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In Journal of the science of food and agriculture

BACKGROUND : Strawberry quality is one of the most important factors that guarantees consistent commercialization of the fruit and ensures the consumer's satisfaction. This work makes innovative use of Random Forest (RF) to predict sensory measures of strawberries and to classify them in "satisfied" or "not satisfied" and "would pay more" or "wouldn't pay more" using physical and physical-chemical variables. The RF-based model predicts the acceptance, expectation, ideal of sweetness, ideal of acidity, and the ideal of succulence based on the physical and physical-chemical data, which are used as input for the RF-based classification model.

RESULTS : The RF achieved a coefficient of determination R2 > 0.72 and a root-mean-squared error (RMSE) smaller than 0.17 for the prediction task, which indicates that one can estimate the sensory measures of strawberries using physical and physical-chemical data. Furthermore, the RF was able to correctly classify 87.95% of the strawberry samples in the classes "satisfied" and "not satisfied" and 78.99% in the classes "would pay more" or "wouldn't pay more". Additionally, a two-step RF model, which employed both physical and physical-chemical data to classify strawberry samples regarding the consumer's response, correctly classified 100% and 90.32% of the samples with respect to the consumer's satisfaction and its willingness to pay more, respectively.

CONCLUSION : The results indicate that the developed models can be used in the quality control of strawberries, supporting the establishment of quality standards that consider the consumer's response. Additionally, the proposed methodology can be extended to control the sensory quality of other fruits. This article is protected by copyright. All rights reserved.

Ribeiro Michele N, Carvalho Iago A, Fonseca Gabriel A, Lago Rafael C, Rocha Lenízy C R, Ferreira Danton D, Vilas Boas Eduardo V B, Pinheiro Ana C M

2021-Jan-15

classification, machine learning, random forests, regression, sensory response, strawberry