Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 173

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium spec. Infections on Wheat

Open access
Bauriegel, Elke, Herppich, Werner·2014·Agriculture

Abstract

In recent years, market pressures have reinforced the demand to solve the problem of an increased occurrence of Fusarium head blight (FHB) in cereal production, especially in wheat. The symptoms of this disease are clearly detectable by means of image analysis. This technique can therefore be used to map occurrence and extent of Fusarium infections. From this perspective, a separate harvest in the field can be taken into consideration. Based on the application of chlorophyll fluorescence and hyperspectral imaging, characteristics, requirements and limitations of Fusarium detection on wheat, both in the field and in the laboratory, are discussed. While the modification of spectral signatures due to fungal infection allows its detection by hyperspectral imaging, the decreased physiological activity of tissues resulting from Fusarium impacts provides the base for CFI analyses. In addition, the two methods are compared in view of their usability for the detection of Fusarium, and different approaches for data analysis are presented.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/agriculture4010032

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 173

Metadata

Authors
Bauriegel, E., & Herppich, W.
Venue
Agriculture
Publisher
MDPI AG
Published
2014-03-24
Volume
4
Issue
1
Pages
32-57
ISSN
2077-0472 (ISSN-L)
OpenAlex
W1984185202
Cited by
173
References
1
FWCI
10.81
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium spec. Infections on Wheat. https://app.cochat.ai/papers/10.3390/agriculture4010032
The paper
Bauriegel, E., & Herppich, W. (2014). Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium spec. Infections on Wheat. Agriculture. https://doi.org/10.3390/agriculture4010032

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.