Banana blood disease is a banana wilt disease caused by Ralstonia syzygii subsp. celebesensis (RSC) poses a serious threat to banana plantations, particularly in Indonesia and Malaysia. Yet, the current control methods are inadequate to mitigate the disease. Biological control agents (BCAs) offer a promising solution by using beneficial microorganisms to control pathogens. Among BCAs, lactic acid bacteria (LAB) have gained increasing attention in agriculture due to their ability to produce a variety of antimicrobial compounds. This study investigates the antimicrobial substances produced by Lactiplantibacillus plantarum and Lacticaseibacillus paracasei against RSC using cell-free supernatants (CFS) and liquid-liquid extraction (LLE). The inhibitory effect of the LAB extracts against RSC was evaluated using agar well diffusion method. Liquid chromatography-mass spectrometry analysis confirmed the bioactive metabolites with potential antibacterial activity against RSC are monoglucosyl-enterobactin, (6Z,9Z,12Z)-octadecatrienoic acid, and 2-(hydroxymethyl)-3-(acetamidomethylene)succinate from CFS-L. plantarum; canavanine, norspermidine and 4-gua-nidinobutanamide in CFS-L. paracasei; sinapic acid, lecanoric acid and D-glucono-1,5-lactone in LLE-L. plantarum and lithocholic acid, orotic acid and sterculic acid in LLE-L. paracasei. A scanning electron microscope has shown disruption and damage to the RSC cells during LAB treatment. These findings highlight the potential of L. plantarum and L. paracasei metabolites for biocontrol applications.
Cadra cautella (Walker, 1863) is a global pest of agricultural stored commodities, particularly date fruits, in the field and storage. To reduce C. cautella populations in stored agricultural goods, it is recommended to use ecologically friendly methods rather than chemical treatments. In this regard, current research evaluated the efficacy of various indigenous strains of the entomopathogenic fungus Beauveria bassiana (Bals.-Criv.). Vuill. (1912), fungal isolates against C. cautella last-instar larvae under laboratory conditions. The last instar larvae were incubated in Petri plates with dry Beauveria bassiana inoculum (1 & times; 107 conidia/mL) for five minutes per fungal isolate. The susceptibility of C. cautella larvae to fungal infection was tested until either 100% mortality across all treatments was achieved or the control larvae had transformed into pupae. The results showed that, compared with the control treatment, all fungal isolates were pathogenic to C. cautella larvae, with varying levels of reaction and durations of mortality. After four days of inoculation, the B. bassiana isolates BbSA-5, BbSA-8, and BbSA-9 infected treated C. cautella larvae at rates of 16.66%, 23.33%, and 43.33%, respectively. The death rate of C. cautella larvae increased significantly, reaching 91.66% for BbSA-5 isolates after eight days of the treatment, while BbSA-5 and BbSA-9 isolates achieved 100% mortality after sixteen days. The control treatment resulted in no larval mortality. Furthermore, all C. cautella larvae in the control group pupated and successfully matured into adults. It is determined that the examined dry formulations of local fungal isolates have the capacity to protect stored agricultural commodities, including date fruits, from C. cautella infestation.
Bacterial panicle blight (BPB), caused by Burkholderia glumae, is a major and rising threat to global rice production. Its severity is heightened by climate change, with outbreaks driven by high temperatures and humidity during the vulnerable flowering stage. Current management is hampered by delayed detection and a disconnect between diagnostic tools and predictive models. This review synthesises advances across climatology, molecular biology, and computational agriculture to address this gap. We analyse climate-driven disease dynamics, precise molecular diagnostics, and the emergence of AI for real-time image-based detection and weather-based forecasting. The novel contribution of this work is the proposal of an Integrated Multimodal AI Framework (IMAF) that converges these domains. The IMAF links climate modelling, sensor data, and computer vision to enable proactive, climate-resilient disease forecasting and decision support. This synthesis represents a critical paradigm shift from reactive management to intelligent, predictive intervention. We conclude with a roadmap for developing and deploying such integrated systems to enhance global rice resilience.
We report the first detection of the plant pathogenic yeast Eremothecium coryli in the Czech Republic and identify the invasive brown marmorated stink bug, Halyomorpha halys, as a vector. E. coryli causes yeast spot diseases in crops such as soybeans, hazelnuts, and tomatoes, primarily in tropical and subtropical regions. The yeast was identified in the foregut of H. halys specimens collected in a cherry orchard near the hazelnut shrubs using PCR amplification and sequencing of the ITS and LSU gene regions. Phylogenetic analysis confirmed the identity of E. coryli and its association with H. halys, as discussed.
