Evidence map›Paper›PMID 37267341›Full record

ArticlePloS one2023

Designing profitable and climate-smart farms using virtual reality.

Remy Lasseur, Seth Laurenson, Mohsin Ali, Ian Loh, Mike Mackay

Abstract read
In one paragraph

Article in PloS one, 2023. 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.

Remy LasseurAgResearch, Lincoln Research Centre, Private Bag 4749, Christchurch, New Zealand.ORCID 0000-0002-5134-1310
Seth LaurensonAgResearch, Lincoln Research Centre, Private Bag 4749, Christchurch, New Zealand.
Mohsin AliMohsin Media Designer, Wellington, New Zealand.
Ian LohMohsin Media Designer, Wellington, New Zealand.
Mike MackayAgResearch, Lincoln Research Centre, Private Bag 4749, Christchurch, New Zealand.ORCID 0000-0003-3948-8130

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many pastoral farmers are searching for ways to lower the carbon emission footprint that is generated by livestock. Planting trees on the farm is currently a popular option for farmers to offset their emissions yet requires knowledge of suitable tree species and locations to plant them. This paper describes a decision-support tool aimed at helping farmers to create and visualise different planting designs while balancing the objectives of sequestering carbon and maintaining farm profitability. We take an innovative approach by combining virtual reality technology with biophysical models to create an environment where the user can actively create virtual future farm scenarios. Through the creation process, the user can simultaneously balance multiple objectives including farm aesthetics, economic returns, business and environmental ambitions, and carbon emissions (net) balance. For this proof-of-concept study, we incorporate virtual reality technology in Unreal Engine, environmental and financial data, and high-resolution spatial layers from an operational 400-hectare livestock farm in New Zealand.

Indexed as

DairyingVirtual RealityAnimalsCarbonFarmersFarmsHumansLivestockCarbon

Identifiers

PMID37267341
PMCPMC10237638

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.