Evidence map›Paper›PMID 36366030›Full record

ReviewSensors (Basel, Switzerland)2022

Trends of Augmented Reality for Agri-Food Applications.

Junhao Xie, Jackey J K Chai, Carol O'Sullivan, Jun-Li Xu

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Junhao XieSchool of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
Jackey J K ChaiSchool of Computer Science and Statistics, Trinity College Dublin, College Green, Dublin 2, Ireland.ORCID 0000-0002-2645-7012
Carol O'SullivanSchool of Computer Science and Statistics, Trinity College Dublin, College Green, Dublin 2, Ireland.
Jun-Li XuSchool of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.ORCID 0000-0002-4442-7538

Funding

Science Foundation Ireland 18/CRT/6224
6 · The paper itself

Abstract

Recent years have witnessed an increasing interest in deploying state-of-the-art augmented reality (AR) head-mounted displays (HMDs) for agri-food applications. The benefits of AR HMDs to agri-food industry stakeholders (e.g., food suppliers, retail/food service) have received growing attention and recognition. AR HMDs enable users to make healthier dietary choices, experience novel changes in their perception of taste, enhance the cooking and food shopping experience, improve productivity at work and enhance the implementation of precision farming. Therefore, although development costs are still high, the case for integration of AR in food chains appears to be compelling. This review will present the most recent developments of AR HMDs for agri-food relevant applications. The summarized applications can be clustered into different themes: (1) dietary and food nutrition assessment; (2) food sensory science; (3) changing the eating environment; (4) retail food chain applications; (5) enhancing the cooking experience; (6) food-related training and learning; and (7) food production and precision farming. Limitations of current practices will be highlighted, along with some proposed applications.

Indexed as

Augmented RealitySmart GlassesAttentionLearningagricultureaugmented realityfoodHMDnutritionsensory science

Identifiers

PMID36366030
PMCPMC9653656

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.