MODELING OF SUPERIMPOSED SPATIAL PATTERNS OF BACTERIAL BROWN SPOT OF SNAP BEAN

Snap bean plants within seven-row segments that ranged from 30 to 108 m were sampled using a 2,4-systematic sampling plan: Two adjacent plan ts were sampled and evaluated for bacterial brown spot, four adjacent plants were skipped, two adjacent plants were sampled, etc. This sampl ing plan was developed using a priori knowledge of disease patterns in 5-m row segments. Every leaflet on every sampled plant was assessed f or bacterial brown spot, and disease on these plants was quantified as the proportion of diseased leaflets per plant. Arcsine square root-tr ansformed disease-incidence values were analyzed for spatial patterns using autoregressive integrated moving average (ARIMA) modeling. Three of seven data sets were described by a generalized ARIMA(1 0 1) model . These data sets exhibited the expected patterns of disease, based on previous descriptions of disease patterns in 5-m row segments. Of the remaining four data sets, one was modeled by an ARIMA(1 0 2) model, t wo by an ARIMA(1 0 3) model, and one by an ARIMA(1 0 4) model. These d ata sets exhibited the expected patterns, as well as additional patter ns that recurred at intervals of six to 11, 12 to 17, or 18 to 23 plan ts, respectively. Significant autocorrelations at distances of six to 23 plants were also found in residuals from 24 of 55 5-m row segments evaluated for bacterial brown spot and modeled using ARIMA models. The se patterns appear to occur frequently in commercial snap bean fields.