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.
Pandey, S. (2023). Robotic Soil Instrument. Afribary. Retrieved from https://track.afribary.com/works/robotic-soil-instrument
Pandey, Santosh "Robotic Soil Instrument" Afribary. Afribary, 18 Feb. 2023, https://track.afribary.com/works/robotic-soil-instrument. Accessed 23 Nov. 2024.
Pandey, Santosh . "Robotic Soil Instrument". Afribary, Afribary, 18 Feb. 2023. Web. 23 Nov. 2024. < https://track.afribary.com/works/robotic-soil-instrument >.
Pandey, Santosh . "Robotic Soil Instrument" Afribary (2023). Accessed November 23, 2024. https://track.afribary.com/works/robotic-soil-instrument