Evidence map›Paper›PMID 41844764›Full record

ArticleScientific reports2026

Biostimulant-driven improvement in yield, seed quality, and soil health of peanut (Arachis hypogaea L.) cultivated in arid sandy environment.

Lamy Mamdoh Mohamed Hamed

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Lamy Mamdoh Mohamed HamedDepartment of Environment and Agricultural Natural Resources, College of Agricultural and Food Sciences, King Faisal University, P.O. Box 420, 31982, Al-Ahsa, Saudi Arabia. Lamy.hamed@kfu.edu.sa.ORCID http://orcid.org/0000-0002-4798-4428

Funding

Deanship of Scientific Research, King Faisal University KFU254538
6 · The paper itself

Abstract

Two field experiments were conducted during the 2023 and 2024 summer seasons to evaluate the effects of commercial biostimulants on peanut (Arachis hypogaea L.) productivity and soil health under arid sandy soil conditions along the Alexandria Desert Road, Egypt. A randomized complete block design with four treatments control, Humic King (humic acid), Biofertile (microbial inoculant; Azospirillum brasilense and Bacillus megaterium), and Kelpak (seaweed extract) was implemented with three replicates. Biostimulant applications enhanced several agronomic and quality parameters compared with the control. Total dry weight increased by up to 10.2%, while pod yield improved from 1.93 to 1.99 t ha⁻¹ in the control to a maximum of 3.41 t ha⁻¹ under humic acid treatment. Harvest index increased significantly from approximately 30% in untreated plants to 35.7% under humic acid application (p ≤ 0.05). Seed oil content reached 43.2% under humic acid compared with 41.4% in the control, whereas seaweed extract increased seed protein content by up to 14.4%. Post-harvest soil analyses indicated improvements in organic matter, available nitrogen, and reductions in salinity-related parameters, particularly under humic acid and microbial treatments. Overall, Humic King demonstrated the most consistent agronomic and soil benefits, supporting its recommendation for peanut cultivation in nutrient-deficient sandy soils under arid conditions.

Indexed as

ArachisSeedsSoilAzospirillum brasilenseBacillus megateriumDesert ClimateEgyptHumic SubstancesSandSoil MicrobiologyHumic SubstancesSandSoilArachis hypogaeaGrowthMicrobial inoculantsQualitySoil fertilitySustainable agriculture

Identifiers

PMID41844764
PMCPMC13128882

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.