Explore recent research papers collected from PubMed.
This review examines the metabolic responses and biochemical pathways involved in drought stress tolerance across major tuber crops, including potato. It highlights how altered metabolites contribute to plant resilience, providing insights for breeding and genetic improvement strategies.
This paper introduces PotatoGuardNet, a deep learning framework based on Inception-ResNet-V2 and Faster-RCNN designed for the automated detection and classification of potato leaf diseases. The model achieves high accuracy in identifying disease patterns from the PlantVillage dataset, offering a potential tool for improving potato pathology monitoring and crop protection.
This study investigates how silica nanoparticles modulate potato plant defenses against the peach potato aphid across different developmental stages. It evaluates the impact of these treatments on tritrophic interactions, providing insights into stage-specific plant-pest-predator dynamics in potato cultivation.
This paper describes the development of a lightweight and scalable deep learning framework for the real-time detection of potato leaf diseases. The research focuses on providing an efficient computational tool for identifying pathological conditions in potato crops to facilitate timely agricultural interventions.
This study investigates factors influencing wireworm damage in potato tubers, focusing on cultivar susceptibility, soil moisture, and harvest timing. The findings suggest that selecting resistant cultivars and managing environmental factors can mitigate crop losses, providing insights for potato breeding and pest management strategies.
This study investigates the impact of incorporating mashed potato into yogurt at different concentrations to evaluate its techno-functional properties. Results indicate that adding mashed potato reduces syneresis and modifies texture and viscosity, with a 25% concentration providing optimal stability and texture for fermented dairy applications.