World population is expected to reach 9.7 billion by 2050. Climate change is making the traditional agricultural practice increasingly difficult. To address the looming food crisis, we need to develop revolutionary agriculture techniques along with new crop plants that can double or triple the crop yields with less arable lands. Developing novel methods to improve plant health and production is currently highly demanded.

Plants are immobile and cannot escape from a harsh environment or any predators. Though plants cannot walk away, during the evolutionary process, most plants develop sophisticated mechanisms to move their roots, leaves, flowers, and stems in order to capture nutrient and sunlight, defend enemies, and acclimatize to harsh environment. Plants can also have micro-movement as a response to microbial pathogen and abiotic stress (salt, drought, light, pH, temperature etc.). The subtle micro-movement is difficult to be observed by naked eyes, but it can be recorded by video camera. The micro-movement patterns of plants grown under “healthy condition” could be different from those grown under “stressed conditions”. We propose to develop an image analysis system integrates with machine learning to interpret plant movement patterns under different growth conditions. The processed image data will be converted to audible sounds. We hypothesize that plants grown under stressed conditions will make “crying” motions, while the healthy plants will make “happy” motions, can be rendered audible through sonification. We will use such observations to inform and improve the algorithm that will drive the mimic sound, to treat plants, and thereby improve plant performance. This will result in a feedback loop between the plant motion and the ensuing sonic treatment.

In this project, four Virginia Tech faculty members and their research groups will combine their interdisciplinary expertise to develop an innovative approach to observe or listen to plants in response to various stress stimuli, and design new agricultural practice to improve plant performance.