Mitochondrial genome sequencing is a valuable tool for investigating mitogenome evolution, species phylogeny, and population genetics. Chimonanthus praecox (L.) Link, also known as "La Mei" in Chinese, is a famous ornamental and medical shrub belonging to the order Laurales of the Calycanthaceae family. Although the nuclear genomes and chloroplast genomes of certain Laurales representatives, such as Lindera glauca , Laurus nobilis , and Piper nigrum , have been sequenced, the mitochondrial genome of Laurales members remains unknown. Here, we reported the first complete mitogenome of C. praecox . The mitogenome was 972,347 bp in length and comprised 60 unique coding genes, including 40 protein-coding genes (PCGs), 17 tRNA genes, and three rRNA genes. The skewness of the PCGs showed that the AT skew (-0.0096233) was negative, while the GC skew (0.031656) was positive, indicating higher contents of T's and G's in the mitochondrial genome of C. praecox . The Ka/Ks ratio analysis showed that the Ka/Ks values of most genes were less than one, suggesting that these genes were under purifying selection. Furthermore, there is a substantial abundance of dispersed repeats in C. praecox , constituting 16.98% of the total mitochondrial genome. A total of 731 SSR repeats were identified in the mitogenome, the highest number among the eleven available magnoliids mitogenomes. The mitochondrial phylogenetic analysis based on 29 conserved PCGs placed the C. praecox in Lauraceae, and supported the sister relationship of Laurales with Magnoliales, which was congruent with the nuclear genome evidence. The present study enriches the mitogenome data of C. praecox and promotes further studies on phylogeny and plastid evolution.

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Introduction Fangchenggang is situated in the Guangxi Zhuang Autonomous Region, China, renowned for its rich biodiversity and ethnically diverse population. The Zhuang people, constituting the largest minority group in the area, possess a wealth of traditional knowledge concerning wild edible plants (WEPs) owing to the region's favorable environment and dietary customs. With the rapid development of urbanization, tourism, and trade, the Zhuang people's food culture, including the consumption of wild edible plants, has become an attractive aspect of urban development. However, there is almost no comprehensive report available on WEPs consumed by the Zhuang people. The objectives of this study were to: (1) conduct a comprehensive ethnobotanical investigation of the WEPs among the Zhuang people in the region; (2) evaluate the cultural food significance index (CFSI) for the local communities; (3) summarize the cultural characteristics of the wild edible plants consumed, providing scientific support for the development of Fangchenggang as a sustainable and attractive tourism destination. Methods Ethnobotanical investigation including market surveys, semi-structured interviews, key informant interviews and participatory observations was conducted in Fangchenggang from January 2021 to March 2023. A total of 137 informants were selected using the snowball method. Information about WEPs, including vernacular names, food categories, parts used, mode of consumption, collecting season, and recipes, was collected and recorded. The CFSI (cultural food significance index) was calculated to identify the most culturally significant WEPs. Results A total of 163 species of wild edible plants consumed by the Zhuang people were identified, belonging to 67 families. The main categories of WEPs include wild vegetables (69) and tea substitutes (42). The most commonly consumed parts are fruits (37), followed by whole plants (33) and leaves (21), with herbaceous plants (74) being the most numerous. The availability of wild edible plants remains high throughout the year, with the peak seasons occurring in August and October, and significant abundance also noted in July and November. In the highly significant category (CFSI > 500), a total of 15 plant species were identified, which play a crucial role in the local diet. Additionally, 17 alien species have become part of the local consumption of wild plants, with 7 species listed as invasive alien species. DISCUSSION AND CONCLUSIONS: This study documented 163 wild edible plant species and their associated traditional knowledge of the Zhuang people. The research identified culturally significant WEPs and analyzed their multiple uses. The historical development of wild plant consumption in Fangchenggang showed the strong influence of natural and social environments on the Zhuang ethnic group's dietary traditions. The WEPs are characterized by "sour food", "fresh ingredients" and "cold dishes", aligning with their health-oriented philosophy of "homology of medicine and food". Future prospects encompass the cultivation of economically sustainable wild edible plants (WEPs), the preservation of their traits through cross-breeding, ensuring safe consumption through research and safety evaluations, and advocating for the preservation of WEPs' culinary culture to support tourism and sustainable urban development.

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The study of gene family evolution has benefited from the use of phylogenetic tools, which can greatly inform studies of both relationships within gene families and functional divergence. Here, we propose the use of a network-based approach that in combination with phylogenetic methods can provide additional support for models of gene family evolution. We dissect the contributions of each method to the improved understanding of relationships and functions within the well-characterized family of AGAMOUS floral development genes. The results obtained with the two methods largely agreed with one another. In particular, we show how network approaches can provide improved interpretations of branches with low support in a conventional gene tree. The network approach used here may also better reflect known and suspected patterns of functional divergence relative to phylogenetic methods. Overall, we believe that the combined use of phylogenetic and network tools provide a more robust assessment of gene family evolution.

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The most commonly used plant source of β-elemene is Curcuma wenyujin Y. H. Chen & C. Ling (syn. of Curcuma aromatic Salisb.) with its content in supercritical CO₂ extract up to 27.83%. However, the other rich source of this compound is Nigella damascena L. essential oil, in which β-elemene accounts for 47%. In this work, the effective protocol for preparative isolation of β-elemene from a new source- N. damascena essential oil-using high performance counter-current chromatography HPCCC was elaborated. Furthermore, since sesquiterpens are known as potent antimicrobials, the need for finding new agents designed to combat multi-drug resistant strains was addressed and the purified target compound and the essential oil were tested for its activity against a panel of Gram-positive and Gram-negative bacteria, fungi, and mycobacterial strains. The application of the mixture of petroleum ether, acetonitrile, and acetone in the ratio 2:1.5:0.5 ( v/v ) in the reversed phase mode yielded β-elemene with high purity in 70 min. The results obtained for antimicrobial assay clearly indicated that N. damascena essential oil and isolated β-elemene exert action against Mycobacterium tuberculosis strain H37Ra.

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Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99.89% for the Swedish Leaf dataset. In addition, the Relief feature selection method achieved the highest classification accuracy of 98.13% after 80 (or 60%) of the original features were reduced, from 133 to 53 descriptors in the myDAUN dataset with the reduction in computational time. Subsequently, the hybridisation of four descriptors gave the best results compared to others. It is proven that the combination MSD and HOG were good enough for tropical shrubs species classification. Hu and ZM descriptors also improved the accuracy in tropical shrubs species classification in terms of invariant to translation, rotation and scale. ANN outperformed the others for tropical shrub species classification in this study. Feature selection methods can be used in the classification of tropical shrub species, as the comparable results could be obtained with the reduced descriptors and reduced in computational time and cost.

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