Application of natural fining agents to clarify fruit juices

Analysis of sediment re-formation factors after ginseng beverage clarification based on XGBoost machine learning algorithm

The aim of this study was to explore the sediment re-formation factors of ginseng beverages subjected to four clarification ways (11 subgroups) including the ethanol precipitation, enzymatic treatment, clarifier clarification, and Hollow Fiber Column (HFC) methods, based on the Extreme Gradient Boosting (XGBoost) model. The results showed that the clarity of the ginseng beverages was significantly improved by all the clarification treatments, but still formed sediment after storage. HFC method exhibited the highest transmittance, the least sediment, and stronger antioxidant activity in the clarification treatment groups. According to the results of chemical composition analyses and partition coefficients, carbohydrates, saponins, proteins and metal elements were involved in varying degrees in the re-formation of the sediments in ginseng beverage after clarification. Based on the above data, the XGBoost model predicted that protein, Rd, Na, K, and total saponins were the five most important chemical components affecting the sediment re-formation in ginseng beverages.

Dynamic changes and correlation of quality, flavor and microorganisms of Mei (Prunus mume) vinegar during fermentation and clarification

Mei (Prunus mume) is a highly nutritious fruit whose value is often underutilized due to its perishable nature and challenges in post-maturation storage. This study evaluated the changes and correlations among quality, volatile flavor compounds (VFCs), and microorganisms in Mei vinegar (MV) during acetic acid fermentation (AAF) and low temperature clarification (LTC) using various clarifiers. The results indicated that AAF enhanced the bioactive components and antioxidant capacity of MV. A total of 73 VFCs were identified, comprising 9 alcohols, 28 esters, 5 aldehydes, 18 acids, 4 phenols, 1 ketone, 5 alkanes, and 3 others. Among these, the number and relative content of esters and acids exhibited dominance both in AAF and LTC. Firmicutes and Pediococcus were predominant at the phylum and genus levels, respectively. After 1 d of AAF, the relative abundances of Firmicutes and Pediococcus increased significantly, while LTC reduced their abundance. Among the 20 stable VFCs in MV, most esters and alcohols showed positive correlations with the top 10 bacteria at the phylum and genus levels, while certain acids were negatively correlated with these bacteria. Therefore, these findings offer valuable insights for the development of MV, the selection of clarifiers, and offer a theoretical basis for improving MV quality and flavor.

Optimization of α-L-arabinofuranosidase CcABF on clarification and beneficial active substances in fermented ginkgo kernel juice by artificial neural network and genetic algorithm

This study aimed at using α-L-arabinofuranosidase CcABF to improve the clarity and active substances in fermented ginkgo kernel juice by artificial neural network (ANN) modeling and genetic algorithm (GA) optimization. A credible three-layer feedforward ANN model was established to predict the optimal parameters for CcABF clarification. The experiments proved the highest transmittance of 89.40% for fermented ginkgo kernel juice with this understanding, which exhibited a 25.56% increase over the unclarified group. With the clarification of CcABF, the antioxidant capacity in juice was enhanced with the increase of total phenolic and flavone contents, and the maximum DPPH and hydroxyl radical scavenging rates were increased by 89.71% and 26.65%, respectively. The contents of toxic ginkgolic acids declined markedly, while the active ingredients of ginkgetin and ginkgolide B showed a modest increase. Moreover, changes in free amino acids and volatile compounds improved the nutritive value and flavor of clarified fermented ginkgo kernel juice.