Evidence map›Paper›PMID 39479700›Full record

ArticleFood science & nutrition2024

Nonindustrial pretreatment and enzymes can yield sufficient calories from lignocellulosic biomass for human survival.

Niroshan Siva, Charles T Anderson

Abstract read
In one paragraph

Article in Food science & nutrition, 2024. 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

2 authors.

Niroshan SivaDepartment of Biology The Pennsylvania State University University Park Pennsylvania USA.
Charles T AndersonDepartment of Biology The Pennsylvania State University University Park Pennsylvania USA.ORCID https://orcid.org/0000-0001-7481-3571

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Following a global catastrophe causing reduced sunlight, the environment would become unfavorable for crop growth. Under such conditions, people might need to convert inedible plant biomass into food to meet their daily nutritional requirements. However, the possibility of converting biomass into food under low-resource conditions has not been thoroughly studied. To address this uncertainty, we evaluated the potential for using resources available in a typical household to extract sugars from willow biomass and meet the carbohydrate needs of an adult. Grinding willow biomass in a household blender for 24 min produced willow particles similar to those produced in a laboratory-scale Wiley mill. Thermal treatments of these particles with hot water extraction, pressure cooking, or microwaving only extracted 0.5%-0.8% (w/w) glucose from the biomass. Household acid or alkali treatments yielded only 0.5% (w/w) glucose. These sugar yields would be insufficient to provide nutrition to an adult. In contrast, enzymatic hydrolysis of pretreated willow at 50°C for 72 h yielded 2%-8% (w/w) glucose, and pretreating willow with sodium hydroxide and pressure before enzymatic treatment increased glucose yields to 28% (w/w). With this pretreatment approach and subsequent enzymatic conversion, ~1.4 kg of biomass/day could potentially fulfill the energy needs of an adult under post-catastrophic conditions. We posit that while biomass can be successfully pretreated for enzymatic deconstruction at a household level, producing sufficient enzymes for efficient sugar extraction from inedible plant biomass in a post-catastrophic environment might not be feasible at the household scale, thus requiring community-scale infrastructure and coordination.

Indexed as

biomass conversionemergency foodsglobal catastropheplant biomasssugar extraction

Identifiers

PMID39479700
PMCPMC11521637

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.