Evidence map›Paper›PMID 40719213›Full record

ArticleCurrent protocols2025

A High-Throughput Hydroponic Assay for Rapidly Screening Drought Tolerance in Potato.

Muhammad Awais Zahid, Nam Phuong Kieu

Abstract read
In one paragraph

Article in Current protocols, 2025. 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.

Muhammad Awais ZahidDepartment of Plant Protection Biology, Swedish University of Agricultural Sciences, Lomma, Sweden.ORCID https://orcid.org/0000-0001-7065-5369
Nam Phuong KieuDepartment of Plant Protection Biology, Swedish University of Agricultural Sciences, Lomma, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Potato (Solanum tuberosum L.) yield is highly sensitive to drought stress, yet robust phenotyping methods for drought tolerance remain scarce. To address this challenge, we present a rapid, high-throughput hydroponic assay designed as an efficient pre-screening tool for evaluating potato cultivars and CRISPR-edited lines. This protocol serves as a foundational screen, enabling researchers to identify the most promising genotypes before committing resources to more extensive soil or field trials. The system uses repurposed pipette tip boxes as low-cost, scalable hydroponic units, making the method highly accessible. Over a five-week period, plantlets are subjected to controlled 24-hr osmotic stress with polyethylene glycol (PEG-6000) and then assessed for resilience based on biomass, photosynthetic measurements, and visual recovery. This resource-efficient assay provides a controlled environment to minimize experimental noise and has been successfully applied to characterize CRISPR-edited potato lines. By providing a reproducible platform for initial evaluation, this protocol accelerates the selection pipeline for developing robust potato varieties for a changing climate. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of stem explants and in vitro rooting Basic Protocol 2: Assembly and maintenance of tip-box hydroponic units Basic Protocol 3: PEG-induced drought treatment and recovery Basic Protocol 4: Post-stress phenotypic, biomass, and photosynthetic analysis.

Indexed as

DroughtsHigh-Throughput Screening AssaysHydroponicsSolanum tuberosumDrought Resistanceabiotic stress screeningCRISPRdrought tolerancehigh‐throughput phenotypingpotato (Solanum tuberosum)

Identifiers

PMID40719213
PMCPMC12302303

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.