Evidence map›Paper›PMID 40461624›Full record

ArticleScientific reports2025

Modeling potential of halophytes in the production of biofuel and edible oil using linear regression and an adaptive neuro-fuzzy inference system.

Azin Sharafi, Seyed Akbar Javadi, Ehsan Zandi Esfahan, Mohammad Jaffari, Mahshid Souri

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Article in Scientific reports, 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Azin SharafiScience and Research Branch, Islamic Azad University, Tehran, Iran. Azin.sharafi@gmail.com.
Seyed Akbar JavadiScience and Research Branch, Islamic Azad University, Tehran, Iran. a.javadi@srbiau.ac.ir.
Ehsan Zandi EsfahanResearch Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization, Tehran, Iran.
Mohammad JaffariFaculty of Natural Resources, University of Tehran, Karaj, Iran.
Mahshid SouriResearch Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Halophyte plants are capable of tolerating high salinity due to their unique morphological characteristics, vegetative forms, physiological attributes, and specific salt tolerance mechanisms. These plants offer significant economic benefits, prompting research into their potential use in biofuel and edible oil production. This study focused on three plant species: Haloxylon persicum, Tamarix ramossisima, and Halocnemum strobilaceum. Samples were collected at distances of 1000, 1500, 2000, and 5000 m from the Miduk mining site in Shahrbabek, with four replications of 20 individual plants each. Data regarding plant characteristics, seed oil content, ethanol, and lignin production potential were measured and analyzed. The results indicated that Haloxylon persicum has a higher cellulose-to-hemicellulose ratio compared to lignin, making it a suitable raw material for bioethanol production. Additionally, gas chromatography analysis of the oil revealed that halophyte seeds contain ten fatty acids: five saturated fatty acids-lauric acid, myristic acid, palmitic acid, stearic acid, and arachidic acid-and five unsaturated fatty acids-behenic acid, oleic acid, linoleic acid, alpha-linoleic acid, and stearidonic acid. Haloxylon persicum also proved to be more suitable for edible oil production due to its higher oil content. Furthermore, results from the modeling section revealed that the adaptive neuro-fuzzy inference system exhibited greater accuracy than linear regression in predicting biofuel and edible oil parameters in coastal species.

Indexed as

BiofuelsPlant OilsSalt-Tolerant PlantsTamaricaceaeFatty AcidsFuzzy LogicLigninLinear ModelsSeedsBiofuelsFatty AcidsLigninPlant OilsANFISEthanolHalophyteLigninPredictionSeed oil

Identifiers

PMID40461624
PMCPMC12134103

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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 OpenQuestion graph.