Evidence map›Paper›PMID 42505845›Full record

ReviewInsects2026

Selective Breeding and Trait Improvement of Insect Natural Enemies for Ecologically Robust Biological Control.

Xu Chen, Jie Wang, Yong-Ming Chen, Lian-Sheng Zang, Su Wang

Abstract readReview
In one paragraph

Review in Insects, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Xu ChenKey Laboratory of Natural Enemies Insects, Ministry of Agriculture and Rural Affairs, Institute of Plant Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.
Jie WangCollege of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou 311121, China.ORCID 0000-0003-3100-3290
Yong-Ming ChenState Key Laboratory of Green Pesticides, Guizhou University, Guiyang 550025, China.ORCID 0000-0002-6287-7997
Lian-Sheng ZangState Key Laboratory of Green Pesticides, Guizhou University, Guiyang 550025, China.
Su WangKey Laboratory of Natural Enemies Insects, Ministry of Agriculture and Rural Affairs, Institute of Plant Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.ORCID 0000-0001-5166-0250

Funding

National Key R&D Program of China 2023YFD1400600
6 · The paper itself

Abstract

Insect natural enemies are central agents in biological-control programs. Their pest-suppression performance depends not only on release strategy, but also on traits shaped by long-term laboratory rearing and selection. Conventional mass-rearing systems usually evaluate insect natural enemies using production-oriented indicators, such as survival, fecundity, emergence rate, sex ratio and production cost. However, continuous mass rearing can drive laboratory adaptation, genetic drift, inbreeding, shifts in host or prey use, and reduced field performance. In this review, we summarize key target traits for insect natural enemy improvement, including production efficiency, host or prey use, parasitism, predation, nonreproductive host killing, stress tolerance, pesticide compatibility, dispersal, retention and field efficacy. We further discuss how recurrent artificial selection, hybridization, population genetics, and genomics approaches can be integrated to improve insect natural enemies while maintaining genetic quality. Finally, we discuss the links among trait screening, selection design, quality control, storage and transport, and field-performance validation in the development and application of selected lines or improved strains. Overall, this review highlights practical directions for developing stable and field-proven natural enemy lines. Beyond agriculture, this perspective may also support ecological design in urban landscapes through natural enemy conservation and reduced pesticide use.

Indexed as

artificial selectionbiological controlgenetic improvementnatural enemiesquality controlselective breeding

Identifiers

PMID42505845
PMCPMC13411242

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.