Evidence map›Paper›PMID 38745317›Full record

ArticleBMC plant biology2024

Unravelling the metabolomic diversity of pigmented and non-pigmented traditional rice from Tamil Nadu, India.

Venkatesan Subramanian, Udhaya Nandhini Dhandayuthapani, Senthilraja Kandasamy, Jidhu Vaishnavi Sivaprakasam, Prabha Balasubramaniam, Mohan Kumar Shanmugam, Sriram Nagappan, Subramanian Elangovan, Umesh Kanna Subramani, Kumaresan Palaniyappan and 2 more

Abstract read
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Article in BMC plant biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Venkatesan SubramanianDirectorate of Research, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India.
Udhaya Nandhini DhandayuthapaniCentre of Excellence in sustaining Soil Health, Anbil Dharmalingam Agricultural College & Research Institute, Trichy, Tamil Nadu, 620 027, India.
Senthilraja KandasamyDirectorate of Research, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India.
Jidhu Vaishnavi SivaprakasamAmrita School of Agricultural Sciences, Tamil Nadu, Coimbatore, 642 109, India.
Prabha BalasubramaniamDepartment of Renewable Energy Engineering, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India.
Mohan Kumar ShanmugamAgro-Climatic Research Centre, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India.
Sriram NagappanDirectorate of Research, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India.
Subramanian ElangovanKrishi Vigyan Kendra, Madurai, Tamil Nadu, 625 104, India.
Umesh Kanna SubramaniOffice of the Vice Chancellor, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India.
Kumaresan PalaniyappanAgribusiness Development, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India.
Geethalakshmi VellingiriAgro-Climatic Research Centre, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India. geetha@tnau.ac.in.
Raveendran MuthurajanDirectorate of Research, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India. raveendrantnau@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rice metabolomics is widely used for biomarker research in the fields of pharmacology. As a consequence, characterization of the variations of the pigmented and non-pigmented traditional rice varieties of Tamil Nadu is crucial. These varieties possess fatty acids, sugars, terpenoids, plant sterols, phenols, carotenoids and other compounds that plays a major role in achieving sustainable development goal 2 (SDG 2). Gas-chromatography coupled with mass spectrometry was used to profile complete untargeted metabolomics of Kullkar (red colour) and Milagu Samba (white colour) for the first time and a total of 168 metabolites were identified. The metabolite profiles were subjected to data mining processes, including principal component analysis (PCA), Orthogonal Partial Least Square Discrimination Analysis (OPLS-DA) and Heat map analysis. OPLS-DA identified 144 differential metabolites between the 2 rice groups, variable importance in projection (VIP) ≥ 1 and fold change (FC) ≥ 2 or FC ≤ 0.5. Volcano plot (64 down regulated, 80 up regulated) was used to illustrate the differential metabolites. OPLS-DA predictive model showed good fit (R2X = 0.687) and predictability (Q2 = 0.977). The pathway enrichment analysis revealed the presence of three distinct pathways that were enriched. These findings serve as a foundation for further investigation into the function and nutritional significance of both pigmented and non-pigmented rice grains thereby can achieve the SDG 2.

Indexed as

MetabolomicsOryzaGas Chromatography-Mass SpectrometryIndiaMetabolomePigmentationPrincipal Component AnalysisGas chromatography-mass spectrometryKEGG pathwayMetabolite biomarkersPrincipal compound analysisSDG 2Traditional rice varietyUnivariate and multivariate analysis

Identifiers

PMID38745317
PMCPMC11095017

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