Goose parvovirus (GPV) leads to a huge loss in the poultry industry, and early diagnosis is required to prevent the disease from spreading. At present, there are a variety of detection methods for GPV infection, and the ELISA method has the advantages of simple and rapid operation. However, most ELISA methods for detecting GPV can only detect the antibody level of the sample, but cannot distinguish between the GPV infection and vaccine immunization antibodies. Therefore, this study has a wider application value by establishing the detection method based on the structure and non-structural protein of the virus. The GPV non-structural (NS1) and structure (VP3) fusion proteins were used as coating antigens to establish 2 indirect ELISA methods, and the detection conditions were optimized. A series of experiments proved that the detection method has good specificity, sensitivity, and repeatability. The test results of 120 immune sera samples and 145 natural infection serum samples showed that the positive rates of immunized serum were 9.17% (NS1) and 88.33% (VP3), and the positive rates of natural infection were 88.97% (NS1) and 86.21% (VP3), which distinguish between the GPV infection and vaccine immunization antibodies. The establishment of 2 indirect ELISA methods using NS1 and VP3 proteins as inclusion antigens provides a new method for detecting GPV infection and inactivated immune antibodies, which lays a foundation for the serological diagnosis and epidemiological monitoring of GPV.
