Automatic harvesting robots are crucial for enhancing agricultural productivity, and precise fruit maturity detection is a fundamental and core technology for efficient and accurate harvesting. Strawberries are distributed irregularly, and their images contain a wealth of characteristic information. This characteristic information includes both simple and intuitive features, as well as deeper abstract meanings. These complex features pose significant challenges to robots in determining fruit ripeness. To increase the precision, accuracy, and efficiency of robotic fruit maturity detection methods, a strawberry maturity detection algorithm based on an improved CES-YOLOv8 network structure from YOLOv8 was developed in this study. Initially, to reflect the characteristics of actual planting environments, the study collected image data under various lighting conditions, degrees of occlusion, and angles during the data collection phase. Subsequently, parts of the C2f module in the YOLOv8 model’s backbone were replaced with the ConvNeXt V2 module to enhance the capture of features in strawberries of varying ripeness, and the ECA attention mechanism was introduced to further improve feature representation capability. Finally, the angle compensation and distance compensation of the SIoU loss function were employed to enhance the IoU, enabling the rapid localization of the model’s prediction boxes. The experimental results show that the improved CES-YOLOv8 model achieves an accuracy, recall rate, mAP50, and F1 score of 88.20%, 89.80%, 92.10%, and 88.99%, respectively, in complex environments, indicating improvements of 4.8%, 2.9%, 2.05%, and 3.88%, respectively, over those of the original YOLOv8 network. This algorithm provides technical support for automated harvesting robots to achieve efficient and precise automated harvesting. Additionally, the algorithm is adaptable and can be extended to other fruit crops.

Polianthes tuberosa is a popular ornamental plant. Its floral scent volatiles mainly consist of terpenes and benzenoids that emit a charming fragrance. However, our understanding of the molecular mechanism responsible for the floral scent of P. tuberosa is limited. Using transcriptome sequencing and de novo assembly, a total of 228,706,703 high-quality reads were obtained, which resulted in the identification of 96,906 unigenes (SRA Accession Number SRP126470, TSA Acc. No. GGEA00000000). Approximately 41.85% of the unigenes were functionally annotated using public databases. A total of 4,694 differentially expressed genes (DEGs)were discovered during flowering. Gas chromatography-mass spectrometry analysis revealed that the majority of the volatiles comprised benzenoids and small amounts of terpenes. Homology analysis identified 13 and 17 candidate genes associated with terpene and benzenoid biosynthesis, respectively. Among these, PtTPS1, PtDAHPSs, PtPAL1, and PtBCMT2 might play important roles in regulating the formation of floral volatiles. The data generated by transcriptome sequencing provide a critical resource for exploring concrete characteristics as well as for supporting functional genomics studies. The results of the present study also lay the foundation for the elucidation of the molecular mechanism underlying the regulation of floral scents in monocots.

Oncidium hybridum is one of the important cut-flowers in the world. However, the lack of aroma in its cut-flower varieties greatly limits the sustainable development of the Oncidium hybridum cut-flowers industry. This paper is an integral investigation of the diel pattern and influencing factors of the aroma release of Oncidium Twinkle ‘Red Fantasy’. GC-MS analysis revealed that the release of 3-Carene peaked at 10:00, while Butyl tiglate and Prenyl senecioate did so at 14:00, with a diel rhythm. By analyzing the correlation network between aroma component synthesis and differentially expressed genes, 15 key structural genes were detected and regulated by multiple circadian rhythm-related transcription factors. Cluster-17371.18_TPS, Cluster-65495.1_TPS, Cluster-46699.0_TPS, Cluster-60935.10_DXS, Cluster-47205.4_IDI, and Cluster-65313.7_LOX were key genes in the terpenoid and fatty acid derivative biosynthetic pathway, which were co-expressed with aroma release. Constant light/dark treatments revealed that the diurnal release of 3-Carene may be influenced by light and the circadian clock, and Butyl tiglate and Prenyl senecioate may be mainly determined by endogenous circadian clock. Under constant light treatment, the TPS, DXS, IDI, and LOX genes seem to lose their regulatory role in the release of aroma compounds from Oncidium Twinkle ‘Red Fantasy’. Under constant dark treatment, the TPS genes were consistent with the release pattern of 3-Carene, which may be a key factor in regulating the diel rhythm of 3-Carene biosynthesis. These results laid a theoretical foundation for the study of floral transcriptional regulation and genetic engineering technology breeding of Oncidium hybridum.

Phalaenopsis is one of the most economically valuable genera in the Orchidaceae family. However, the common varieties of Phalaenopsis in the market rarely have fragrance, greatly limiting the sustainable development of the Phalaenopsis industry. Here, an integrated investigation was conducted on the patterns and determinants of aroma release in Phalaenopsis. GC-MS/MS analysis revealed that the primary volatile organic compounds (VOCs) in 10 fragrant Phalaenopsis cultivars are consistent. Terpenoids, alcohols, ketones, and esters collectively accounted for an average of 66.59% of the total VOCs across these 10 varieties. By performing metabolomic and transcriptomic analyses, we investigated the variation in 1532 VOCs in four different developmental stages of Phalaenopsis Formosa Sweet Memory. Metabolite analysis revealed that the levels of total volatiles, terpenoids, esters, and heterocyclic compounds were significantly upregulated during the flowering stages, and Linalool, β-Ocimene, and Methyl Benzoate were selected as key metabolites. While analyzing the correlation network between aroma components synthesis and differentially expressed genes, 33 key structural genes were detected and regulated by transcription factors. PAXXG356500_TPS, PAXXG333030_4CL, and PAXXG061420_SAM were key genes in the terpenoids and esters’ biosynthetic pathway, and they were co-expressed with aroma release. In summary, this study characterized the key metabolic pathways involved in aroma formation in Phalaenopsis and constructed the corresponding transcriptional regulatory network. These results laid a theoretical foundation for the subsequent research on aroma of Phalaenopsis and genetic engineering technology breeding.

Madagascar periwinkle (Catharanthus roseus [L.] G. Don) is a valuable medicinal and ornamental plant, prized for its diverse alkaloid compounds and aesthetic traits. While extensively studied for pharmaceutical applications, its current understanding of preliminary genetic inheritance of ornamental traits and ornamental breeding research are less advanced compared to other horticultural crops. This review systematically examines the germplasm resources, genetic diversity, and breeding advancements in ornamental periwinkle, covering the utilization of wild and cultivated varieties, mutation and polyploidy breeding, and recent genomic sequencing efforts. The potentially genetic mechanisms underlying key ornamental characteristics such as flower color, flower type, and plant architecture are discussed, and emerging approaches evaluated, including marker-assisted selection, interspecific hybridization, and CRISPR-based editing integrated with multi-omics platforms, for trait decoding and precision breeding. Strategies are also highlighted to enhance resistance to prevalent diseases such as die-back and root rot. Finally, future research directions aimed at developing resilient, high-alkaloid cultivars suitable for sustainable ornamental horticulture are proposed. This work provides a comprehensive resource for accelerating molecular breeding and improving ornamental traits in C. roseus.

Dickeya and Pectobacterium species are globally important soft rot pathogens causing significant crop losses. From 2024 to 2025, 120 Oncidium plants with soft rot symptoms were collected from six areas in Fujian Province, China, yielding 91 bacterial isolates. 16S rRNA gene sequencing revealed that 69 isolates (75.82%) belonged to Dickeya and Pectobacterium . Subsequent gapA phylogenetic analysis identified these as three species: 61 Dickeya fangzhongdai (88.41%), 6 D. zeae (8.70%), and 2 Pectobacterium aroidearum (2.90%). Multilocus sequence analysis based on 16 housekeeping genes, together with whole-genome sequencing and in silico analyses (average nucleotide identity and in silico DNA–DNA hybridization), confirmed the species-level identification, with all values exceeding established thresholds. This is the first report of D. fangzhongdai , D. zeae , and P. aroidearum causing soft rot in Oncidium orchids. Pathogenicity assays on 137 accessions (comprising commercial cultivars, breeding lines, and wild accessions) showed that Dickeya strains exhibited strong virulence (mean lesion: 21.63 to 23.34 mm), while P. aroidearum was significantly weaker (8.83 mm). Wild accessions displayed the highest resistance (7.62 to 16.91 mm), followed by commercial cultivars (8.75 to 24.47 mm), with breeding lines most susceptible (10.22 to 31.13 mm). Five resistant accessions were identified, including two broad-spectrum resistant wild accessions (86 and 130) with stable resistance to all five tested strains (lesion: 2.36 to 3.48 mm). Host range assays showed that the pathogens could infect eight additional orchid genera, indicating broad pathogenic potential. This study provides the first comprehensive characterization of these three pathogens in Oncidium soft rot and identifies valuable resistant germplasm for breeding programs.