THE SOYBEAN CYST NEMATODE (SCN) IS THE MOST DAMAGING SOYBEAN PEST IN THE UNITED STATES AND CANADA. SUSTAINABLE SOYBEAN PRODUCTION IS THREATENED BY THE NARROW GENETIC BASE OF RESISTANCE GENES USED IN ALMOST ALL SCN-RESISTANT SOYBEAN VARIETIES. SCN POPULATIONS ARE BUILDING UP REPRODUCTION ON THE COMMONLY USED RESISTANCE GENES, AND NEW VARIETIES WITH UNIQUE RESISTANCE GENES ARE DESPERATELY NEEDED. IDENTIFYING RESISTANT PLANTS DEVELOPED IN SOYBEAN BREEDING PROGRAMS REQUIRES LARGE-SCALE SCREENING OF PLANTS IN GREENHOUSE EXPERIMENTS. THE ONLY WAY TO DETERMINE IF SOYBEAN LINES ARE RESISTANT TO SCN IS TO MANUALLY DISLODGE ADULT CYST NEMATODE FEMALES AND CYSTS FROM ROOTS WITH WATER AND TO COUNT THEM. THIS PROCESS IS TEDIOUS, UNPLEASANT, TIME CONSUMING, AND LABOR INTENSIVE, THUS EXPENSIVE.TO ALLEVIATE THE ABOVEMENTIONEDCRITICAL BOTTLENECK, WE WILL DEVELOP AN AUTOMATED INSTRUMENT TO LOAD NUMEROUS ROOT SAMPLES, TRANSPORT THEM ON A TRAIN SYSTEM, SPRAY INDIVIDUAL ROOTS, AND COLLECT EXTRACTED ADULTSCN FEMALES AND CYSTS IN CATCH SIEVES. IMAGING MODULES DEVELOPED WITH DEEP LEARNING WILL BE INCORPORATED FOR SMARTER IDENTIFICATION OF NEMATODE FEMALES AND CYSTS. THE PROPOSED OBJECTIVES ARE TO: (I) DESIGN AND BUILD THE HARDWARE COMPONENTS, (II) DEVELOP THE ROOT AND ADULT FEMALE/CYST IMAGING MODULES, AND (III) INTEGRATE THE ENTIRE SYSTEM AND CONDUCT GREENHOUSE EXPERIMENTS. AUTOMATION OF ROOT SPRAYING TO DISLODGE ADULT SCN FEMALES AND CYSTS, ALONG WITH HIGH-THROUGHPUT IMAGING OF ROOTS AND EXTRACTED MATERIAL, HAS NEVER BEEN ATTEMPTED BEFORE. THIS INSTRUMENT AND SOFTWARE WILL EXPEDITE THE SEARCH FOR NEW MANAGEMENT STRATEGIES TO CONTROL THE YIELD LOSS CAUSED BY SCN.