Evidence map›Paper›PMID 42283013›Full record

ReviewFrontiers in veterinary science2026

Estrus detection in dairy cattle: an updated review on strategies and technologies.

Devaraj Sankarganesh, Parcha Durga Sai Sita Yesaswini Krishna Prasad, Shivani Sujit, Annis Inncia Gnana Thiraviam, Divakar Justus Ambrose

Abstract readReview
In one paragraph

Review in Frontiers in veterinary science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Devaraj SankarganeshSchool of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Parcha Durga Sai Sita Yesaswini Krishna PrasadSchool of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Shivani SujitSchool of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Annis Inncia Gnana ThiraviamSchool of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Divakar Justus AmbroseDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many factors may negatively affect dairy cattle productivity, among which imprecise estrus detection is a major contributor to low reproductive efficiency. Given that artificial insemination is widely used in the dairy industry, accurate estrus detection is of great importance. Estrus synchronization using hormonal treatments is a common approach to regulate the estrous cycle and to improve the efficiency of estrus detection. Estrus detection using artificial intelligence-aided data analyses is a new development. Biomarker-based chemical sensors and activity based wearable and implantable sensors are also available for monitoring. Behavioral datasets have been used in machine learning and other approaches; however, such datasets must be validated for their applicability in detecting estrus before being utilized by dairy farmers. The cumulative knowledge of estrus detection approaches, their merits, demerits, applicability, and cost-effectiveness is highly warranted. Therefore, here, we provide an update on the recent approaches and technologies used for estrus detection, particularly in dairy cattle, and discuss emerging experimental technologies with potential for future applications.

Indexed as

estrogenfemale dairy cattleprogesteronesilent heatwearable electronic devices

Identifiers

PMID42283013
PMCPMC13251696

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.