Benchmarking Machine Learning Approaches to Evaluate the Cultivar Differentiation of Plum (Prunus domestica L.) Kernels

نویسندگان

چکیده

Plum fruit and kernels offer bioactive material for industrial production. The promising procedure distinguishing plum kernel cultivars used in this study comprised two stages: image analysis to compute the texture parameters of belonging three ‘Emper’, ‘Kalipso’, ‘Polinka’, discriminant using machine learning algorithms classify based on selected textures with highest discriminative power. models built separately sets from all color channels L, a, b, R, G, B, U, V, S, X, Y, Z, space Lab channel b KStar (Lazy), PART (Rules), LMT (Trees) classifiers provided average accuracies reaching 98% case classifier. In case, individual were discriminated 97% ‘Emper’ ‘Kalipso’ 99% ‘Polinka’. values other performance metrics also satisfactory, higher than 0.95. ROC curves quite smooth steady most satisfactory curve kernels. present sheds light an objective, non-destructive, inexpensive cultivar discrimination

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ژورنال

عنوان ژورنال: Agriculture

سال: 2022

ISSN: ['2077-0472']

DOI: https://doi.org/10.3390/agriculture12020285