Evidence map›Paper›PMID 40063508›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Wood Biomolecules as Agricultural Adjuvants for Effective Suppression of Droplet Rebound from Plant Foliage.

Mamata Bhattarai, Hedar Al-Terke, Kai Liu, Zhangmin Wan, Petri Kilpeläinen, Alistair W T King, Alexey Khakalo, Jiayun Xu, Chunlin Xu, Robin H A Ras and 2 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Mamata BhattaraiDepartment of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Espoo, FI-00076, Finland.ORCID https://orcid.org/0000-0001-7121-4602
Hedar Al-TerkeDepartment of Applied Physics, Aalto University, Espoo, FI-00076, Finland.
Kai LiuDepartment of Applied Physics, Aalto University, Espoo, FI-00076, Finland.
Zhangmin WanDepartment of Chemical & Biological Engineering, Department of Chemistry, Department of Wood Science, Bioproducts Institute, The University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
Petri KilpeläinenProduction Systems, Biomass Fractionation Technologies, Natural Resource Institute Finland (LUKE), Viikinkaari 9, Helsinki, 00790, Finland.ORCID https://orcid.org/0000-0002-0982-0123
Alistair W T KingBioinspired Materials, Cellulose Coatings and Films, VTT Technical Research Centre of Finland Ltd., Tietotie 4E, Espoo, FI-02044, Finland.ORCID https://orcid.org/0000-0003-3142-9259
Alexey KhakaloBioinspired Materials, Cellulose Coatings and Films, VTT Technical Research Centre of Finland Ltd., Tietotie 4E, Espoo, FI-02044, Finland.ORCID https://orcid.org/0000-0001-7631-9606
Jiayun XuLaboratory of Natural Materials Technology, Åbo Akademi University, Henrikinkatu 2, Turku, FI-20500, Finland.
Chunlin XuLaboratory of Natural Materials Technology, Åbo Akademi University, Henrikinkatu 2, Turku, FI-20500, Finland.ORCID https://orcid.org/0000-0003-1860-9669
Robin H A RasDepartment of Applied Physics, Aalto University, Espoo, FI-00076, Finland.ORCID https://orcid.org/0000-0002-2076-242X
Bruno D MattosDepartment of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Espoo, FI-00076, Finland.ORCID https://orcid.org/0000-0002-4447-8677
Orlando J RojasDepartment of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Espoo, FI-00076, Finland.ORCID https://orcid.org/0000-0003-4036-4020

Funding

Academy of Finland, Life-Inspired Hybrid Materials (2022-2029) 346109Academy of Finland's Flagship Programme - Competence Center for Materials Bioeconomy, FinnCERES 318890Academy of Finland's Flagship Programme - Competence Center for Materials Bioeconomy, FinnCERES 318891Canada Excellence Research Chairs, Government of Canada CERC-2018-00006European Research Council, H2020 788489Natural Resources Institute Finland (Luke) 41007-00212300
6 · The paper itself

Abstract

The agrochemical run-off associated with crop control is an unintended consequence of droplet rebound from plant foliage, which negatively affects crop performance and the environment. This is most critical in water-based formulations delivered on plant surfaces that are typically waxy and nonwetting. This study introduces an alternative to synthetic surfactants and high molecular weight polymers that are used as spreading agents for agrochemicals. Specifically, biopolymeric adjuvants (hemicelluloses and oligomeric lignin) extracted from wood by pressurized hot water are shown for their synergistic pinning capacity and surface activity that can effectively suppress droplet rebound from hydrophobic surfaces. Hemicellulose and lignin mixtures, alongside several model compounds, are investigated for understanding the dynamics of droplet impact and its correlation with biomacromolecule formations. The benefit of utilizing lean solutions (0.1 wt.% concentration) is highlighted for reducing droplet rebounding from leaves, outperforming synthetic systems in current use. For instance, a tenfold deposition improvement is demonstrated on citrus leaves, because of a significantly suppressed droplet roll-off. These results establish the excellent prospects of wood extracts to improve crop performance.

Indexed as

AgricultureAgrochemicalsPlant LeavesWoodLigninPolysaccharidesAgrochemicalshemicelluloseLigninPolysaccharidesadhesionagrochemical spreadingcrop protectiondroplet bouncinghemicellulosesleaves, lignin

Identifiers

PMID40063508
PMCPMC12061315

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.