Nematodes cause hundreds of millions of dollars in yield losses annually to USA agricultural products (Molinari, 2011 and Allen et al., 2017). Soil sampling is an efficient way to determine if Soybean Cyst Nematodes (SCN) are present in a field. From a practical standpoint, nematode detection and characterization based on the physical collection of soil samples is labor-intensive and time-consuming. The population of cyst nematodes in the infected area depends on soil and climate conditions and existing of the host plant. Therefore, accurate detection and quantifying spatially aggregated nematodes, especially in a large production field, is challenging. In addition, early detection is important to manage SCN and minimize yield loss. More importantly, soil sampling from different locations in a zigzag pattern and mixing them before sending them to the lab may provide unreal nematode counts (mixing the low counts with high counts samples results in averaging down the threshold).

The objectives of this project are to; a) Define and quantify the significant environmental and soil factors (the physical, chemical, and biological properties) that impact or regulate the spatial relationships, population dynamics, and survival of SCN in soybean fields in MN and SD; b) Establish three "Prototype Fields" to train producers; c) Demonstrate and evaluate the effects of the Site-specific SCN detection on crop yield and farm profits; d) Implement an intensive training program in Minnesota and South Dakota for crop consultants, technology providers, and agronomists to become the primary providers of the Site-specific SCN.

This is a three-year project, with the overarching goal of assisting Minnesota and South Dakota soybean producers in adopting advanced technologies, including site-specific detection strategies and Precision Cover Cropping System (PCCS) as robust mitigation, in improving the SCN management in infested fields. We will develop and test concepts and technologies for site-specific detection and control of plant-parasitic nematodes to increase yield and farm profit and reduce the chemical use.

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Abstract:
This study aims to leverage site-specific management (SSM) strategies to understand field variation and soil properties and make informed decisions on SCN management. Key objectives include mapping Soybean fields for soil electrical conductivity and analyzing the correlation between SCN egg counts and soil variations. Our findings reveal significant correlations between soil properties and nematode counts, supporting the delineation of management zones. This study will underscore the potential of targeted management strategies in controlling nematode infestations and enhancing soybean productivity.
Procedures:
Before planting on May 4th, EC data were collected from a highly susceptible Soybean field located at the South Dakota State University research farms in southeast South Dakota, using the EM-38 electromagnetic induction device. The EM-38 measures the strength of the induced magnetic field through the soil, indicating the electrical conductivity of the soil. The EM-38, mounted on a sled, took EC measurements of the soil every few seconds while being towed behind a vehicle through the fields. Subsequently, the data were downloaded and imported into an agricultural GIS program (SMS)to create management zones based on five ranges of shallow EC data, from highest to lowest.

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Nematode count vs Soil properties
A significant correlation between soil nematode distribution and various soil characteristics,
including pH, compaction, clay content, and organic matter, has been revealed by the
research findings, which align with consistent patterns observed in previous studies.
However, it is essential to acknowledge that due to many variations in the field and
ongoing projects with diverse objectives, the current assessment is not definitive and may
result in different outcomes in other locations. Based on observations, it has been noticed
that areas with high soil strength restrict nematode breeding, while nematodes thrive
more in less compacted soil. A similar trend is also observed for clay content. However,
the relationship with soil organic matter is not as straightforward. In areas where organic
matter is high, an increase in nematode counts has been observed, which contrasts with
findings from some previous studies. This pattern might be attributed to the potential
absence of other soil microorganisms that could feed on nematodes or compete with
them, possibly suppressing nematode populations below a threshold that limits their life
cycles. Further observations and data collection are expected to clarify this correlation.
Despite the presence of weak correlations between the results, which could be influenced
by the small number of observations and various errors, such as differences in treatments
and conditions, it is evident that pH and soil texture play significant roles in determining
the distribution of SCN eggs. Generally, areas with low pH and a high percentage
of silt tend to exhibit higher nematode counts compared to other areas.

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Update:

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Adopting advanced technologies, including site-specific detection strategies and Precision Cover Cropping System (PCCS) as robust mitigation, results in improving the SCN management in infested fields leading to a higher yield and chemical control.