A Mechanistic Approach To Assessing the Potential for Cover Crops To Serve as Trap Crops for the Soybean Cyst Nematode.

The effects of cover crops on the biology of the soybean cyst nematode (SCN; Heterodera glycines) are not well established. It is possible that cover crops may reduce SCN population densities by acting as trap crops. Cover crops with potential to serve as trap crops may stimulate hatching and/or attract hatched SCN juveniles and also may be penetrated by large numbers of nematodes that cannot feed. Experiments were conducted to determine whether root exudates (REs) and soil leachates (SLs) from various cover crop plants affected SCN hatching and chemotaxis and if there were significant differences in SCN juvenile root penetration among different cover crop plant types. In 14-day-long hatching experiments, there was greater SCN hatching in crimson clover (Trifolium incarnatum) REs and SLs than in REs and SLs from all other cover crop treatments in the experiments. No other cover crop REs and SLs significantly affected hatching. In chemotaxis experiments, SCN juveniles were attracted to REs and SLs from annual ryegrass (Lolium multiflorum) and cereal rye (Secale cereale) after 24 h. In greenhouse experiments, significantly more SCN juveniles penetrated the roots of single cultivars of crimson clover, mustard (Brassica juncea), and rapeseed (B. napus) than 11 other cover crop species/cultivars evaluated in the experiment over the course of 20 days. Few SCN juveniles penetrated the roots of annual ryegrass and cereal rye. The results suggest that crimson clover, grown as a cover crop, has the most potential to act as a trap crop for SCN. Cover crop plants may affect SCN biology in ways other than the mechanisms investigated in these experiments.

New methods of removing debris and high-throughput counting of cyst nematode eggs extracted from field soil.

The soybean cyst nematode (SCN), Heterodera glycines, is the most damaging pathogen of soybeans in the United States. To assess the severity of nematode infestations in the field, SCN egg population densities are determined. Cysts (dead females) of the nematode must be extracted from soil samples and then ground to extract the eggs within. Sucrose centrifugation commonly is used to separate debris from suspensions of extracted nematode eggs. We present a method using OptiPrep as a density gradient medium with improved separation and recovery of extracted eggs compared to the sucrose centrifugation technique. Also, computerized methods were developed to automate the identification and counting of nematode eggs from the processed samples. In one approach, a high-resolution scanner was used to take static images of extracted eggs and debris on filter papers, and a deep learning network was trained to identify and count the eggs among the debris. In the second approach, a lensless imaging setup was developed using off-the-shelf components, and the processed egg samples were passed through a microfluidic flow chip made from double-sided adhesive tape. Holographic videos were recorded of the passing eggs and debris, and the videos were reconstructed and processed by custom software program to obtain egg counts. The performance of the software programs for egg counting was characterized with SCN-infested soil collected from two farms, and the results using these methods were compared with those obtained through manual counting.