imaging and machine learning algorithm. The proline, Brix and color properties of twenty honey samples were determined. Proline and Brix values were classified and estimated using the classification and regression tree (CART) algorithm. The mean proline and Brix content in honey samples was 678.83±192.16 mg/kg and 83.2±0.79%, respectively. CART analysis revealed that high proline honey samples had L values above 48.143 and b* values below 35.416. In contrast, honey samples with low Brix values were characterized by L and a* values below 55.860 and 53.660, respectively, and were identified as freshly harvested. The CART algorithm classified the proline and Brix values with an accuracy of 95% and 100%, respectively (p< 0.001). As a result, whitish, bluish, blackish and greenish honeys are of higher quality due to high proline and low Brix content. However, to accurately assess honey quality based on its color traits, comprehensive studies with more honey samples and origin, are required.

Keywords

Adulteration, Proline, Brix, Honey quality, CART algorithm

Bal Kalitesini Tahmin Etmek İçin Ucuz, Tahribatsiz Bir Teknik: Termal Görüntüleme ve Makine Öğrenimi

Abstract

Bu çalışmanın amacı, termal görüntüleme ve makine öğrenmesi yaklaşımı kullanılarak baldaki prolin ve Brix içeriğine dayalı bal kalitesinin tahmin edilmesidir. 20 farklı bal örneğine ait prolin, Brix ve renk özellikleri belirlendi. Prolin ve Brix seviyeleri, sınıflandırma ve regresyon ağacı algoritması kullanılarak tahmin edildi ve sınıflandırıldı. Ballarda ortalama prolin ve Brix içeriği sırasıyla 678,83±192,16 mg/kg ve %83,2±0,79 olarak belirlendi. CART analizi ile yüksek prolinli balların L değerlerinin 48.143'ün üzerinde ve b* değerlerinin ise 35.416'nın altında olduğu tespit edildi. Ancak, Brix değeri düşük olan balların ise sırasıyla 55.860 ve 53.660'ın altında L ve a* değerlerine sahip olduğu ve yeni hasat edildiği bulunmuştur. CART algoritması ile prolin ve Brix seviyeleri sırasıyla %95 ve %100 doğrulukla sınıflandırdı (p< 0.001). Sonuç olarak, beyazımsı, mavimsi, siyahımsı ve yeşilimsi balların yüksek prolin ve düşük Brix içeriği nedeniyle daha kaliteli olduğu belirlenmiştir. Ancak renk özelliklerine dayalı balın kalitesini doğru bir şekilde değerlendirmek için daha fazla ve farklı orijinli bal örnekleri ile kapsamlı çalışmalara ihtiyaç vardır.

Keywords

Tağşiş, Prolin, Brix, Balın kalitesi, CART algoritması

Ethical Statement

Çalışmada etik beyan gerektirecek şekilde herhangi bir hayvan veya insan kullanılmamıştır.

Supporting Institution

Bu çalışma herhangi bir kurumdan destek alınmadan yürütülmüştür.

Thanks

Bal örneklerini sağlayan arı yetiştiricilerine teşekkür ederim.

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