When applying for the registration of the technical grade active ingredient (TGAI), it is important that the active ingredient and the associated impurities are reliably quantified. The accuracy of measurement is pivotal for ensuring the efficacy of the active ingredient. With the rapid development of science and technology, traditional titration assay methods are increasingly being replaced by computer-enabled chromatographic systems, which include HPLC and GC. However, these software packages do not routinely generate data with the appropriate number of significant figure. To address this, the analyst must undertake further data processing and complete an error analysis based on the principles of significance arithmetic. Although the significance arithmetic theory has been applied for some time, analysts frequently underestimate its importance and inadequately address it. This has led to erroneous results appearing in the application data package. Such errors may negatively impact on the perceived reliability of the data and mislead the registration authorities.
This paper is to reiterate the rules relating to significant figures and significance arithmetic and to demonstrate their application in the pesticides registration in a government regulatory authority. Three typical examples demonstrating the correct use of significant figures in the registration of TGAI are presented in this paper, including the correct use of significant figures in quantifying the active constituents, calculating mass accountability, and determining the validation data.

When presenting data on the active ingredient content and the linearity data, the significance arithmetic multiplication/division rule must be followed, and the calculated results have to be rounded to match the least significant figure of the numbers being multiplied or divided.

When calculating the mass accountability of all ingredients in a technical grade active ingredient, the addition/subtraction arithmetic rule applies. The calculated value is rounded to the number of significant figures in the most uncertain of the numbers being summed or subtracted.