Evidence map›Paper›PMID 40692673›Full record

ReviewFrontiers in plant science2025

A review of ultrasound monitoring applications in agriculture.

Muhammad Awais Sattar, Dina Shona Laila

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 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.

  1. Article
  2. Article
  3. Article
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

2 authors.

Muhammad Awais SattarAutomatic Control, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden.
Dina Shona LailaAutomatic Control, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pursuing agricultural intensification to raise productivity has brought challenges such as involvement of high capitals, often in the form of loans, environmental damage, and ecosystem disruption. These challenges increase risks in agricultural practice that require good management and control. This increases the need for real-time, non-destructive monitoring technologies that can improve crop productivity, enhance land use, and facilitate environmentally friendly agriculture. Due to its unique capacity to non-destructively examine plants' internal biological and structural properties, ultrasound has emerged as a promising non-invasive technique providing insights often unattainable with traditional optical, spectral, or chemical sensors. This review aims to provide an up-to-date state of the art in ultrasound-based monitoring applications within major agricultural areas: soil characterization, seed quality control, plant health, stress monitoring, pests and diseases detection, and fruit ripening assessment. This review explores how contact and non-contact ultrasound measurements are scalable and versatile, bridging the gaps between laboratory and field-deployed systems. Integrating ultrasound monitoring with artificial intelligence and Internet of Things (IOT) frameworks further enhances modality accuracy and can detect stress, diseases, and other physiological changes in crops sooner. Overcoming challenges such as environmental acoustic noise will require further work. Still, recent advances such as improved signal filtering algorithms, new transducer designs, better field sensitivity, and broader collaboration to standardize ultrasound measurement protocols indicate a growing trend toward increased on-field use of ultrasound. Finally, the review also discusses the current limitations and future research directions of how ultrasound-based monitoring can catalyse a new paradigm of sustainable data-driven agriculture that meets food security needs.

Indexed as

crop yieldnondestructive testingprecision agriculturesustainabilityultrasound

Identifiers

PMID40692673
PMCPMC12277354

What Socratic 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 Socratic graph.