Member Login


Subscribe to Our Newsletter


  • {{ error }}

Using HG Type to Select SCN-Resistant Soybean Varieties

Heterodera glycines, the soybean cyst nematode (SCN), has been and continues to be a major yield-limiting pest of soybean. Results from the latest survey of disease and nematode pests in the Midsouth states show it to be a significant contributor to pest-related soybean yield losses in each of the last six years.

Choosing soybean varieties with genetic resistance to SCN has long been a major economical defense against this pest, and breeders/geneticists have continued to thwart the negative effects of SCN by releasing new soybean varieties with resistance to evolving types of this pest. The long-term effectiveness of genetic resistance to SCN is documented in a paper by Rincker et al. (Crop Sci., Jan. 2017) entitled “Impact of Soybean Cyst Nematode Resistance on Soybean Yield”.

Populations of SCN in soybean fields exhibit diversity in their ability to develop on resistant soybean varieties, and this variation has implications for management strategies that can be used to mitigate SCN damage. Since 1970, this diversity has been characterized by assigning a race designation to an SCN population in a given field. According to Dr. Terry Niblack et al. in an article entitled “A revised classification scheme for genetically diverse populations of H. glycines” (J. of Nematology, Dec. 2002), an HG Type test better describes how a field population of H. glycines will affect a soybean variety that is planted in a given field that is infested with SCN. The authors further state that the HG Type test can 1) serve as a mechanism for classifying differences among field populations or population changes over time, 2) can be used by nematologists and breeders to develop resistant soybean varieties and to describe populations used for screening, and 3) can be used to develop management recommendations for producers.

The HG Type test uses seven indicator lines that have been used as sources of resistance for developing SCN-resistant varieties, and a susceptible check (See below). A Female Index [FI = (mean number of SCN females on a soybean line being tested divided by mean number of females on the standard susceptible check) x 100] is used to assign HG Type to a field population of SCN. A cutoff number of 10 was chosen for FI because it is assumed that populations with FI’s less than 10 would not maintain themselves in the confines of a single growing season. Results from an HG Type test must show the FI value along with the HG Type designation to avoid the inference that all populations with the same HG Type are equivalent.

If any of the seven indicator lines shown in the below example produce an FI ≥ 10 from the nematode sample, then varieties with that source of resistance against SCN should not be used in the sampled field. Conversely, if the nematode population produces an FI < 10 on all the indicator lines, then any variety can be planted in the sampled field without regard for SCN resistance.

Drs. Greg Tylka and Terry Niblack provide an example (Tylka and Niblack, NCSRP) of how the HG Type Test is used to determine the SCN population in a field.

            Lee 74 (standard susceptible check)  250 females (10% = 25)

            Peking (indicator line 1)                      17 females (17/250 = 7 FI)

            PI 88788 (indicator line 2)                  73 females (73/250 = 29 FI))

            PI 90763 (indicator line 3)                  3 females (3/250 = 1 FI)

            PI 437654 (indicator line 4)                19 females (19/250 = 8 FI)

            PI 209332 (indicator line 5)                9 females (9/250 = 4 FI)

            PI 89772 (indicator line 5)                  16 females (16/250 = 6 FI)

            Cloud (indicator line 7)                       28 females (28/250 = 11 FI)

In the above example, the number of females on the roots of PI 88788 (FI = 29) and Cloud (FI = 11) exceed 10% of the number of females on Lee 74. Thus, the nematode population in this field is classified as HG Type 2.7 and the producer should consider growing an SCN-resistant variety that obtained its resistance from a source other than PI 88788 or Cloud. Note that the number of females on PI 88788 and Cloud are quite different. This confirms the importance of showing the FI value along with the HG Type designation to avoid the inference that all populations with the same HG Type are equivalent. Also, another SCN population could have twice the number of females on the same two indicator lines shown above (i.e., 146 and 56), but would still be classified as HG Type 2.7. However, the virulence of the population would be much greater on both indicator lines in the latter case.

The HG Type test for SCN populations has become increasingly important because almost all SCN-resistant soybean varieties have SCN resistance genes from PI 88788. According to Dr. Niblack (Plant Health Progress, Jan. 2008), a significant portion of SCN populations in Illinois have adapted to PI 88788 to some degree, which in effect reduces the effectiveness of SCN-resistant varieties with this source of resistance. It is likely that this adaptation of SCN to PI 88788-derived resistance has/is occurring in other US soybean producing areas that have relied on this source of resistance for the development of SCN-resistant varieties.

Thus, the HG Type test is made to order to determine if SCN-resistant varieties that have been grown for an extended period in the same field have resulted in the selection of the SCN population in that field against the resistance acquired from PI 88788. This is why merely changing varieties for a given field that is infested with SCN will be ineffective if these different varieties all have SCN resistance acquired from the same source. This could explain why soybean growers may be seeing declining performance from SCN-resistant varieties in SCN-infested fields.

Click here for an article that has more detail about HG Type testing for SCN-infested fields, along with associated resources.

Composed by Larry G. Heatherly, Mar. 2017,