Evidence map›Paper›PMID 42280276›Full record

ArticleMolecules (Basel, Switzerland)2026

Effects of Chemical Composition on Anaerobic Digestion Kinetics of Sugar Beet Pulp: Gompertz and Two-Fraction Kinetic Modelling.

Krzysztof Pilarski, Agnieszka A Pilarska, Piotr Boniecki, Karol Durczak, Piotr Sołowiej

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2026. 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.

Krzysztof PilarskiDepartment of Biosystems Engineering, Poznań University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland.ORCID 0000-0003-0810-8086
Agnieszka A PilarskaDepartment of Hydraulic and Sanitary Engineering, Poznań University of Life Sciences, Piątkowska 94A, 60-649 Poznań, Poland.ORCID 0000-0001-6128-0315
Piotr BonieckiDepartment of Biosystems Engineering, Poznań University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland.ORCID 0000-0002-9239-4072
Karol DurczakDepartment of Biosystems Engineering, Poznań University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland.ORCID 0000-0003-4811-005X
Piotr SołowiejFaculty of Technical Sciences, University of Warmia and Mazury in Olsztyn, Oczapowskiego 2, 10-719 Olsztyn, Poland.ORCID 0000-0002-6840-0962

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anaerobic digestion (AD) of agro-industrial residues supports the green energy transition by converting organic matter into renewable biogas. Sugar beet pulp is a highly fermentable feedstock, although its process response may vary with chemical composition. This study examined how chemical composition affects mesophilic biogas-production kinetics of sugar beet pulp prepared under laboratory conditions from surplus sugar beet roots. The roots represented ten sugar beet varieties (A-J), and the prepared pulp was characterised for pH, dry matter, organic dry matter, mineral composition, and the relative shares of simple sugars, polysaccharides, protein, and fibre. Batch digestion tests were performed at 39 °C for 30 days. Production curves were analysed using complementary kinetic models (modified Gompertz and a two-fraction first-order model) to capture the lag phase and the contributions of rapidly and slowly degradable substrate pools. Biogas yields ranged from 126 to 141 m

Indexed as

Beta vulgarisBiofuelsAnaerobiosisHydrogen-Ion ConcentrationKineticsMethaneBiofuelsMethaneanaerobic digestionchemical compositionkinetic modellingmethane kineticssugar beet pulp

Identifiers

PMID42280276
PMCPMC13257436

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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.