Evidence map›Paper›PMID 39251762›Full record

ArticleNature food2024

Artificial intelligence can regulate light and climate systems to reduce energy use in plant factories and support sustainable food production.

Benjamin Decardi-Nelson, Fengqi You

Abstract read
PubMed Publisher
In one paragraph

Article in Nature food, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
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  6. Review
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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.

Benjamin Decardi-NelsonSystems Engineering, Cornell University, Ithaca, NY, USA.
Fengqi YouSystems Engineering, Cornell University, Ithaca, NY, USA. fengqi.you@cornell.edu.ORCID http://orcid.org/0000-0001-9609-4299

Funding

U.S. Department of Agriculture (United States Department of Agriculture) 2022-51181-38324
6 · The paper itself

Abstract

Plant factories with artificial lighting (PFALs) can boost food production per unit area but require resources such as carbon dioxide and energy to maintain optimal plant growth conditions. Here we use computational modelling and artificial intelligence (AI) to examine plant-environment interactions across ten diverse global locations with distinct climates. AI reduces energy use by optimizing lighting and climate regulation systems, with energy use in PFALs ranging from 6.42 kWh kg

Indexed as

Artificial IntelligenceCarbon DioxideClimateConservation of Energy ResourcesFood SupplyLightLightingTemperatureCarbon Dioxide

Identifiers

What OpenQuestion holds

Textmetadata
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.