Evidence map›Paper›PMID 42903053›Full record

ReviewOpen research Europe2026

New challenges in horticultural IPM: artificial intelligence can enhance the use of biocontrol agents.

Andrea Lovazzano

Abstract readReview
In one paragraph

Review in Open research Europe, 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

1 author.

Andrea LovazzanoDipartimento di Scienze Agrarie Alimentari e Agro-ambientali, Universita degli Studi di Pisa, Pisa, Tuscany, 56124, Italy.ORCID https://orcid.org/0000-0002-7445-6460

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern horticulture faces the dual imperatives of increasing global food production while mitigating the severe environmental and health impacts of conventional chemical pesticides. Biological control agents (BCAs), which utilize beneficial microorganisms, macroorganisms, semiochemical and botanicals to suppress pathogens, represent a cornerstone of sustainable agriculture but have been historically constrained by inconsistent field performance, high specificity, and slow action. Concurrently, Artificial Intelligence (AI) is emerging as a transformative force in agriculture, offering a powerful suite of tools for data analysis, prediction, and automation. The synergy of BCAs and AI creates advanced strategies where AI directly addresses the inherent limitations of biological control. It can foster the deployment of AI-driven predictive models for proactive pest outbreak forecasting, enabling timely and effective BCA application. Furthermore, it details the role of precision robotics and drones, guided by computer vision, in the targeted delivery of these agents. These components are synthesized into the concept of Integrated Pest Management (IPM) 5.0, where intelligent decision support systems orchestrate a holistic, data-driven approach to plant health. However, the realization of this vision is contingent on overcoming significant economic, regulatory, and adoption hurdles. High initial costs, complex and divergent regulatory countries in the EU and US, and socio-technical barriers to farmer adoption present formidable challenges. A focus on developing robust, low-cost technologies, enhancing BCA formulation and stability, creating interoperable data frameworks, and addressing the socio-economic factors is necessary to translate technological potential into widespread, sustainable practice.

Indexed as

natural enemies; sustainability; agroecosystem; plant health; robotics; DSS; machine learning; computer vision

Identifiers

PMID42903053
PMCPMC13679776

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.