Evidence map›Paper›PMID 41228854›Full record

ReviewSensors (Basel, Switzerland)2025

Harnessing Beneficial Microbes and Sensor Technologies for Sustainable Smart Agriculture.

Younes Rezaee Danesh

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
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.

Younes Rezaee DaneshDepartment of Plant Protection, Faculty of Agriculture, Van Yuzuncu Yil University, Van 65090, Türkiye.ORCID 0000-0003-1060-0264

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of beneficial microorganisms with sensor technologies represents a transformative advancement toward sustainable smart agriculture. This review synthesizes recent progress in combining microbial bioinoculants with sensor-based monitoring systems to enhance crop productivity, resource-use efficiency, and environmental resilience. Beneficial bacteria and fungi improve nutrient cycling, stress tolerance, and soil fertility thereby reducing the reliance on chemical fertilizers and pesticides. In parallel, sensor networks-including soil moisture, nutrient, environmental, and remote-sensing platforms-enable real-time, data-driven management of agroecosystems. Integrated microbe-sensor approaches have demonstrated 10-25% yield increases and up to 30% reductions in agrochemical inputs under optimized field conditions. We propose an integrative Microbe-Sensor Closed Loop (MSCL) framework in which microbial activity and sensor feedback interact dynamically to optimize inputs, monitor plant-soil interactions, and sustain productivity. Key applications include precision fertilization, stress diagnostics, and early detection of nutrient or pathogen imbalances. The review also highlights barriers to large-scale adoption, such as variable field performance of inoculants, high sensor costs, and limited interoperability of data systems. Addressing these challenges through standardization, cross-disciplinary collaboration, and farmer training will accelerate the transition toward climate-smart, self-regulating agricultural systems. Collectively, the integration of biological and technological innovations provides a clear pathway toward resilient, resource-efficient, and ecologically sound food production.

Indexed as

AgricultureBiosensing TechniquesBacteriaCrops, AgriculturalFertilizersFungiSoilSoil MicrobiologyFertilizersSoilbeneficial microbesprecision farmingsensor technologiessoil healthsustainable agriculture

Identifiers

PMID41228854
PMCPMC12610114

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.