Since the advent of genetic engineering in the 1970s, concerns arose about risks of this technology that led to enforce labeling of transgenic crops. Therefore, it seems, it is necessary to use valid methods to identify transgenic crops to reduce or minimize relative potential errors. The validity of such methods depends on the sampling and the uniformity of distribution of transgenic crop under study. In most cases, the sampling is a source of error. Therefore, some software such as SISSI is designed to reduce sampling errors. This software which works based on Jackknife method is a new tool to determine optimum sample size for the experimental data set. The method estimates the population variance when there is little information about the population. The software graphically displays results as also changes in the mean and standard deviation of the population. Moreover, it has the option to determine the sample size automatically. One of its applications of this is to determine optimal sample size for transgenic shipments that are not uniform. The detection of transgenic material in commercial samples with high sensitivity in the international trade is another instance of its applications.