Evidence map›Paper›PMID 40832582›Full record

ArticlePeerJ2025

Impact of foliar application using amino acids, yeast extract, and algae extract in different concentrations on growth parameters, yield traits, grain quality, and nitrogen-related parameters of wheat in arid environments.

Mohamed Ebaid, Mohamed E El-Temsah, Mohamed A Abd El-Hady, Amirah S Alahmari, Ahmed S M El-Kholy, Diaa Abd El-Moneim, Ahmed M Saad

Abstract read
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

7 authors.

Mohamed EbaidPlant Production Department, Arid Lands Cultivation Research Institute (ALCRI), City of Scientific Research and Technological Applications (SRTA-City), New Borg El-Arab City, Alexandria, Egypt.
Mohamed E El-TemsahAgronomy Department, Faculty of Agriculture, Ain Shams University, Cairo, Egypt.
Mohamed A Abd El-HadyAgronomy Department, Faculty of Agriculture, Ain Shams University, Cairo, Egypt.
Amirah S AlahmariDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Ahmed S M El-KholyAgronomy Department, Faculty of Agriculture, Zagazig University, Zagazig, Egypt.
Diaa Abd El-MoneimDepartment of Plant Production (Genetic Branch), Faculty of Environmental Agricultural Sciences, Arish University, El-Arish, Egypt.ORCID 0000-0003-3285-0563
Ahmed M SaadAgronomy Department, Faculty of Agriculture, Benha University, Benha, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wheat cultivation in arid environments faces significant challenges, necessitating innovative approaches to enhance productivity under current climate change conditions. Foliar application with bio-stimulants, such as amino acids, yeast extract, and algae extract, offers a sustainable solution to improve wheat growth, yield, and physiological efficiency under these conditions. A field trial was carried out over two winter growing seasons to assess the comparative effects of these bio-stimulants applied at varying concentrations on growth parameters, yield traits, grain quality, and nitrogen-related parameters. Treatments included an untreated control (sprayed with distilled water) and foliar applications at different concentrations: amino acids (1.5 and 3 ml/L), yeast extract (50 and 100 ml/L), and algae extract (5 and 10 ml/L). The results demonstrated that all bio-stimulant treatments significantly enhanced all studied parameters compared to the untreated control. The highest concentrations of each treatment (3 ml/L for amino acids, 10 ml/L for algae extract, and 100 ml/L for yeast extract) produced the greatest improvements, with amino acids at 3 ml/L exhibiting the strongest effects. Specifically, amino acids at 3 ml/L improved plant height by 12.46% and 21.56%, chlorophyll content by 22.32% and 19.12%, and plant dry weight by 63.30% and 70.38% in the first and the second seasons, respectively. Yield traits, including number of spikes, spike length, spike weight, number of spikelets per spike, number of grains per spike, and 1,000-grain weight, were also significantly improved, with amino acids at 3 ml/L producing the highest values. Grain yield, straw yield, and biological yield increased by 44.74% and 43.92%, 35.34% and 42.37%, and 36.29% and 43.95%, respectively, in the first and second seasons. Nitrogen content in both grains and straw was higher in treated plants, with amino acids at 3 ml/L enhancing grain nitrogen content by 25.52% and 22.50% and straw nitrogen content by 41.03% and 56.45% in the first and second seasons. The improvement resulted from amino acids at 3 ml/L followed by the application of algae extract at 10 ml/L and yeast extract at 100 ml/L, with all treatments showing significant improvements over the untreated control. Principal component analysis and heatmap analyses confirmed that higher concentrations of amino acids, algae extract, and yeast extract had the most positive effects on wheat growth and nitrogen-related parameters, while the untreated control and lower concentrations showed weaker results. These findings demonstrated that foliar application of amino acids, particularly at 3 ml/L, is a highly effective strategy for improving wheat productivity, grain quality, and nitrogen use efficiency in arid environments.

Indexed as

Amino AcidsEdible GrainNitrogenTriticumDesert ClimatePlant LeavesSeasonsYeastsAmino AcidsNitrogenArid environmentsBio-stimulantsFoliar nutritionNitrogen parametersPhysiological performanceSustainable agricultureWheat growth and productivity

Identifiers

PMID40832582
PMCPMC12360320

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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 OpenQuestion graph.