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To study the difference in the contents of phenolics and the antioxidant activities between two kinds of Hawk tea of different maturity levels, and to evaluate their qualities, the contents of 15 phenolic compounds were determined using LC-MS/MS method. Then, the antioxidant activities of two types of tea were evaluated using DPPH radical scavenging rate, ABTS+ radical scavenging rate, and Fe3+ ferric reducing antioxidant power (FRAP). And then, the contents of 15 phenolic compounds and the antioxidant activities between two kinds of Hawk tea of different maturity levels were analyzed by analysis of variance (ANOVA). Based on the contents of 15 phenolic compounds, hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least square-discriminant analysis (OPLS-DA) were used to classify two kinds of Hawk tea. Finally, the contribution of different phenolic compounds in Hawk tea to antioxidation was discussed by partial least square regression analysis (PLSR). The results were as follows: (1) The contents of catechin, p-coumaric acid, isoquercitrin, hyperoside, nicotiflorin, astragalin, kaempferol, quercetin, and afzelin in tender leaf tea were significantly higher than those in old leaf tea, among which the average contents of catechin, isoquercitrin, and astragalin were higher than those in old leaf tea by 1 039.43, 169.12 and 257.35 mg·100 g-1, respectively. The results of HCA, PCA, and OPLS-DA could distinguish two kinds of Hawk tea. (2) The ANOVA showed significant differences in DPPH radical scavenging rate, ABTS+ radical scavenging rate, and FRAP between two kinds of tea, with the tender leaf tea superior to the old leaf tea. (3) The PLSR suggested that isoquercitrin, catechin, astragalin, chlorogenic acid, hyperoside, p-coumaric acid, and kaempferol were the main phenolic compounds those contributed to the antioxidant activity of Hawk tea. This study can provide a reference for Hawk tea's quality control and application promotion.

A transition metal-free dehydrative allylation of stabilized P-ylides with activated allylic alcohols has been developed. This protocol utilizes a calcium catalyst to facilitate the cleavage of C–OH bonds and enables smooth dehydrative cross-coupling with P-ylides, resulting in water as the sole by-product. Remarkably, this transformation exhibits excellent tolerance towards a diverse range of allylic alcohols and P-ylides. Furthermore, the subsequent Wittig reaction affords a wide array of highly functionalized 1,4-dienes with high yields. [ABSTRACT FROM AUTHOR]

Natural products from endolichenic fungi, isolated from different lichen species, have been attracting much attention because of their potential to produce metabolites with activities and/or new structures. The filamentous fungus M227‐2 isolated from lichen in Ny‐Alesund Arctic showed significant anti‐microbial activity and was identified as Cochliobolus kusanoi based on 18S rDNA. Secondary metabolites of M227‐2 were investigated in order to exploit them as lead compounds for new antibiotics. Chemical investigation on M227‐2 led to the isolation of three phomalone derivatives (products 1–3). Their structures were elucidated on the basis of their NMR and MS spectral data. Product 2 was new, whereas products 1 and 3 were isolated for the first time from the species. The biosynthetic pathway is also proposed. The filamentous fungus M227‐2 was isolated from lichen in Ny‐Alesund Arctic, which showed significant anti‐microbial activity and was identified as Cochliobolus kusanoi based on 18S rDNA. Chemical investigation on M227‐2 led to the isolation of three phomalone derivatives (product 1–3). Their structures were elucidated on the basis of their NMR and MS spectral data. [ABSTRACT FROM AUTHOR]

Protein, fat and somatic cells are three important reference indicators in milk purchase, which determine the quality and price of milk. The traditional chemical analysis methods of these indexes are time-consuming and pollute the environment, while the mid-infrared spectrum has the advantages of fast, non-destructive and simple operation. In order to realize the rapid classification of milk quality and improve the production efficiency of dairy enterprises, 3216 Holstein milk samples were chosen as the research objects and mid-infrared spectroscopy technology was applied to realize the detection and classification of 4 different quality milks during the purchase process. The spectrum was preprocessed by using the first derivative and the first difference, and combined with the algorithm competitive adaptive reweighted sampling (CARS) and the shuffled frog leaping algorithm (SFLA), the effective characteristic variables that could represent different milks were selected, and the SVM model was established. Among them, the penalty parameter c and the kernel function parameter g which were the key parameters of the SVM model were optimized by using the grid search method (GS), genetic algorithm (GA) and particle swarm algorithm (PSO). The training time of GS, GA and PSO algorithms were compared, the results showed that the training time of GS was much longer than that of GA and PSO algorithms.The SFLA algorithm was generally better than the CARS algorithm, and the PSO optimized the SVM model the best. After the first-order difference preprocessing, the PSO-SVM established by using the SFLA algorithm to filter the characteristic variables, the accuracy of the training set, the accuracy of the test set and the AUC were 97.8%, 95.6% and 0.96489, respectively. This model has a high accuracy rate and has practical application value in the milk industry.