6533b7ddfe1ef96bd12751ff

RESEARCH PRODUCT

Quality Control of Agrochemical Formulations by Diffuse Reflectance near Infrared Spectrometry

Sergio ArmentaSalvador GarriguesMiguel De La Guardia

subject

Materials scienceQuality (physics)Solvent freeAgrochemicalbusiness.industryNear-infrared spectroscopyAnalytical chemistryNear-Infrared SpectrometryDiffuse reflectionbusinessEnvironmentally friendlySpectroscopy

description

A near infrared (NIR)-based methodology has been developed for the determination of 11 pesticides in commercially available formulations. This solvent free, fast and environmentally friendly method was based on the direct measurement of the diffuse reflectance spectra of solid samples, a hierarchical cluster classification and the use of multivariate calibration models to determine each considered active principle in agrochemicals. The proposed partial least squares (PLS) models used for quantification of each compound were built from specific calibration sets composed of nine spectra corresponding to triplicate measurements of a single well characterised commercial sample and two additional doped (under- and over-dosed) samples. Different formulations and commercial samples were employed as validation sets. Data obtained by PLS/NIR were comparable with results found by reference liquid chromatography procedures. For bensulfuron, buprofezin and metalaxyl determination, the information in the spectral range between 1000 nm and 2640 nm of the zero order reflectance spectra was used. For chlorsulfuron, cyromazine, daminozide, diuron, fenoxycarb, iprodione, procymidone and tricyclazole determination, the information of the first order derivative spectra in the range between 1000 nm and 2640 nm was used. In both cases, a linear removed correction was applied as data pre-treatment. The developed PLS/NIR method can be applied directly to solid samples without using any solvent or sample pre-treatment and thus any contact between the operator and toxic reagents is avoided providing a safe and environmentally acceptable analytical methodology.

https://doi.org/10.1255/jnirs.767