Evidence map›Paper›PMID 40128551›Full record

ArticleScientific reports2025

Machine learning insights for sustainable hydroponic cultivation and growth monitoring of allium cepa using smart hydro kit.

Monica Dutta, Deepali Gupta, Sapna Juneja, Saleh AlNadhari, Samir Brahim Belhaouari

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

5 authors.

Monica DuttaInstitute of Engineering and Technology, Chitkara University, Chandigarh, Punjab, India.
Deepali GuptaInstitute of Engineering and Technology, Chitkara University, Chandigarh, Punjab, India.
Sapna JunejaKIET Group of Institutions, Ghaziabad, India.
Saleh AlNadhariDeanship of Scientific Research, King Saud University, 11451, Riyadh, Saudi Arabia.
Samir Brahim BelhaouariDivision of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar. sbelhaouari@hbku.edu.qa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research paper emphasizes the growing importance of Allium Cepa (Onions)-a medicinal plant, as a safe and effective alternative to conventional medicinal therapies for both humans and livestock. The increasing concerns over the high costs and side effects of traditional treatments have shifted attention towards herbal medicine, known for its minimal side effects and cost-effectiveness. Additionally, cultivating Onions promotes public health and contributes to economic growth through responsible cultivation and use. The widespread use of machine learning in smart hydroponics is also explained in the manuscript. The study introduces the 'Smart Hydro Kit,' an innovative and compact device designed to monitor and automate the environmental conditions for the hydroponic cultivation of Onions, enhancing sustainability. The performance of onion shoots and bulbs cultivated through hydroponics is compared with soil-based methods using various qualitative and quantitative metrics. Results demonstrate that hydroponic cultivation significantly outperforms soil cultivation. The findings are further validated using the 'AquaCrop' simulation tool.

Indexed as

HydroponicsMachine LearningOnionsPlant RootsPlant ShootsSoilSoilHydroponicInfrastructureInnovationMachine learningMedicinal plantsSimulatorSustainability

Identifiers

PMID40128551
PMCPMC11933250

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.