Evidence map›Paper›PMID 33178239›Full record

ArticleFrontiers in plant science2020

A Non-destructive Method to Quantify Leaf Starch Content in Red Clover.

Lea Antonia Frey, Philipp Baumann, Helge Aasen, Bruno Studer, Roland Kölliker

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2020. 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
0.8field-weighted citation impact, top 26% of its field
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, 6 citations in OpenAlex.

  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

5 authors at 1 institution in 1 country.

Lea Antonia FreyMolecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Philipp BaumannSustainable Agroecosystems, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Helge AasenCrop Science, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Bruno StuderMolecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Roland KöllikerMolecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
ETH Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grassland-based ruminant livestock production provides a sustainable alternative to intensive production systems relying on concentrated feeds. However, grassland-based roughage often lacks the energy content required to meet the productivity potential of modern livestock breeds. Forage legumes, such as red clover, with increased starch content could partly replace maize and cereal supplements. However, breeding for increased starch content requires efficient phenotyping methods. This study is unique in evaluating a non-destructive hyperspectral imaging approach to estimate leaf starch content in red clover for enabling efficient development of high starch red clover genotypes. We assessed prediction performance of partial least square regression models (PLSR) using cross-validation, and validated model performance with an independent test set under controlled conditions. Starch content of the training set ranged from 0.1 to 120.3 mg g

Indexed as

forage qualitygrasslandhyperspectral imagingpartial least square regressionred cloverstarch content

Identifiers

PMID33178239
PMCPMC7593268
OpenAlexW3092669478

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.