Evidence map›Paper›PMID 36760650›Full record

ArticleFrontiers in plant science2023

A variety test platform for the standardization and data quality improvement of crop variety tests.

Feng Yang, Zhongqiang Liu, Yuxi Wang, Xiaofeng Wang, Qiusi Zhang, Yanyun Han, Xiangyu Zhao, Shouhui Pan, Shuo Yang, Shufeng Wang and 3 more

Abstract read
In one paragraph

Article in Frontiers in plant science, 2023. 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. 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

13 authors.

Feng YangInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Zhongqiang LiuInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Yuxi WangNational Agro-Tech Extension and Service Center, Beijing, China.
Xiaofeng WangInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Qiusi ZhangInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Yanyun HanInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Xiangyu ZhaoInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Shouhui PanInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Shuo YangAgChip Science and Technology (Beijing) Co., Ltd., Beijing, China.
Shufeng WangInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Qi ZhangInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Jun QiuNational Agro-Tech Extension and Service Center, Beijing, China.
Kaiyi WangInformation Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Variety testing is an indispensable and essential step in the process of creating new improved varieties from breeding to adoption. The performance of the varieties can be compared and evaluated based on multi-trait data from multi-location variety tests in multiple years. Although high-throughput phenotypic platforms have been used for observing some specific traits, manual phenotyping is still widely used. The efficient management of large amounts of data is still a significant problem for crop variety testing. This study reports a variety test platform (VTP) that was created to manage the whole workflow for the standardization and data quality improvement of crop variety testing. Through the VTP, the phenotype data of varieties can be integrated and reused based on standardized data elements and datasets. Moreover, the information support and automated functions for the whole testing workflow help users conduct tests efficiently through a series of functions such as test design, data acquisition and processing, and statistical analyses. The VTP has been applied to regional variety tests covering more than seven thousand locations across the whole country, and then a standardized and authoritative phenotypic database covering five crops has been generated. In addition, the VTP can be deployed on either privately or publicly available high-performance computing nodes so that test management and data analysis can be conveniently done using a web-based interface or mobile application. In this way, the system can provide variety test management services to more small and medium-sized breeding organizations, and ensures the mutual independence and security of test data. The application of VTP shows that the platform can make variety testing more efficient and can be used to generate a reliable database suitable for meta-analysis in multi-omics breeding and variety development projects.

Indexed as

crop variety testdata quality controlstandardizationstatistical analysistrait data

Identifiers

PMID36760650
PMCPMC9902355

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.