IDBR: TYPE A: Instrument to extract and quantify soil-borne, parasitic nematode pests of agricultural crops

点击翻译按钮获取中文摘要

An award is made to Iowa State University (ISU) to develop an automated instrument that can extract and quantify nematodes (roundworms) from soil samples. Identifying crop nematode infestation with a quick and reliable soil analysis technique is possibly the Holy Grail in plant nematology. In this context, an automated instrument to determine cyst nematode egg numbers will be truly appealing for farmers, plant scientists, and agribusinesses. Knowing the nature and level of cyst nematode infestation in a field will help the farmer monitor the effectiveness of and plan for better pest management strategies, thereby improving soybean productivity. The instrument technology will be disseminated through extension talks to Iowa farmers and agribusiness personnel, online newsletters, videos on educational websites, and demonstrations at scientific and farmer conferences. Outreach will be conducted to stakeholders in the seed industry and universities to convince them to test the new instrument and provide feedback. In addition, programs will be developed to train minority and female life science students in programming and engaging third grade Iowa students through a unique NSF STEM-C project called Trinect.Plant-parasitic nematodes, such as the Soybean Cyst Nematode (SCN), are microscopic worms that damage plants and reduce crop yields worldwide. The only definite way to accurately identify SCN infestations and predict future crop damage in fields is by extracting and counting the number of SCN worms, cysts, and eggs in the soil. Current nematode extraction procedures and instruments are very old and labor intensive, and it is challenging to automate methods of soil processing and analysis. This project is to build a modern, automated instrument to perform all the mechanical functions involved in current nematode extraction procedures. Also, a smartphone-based microscope with custom software will be realized for the counting of SCN worms, cysts, and eggs. This automation will improve data consistency and reliability, reduce labor costs, and increase SCN testing of fields. The new instrument is designed to be flexible in operation for extracting different types of plant-parasitic nematodes, soil-borne fungal spores, and weed seeds.