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Abstract
Field spatial heterogeneity often obscures treatment effects in soybean cyst nematode (SCN) management trials. We compared tensor-product penalized spline (TPS) models to a traditional split-plot ANOVA model to evaluate two genetic resistance sources (PI 88788 and Peking) and fluopyram seed treatment against HG Type 1.2.5.7 SCN populations in Ohio. By definition, HG Type 1.2.5.7 reproduces >10% of the level on a susceptible soybean line when tested on Peking and PI 88788 resistance sources. TPS models substantially improved model fit (62.2 AIC units for yield, 27.5 for reproduction factor) and precision (lower standard errors; for example 67 to 55 kg ha⁻¹) by explicitly accounting for spatial variation. Our spatially informed analysis revealed critical distinctions in management strategies: Peking-derived resistance significantly outperformed PI 88788, providing a 251 kg ha⁻¹ yield advantage and 37% reduction in SCN reproduction. In contrast, fluopyram seed treatment increased yield by 113 kg ha⁻¹ but did not suppress nematode reproduction, functioning as a yield protectant rather than an SCN population management tool. While treatment effect estimates were slightly lower than ANOVA for yield responses, the TPS model provided higher control efficacy estimates, reflecting the spatial adjustment. These results demonstrate that effective management of SCN HG Type 1.2.5.7 requires Peking-derived genetics as the foundation, with seed treatments serving supplementary roles in integrated strategies. Careful stewardship of Peking-derived resistance is essential to preserve this critical management tool for growers.
Keywords
Heterodera glycines, seed treatment, spatial analysis, integrated pest management, resistance source
DOI
10.5703/1288284318181
Spatial modeling improves field assessment of integrated SCN management
Field spatial heterogeneity often obscures treatment effects in soybean cyst nematode (SCN) management trials. We compared tensor-product penalized spline (TPS) models to a traditional split-plot ANOVA model to evaluate two genetic resistance sources (PI 88788 and Peking) and fluopyram seed treatment against HG Type 1.2.5.7 SCN populations in Ohio. By definition, HG Type 1.2.5.7 reproduces >10% of the level on a susceptible soybean line when tested on Peking and PI 88788 resistance sources. TPS models substantially improved model fit (62.2 AIC units for yield, 27.5 for reproduction factor) and precision (lower standard errors; for example 67 to 55 kg ha⁻¹) by explicitly accounting for spatial variation. Our spatially informed analysis revealed critical distinctions in management strategies: Peking-derived resistance significantly outperformed PI 88788, providing a 251 kg ha⁻¹ yield advantage and 37% reduction in SCN reproduction. In contrast, fluopyram seed treatment increased yield by 113 kg ha⁻¹ but did not suppress nematode reproduction, functioning as a yield protectant rather than an SCN population management tool. While treatment effect estimates were slightly lower than ANOVA for yield responses, the TPS model provided higher control efficacy estimates, reflecting the spatial adjustment. These results demonstrate that effective management of SCN HG Type 1.2.5.7 requires Peking-derived genetics as the foundation, with seed treatments serving supplementary roles in integrated strategies. Careful stewardship of Peking-derived resistance is essential to preserve this critical management tool for growers.