Abstract
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.
Highlights
Soybeans are an important crop for global food security
Amongst all pathogen-caused soybean diseases, the soybean cyst nematode (SCN), Heterodera glycines, has been ranked as the most damaging in the United States for the past two decades and yield losses caused by SCN have become a worldwide issue[8,9,10]
The risks of not knowing the presence and population density of SCN in a timely manner can be detrimental to future crop yields[7,9]
Summary
Soybeans are an important crop for global food security. Every year, soybean yields are reduced by numerous soybean diseases, the soybean cyst nematode (SCN). Amongst all pathogen-caused soybean diseases, the soybean cyst nematode (SCN), Heterodera glycines, has been ranked as the most damaging in the United States for the past two decades and yield losses caused by SCN have become a worldwide issue[8,9,10]. Often causes no obvious aboveground symptoms during the growing season[7,9,15] This makes it nearly impossible to predict SCN population densities by visual inspection of crops or soil. The only definitive way to accurately assess SCN population densities in a field is to directly extract nematode cysts from soil and extract and count the eggs from the c ysts[12,14,15,16,17,18]. A nematode-counting slide or microfluidic flow chip is used to view and count the nematode cysts or eggs[24]
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