PLANTS SEND INTERNAL SIGNALS WITHIN THEMSELVES WHEN THEY EXPERIENCE STRESSES OF DIFFERENT FORMS. MEASURING THESE SIGNALS AND INTERPRETING CAN CREATE NEW TECHNOLOGY TO DETECT STRESSES EARLY, IN TIME TO INTERVENE AND PREVENT CROP YIELD LOSS. PLANTS THEMSELVES ARE PERHAPS THE MOST SENSITIVE 'DETECTORS' OF THEIR IMMEDIATE ENVIRONMENT, AND TAPPING THIS INFORMATION CAN GIVE FARMERS AND OTHER STAKEHOLDERS ACCESS TO UNPRECEDENTED INFORMATION ABOUT GROWING CONDITIONS. HIGH TEMPERATURE, BACTERIA, MECHANICAL DAMAGE AND EXCESS LIGHT ALL PRODUCE THESE TYPES OF STRESS WAVES, AND RECENT TECHNOLOGY FROM MIT CAN INTERCEPT THESE WAVES AND DIGITIZE THEM FOR USE WITH HARDWARE AS SIMPLE AS A SMART PHONE CAMERA AND PROCESSOR. OUR PRELIMINARY DATA SHOWS THAT DIFFERENT STRESSES ENCODE FOR DIFFERENT WAVEFORMS OR SIGNALS SENT BY THE PLANT THROUGHOUT ITS TISSUES. THIS 'LANGUAGE', IF WE CAN INTERPRET AND LEARN TO ANALYZE IT, COULD PROVIDE THE FIRST EARLY PREDICTORS OF EVERYTHING FROM PLANT DISEASES TO UNANTICIPATED ENVIRONMENTAL IMPACTS THAT REDUCE CROP YIELD. THE PROJECT WILL DEVELOP AND USE THESE NEW TYPES OF SENSORS, RECORD AND CLASSIFY THE VARIOUS WAVEFORMS IN AN ACCESSIBLE DATABASE, AND EXTEND THIS ANALYSIS TO A POPULATION OF ECONOMICALLY IMPORTANT CROPS.