ReviewWorld journal of microbiology & biotechnology2026
Microbial innovations for climate-resilient agriculture: mechanisms, applications, and emerging technologies.
Review in World journal of microbiology & biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Editorial for the Special Issue "Advances in Microbial and Plant Biotechnology".Microorganisms · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Agriculture is increasingly challenged by climate change-driven stresses, including rising temperatures, erratic rainfall, soil degradation, with increased frequency of pests and disease outbreaks. This disrupts crop productivity and threatens global food security, underscoring the urgent need for sustainable, adaptive strategies, which are environment-friendly. Microorganisms, integral to soil health, nutrient cycling, and plant stress physiology, offer promising nature-based solutions for climate resilient agriculture. Yet their potential remains underutilized due to technical, ecological, and socio-economic barriers that hinder widespread adoption. This review addresses these research gaps and practical challenges, while outlining future perspectives for scaling up microbe-based technologies through integration with omics and AI tools. The major points addressed in this review are (1) Major advances in microbial applications that directly support crop resilience and ecosystem sustainability. It examines recent progress made towards enhancing the effectiveness of biofertilizers (including mycorrhizal fungi), biopesticides and developing novel products, detailing how these innovations enhance nutrient acquisition, regulate phytohormonal balance, improve water-use efficiency, mitigate abiotic stresses such as drought, salinity, heat and pH, and minimize losses incurred due to pathogen and pests; (2) Mechanistic insights into microbial mediation of nutrient cycling, soil aggregation, and stress alleviation in terms of plant-microbe or soil-plant microbiome networking; (3) The role of emerging biotechnological tools, including metagenomics, microbiome engineering, and synthetic biology, that enable the design of more effective and context-specific microbial interventions that can be integrated with artificial intelligence (AI) and machine learning (ML) tools for precise application (4) Emphasis on both the benefits and constraints of microbial inoculants is documented as well as novel strategies for their effective use as sustainable solutions for climate ready agriculture. Ultimately, microbial innovations are positioned as pivotal in building climate-resilient agroecosystems capable of sustaining productivity and reducing environmental footprints.
Indexed as
Identifiers
42250135What OpenQuestion holds
Registered trials
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.