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.
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Introduction
Garlic (Allium sativum L.)is a bulb crop containing 2-4 layers of concentric semi-thick curvy masses known as cloves. The centre of garlic has a woody stem. It is grown worldwide, and 90% of garlic production is restricted to the Asian subcontinent, particularly in China and India (FAO, 2021). Garlic is mainly used for culinary purposes as a thickening agent in food preparation. It is also used to produce various processed products, namely pickles, paste, flakes, grits, powder, and so on. Garlic has a specific aroma, so it is also used to prepare mayonnaise, sausages, ketchup, and stews (Prasad et al., 2002). Its demand has increased several-fold because of its potential roles, i.e., as a flavouring agent, thickening agent, antimicrobial, therapeutic and medicinal properties. Recently, various researchers have proven that it reduces arterial pressure, controls platelet aggregation, inhibits cancer cells, and controls the cholesterol level in the blood (Pardo et al., 2007; Rekowska and Skupień. 2009; Shekhar et al., 2023).Since antiquity, raw garlic paste was traditionally combined with turmeric and/or onion to help relieve pain and sprains. These health benefits may be due to the occurrence of various types of volatile and non-volatile compounds. S-alk(en)yl-L-cysteine sulfoxide (alliin), which is present in the cytoplasmic vesicles at approximately 1%, is one of the significant compounds associated with raw garlic (Amagase et al., 2001). When raw garlic is crushed, the alliin reacts with the alliinase enzyme and forms allicin, an active unstable compound containing 60-80% of total thiosulfinates (Block, 1992). Other compounds, such as ammonia and pyruvic acid, are also formed during hydrolysis. Pyruvic acid, a stable compound, is correlated with the pungency of garlic. Although garlic contains a high concentration of bioactive compounds, it also contains a small quantity of anti-nutritional compounds, particularly tannins, saponins, phytic acid, flavonoids, and steroids (Yusuf et al., 2018). Garlic is generally peeled before its use and mainly hand-peeled with the help of a knife. This method is laborious, time-consuming, expensive, and questionable regarding the uniformity of quality parameters. At the same time, with the change in lifestyles, there is an increase in the demand for either minimally processed products or semi-processed products for time-saving and ease of use for intended purposes. Due to this, peeled garlic demand on an industrial and home scale increased massively.
Lye peeling is one of the unit operations used for peeling of fruits and vegetables (Ramaswamy and Marcotte 2006). Garlic peel is rich in pectin, lignin, cellulose, and hemicellulose. Pectin acts as a binding agent, and lignin, an aromatic biopolymer, tightly binds cellulosic and hemicellulosic compounds. NaOH (10%)solution reduces the pectin and lignin content by breaking down or dissolving these compounds (Kumar et al., 2022). It also dissolves the inner epicuticular wax by penetrating the epidermis layer, digests the cell walls and middle lamella, and loosens the thin membrane skin (Gould, 2013). Lye peeling may assist in removing potato skin and can hinder the enzymatic browning reaction by decreasing the reducing sugar concentration (Hidayat and Setyadjit 2019).
Dynamic model behaviour in the processing of some specific agricultural commodities using artificial neural networks (ANN) has gained momentum due to the ability to learn the neural networks. It is suitable for identifying complex agricultural product quality responses that mathematical approaches do not solve quickly. The ANN model was tried to dry sliced potatoes and fresh green peas to predict moisture content and residual vitamin C (Kamiński et al., 1998). At the same time, the PCA technique was used for the optimization of microwave roasting of black rice based on a developed correlation between the resultant parameters, namely physical-functional properties, thermal properties, antioxidant and anthocyanin content (Arora et al., 2021).
The present research was planned to study the effects of lye concentrations on garlic peeling without affecting the quality attributes, namely chemical parameters, pungency factors, antioxidants, and anti-nutritional properties. A quality parameters prediction model was developed to assess the effectiveness of lye peeling behaviour using ANN. PCA was applied to position the lye-peeled and manually peeled garlic based on a developed correlation between the measured parameters and applied lye concentrations.
Conclusion
Concentration-dependent lye peeling of garlic cloves was carried out, maintaining temperature and exposure time as a constant. The effective peeling was found with the 12% lye solution. At the optimized condition of peeling reducing sugar significantly reduced and helped in obtaining dehydrated garlic brighter without affecting other quality attributes. At the same time, anti-nutritional compounds, namely tannin, phytic acid, and saponin, decreased significantly. PCA showed that LP12 correlates better with TPC, TFC, AA, AC, PA, and RS, having a minimum unpeeled garlic surface area. The found regression correlations 1.00000, 0.99572, and 0.99054 for training, validation, and testing of ANN model reflected the applicability of the developed two-layered feed-forward ANN model in the process prediction inefficient manner. The application of ANN may be used to predict online garlic peeling and successfully estimate quality parameters at a commercial scale.