Management of bakanae disease of rice using biocontrol agents and insights into their biocontrol mechanisms

Rapid and accurate identification of bakanae pathogens carried by rice seeds based on hyperspectral imaging and deep transfer learning

Bakanae disease is a common seed-borne disease of rice. Rapid and accurate detection of bakanae pathogens carried by rice seeds is essential for the health of rice germplasm resources and the safety of rice production. This study aims to propose a general framework for species identification of major bakanae pathogens carried by rice seeds based on hyperspectral imaging and deep transfer learning. Seven varieties of rice seeds and four kinds of bakanae pathogens were analyzed. One-dimensional deep convolution neural networks (DCNNs) were first constructed using complete datasets. They achieved accuracies larger than 96.5% on the testing sets of most datasets, exceeding the conventional SVM and PLS-DA models. Then the developed DCNNs were transferred to detect other complete training sets. Most of the deep transferred models achieved comparable or even better performance than the original DCNNs. Two smaller target training sets were further constructed by randomly selecting spectra from the complete training sets. As the size of the target training sets reduced, the accuracies of all models on the corresponding testing sets also decreased gradually. Visualization analysis were conducted using the t-distribution stochastic neighbor embedding (t-SNE) algorithm and a proposed gradient-weighted activation wavelength (Grad-AW) method. They all showed that deep transfer learning could utilize the representation patterns in the source datasets to improve the target tasks. The overall results indicated that the bakanae pathogens were all identified accurately under our proposed framework. Hyperspectral imaging combined with deep transfer learning provided a new idea for the quality detection of large-scale seeds in modern seed industry.

Evaluation of Trichoderma spp. on Fusarium oxysporum f. sp. asparagi and Fusarium wilt Control in Asparagus Crop

Among the key diseases affecting the asparagus crop (Asparagus officinalis L.), vascular wilting of asparagus caused by Fusarium oxysporum f. sp. asparagi stands out worldwide. This disease significantly shortens the longevity of the crop and limits economic production. Traditional control measures have been largely ineffective, and chemical control methods are difficult to apply, making biological control approaches, specifically the use of Trichoderma, an economical, effective, and risk-free alternative. This study aimed to identify the main factors that affect the efficacy of biopesticides studied as Biological Control Agents (BCAs) against Fusarium wilt in asparagus and to assess the efficacy of Trichoderma-based biopesticides under greenhouse and semi-field conditions. We evaluated the response of three Trichoderma spp. (T. atroviride, T. asperellum, and T. saturnisporum) to environmental variables, such as temperature and water activity, and their antagonistic capacity against Fusarium oxysporum f. sp. asparagi. All three Trichoderma species inhibited the growth of the pathogen in vitro. A decrease in water activity led to a greater reduction in the growth rate. The efficacy of the three biological control agents decreased with higher temperatures, resulting in minimal inhibition, particularly under conditions of restricted available water in the environment. The effect of the fungal inoculum density was also analyzed at two different temperatures. A direct correlation between the amount of inoculum and the score on the Disease Severity Index (DSI) was observed. A notable reduction in DSI was evident in treatments with high inoculum density (106 conidium/mL) for all three species of Trichoderma tested at both temperatures. In greenhouse and semi-field tests, we observed less disease control than expected, although T. asperellum and T. atroviride showed lower disease severity indices and increased the dry weight of seedlings and crowns, whereas T. saturnisporum resulted in the highest disease rate and lowest dry weight. This work highlights that the efficacy of Trichoderma as BCAs is influenced by various factors, including the quantity of soil inocula, and environmental conditions. The study findings have strong implications for selecting appropriate Trichoderma species for controlling specific pathogens under specific environmental conditions.

An explanation of the mystifying bakanae disease narrative for tomorrow's rice

Rice production is severely hampered by the bakanae disease (Fusarium fujikuroi), formerly recognized as Fusarium moniliforme. F. moniliforme was called the F. fujikuroi species complex (FFSC) because it was later discovered that it had some separate species. The FFSC's constituents are also well recognized for producing phytohormones, which include auxins, cytokinin, and gibberellins (GAs). The normal symptoms of bakanae disease in rice are exacerbated by GAs. The members of the FFSC are responsible for the production of fumonisin (FUM), fusarins, fusaric acid, moniliformin, and beauvericin. These are harmful to both human and animal health. This disease is common around the world and causes significant yield losses. Numerous secondary metabolites, including the plant hormone gibberellin, which causes classic bakanae symptoms, are produced by F. fujikuroi. The strategies for managing bakanae, including the utilization of host resistance, chemical compounds, biocontrol agents, natural goods, and physical approaches, have been reviewed in this study. Bakanae disease is still not entirely preventable, despite the adoption of many different tactics that have been used to manage it. The benefits and drawbacks of these diverse approaches are discussed by the authors. The mechanisms of action of the main fungicides as well as the strategies for resistance to them are outlined. The information compiled in this study will contribute to a better understanding of the bakanae disease and the development of a more effective management plan for it.