  Soybeans are an important crop for global food security. Every year, soybean
yields are reduced by numerous soybean diseases, particularly the soybean cyst
nematode (SCN). It is difficult to visually identify the presence of SCN in the
field, let alone its population densities or numbers, as there are no obvious
aboveground disease symptoms. The only definitive way to assess SCN population
densities is to directly extract the SCN cysts from soil and then extract the
eggs from cysts and count them. Extraction is typically conducted in commercial
soil analysis laboratories and university plant diagnostic clinics and involves
repeated steps of sieving, washing, collecting, grinding, and cleaning. Here we
present a robotic instrument to reproduce and automate the functions of the
conventional methods to extract nematode cysts from soil and subsequently
extract eggs from the recovered nematode cysts. We incorporated mechanisms to
actuate the stage system, manipulate positions of individual sieves using the
gripper, recover cysts and cyst-sized objects from soil suspended in water, and
grind the cysts to release their eggs. All system functions are controlled and
operated by a touchscreen interface software. The performance of the robotic
instrument is evaluated using soil samples infested with SCN from two farms at
different locations and results were comparable to the conventional technique.
Our new technology brings the benefits of automation to SCN soil diagnostics, a
step towards long-term integrated pest management of this serious soybean pest.
