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https://www.selleckchem.com/products/apx2009.html " Seven classification algorithms including "Naïve Bayes, support vector machine, gradient boosting classifier, K-nearest neighbors, artificial neural network, logistic regression, and AdaBoost" were used to classify the preprocessed data. Results showed that the Naïve Bayes algorithm with 90.2% provided the highest accuracy among the others, and the support vector machine and gradient boosting classifier with 88.2% were in the next ranks.The nutritional and antinutrient composition of Heteromorpha arborescens (Spreng.) Cham. & Schltdl. leaves was reported in this study. Proximate analysis revealed the presence of 8.5% total ash, 4.92% crude fat, 8.41% moisture, 15.74% crude protein, 21.48% crude fiber, 40.95% carbohydrates, and 271.04 kcal/100 g energy value. Mineral analysis showed that H. arborescens leaves are very rich in K, Ca, and Fe. Considerable amounts of Mg, Mn, Na, P, Cu, and Zn were also present. Vitamin analysis showed that the plant has a high content of vitamins A, C, and E. The antinutrients evaluated were phytate, oxalate, saponin, and alkaloids, all of which were below toxic levels except for saponin which was observed at moderately high level. The results credibly indicate that H. arborescens leaves are nutrient-rich and can contribute effectively to the daily nutrient requirements alongside its therapeutic properties.In this study, the effects of adding Gaz-angubin at three different levels (5%, 10%, and 15% w/v) and bitter orange peel extract with three different concentrations (0.025%, 0.050%, and 0.075% w/v) on selected characteristics of the flavored milk were investigated during 10-day storage at 4°C. The results showed that increasing the level of Gaz-angubin and bitter orange peel extract increased viscosity, antioxidant activity, and total polyphenol content, decreased total microbial count, and improved the sensory characteristics of the flavored milk (p less then .05). Generally, the fl

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