An automatic fluorescence phenotyping platform to evaluate dynamic infection process of -green fluorescent protein in tobacco leaves.

Abstract in brief

• The study describes the development of a low-cost, automated phenotyping platform that uses machine vision and digital imaging to evaluate the fluorescent response in tobacco leaves infected with TMV-GFP, simplifying traditional labor-intensive detection methods.
• A 7-day dynamic experiment with tobacco samples, including wildtype and mutant lines, was conducted to assess the platform's effectiveness; results showed that fluorescence traits like area and brightness increased over time, with distinct trends among different mutant lines.
• The platform successfully automates the extraction of fluorescence-related traits with high accuracy, making it a useful tool for monitoring the infection process and understanding TMV behavior in tobacco plants.]