The Influencing Factors of Nutrients and Metabolites in Plants

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Plant Metabolism".

Deadline for manuscript submissions: 25 August 2026 | Viewed by 1552

Special Issue Editors


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Guest Editor
Agro-Food Technology and Quality Laboratory, Regional Center of Agricultural Research of Meknes, National Institute of Agricultural Research, Rabat 10090, Morocco
Interests: plant engineering; plant biochemistry; food structure; biophysical mechanisms; food processing; food preservation; food chemistry; food quality; food analysis; food safety; food science and technology; food processing and engineering; data mining; chemometrics; molecular structure
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Guest Editor
Oasis System Research Unit, Regional Center of Agricultural Research of Errachidia, National Institute of Agricultural Research, P.O. Box 415, Rabat 10090, Morocco
Interests: food analysis; extraction; antioxidants; antioxidant activity; phytochemicals; natural product chemistry; chromatography; antibacterial activity; food & nutrition; antimicrobials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Plants continually modulate nutrient uptake, transport, allocation, and assimilation while dynamically reprogramming primary and specialized metabolism in response to fluctuating internal and external conditions. For this Special Issue, 'The Influencing Factors of Nutrients and Metabolites in Plants', we invite original research articles and reviews that identify, disentangle, and quantify the major drivers shaping plant nutrient status and metabolite composition across tissues, developmental stages, genotypes, and environments. We welcome contributions addressing abiotic constraints, biotic interactions, and genetic, epigenetic, and regulatory determinants of metabolic plasticity and homeostasis.

Submissions integrating metabolomics and ionomics with transcriptomics, proteomics, metabolic flux analysis, isotope tracing, metabolic fingerprinting, and high-resolution phenotyping—supported by rigorous chemometrics, multivariate statistics, and multi-omics data integration—are particularly encouraged. Artificial intelligence and machine learning approaches for pattern recognition, prediction, and modeling of complex metabolic networks are also welcome. Work linking genetic variation to metabolic phenotypes using quantitative genetics or gene editing is of particular interest.

Special emphasis will be placed on time-resolved and field-based studies that capture seasonal and annual metabolite dynamics, assess metabolite stability and reproducibility across years or locations, or that link biochemical variation to stress resilience, resource use efficiency, yield, and nutritional quality. Studies addressing climate adaptation, soil–plant nutrient interactions, and the rhizosphere metabolome are also encouraged.

Dr. Lahcen Hssaini
Dr. Eimad Dine Tariq Bouhlali
Guest Editors

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Keywords

  • metabolic reprogramming
  • nutrient homeostasis
  • metabolic flux analysis
  • plant-environment interactions
  • chemometric analysis
  • metabolic phenotyping
  • stress metabolomics
  • metabolic engineering
  • precision phenotyping

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Published Papers (2 papers)

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Research

15 pages, 8491 KB  
Article
Transcriptomics and Metabolomics Analysis Reveal the Mechanism of Petal Number Variation in Gardenia jasminoides
by Bo Gao, Yi Lu, Wenhuan Lai, Yiwen Liao, Liang Dong, Qigong Zhang, Shuangquan Zou and Xiaoxing Zou
Metabolites 2026, 16(2), 130; https://doi.org/10.3390/metabo16020130 - 13 Feb 2026
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Abstract
Background/Objectives: This study was based on the joint analysis of transcriptome and metabolome to explore the key genes and metabolic pathways of gardenia single flower petal number variation and to explore the possible mechanism of floral organ variation. Methods: Five, six, [...] Read more.
Background/Objectives: This study was based on the joint analysis of transcriptome and metabolome to explore the key genes and metabolic pathways of gardenia single flower petal number variation and to explore the possible mechanism of floral organ variation. Methods: Five, six, and seven petals of single-flower gardenia were selected as test materials for transcriptome and metabolome determination to excavate the key genes in regulating petal number in gardenia. Results: Metabolomic analysis identified triethylamine, succinic acid, succinylaldehyde, 2-phenylethanol, and o-xylene as the top five differentially expressed metabolites affecting petal number variation in gardenia. In the KEGG enrichment analysis, gardenia five, six, and seven DEGs were mainly enriched in amphetamine biosynthesis, the biosynthesis of plant secondary metabolites; transcriptome results showed that the identified differential transcription factors mainly come from NAC, ERF, C2H2, MYB, and MADS-box gene families; the expression of GjMADS50, GjMADS59, and GjERF28 changed with the increase in petal number. The commonality between gardenia five, six, and seven flowers exceeded the difference, and the expression pattern of MADS-box and ERF gene family members was the upregulation of GjERF28, GjERF39, and GjMADS67 and downregulation of GjMADS50, GjMADS59, and GjMADS60. Conclusions: We propose that ERF transcription factors may determine the initial number of petal primordia by mediating gibberellin biosynthesis or signaling, thereby coordinately regulating floral meristem activity and specific metabolic states. Full article
(This article belongs to the Special Issue The Influencing Factors of Nutrients and Metabolites in Plants)
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29 pages, 3515 KB  
Article
Genotype × Environment Shapes Fig Seed Oil Metabolic Fingerprinting
by Charaf Ed-dine Kassimi, Souhaila Hadday, Souhaila Bouchelta, Ahmed Irchad, Ibtissame Guirrou, Karim Houmanat, Fedoua Diai, Lhoussain Hajji and Lahcen Hssaini
Metabolites 2026, 16(2), 127; https://doi.org/10.3390/metabo16020127 - 12 Feb 2026
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Abstract
Background/Objectives: Fig (Ficus carica L.) seed oil represents an underexplored by-product with considerable nutraceutical potential. However, systematic evaluation of genotype × environment (G × E) interactions affecting its biochemical composition remains limited. This study assessed compositional variability across fig varieties, identified metabolic [...] Read more.
Background/Objectives: Fig (Ficus carica L.) seed oil represents an underexplored by-product with considerable nutraceutical potential. However, systematic evaluation of genotype × environment (G × E) interactions affecting its biochemical composition remains limited. This study assessed compositional variability across fig varieties, identified metabolic trade-offs, and developed rapid authentication protocols using FTIR-ATR spectroscopy to support predictive G × E models and marker-assisted selection. Methods: Thirty-seven fig varieties were evaluated across two consecutive harvest years (2023–2024) in Morocco. Conventional biochemical analyses measured total phenolic content (TPC), total flavonoid content (TFC), DPPH and ABTS antioxidant activities, and oil yield. FTIR-ATR spectroscopy characterized spectral variations, with ANOVA assessing effects of year, variety, and G × E interactions. Principal Component Analysis (PCA) discriminated genotypes and years. Results: TPC varied substantially (16.5–115.1 mg GAE/100 g oil), declining 36% from 2023 (48.7 ± 16.6 mg GAE/100 g) to 2024 (31.2 ± 16.6 mg GAE/100 g; F = 1372.84, p < 0.001), with TFC showing parallel trends (15.6 vs. 11.8 mg QCE/100 g). DPPH activity increased 34% in 2024 (58.5% vs. 43.7%), while ABTS activity decreased 18.6% from 32.34 ± 14.28% to 26.31 ± 6.10% (p < 0.001). Oil yield decreased from 26.7% to 21.2% and negatively correlated with phenolic accumulation (r = −0.49, p < 0.001). FTIR-ATR identified diagnostic peaks (e.g., 3012, 2928 cm−1), with significant G × E effects (p < 0.001). PCA captured 75.4–84.5% variance, discriminating genotypes and years. Stable high-value cultivars included ‘Dottato Perguerolles’, ‘VCR 276/49’, and ‘Ferqouch Jmel’. Conclusions: Genotypic differences and year-to-year environmental conditions significantly influence fig seed oil composition. The observed negative correlation between oil yield and phenolic content indicates a trade-off between lipid biosynthesis and secondary metabolism. FTIR-ATR spectroscopy coupled with multivariate analysis enables reliable variety discrimination and year differentiation, supporting the development of stable cultivars for nutraceutical applications. Full article
(This article belongs to the Special Issue The Influencing Factors of Nutrients and Metabolites in Plants)
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