Assessing the Quality of Lye-Peeled Garlic: A Concentration-Dependent Approach with Artificial Neural Networks and Multivariate Analysis

Abstract— The effectiveness of lye-peeled garlic was evaluated based on its chemical characteristics: allicin content, pyruvic acid, total phenolic content (TPC), total flavonoid content (TFC), antioxidant activity (AA), and anti-nutritional properties. The garlic cloves were peeled using the lye solutions (2–16%) in a ratio of 1:5 at 40±2 °C exposed for 7 min. The principal component analysis (PCA) was used to develop to assess the effectiveness of lye-peeling on the quality parameters. In addition, a two-layered feed-forward artificial neural network (ANN) was applied to develop a model to assess the quality parameters of peeled garlic. The found regression correlations 1.00000, 0.99572, and 0.99054 found for training, validation, and testing of artificial neural networks reflected the applicability of the developed model in quality assessment as regression performance was found to be 0.99005. It is concluded that 12% lye solution for peeling garlic cloves provides better quality, having less unpeeled garlic surface area. Therefore, this research highlights the application of lye concentration along with suitable temperature for garlic peeling with affecting the phytochemicals and nutritional quality of garlic.