Xinyang Maojian (XYMJ) tea is one of the world’s most popular green teas; the development of new sprouts directly affects the yield and quality of tea products, especially for XYMJ, which has hairy tips. Here, we used transcriptome and small RNA sequencing to identify mRNAs and miRNAs, respectively, involved in regulating leaf development in different plant tissues (bud, leaf, and stem). We identified a total of 381 conserved miRNAs. Given that no genomic data for XYMJ green tea are available, we compared the sequencing data for XYMJ green tea with genomic data from a closely related species (Tieguanyin) and the Camellia sinensis var. sinensis database; we identified a total of 506 and 485 novel miRNAs, respectively. We also identified 11 sequence-identical novel miRNAs in the tissues of XYMJ tea plants. Correlation analyses revealed 97 miRNA–mRNA pairs involved in leaf growth and development; the csn-miR319-2/csnTCP2 and miR159–csnMYB modules were found to be involved in leaf development in XYMJ green tea. Quantitative real-time PCR was used to validate the expression levels of the miRNAs and mRNAs. The miRNAs and target genes identified in this study might shed new light on the molecular mechanisms underlying the regulation of leaf development in tea plants.

Spine grape ( Vitis davidii Foëx), an important wild grape species in South China, has gained attention because of its health-promoting effects and use in the wine industry. Fruit quality plays an important role in determining the quality of wine; however, a suitable evaluation system to monitor its fruit quality has not been established. The fruit quality characteristics (phenolics and aromas) of 15 spine grapes grown in China were evaluated using a combination of principal component and cluster analyses. The total sugar, organic acid, and phenolic content ranged from 81.80 to 154.89 mg·g ⁻¹ , 8.02 to 15.48 mg·g ⁻¹ , and 5.58 to 20.12 mg·g ⁻¹ , respectively. The comprehensive assessment by principal component analysis revealed that ‘Red xiangzhenzhu’ had the highest quality and ‘Hongjiangci10’ and ‘Ziluolan’ the lowest quality. Cluster analysis using k-means grouped the cultivars into three clusters based on their quality: Cluster 1 grouped those with inferior quality (‘Hongjiangci09’, ‘Hongjiangci10’, ‘Hongjiangci11’, and ‘Hongjiangci07’, etc.), Cluster2 grouped those with average quality (‘Ciputao3#,’ ‘Ziluolan’, and ‘Xiangci4#’), and Cluster3 grouped those with superior quality (‘Red xiangzhenzhu’ and ‘Green xiangzhenzhu’). A combination of principal component analysis and cluster analysis provides a comprehensive and objective evaluation system for determining the quality of grape cultivars. This study is important for the systematic evaluation and utilization of spine grape resources.

In this study, the aroma of 182 table grapes was detected using a PEN3.5 electronic nose in order to explore the aroma components of table grape berries and provide a reference for aroma evaluation and quality improvements. Table grape varieties from the Zhengzhou Fruit Research Institute of the Chinese Academy of Agricultural Sciences were used as research materials. All of them were harvested in fruit trees over 10 years old from August to October 2023, which provided a reference for aroma evaluation and quality improvement of the table grapes. Radar analysis, correlation analysis, principal component (PCA) analysis, cluster analysis, and difference analysis were used to study these aroma substances. The results show that the sensor contribution rate from high to low is W5S (nitrogen oxides), W2S (alcohols and some aromatic compounds), W1S (alkanes), and W2W (sensor contribution rate from high to low). Cluster analysis can distinguish the varieties of table grapes a with common aroma content, and the varieties with a higher content are in the second category (II). PCA showed that the contribution rate of the first and second principal components of the three main sensors was 97.6% and 2.3%, respectively, and the total contribution value was 99.9%. The contribution rates of the first and second principal components of the three aromatic sensors are 79.5% and 15.9%, respectively, and the total contribution value is 95.4%. The results showed that there were significant differences in the content and composition of aroma substances in different grape varieties. Eight special germplasm with strong aroma (organic compounds of nitrogen oxides, alcohols, alkanes and sulfur) were selected: ‘Spabang’, ‘Neijingxiang’, ‘Zaotian Muscat’, ‘Jinmeigui’, ‘Zhengguo 6’, ‘Muscat Angel’, ‘Zizao’, and ‘Qiumi’. This study confirmed that electronic nose technology can effectively distinguish different varieties of table grapes. This study not only provides a scientific basis for the variety selection for the table grape processing industry, but it can also be used for male or female grape hybridization, which provides valuable data resources for table grape breeding.