Plant epidemics have long threatened crop yields and the global economy, with novel pathogenic variants and disease synergism worsening the issue. These destructive plant diseases cause global crop yield losses of up to 40% for maize, potato, rice, soybean, and wheat, resulting in annual financial losses of $220 billion. The UN's 2024 Global Report on Food Crises indicates that nearly 282 million people across 59 countries are experiencing acute food insecurity, a number that has increased since 2019. Crop loss due to plant pathogens and extreme climate are key drivers of this food crisis, exacerbating environmental and socio-economic conditions in affected regions and disproportionately impacting food-insecure populations. Therefore, being able to easily conduct plant disease diagnosis in the field is of great importance for smallholder farmers to prevent disease outbreaks and accurately adopt control strategies. This research focuses on developing quick sample preparation protocols, aiming for efficiently extracting total nucleic acids that are ready for downstream molecular assays, such as polymerase chain reaction (PCR), directly from plant tissues. As a follow-up, an emerging molecular technique, loop-mediated isothermal amplification (LAMP), was integrated with quick sample preparation protocol to develop a colorimetric sensing strategy for plant disease detection in a greenhouse. Subsequent efforts to design and prototype a “pushing-valve” microfluidic chip, as an easy-to-use platform toward in-field disease detection, were also presented in this research. In general, this whole research aims to allow farmers and growers to prepare ready-to-use nucleic acids straight from plants of interest and carry out subsequent detection in a portable manner. Such a platform would benefit disease prevention and management on smallholder farms by removing the need for processing and analyzing large quantities of field samples by laboratory workers. This holds a great potential to improve in-field plant diagnostics in resource-limited settings.
