Soybean cyst nematode (Heterodera glycines) resistant cultivar rotation system impacts nematode population density, virulence, and yield
Introduction
Soybean (Glycine max L. Merrill) is a widely used legume crop contributing to 70% of the total protein meal and 28% of total vegetable oil consumption worldwide (ASA, 2019). The United States produces the highest percentage of the world's soybeans annually (ASA, 2019), and the North Central region alone produces 82% of the total US soybean crop (Licht, 2019). The soybean cyst nematode (SCN; Heterodera glycines Ichinohe, 1952) is one of the most economically damaging pests of soybeans worldwide (Wrather et al., 2010; Kim et al., 2016). This pest was first reported in the US in 1954 in North Carolina (Winstead et al., 1955), and by 2017, it was reported in all US soybean-growing states (Tylka and Marett, 2021). The soybean cyst nematode was not discovered in Michigan until 1987 (Warner et al., 1994), but has since spread to every soybean-producing county in Michigan's lower peninsula, except for Presque Isle. Nationally, SCN causes more yield loss than any other soybean disease (Allen et al., 2017), directly leading to $469 to $818 million in soybean yield losses annually (Matthews and Youssef 2016). In Michigan alone, SCN causes $40 million in economic damage each year (Tylka and Marett, 2021).
Due to SCN's potential to cause substantial soybean yield loss world-wide, there is need for effective yet sustainable management practices. Thus far, effective tactics include field sanitation, crop rotation, composts or manures, nematicide seed treatments, and plant genetic resistance (Levene et al., 2020). While genetic resistance is the most effective control tactic against SCN, many SCN populations have adapted to the commercially available sources of resistance (Niblack et al., 2006). Genetic variation among SCN populations in the US was reported within a few years of SCN's first detection (Ross, 1962). From 1954 to 1970, 11 unique SCN populations were reported from Virginia, North Carolina, Missouri, Arkansas, Illinois, Tennessee, Mississippi, and Kentucky (Miller, 1970). These populations differentiated based on their ability to develop females on various soybean lines including PI548402, commonly known as Peking, Pine Dell Perfections, PI91684, PI88788, PI87631-1, PI79683, PI91684, and PI84611 (Miller, 1970). A 16-race identification system was developed based on phenotypic response on five soybean lines (PI548402, ‘Pickett’, PI88788, PI90763, and ‘Lee’) (Golden, 1970; Riggs and Schmitt, 1988), and later an HG type test (“HG” for Heterodera glycines) based on the seven indicator lines that have been used in commercially available cultivars (1: PI548402, 2: PI88788, 3: PI90763, 4: PI437654, 5: PI209332, 6: PI89772, and 7: PI48316 ‘Cloud’) was developed (Niblack et al., 2002). Knowing the HG type can allow a grower to select a soybean variety with greater yield potential even in fields with high SCN levels. Still, to maintain the effectiveness of these genetic traits, multiple management strategies, such as rotation of different sources of resistance, should be implemented.
Soybean's resistance to SCN is multigenic: it involves both dominant and recessive genes (Concibido et al., 2004). In the US, even though over 100 sources of soybean resistance to SCN have been identified, only a few of these sources are used for commercial level SCN resistant soybean variety development (Shannon et al., 2004). The most used sources of resistance are derived from the genotypes PI548402 and PI88788 (Meinhardt et al., 2021). PI88788 has resistance genes rhg1-b and PI548402 has rhg1-a and Rhg4 (Cook et al., 2012; Liu et al., 2012; 2017). The resistance in PI548402 involves a rapid and potent response at the site of infection developing a necrotic layer that surrounds the head of the nematode (Kim et al., 1987; Endo, 1991). However, in the PI88788 resistance lines, the initial cell that the nematode parasitizes undergoes necrosis once infected (Kim et al., 1987; Endo, 1991). The effectiveness of using resistant cultivars for SCN management depends on the genetic interaction between cultivars, the number of copies of resistance genes at the rhg1 and Rhg4 loci, and the type of SCN populations (Kandoth et al., 2017; Markell et al., 2020).
The sources of SCN-resistance for soybean cultivars commonly grown in Michigan are PI548402 and PI88788, PI88788 being the most common (F. Warner, 2021; personal communication). According to the SCN Coalition Program, the majority of the soybean cultivars planted in the Midwest are derived from PI88788 resistance source. Currently, soybean fields in Michigan typically have HG type 1.2 (Warner and Tany, 2020), which indicates SCN reproduction on both PI548402 and PI88788, but the virulence of SCN is shifting in Michigan, as reported in many other states in the North Central US (Niblack et al., 2008; Howland et al., 2018; Chen, 2020). Rotating sources of resistance might slow the aggressiveness of SCN populations, but this needs to be investigated with soybean varieties available in Michigan. In this research, our main objective was to evaluate the rotation of commercially available soybean cultivars from two sources of resistance for sustainable management of SCN in Michigan. We had three sub-objectives for this project: 1) to evaluate the impact of rotation of commercially available SCN resistant cultivars derived from PI548402 and PI88788 compared to continuous uses of cultivars derived from a single source of resistance and a susceptible soybean cultivar on SCN population density, virulence, and soybean yield under field conditions; 2) to determine if the rotations shifted the HG type of existing SCN field populations, and 3) to analyze the reproduction of SCN from continuous PI88788 in different rotations of PI548402, PI88788, PI437654, and susceptible soybeans varieties in the greenhouse.
Section snippets
Field trial: rotation of SCN resistant varieties
A field trial was conducted in a commercially managed field with a history of SCN located near Saint Charles, MI (latitude: 43.2590489; longitude: −84.0901567) from 2017 to 2020. Prior to the field trial establishment, the SCN resistance source PI548402 was planted in the field and the HG type of the native SCN population was 1.2. A randomized complete block design experiment with four replications was established with the following cultivar rotation systems using cultivars derived from
Effect of the rotation of SCN-resistant soybean varieties on SCN density
Throughout the duration of this experiment, soybean cyst nematode population densities and soybean yields were analyzed annually. In 2018, after two seasons of rotation, SCN cyst abundance significantly differed among the six rotations. Switching Peking and PI88788 sources of resistance in the first year of the trial (8DV/5DV/8DV/5DV) resulted in significantly lower SCN cyst densities with an average of 17.3 cysts/100 cm3 soil (p = 0.019), compared to plots rotated from Peking to Susceptible
Discussion
Even though different SCN management strategies are available to manage SCN infestations, the most effective methods to protect soybean yields in infested fields are nonhost crop rotation and the use of SCN-resistant soybean cultivars (Niblack, 2006). The most widely used SCN resistant soybean varieties contain genes derived from PI88788 (McCarville et al., 2017; Howland et al., 2018). Continuous planting of the same type of resistance is not recommended (Niblack et al., 2008; McCarville et
Conclusions
We found five main takeaways from this research trial: 1) Rotating soybean cultivars derived from Peking and PI88788 sources of resistance can lower SCN population densities; 2) Continuous use of PI548402 or PI88788-derived varieties or including SCN susceptible soybeans in the rotation increased SCN densities; 3) While there were no substantial soybean yield differences in 2017 among the rotations, rotation with Peking- and PI88788-derived varieties resulted in higher yields in 2018–2020,
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors would like to acknowledge Kristin Poley and Jeff Shoemaker for starting the field trial in 2017. They would also like to thank Lauren Rodriguez, Cameron Kennard, Evan DeYoung, Avi Grode, and Mikhel Waling for technical assistance. Sincere thanks to Dr. George Bird for his critical review of our manuscript. Lastly, thanks to Michigan Soybean Promotion Committee (MSPC) and North Central (NC) IPM for funding and to MSPC who provided funds for all four years.
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