Introduction: Precise semantic segmentation of microbial alterations is paramount for their evaluation and treatment. This study focuses on harnessing the SegFormer segmentation model for precise semantic segmentation of strawberry diseases, aiming to improve disease detection accuracy under natural acquisition conditions.Methods: Three distinct Mix Transformer encoders - MiT-B0, MiT-B3, and MiT-B5 - were thoroughly analyzed to enhance disease detection, targeting diseases such as Angular leaf spot, Anthracnose rot, Blossom blight, Gray mold, Leaf spot, Powdery mildew on fruit, and Powdery mildew on leaves. The dataset consisted of 2,450 raw images, expanded to 4,574 augmented images. The Segment Anything Model integrated into the Roboflow annotation tool facilitated efficient annotation and dataset preparation.Results: The results reveal that MiT-B0 demonstrates balanced but slightly overfitting behavior, MiT-B3 adapts rapidly with consistent training and validation performance, and MiT-B5 offers efficient learning with occasional fluctuations, providing robust performance. MiT-B3 and MiT-B5 consistently outperformed MiT-B0 across disease types, with MiT-B5 achieving the most precise segmentation in general.Discussion: The findings provide key insights for researchers to select the most suitable encoder for disease detection applications, propelling the field forward for further investigation. The success in strawberry disease analysis suggests potential for extending this approach to other crops and diseases, paving the way for future research and interdisciplinary collaboration.

There has been a growing interest in functional foods in recent years to improve health and boost immunity, particularly since the COVID-19 pandemic, which reflects their significant role in promoting health and preventing various diseases, especially metabolic disorders. This study investigated the antimicrobial, antioxidant, anticoagulant, and prebiotic activities of six different oils: Calotropis procera oil (CPO), Chia seed oil (CSO), Moringa oil (MO), Neem oil (NO), Black seed oil (BSO), and Wheat germ oil (WGO) and their potential applications in health and nutrition. The DPPH and ABTS assays were used to evaluate the antioxidant activity of these oils. A good diffusion assay and minimum inhibitory concentrations (MIC) method were used to investigate the antimicrobial activity against pathogenic bacteria and fungi of human interest. Also, the prebiotic activities of oils were tested on three probiotic strains of Lactobacillus to evaluate their role in promoting the growth of beneficial bacteria against the pathogenic E. coli. Furthermore, the haematological effect of these oils was investigated in vitro through measuring their anticoagulant, and Fibrinolytic activity. The results demonstrated that DPPH assay revealed that CPO and WGO exhibited the highest antioxidant activity with IC50 values of 15.2 µg/mL and 18.7 µg/mL, respectively, while BSO showed the least activity with an IC50 of 45.3 µg/mL. Antimicrobial activity, assessed using inhibition zone diameters, showed that CPO had the strongest effect against Staphylococcus aureus with a zone of 22 mm, followed by CSO at 19 mm. In terms of anticoagulant activity, CSO demonstrated the most potent fibrinolytic effect with a clot lysis percentage of 78%, while MO exhibited weaker activity at 35%. Prebiotic testing revealed that individual oils had limited effects on Lactobacillus growth, but a synergistic blend enhanced growth by 25% compared to controls. Overall, this study highlights the diverse health benefits of these oils and their potential as functional food ingredients that could contribute to improved health.