TY - JOUR

T1 - A Negative Binomial Regression Model of the Observed Population Density of Heterodera glycines after Annual Corn Rotation in Nebraska

AU - Pérez-Hernández, Oscar

AU - Giesler, Loren J.

AU - Hilbe, Joseph M.

N1 - Funding Information:
Funding: Funding for this work was provided by the Nebraska Soybean Board Grant No. 55506.

PY - 2019

Y1 - 2019

N2 - In Nebraska, rotation of soybean (Glycine max) fields to corn (Zea mays) is a major practice to manage the soybean cyst nematode (SCN; Heterodera glycines). However, factors associated with SCN population density decline during corn rotation are not clearly defined. This study addresses that question using a modeling approach. Seventy-nine fields were sampled in 2009, 2010, and 2011 to determine SCN population densities (eggs/100 cm3 of soil) before and after rotation. After rigorous field screening and model testing and validation, the regression model Log dðPf Þ = − 2:3360 + 0:8368LogPi + 0:4333pH was developed, where Log Pf is the natural log of SCN eggs at the end of the rotation year, Pi is the population density before rotation, and pH is the soil pH. Model goodness-of-fit was assessed through residual analysis, information criteria, and other remedial measures. Model overdispersion was 1.04. Validation in a 50 and a 75% random sample from the original data set showed little change in model regression coefficients, standard errors, and associated significance, confirming model fit and performance. The model indicates that for one-unit increase in soil pH, SCN Pf is expected to increase by 53.7% at constant Pi, and correspondingly, a 10% change in Pi will result in about 8.3% change in Pf at constant soil pH. The model suggested that SCN population levels before corn rotation and soil pH are major determinants of observed SCN population density reduction after annual corn rotation in Nebraska. This model has potential for use in SCN risk analysis and in predicting SCN population decline after corn rotation in the state.

AB - In Nebraska, rotation of soybean (Glycine max) fields to corn (Zea mays) is a major practice to manage the soybean cyst nematode (SCN; Heterodera glycines). However, factors associated with SCN population density decline during corn rotation are not clearly defined. This study addresses that question using a modeling approach. Seventy-nine fields were sampled in 2009, 2010, and 2011 to determine SCN population densities (eggs/100 cm3 of soil) before and after rotation. After rigorous field screening and model testing and validation, the regression model Log dðPf Þ = − 2:3360 + 0:8368LogPi + 0:4333pH was developed, where Log Pf is the natural log of SCN eggs at the end of the rotation year, Pi is the population density before rotation, and pH is the soil pH. Model goodness-of-fit was assessed through residual analysis, information criteria, and other remedial measures. Model overdispersion was 1.04. Validation in a 50 and a 75% random sample from the original data set showed little change in model regression coefficients, standard errors, and associated significance, confirming model fit and performance. The model indicates that for one-unit increase in soil pH, SCN Pf is expected to increase by 53.7% at constant Pi, and correspondingly, a 10% change in Pi will result in about 8.3% change in Pf at constant soil pH. The model suggested that SCN population levels before corn rotation and soil pH are major determinants of observed SCN population density reduction after annual corn rotation in Nebraska. This model has potential for use in SCN risk analysis and in predicting SCN population decline after corn rotation in the state.

KW - Corn rotation

KW - Cyst nematode epidemiology

KW - Disease development

KW - Disease management

KW - Epidemiology

KW - Negative binomial

KW - Nematode management

KW - Oilseeds and legumes

KW - Spread

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U2 - 10.1094/PDIS-03-19-0681-RE

DO - 10.1094/PDIS-03-19-0681-RE

M3 - Article

C2 - 31613191

AN - SCOPUS:85075813419

SN - 0191-2917

VL - 103

SP - 3093

EP - 3100

JO - Plant disease

JF - Plant disease

IS - 12

ER -