Evidence map›Paper›PMID 35563802›Full record

ArticleCells2022

Improving Microalgal Biomass Productivity Using Weather-Forecast-Informed Operations.

Song Gao, Hongxiang Yan, Nathan Beirne, Mark Wigmosta, Michael Huesemann

Abstract read
In one paragraph

Article in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Microalgae cultivation: closing the yield gap from laboratory to field scale.Frontiers in bioengineering and biotechnology · 2024
    Article
  4. 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.

Song GaoMarine and Coastal Research Laboratory, Pacific Northwest National Laboratory, Sequim, WA 98382, USA.ORCID 0000-0002-7210-4445
Hongxiang YanEnergy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
Nathan BeirneMarine and Coastal Research Laboratory, Pacific Northwest National Laboratory, Sequim, WA 98382, USA.
Mark WigmostaEnergy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
Michael HuesemannMarine and Coastal Research Laboratory, Pacific Northwest National Laboratory, Sequim, WA 98382, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The operation of microalgal cultivation systems, such as culture dilution associated with harvests, affects biomass productivity. However, the constantly changing incident light and ambient temperature in the outdoor environment make it difficult to determine the operational parameters that result in optimal biomass growth. To address this problem, we present a pond operation optimization tool that predicts biomass growth based on future weather conditions to identify the optimal dilution rate that maximizes biomass productivity. The concept was tested by comparing the biomass productivities of three dilution scenarios: standard batch cultivation (no dilution), fixed-rate dilution (harvest 60% of the culture every three days), and weather-forecast-informed dilution. In the weather-forecast-informed case, the culture was diluted daily, and the dilution ratio was optimized by the operation optimization tool according to the future 24 h weather condition. The results show that the weather-forecast-informed dilution improved the biomass productivity by 47% over the standard batch cultivation and 20% over the fixed-rate dilution case. These results demonstrate that the pond operation optimization tool could help pond operators to make decisions that maximize biomass growth in the field under ever-changing weather conditions.

Indexed as

MicroalgaeBiomassPhotobioreactorsWeatherbiomass productivitydilution ratemicroalgaephotobioreactorweather-forecast-informed

Identifiers

PMID35563802
PMCPMC9101621

What OpenQuestion holds

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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.