Sensory characteristics and consumer preference for meat from guinea fowl fed hevea seed meal or cashew nut meal supplemented diets

The fatty acid profile and the quality of breast and leg muscles in female and male pearl gray guinea fowl (Numida meleagris)

The aim of this study was to evaluate the fatty acid (FA) profile and the quality of breast and leg muscles in male and female guinea fowl. In comparison with leg muscles, breast muscles had a higher content of dry matter and total protein, and contained less fat and total collagen (P ≤ 0.05). Sex had no effect on the chemical composition of the studied muscles or the FA profile of intramuscular fat (IMF) (P > 0.05). The IMF of breast muscles was characterized by higher proportions of total saturated fatty acids (SFAs) and polyunsaturated fatty acids (PUFAs), and lower proportions of total unsaturated fatty acids (UFAs) and monounsaturated fatty acids (MUFAs) (P ≤ 0.05) than the IMF of leg muscles. The physicochemical properties of guinea fowl meat were significantly influenced by muscle type (P ≤ 0.05), but not by sex (P > 0.05). Leg muscles were characterized by a higher pH, higher cooking loss, lower lightness (L*), lower drip loss, a higher contribution of redness (a*), and a lower contribution of yellowness (b*) than breast muscles (P ≤ 0.05). The experimental factors had no effect on the sensory attributes or the shear force values of the analyzed muscles (P > 0.05). The unique sensory attributes, high protein content, and low fat content of the analyzed muscles indicate that guinea fowl meat can be a dietary supplement and an addition to other types of meat consumed, especially that most guinea fowl are reared in extensive farming systems that contribute to sustainable food production.

A machine learning method for juice human sensory hedonic prediction using electronic sensory features

This study proposed a method that combines fused electronic sensory analysis technology with artificial neural network to predict the human sensory hedonic of fruit juice. Quantitative descriptive analysis (QDA) and the scoring test method were utilized for human sensory evaluation. The first step involved modeling the fused e-sensory features with human sensory attributes, followed by establishing a fitting model of human sensory attributes and acceptance. The R2 and RMSE values obtained were 0.77 and 0.42 (QDA method), and 0.63 and 0.63 (scoring test method). Finally, the relationship between the fusion e-sensory features and the human sensory hedonic was established. Model-1 achieved an R2 of 0.95 and an RMSE of 0.04, while model-2 achieved an R2 value of 0.88 and an RMSE value of 0.21. This study demonstrates the potential of fusing e-sensory technologies to replace human senses, which may lead to the development of devices with simultaneous multiple senses.