Evidence map›Paper›PMID 36570903›Full record

ArticleFrontiers in plant science2022

Identification of cassava germplasms resistant to two-spotted spider mite in China: From greenhouse large-scale screening to field validation.

Xiao Liang, Qing Chen, Ying Liu, Chunling Wu, Kaimian Li, Mufeng Wu, Xiaowen Yao, Yang Qiao, Yao Zhang, Yue Geng

Abstract read
In one paragraph

Article in Frontiers in plant science, 2022. 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. Frontiers in plant science · 2022
    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.

Xiao LiangEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Qing ChenEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Ying LiuEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Chunling WuEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Kaimian LiTropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agriculture Sciences, Haikou, China.
Mufeng WuEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Xiaowen YaoEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Yang QiaoEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Yao ZhangEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.
Yue GengEnvironment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Utilization of resistant germplasm is considered as an effective, economical and eco-friendly strategy for cassava pest management. Methods: To fill this knowledge gap, we conducted screening of 202 cassava germplasm for resistance to TSSM in China based on the classification of mite damage phenotype, under both greenhouse and field conditions. Results: The three rounds of large-scale greenhouse experiments had identified two highly resistant (HR) varieties (C1115 and MIANDIAN), five resistant (R) varieties (SC5, SC9, SC15, COLUMBIA-4D and LIMIN) and five highly susceptible (HS) varieties (KU50, BREAD, SC205, TMS60444 and BRA900), besides, these 'HR' and 'R' varieties would significantly repress the normal development and reproduction of TSSM. In addition, the 12 cassava varieties selected from the greenhouse screening were further subjected to consecutive five years of field validation at Danzhou, Wuming and Baoshan. The seven resistant varieties not only exhibited stable TSSM-resistance performance across the three field environments, but also possessed the same resistant levels as the greenhouse identification, while the resistant varieties SC5 was an exception, which was identified as moderate resistant in Baoshan, indicating the variety-environment interaction may affect its resistance. Furthermore, regional yield estimation suggested that the higher the resistance level was, the better capacity in reducing the yield losses. Discussion: This study demonstrated that the TSSM-resistant varieties could be considered as ideal materials in mite control or in future breeding programme of mite-resistant cassava plant.

Indexed as

eco-friendlyManihot esculentamite pestresistanceTetranychus urticae

Identifiers

PMID36570903
PMCPMC9768451

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Registered trials

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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.