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Lactic acid bacteria inoculants are employed to accelerate forage ensiling ensuring silage quality. Inoculants for ensiling are not produced locally and are restricted for importation in Sri Lanka. This study evaluated the potential of locally produced, freeze-dried Lactobacillus inoculants containing Lactobacillus plantarum, Lactobacillus rhamnosus, and Lactobacillus oris, on ensiling of guinea grass (Megathyrsus maximus) forage. The experiment was conducted as a complete randomized design (CRD). Guinea grass forage harvested at the 10 % flowering stage were chopped and inoculated with each Lactobacillus (i.e. treatments) species (i.e. 106 CFU/g fresh forage) or sprayed with deionized water (i.e. control). Six laboratory silos were prepared with each inoculant and one silo was the control. Silage samples were taken from 3 silos opened at 2 weeks and from the remaining 3 silos at 52 weeks post-ensiling. All samples were assessed for pH value and lactic acid content. In addition, the samples taken at 52 weeks were analyzed for organic matter digestibility (OMD) and metabolizable energy (ME) content. Guinea grass ensiled with Lactobacillus exhibited significantly (P<0.05) high lactic acid content and low pH value compared to the control as early as 2 weeks ensiling. At 52 weeks, guinea grass inoculated with L. rhamnosus recorded, significantly (P<0.05) higher lactic acid content compared to that inoculated with L. plantarum. Nevertheless, at 52 weeks guinea grass ensiled with, both L. rhamnosus and L. oris recorded significantly lower (P<0.05) pH values than those inoculated with L. plantarum. Inoculation of guinea grass with Lactobacillus significantly (P<0.05) increased the OMD and ME content of silage. This study concluded that locally produced, freeze-dried L. rhamnosus, and L. oris inoculants have the potential to enhance the ensiling guinea grass. [ABSTRACT FROM AUTHOR]

A data management system is crucial to businesses as it efficiently organizes, secures, and leverages data, enabling informed decision-making, streamlined operations, and improved competitiveness. Machine learning enhances data management by automating insights extraction, predictive analytics, and pattern recognition, optimizing data utilization and driving informed business strategies. DOCU SAFE is a web base secure data management system that uses machine learning and NLP to enable organizations to store, manage, and analyze their data securely. The system addresses the challenges associated with data uploading, moving, and processing, including size/storage/volume of data, inconsistency and variety of data, formatting of data, security of data, analyzing and mapping of data, and cost management issues. DOCU SAFE provides a scalable solution for data management, enabling organizations to handle large volumes of data efficiently. The system uses machine learning algorithms to ensure that data is consistent, accurate, and secure, providing organizations with insights that can be used to make informed decisions. The data we enter here can be directed to four categories of classification, hidden and highlight, encryption, and hygiene solutions according to our needs. They currently have many tools in this regard, but there are problems with them. In addition, there are separate tools for data classification, data hidden and highlight, data encryption, data hygiene solutions, and there is no possibility to do everything with one tool/system. Here, all the above issues are the provided by same tool. Overall, DOCU SAFE is an effective solution for organizations that handle sensitive data and need a secure and efficient data management system. [ABSTRACT FROM AUTHOR]

Substantial yield losses have been reported during the storage of Allium cepa L., and effective methods to minimize postharvest losses are currently lacking. Therefore the objectives of this study were to investigate the impact of pre-treatment with Trichoderma asperellum and Trichoderma virens on post-harvest losses during storage and to evaluate factors associated with these losses. The storage behaviors of Allium cepa L. bulbs after different field treatments with Trichoderma spp. were examined using a complete randomized design. The common onion bulb diseases encountered during storage were basal rot and black mould diseases, with Fusarium sp., Mucor sp., Penicillium sp., Aspergillus niger and Aspergillus flavus being associated with diseased bulbs. The results regarding the percentage of diseased bulbs showed that pre-harvest treatments with Trichoderma asperellum and Trichoderma virens did not have a significant effect on disease control during storage. Furthermore, storage losses of onions were attributed to sprouting, rooting and wilting, which were exacerbated by the prevailing temperature (~30-32°C) and relative humidity (~77%-79%) during the storage period. [ABSTRACT FROM AUTHOR]