FT-NIR and linear discriminant analysis to classify chickpea seeds produced with harvest aid chemicals.

Spectroscopy and machine learning (ML) algorithms have provided significant advances to the modern food industry. Instruments focusing on near-infrared spectroscopy allow obtaining information about seed and grain chemical composition, which can be related to changes caused by field pesticides. We investigated the potential of FT-NIR spectroscopy combined with Linear Discriminant Analysis (LDA) to discriminate chickpea seeds produced using different desiccant herbicides at harvest anticipation.

Validation and application of a QuEChERS based method for estimation of half-life of imidazolinone herbicides in soils by LC-ESI-MS/MS.

A modified QuEChERS (quick, easy, cheap, effective, rugged and safe) method was validated and applied for the estimation of half-lives of two imidazolinone group herbicides, imazethapyr and imazapic, in the Dystric Plinthosol (FX) and Ferralsol (LVA) agricultural soils using liquid chromatography tandem mass spectrometry. The solutions were prepared in a matrix extract to avoid matrix effects. The analytical method showed satisfactory specificity, selectivity, linearity (R > 0.