Flavor is one of the most important characteristics that directly determines the popularity of a food. Moreover, the flavor of fruits is determined by the interaction of multiple metabolic components. Pepino, an emerging horticultural crop, is popular for its unique melon-like flavor. We analyzed metabolomics data from three different pepino growing regions in Haidong, Wuwei, and Jiuquan and counted the status of sweetness, acidity, flavor, and overall liking ratings of pepino fruit in these three regions by sensory panels. The metabolomics and flavor ratings were also integrated and analyzed using statistical and machine learning models, which in turn predicted the sensory panel ratings of consumers based on the chemical composition of the fruit. The results showed that pepino fruit produced in the Jiuquan region received the highest ratings in sweetness, flavor intensity, and liking, and the results with the highest contribution based on sensory evaluation showed that nucleotides and derivatives, phenolic acids, amino acids and derivatives, saccharides, and alcohols were rated in sweetness (74.40%), acidity (51.57%), flavor (56.41%), and likability (33.73%) dominated. We employed 14 machine learning strategies trained on the discovery samples to accurately predict the outcome of sweetness, sourness, flavor, and liking in the replication samples. The Radial Sigma SVM model predicted with better accuracy than the other machine learning models. Then we used the machine learning models to determine which metabolites influenced both pepino flavor and consumer preference. A total of 27 metabolites most important for pepino flavor attributes to distinguish pepino originating from three regions were screened. Substances such as N-acetylhistamine, arginine, and caffeic acid can enhance pepino‘s flavor intensity, and metabolites such as glycerol 3-phosphate, aconitic acid, and sucrose all acted as important variables in explaining the liking preference. While glycolic acid and orthophosphate inhibit sweetness and enhance sourness, sucrose has the opposite effect. Machine learning can identify the types of metabolites that influence fruit flavor by linking metabolomics of fruit with sensory evaluation among consumers, which conduces breeders to incorporate fruit flavor as a trait earlier in the breeding process, making it possible to select and release fruit with more flavor.

There is considerable knowledge about plant compounds that produce flavor, scent, and aroma. Aside from the similarities, however, groups of plant-produced nutrients and taste components have little in common with each other. Network analysis holds promise for metabolic gene discovery, which is especially important in plant systems where metabolic networks are not yet fully resolved. To bridge this gap, we propose a joint model of gene regulation and metabolic reactions in two different pepino varieties. Differential metabolomics analysis is carried out for detection of eventual interaction of compound. We adopted a multi-omics approach to profile the transcriptome and metabolome analyze differences in phenolic acids, flavonoids, organic acids, lipids, alkaloids, and sugars between LOF and SRF. The two most predominant classes of metabolites are phenolic acids and lipids in pepino. Overall results show enrichment in most DEGs was carbohydrate and biosynthesis of secondary metabolites pathway. Results of DEMs predominantly comprised N-p-coumaroyl agmatine and tryptamine, and significant differences were observed in their expression between LOF and SRF. Integrated DEMs and DEGs specific networks were constructed by combining two types of networks: transcriptional regulatory networks composed of interactions between DEMs and the regulated genes, and pepino metabolite-metabolite interaction networks. Newly discovered features, such as DEGs (USPA, UBE2 and DELLA) involved in the production of secondary metabolites are found in coregulated gene clusters. Moreover, lipid metabolites were most involved in DEMs correlations by OPLS-DA while identifying a significant number of DEGs co-regulated by SENP1, HMGCS et al. These results further that the metabolite discrepancies result from characterized the nutrients and taste components between two pepino genotype. Among the possible causes of the differences between species in pepino metabolite concentrations is co-regulated by these DEGs, continue to suggest that novel features of metabolite biosynthetic pathway remain to be uncovered. Finally, the integrated metabolome and transcriptome analyses have revealed that many important metabolic pathways are regulated at the transcriptional level. The metabolites content differences observed among varieties of the same species mainly originates from different regulated genes and enzymes expression. Overall, this study provides new insights into the underlying causes of differences in the plant metabolites and suggests that genetic data can be used to improve its nutrients and taste components.

In the present study, we determined the morphological and physiological indicators of Pepino to elucidate its lateral branching responses to different light qualities using a full-spectrum lamp (F) as the control and eight different light ratios using blue light (B) and red light (R). In addition, correlation analysis revealed that the gene expression patterns correlated with lateral branching under various light treatments. Compared with the F treatment, the R treatment increased the plant height and inhibited the elongation of lateral branches, in contrast with the B treatment. The number of lateral branches did not change significantly under different light quality treatments. Moreover, correlation analysis showed that the ratio of blue light was significantly positively correlated with the length of lateral branches and significantly negatively correlated with plant height, aboveground dry weight, and other indicators. We conducted transcriptome sequencing of the sites of lateral branching at three periods under different light quality treatments. The gene related to photodynamic response, cryptochrome (CRY), was the most highly expressed under B treatment, negatively regulated lateral branch length, and positively correlated with plant height. Branched 1, a lateral branch regulation gene, was upregulated under R treatment and inhibited branching. Overall, the red light facilitated internode elongation, leaf area expansion, plant dry weight increase, and inhibition of lateral branching. Soluble sugar content increased, and the lateral branches elongated under blue light. Different light qualities regulated lateral branching by mediating different pathways involving strigolactones and CRY. Our findings laid a foundation for further clarifying the response mechanism of Pepino seedlings to light and provided a theoretical reference for elucidating the regulation of different light qualities on the lateral branching of Pepino.

Pepino (Solanum muricatum), a member of the Solanaceae family originating from South America, is cultivated globally. However, the cultivation range and suitable habitat of Pepino have not been extensively studied, which hampers the further development of its cultivation industry. Therefore, we aimed at enrich and expand the planting scope of Pepino. Currently, the main cultivation areas of Pepino in China are the Yunnan–Guizhou Plateau and the Loess Plateau, where the altitude is above 1000 m. In this study, ArcGIS combined with the MaxEnt model was used for prediction, whose area under curve value was 0.949. The main climatic factors affecting the distribution of Pepino are temperature seasonality, annual means temperature, mean temperature of the coldest quarter, elevation, isothermality, and the climate factors, and their cumulative contribution rate of 87.6%. Pepino's main potential distribution areas are located in Yunnan–Guizhou Plateau, Yunnan Province, Hexi Corridor of Loess Plateau, and low altitude areas of Qinghai–Tibet Plateau. The main distribution ranges from 1000 to 2000 m above sea level, and the total suitable area accounts for 20.09% of China's total land area. The prediction results reveal an expanded potential area for Pepino, with no significant migration in the central region of the main potential distribution area by 2050 and 2070. No studies have been conducted on the open-area cultivation of Pepino in northern China. Our findings revealed that the yield and quality in the four experimental sites and final actual cultivation conditions were consistent with the predicted results of MaxEnt. The yiel d per plant in Xunhua and Minhe was significantly different from that in Xining, which was low, and that in Minhe was the highest. Overall, the fruit quality in the Xining region was the lowest among the three regions, which was related to the climatic differences in each region. These results align with the predicted outcomes, indicating that Xining is the least suitable area. Further, these data verify the accuracy of the prediction results. The climate data of the four regions were analyzed simultaneously to elucidate the influence of different climate conditions on the growth of Pepino. Our findings are of considerable significance for introducing characteristic horticultural crops in the Qinghai–Tibet Plateau and using the MaxEnt model to predict the cultivation range of crops.

Turnip (Brassica rapa ssp. rapa) is considered to be a highly nutritious and health-promoting vegetable crop, whose flesh color can be divided into yellow and white. It is widely accepted that yellow-fleshed turnips have higher nutritional value. However, reports about flesh color formation is lacking. Here, the white-fleshed inbred line, W21, and yellow-fleshed inbred line, W25, were profiled from the swollen root of the turnip at three developmental periods to elucidate the yellow color formation. Transcriptomics integrated with metabolomics analysis showed that the PSY gene was the key gene affecting the carotenoids formation in W25. The coding sequence of BrrPSY-W25 was 1278 bp and that of BrrPSY-W21 was 1275 bp, and BrrPSY was more highly expressed in swollen roots in W25 than in W21. Transient transgenic tobacco leaf over-expressing BrrPSY-W and BrrPSY-Y showed higher transcript levels and carotenoids contents. Results revealed that yellow turnip formation is due to high expression of the PSY gene rather than mutations in the PSY gene, indicating that a post-transcriptional regulatory mechanism may affect carotenoids formation. Results obtained in this study will be helpful for explaining the carotenoids accumulation of turnips.

Plant-specific transcription factors such as the TCP family play crucial roles in light responses and lateral branching. The commercial development of S. muricatum has been influenced by the ease with which its lateral branches can be germinated, especially under greenhouse cultivation during the winter with supplemented LED light. The present study examined the TCP family genes in S. muricatum using bioinformatics analysis (whole-genome sequencing and RNA-seq) to explore the response of this family to different light treatments. Forty-one TCP genes were identified through a genome-wide search; phylogenetic analysis revealed that the CYC/TB1, CIN and Class I subclusters contained 16 SmTCP, 11 SmTCP and 14 SmTCP proteins, respectively. Structural and conserved sequence analysis of SmTCPs indicated that the motifs in the same subcluster were highly similar in structure and the gene structure of SmTCPs was simpler than that in Arabidopsis thaliana; 40 of the 41 SmTCPs were localized to 12 chromosomes. In S. muricatum, 17 tandem repeat sequences and 17 pairs of SmTCP genes were found. We identified eight TCPs that were significantly differentially expressed (DETCPs) under blue light (B) and red light (R), using RNA-seq. The regulatory network of eight DETCPs was preliminarily constructed. All three subclusters responded to red and blue light treatment. To explore the implications of regulatory TCPs in different light treatments for each species, the TCP regulatory gene networks and GO annotations for A. thaliana and S. muricatum were compared. The regulatory mechanisms suggest that the signaling pathways downstream of the TCPs may be partially conserved between the two species. In addition to the response to light, functional regulation was mostly enriched with auxin response, hypocotyl elongation, and lateral branch genesis. In summary, our findings provide a basis for further analysis of the TCP gene family in other crops and broaden the functional insights into TCP genes regarding light responses.