Evidence map›Paper›PMID 40713838›Full record

ArticlePlant methods2025

Quantifying the severity of Marssonina blotch on apple leaves: development and validation of a novel spectral index.

Wenjie Zhang, Chengjian Zhang, Riqiang Chen, Bo Xu, Hao Yang, Haikuan Feng, Dan Zhao, Baoguo Wu, Chunjiang Zhao, Guijun Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plant methods, 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

10 authors.

Wenjie ZhangSchool of Information Science & Technology, Beijing Forestry University, Beijing, 100083, China.
Chengjian ZhangSchool of Information Science & Technology, Beijing Forestry University, Beijing, 100083, China.
Riqiang ChenSchool of Information Science & Technology, Beijing Forestry University, Beijing, 100083, China.
Bo XuKey Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Hao YangKey Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Haikuan FengKey Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Dan ZhaoKey Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Baoguo WuSchool of Information Science & Technology, Beijing Forestry University, Beijing, 100083, China.
Chunjiang ZhaoSchool of Information Science & Technology, Beijing Forestry University, Beijing, 100083, China. zhaocj@nercita.org.cn.
Guijun YangKey Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China. yanggj@nercita.org.cn.

Funding

National Key Research and Development Program of China 2023YFD2000100Natural Science Foundation of China 42171303
6 · The paper itself

Abstract

Apple Marssonina blotch (AMB) is a major disease causing pre-mature defoliation. The occurrence of AMB will lead to serious production decline and economic losses. The precise identification of AMB outbreaks and the measurement of its severity are essential for limiting the spread of the disease, yet this issue remains unaddressed to this day. Given these, we conducted experiments in Qian County, Shaanxi, China, to develop an Apple Marssonina Blotch Index (AMBI) based on hyperspectral imaging, aimed to quantify disease severity at the leaf scale and to monitor infection at the canopy scale. Based on the separability and combination of individual band, characteristic wavelengths were identified in green band, red edge band and near-infrared band to construct AMBI = (R

Indexed as

AppleDisease detectionDisease severityHyperspectral imagingNoninvasive

Identifiers

PMID40713838
PMCPMC12297681

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.