The SISSI program implements a novel approach for the estimation of the optimal sample size in experimental data collection. It provides avisual evaluation system of sample size determination, derived from a resampling-based procedure (namely, jackknife). The approach is based on intensive use of the sample data by systematically taking sub-samples of the original data set, and calculating mean and standard deviation for each of subsamples. This approach overcomes the typical limitations of conventional methods, requiring data-matching statistical assumptions. Visual, easyto-interpret provisions are supplied to display the variation of means and standard deviations as size of generated samples increases. An automatic option for identification of optimal sample size is given, targeted at the size for which the rate of change of means becomes negligible. Alternatively, a manual option can be applied. An ideal application of SISSI is in supporting the collection of plant and soil sample...