Evidence map›Paper›PMID 39834445›Full record

ArticleHeliyon2025

Supervised machine learning and genotype by trait biplot as promising approaches for selection of phytochemically enriched

Hamid Hatami Maleki, Reza Darvishzadeh, Ahmad Alijanpour, Yousef Seyfari

Abstract read
In one paragraph

Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Machine learning analysis of COScientific reports · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hamid Hatami MalekiDepartment of Plant Production and Genetics, Faculty of Agriculture, University of Maragheh, Maragheh, Iran.
Reza DarvishzadehDepartment of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran.
Ahmad AlijanpourDepartment of Forestry, Faculty of Agriculture and Natural Resources, Urmia University, Urmia, Iran.
Yousef SeyfariFaculty of Engineering, University of Maragheh, Maragheh, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sumac is considered as a medicinal and industrial plant. Climate change threats natural ecosystems and hence, evaluation of sumac's genetic diversity, identification of superior genotypes, and conservation of such materials is important. In this study, 5 wild populations of sumac were investigated. Fruits of 75 sumac genotypes (15 genotype per population) were analyzed using HPLC-LC/MS-MS method. Likewise, genomic DNA of 75 genotypes were fingerprinted using 18 ISSR primers. Analysis of variance revealed significant genetic variability among studied populations of sumac considering malic acid, malic acid hexoside 2.71, malic acid hexoside 6.11, coumaric acid, ellagic acid11.49. Malic acid was identified as phytochemical marker in sumac fruit which can be implemented for screening sumac genotypes even from the same population. Genotype by trait analysis revealed V6, V10, D10, D14, A1, A14, K3, K15, N10, and N11 as top-performing genotypes (winners) which possessed the majority of phytochemical constituents in highest value. Here, the identified phytochemically superior sumac group was effectively distinguished from the inferior sumac group using ISSRs information via supervised machine learning. By using 13 feature selection algorithms, ISSR loci (U823) L1, (U835) L1, (U801) L1, (U816) L2, (U816) L4, (U835) L4, (U854) L1, and (U835) L9 were identified as functional markers which could predict phytochemical response of sumac germplasm. In conclusion, there is vast range of phytochemically divergent sumac genotypes in its natural habitats that could effectively recognized in any season by merging artificial intelligence with genomic information.

Indexed as

Artificial intelligenceISSR primerPhytochemical markerSumac

Identifiers

PMID39834445
PMCPMC11745794

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.