Transgenic crops (TCs) have potentially higher yield and quality as compared to their traditional relatives. Cultivation of these crops will lead to less use of chemical pesticides. In addition to its use as food resources, TCs “such as soybeans, canola, cotton, corn and potatoes” are currently being used for livestock feeding. About 90 percent of transgenic soybeans as well as 70 percent of transgenic corns have been assigned to the livestock sector so that, it can be said that TCs constitute a significant part of the fodder needed for livestock feeding. Researches have shown that chemical contents of transgenic crops are same as non-transgenic crops in terms of their chemical composition and amino acid content. Moreover, so far, no allergic property has been reported for TCs. Surveys have also shown that the compounds, digestibility, feed value and safety aspects of TCs were quite substantial equivalence with non-transgenic crops. The present study is an overview of concerns about the use of TCs for livestock feeding.

The software implements standard statistical approaches commonly adopted in validation studies to estimate analytical method performance (limits of detection and quantitation, precision and accuracy). This software can also be used for tests to determine the normal distribution of data, to check the homogeneity of variances as well as a choices of method selection according to specific user needs. The importance of validation of analytical methods have been risen. Validated methods for the detection of genetically modified organisms (GMO) are requested by European union (EU) legislation in order to accept GMO crops on the European market. The AMPE software could be used to synchronize and standardize the results of the assessment of GMO in different countries and the competent authorities. In most cases, validation requires the assessment of the performance of the proposed method by means of an inter laboratory studies. This application has been developed based on international protocols ISO, Codex CCMAS and the ISO 5725 (1994). This software has to compare different methods and evaluate their adequacy with respect to specific needs, based on summarized information collected during the validation and recognition GMO crops.

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.