Pepino (Solanum muricatum) Metabolic Profiles and Soil Nutrient Association Analysis in Three Growing Sites on the Loess Plateau of Northwestern China

Sun, Zhu; Wang, Lihui; Zhang, Guangnan; Yang, Shipeng; Zhong, Qing

doi:10.3390/metabo12100885

Cited by 10 publications

(9 citation statements)

References 52 publications

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“…Clearly, pepino fruits from Jiuquan were greeted more enthusiastically. In our previous study, soil nutrients were used as an environmental factors analysis which showed that total nitrogen (TN), total phosphorus (TP), available phosphorus (AP), available potassium (AK), and organic matter (OM) altered the metabolite profile in both Jiuquan, Haidong, and Wuwei of pepino fruits [ 7 ]. It is not difficult to explain this observation.…”

Section: Discussionmentioning

confidence: 99%

“…The metabolomic detection used pepino grown in the same conditions and harvested at the same time. A total of 85 differential metabolites were used for analysis, including amino acids and derivatives, nucleotides and derivatives, organic acids, phenolic acids, lipids, saccharides, and alcohols identified in a total of 18 samples from these three regions [ 7 ]. Metabolomics profiling identified metabolites and their relative contents are shown in Table S1 .…”

Section: Methodsmentioning

confidence: 99%

“…In China, pepino is mainly grown in the Jiuquan and Wuwei regions in western Gansu and the Haidong region in Qinghai [ 6 ]. Our previous study examined the types and contents of metabolic substances in pepino fruits produced in these three regions by LC-MS [ 7 ], but we did not investigate the substances affecting the flavor of pepino fruits.…”

Section: Introductionmentioning

confidence: 99%

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An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation

Sun

Zhao

et al. 2022

Foods

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation

Sun

Zhao

et al. 2022

Foods

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“…We reviewed a large amount of research and finally located TCP in lateral branch development and light quality response. Unlike for other crops, few studies have been conducted on S. muricatum; the roles of TCPs in light responses in S. muricatum remain largely unknown [ 31 , 32 , 33 ]. Meanwhile, our study unraveled the response of TCPs to light and the regulatory mechanisms in S. muricatum and compared their co-expression network in A. thaliana .…”

Section: Introductionmentioning

confidence: 99%

Systematic Investigation of TCP Gene Family: Genome-Wide Identification and Light-Regulated Gene Expression Analysis in Pepino (Solanum Muricatum)

Zhan

Wang

et al. 2023

Cells

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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.

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“…These researches have identified various organic acids, alkaloids, vitamins, sugars, alcohols, phenolic acids, and other metabolic substances in pepino. 7 Furthermore, the focus has been placed on the flavor and volatile aroma compounds of pepino. As scientific research progressed, the insufficiency of traditional methods became apparent, leading to the gradual emergence of metabolomic and transcriptomic techniques starting in the 1990s.…”

Section: Introductionmentioning

confidence: 99%

Metabolomics analysis of quality components metabolism during the growth process of pepino ( Solanum muricatum ) fruit

Zhao,

Sun,

Wang

et al. 2023

Plant Signaling & Behavior

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Pepino ( Solanum muricatum ), a horticultural crop that has experienced significant growth in the highlands of China over the past two decades, is widely embraced by consumers due to its distinctive taste and nutritional advantages. This study focused on the cultivar ‘Qingcanxiang’ of pepino grown on the Qinghai-Tibetan Plateau was analyzed using UPLC-QTOF-MS and RNA-seq transcriptome sequencing. Fruit samples were collected at three distinct stages of development, and the results of the metabolomics and transcriptomics were compared and correlated. The study’s findings indicate that the ‘Qingcanxiang’ fruit contained a total of 187 metabolites, comprising 12 distinct categories of compounds, including amino acids and their derivatives, organic acids, sugars and alcohols, phenols and phenolic acids. Of these metabolites, 94 were identified as differential. Significant variations in nutrient composition were observed across the three growth stages of the fruit. Specifically, the stage spanning from the growth to the maturation was identified as the critical stages for nutrient accumulation and flavor development. Transcriptome sequencing analysis revealed a set of highly associated genes between aspartate and quinic acid, namely SIR2 , IRAK4 , RP-L29 , and CCNH . These genes are potentially involved in the regulation of both amino acid and phenolic acid synthesis. Through the application of metabolomics and transcriptomics, this investigation elucidates the alterations in metabolites and the underlying molecular regulatory mechanisms of pepino fruits during three growth stages. The findings furnish a theoretical foundation for the evaluation of nutritional quality and the enhancement of breeding strategies for pepino.

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Pepino (Solanum muricatum) Metabolic Profiles and Soil Nutrient Association Analysis in Three Growing Sites on the Loess Plateau of Northwestern China

Cited by 10 publications

References 52 publications

An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation

An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation

Systematic Investigation of TCP Gene Family: Genome-Wide Identification and Light-Regulated Gene Expression Analysis in Pepino (Solanum Muricatum)

Metabolomics analysis of quality components metabolism during the growth process of pepino ( Solanum muricatum ) fruit

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