Analysis of the spatiotemporal structure of rice sheath blight epidemics in a farmer's field

Abstract

The spatiotemporal structures of two rice sheath blight epidemics were studied during two consecutive (rainy and dry) rice cropping seasons in a farmer's field in the Philippines. The amount of primary inoculum in the soil measured at transplanting was higher during the dry than during the rainy season, and showed nonaggregated spatial patterns in both seasons. Disease incidence (percentage tillers infected per hill) was monitored at weekly intervals on a (14 £ 17) grid of rice hills 1 m apart, at the centre of adjacent, nonoverlapping elementary quadrats of 5 £ 5 hills. The rate of disease increase at the onset of the epidemics was higher in the dry than in the rainy season, but was afterwards higher in the rainy than in the dry season. A C(a) test was used to test for overdispersion, and the betabinomial parameter u was used to assess disease aggregation in quadrats consisting of one, two, four, eight and 16 elementary quadrats. Aggregation was detectable at all quadrat sizes throughout the epidemic, according to the C(a) test. u was highest at epidemic onset and at the smallest (elementary) quadrat size, indicating a very strong aggregation of disease at the individual hill scale. u increased until disease incidence reached 40%, then declined over time. u values were generally smaller in the dry season. Semivariograms for both epidemics showed strong initial discontinuities, that is, large variance of disease incidence at the elementary quadrat scale. Some aggregation in the spatial distribution of disease incidence was indicated at higher scales in the rainy season, coinciding with the highest rate of disease increase. Semivariograms did not suggest any structure in the dry season, except for one date in the early epidemic stage. Spatiotemporal autocorrelation of disease incidence at 45 days after transplanting yielded very few variables that contributed significantly to describing the disease incidence and its increase in a given hill. In the rainy season these variables were disease incidence (or increase) in the nearest sampled neighbours, and disease incidence (or increase) observed 1 week earlier in the same hill. In the dry season only disease incidence (or increase) observed 1 week earlier in the same hill was significantly correlated with the current incidence (or its increase). The development of a spatial structure in distribution of disease is hypothesized to coincide with the spread of the pathogen from one hill to another, and with the shift from monocyclic to predominantly polycyclic processes in sheath blight epidemics. These results concur with previous reports in suggesting that management of rice sheath blight should first be directed against the leafborne, polycyclic phase of epidemics, rather than their initial phase.

Resistance to rice sheath blight (Rhizoctonia solani Kühn) [(teleomorph: Thanatephorus cucumeris (A.B. Frank) Donk.] disease: current status and perspectives

“…This aggregation of ShB is a central feature of rice ShB epidemics (Gou et al 1983;Savary et al 1997Savary et al , 2001Gong and Zhang 2002;Tan and Wang 2002) and a critical element to assess resistance (Zadoks and Schein 1979). Inter-plot interaction (Jenkyn et al 1979), on the other hand, is of little concern in the case of this disease.…”

Spatial Pattern of Natural Spread of Rice False Smut (<i>Ustilaginoidea virens</i>) Disease in Fields

“…However, the spatial pattern of spread of the disease in the fields, where rice is grown in natural environment, can provide essential information on key epidemiological processes as has been reported for other diseases (Campbell and Noe, 1985;Madden et al, 1987;Hughes, 1990;Nelson and Campbell, 1993;Camann et al, 1995;Madden et al, 1995;Savary et al, of this work was to try to understand what major 2001; Moreno et al, 2007). To best of our knowledge, there has been no published report on analysis of spatial pattern of natural spread of rice false smut disease.…”

Size, shape and intensity of aggregation of take‐all disease during natural epidemics in second wheat crops

“…, 1995), viruses (Pethybridge & Turechek, 2003), bacteria (Roumagnac et al. , 2004), fungi (Savary et al. , 2001), parasitic plants (Aukema, 2004) and nematodes (Gavassoni et al.…”