Evidence map›Paper›PMID 38656479›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2024

An Overview of High-Throughput Crop Phenotyping: Platform, Image Analysis, Data Mining, and Data Management.

Wanneng Yang, Hui Feng, Xiao Hu, Jingyan Song, Jing Guo, Bingjie Lu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

6 authors.

Wanneng YangNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China. ywn@mail.hzau.edu.cn.
Hui FengNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Xiao HuNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Jingyan SongNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Jing GuoNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Bingjie LuNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this chapter, we explore the application of high-throughput crop phenotyping facilities for phenotype data acquisition and the extraction of significant information from the collected data through image processing and data mining methods. Additionally, the construction and outlook of crop phenotype databases are introduced and the need for global cooperation and data sharing is emphasized. High-throughput crop phenotyping significantly improves accuracy and efficiency compared to traditional measurements, making significant contributions to overcoming bottlenecks in the phenotyping field and advancing crop genetics.

Indexed as

Crops, AgriculturalData MiningImage Processing, Computer-AssistedPhenotypeData ManagementHigh-Throughput Screening AssaysCrop phenomicsCrop phenotype databaseData miningFeature extractionHigh-throughputImage processingPhenotyping platforms

Identifiers

PMID38656479

What OpenQuestion holds

Textmetadata
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.