Visualization of spread of papaya ring spot virus using "raster" package in r statistical environment

Papaya (Carica papaya L.) is an important tropical fruit crop with an increasing market as a health food. India is the leading papya producer. The Papaya Ring Spot Virus (PRSV) is emerging as a major limiting factor in the production of Papaya. The PRSV causes mosaic on the leaves, leading to malformed leaves. Water soaked lesions appear on the stem, fruit and flower drop would be seen, Malformed fruits appear with characteris tic rings on the fruits. Affected plants become unproductive and would die soon after. The PRSV had been extensively described (Singh, 2003 and Tripathi et al., 2008) and is vectored in a non-persistent manner, by aphids Aphis gossypii Glover, Myzus persicae (Sulzer) and A. craccivora Koch (Kalleshwaraswamy and Kumar, 2008). The spread of PRSV would be quite rapid in the field as the rate of spread determines the economic loss caused and it is necessary to visualize this spread. An attempt was made to visualize these parameters using R software which is a free softw are environment for s tatistic al computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS, It is available for free download at (http://www.r-project.org). It has the advantage of providing a free alternative to costly commercial software. Geographic Information Systems (GIS) can be used to effectively visualize spatial data. Raster is a package which runs under R and it was used to visualize the spread through charts. raster uses a spatial (geographic) data structure that divides a region into rectangles called as ‘cells’ (or ‘pixels’) that can store one or more values for each of these cells. Such a data structure could also referred to as a ‘grid’ and is often contrasted with ‘vector’ data that is used to represent points , lines , and polygons . The raster package has functions for creating, reading, manipulating, and writing raster data. The package provides, general raster data manipulation functions that can easily be used to develop more specific functions. It also implements raster algebra and most functions for raster data manipulation that are common in GIS systems. The PRSV disease incidence was recorded on an increasing scale of 1-9 as was present in an 11x43 plot of papaya field infected w ith PRSV, at various time points. The data were entered in a Microsoft Excel 2013 worksheet in a r x c matrix. The disease incidence was recorded at seven different time periods viz 3 Jan 2012, 18 Jan 2012, 25 Jan 2012, 15 Feb 2012, 23 Feb 2012, 1 March 2012, 8 March 2012. Each time period was recorded in a separate work sheet. The changeover in disease inc idence was rec orded by subtrac ting the disease incidence value at the (n) time point from the (n-1 time point), this difference was saved in a separate sheet and indicated the changeover of disease incidence at that time point. All the data recorded Microsoft Excel 2013 worksheet files were finally saved as *.csv (coma separated files) as R and the program raster can read *.csv files natively.