Nicolet iz 10 module

Individual aphids were placed in separate test tubes. Each sample was rubbed on a glass slide and the aphid’s body mass placed on the ATR crystal. In order to establish the differences in the chemical compositions between summer and winter types of C. tujafilina ATR-FTIR spectra obtained from summer and winter were compared [42 (link),43 (link),44 (link),45 (link),46 (link)]. Also the samples collected in subsequent months were compared to establish the chemical changes during three months. For each time interval (summer, winter, October, November, December) measurements were taken on 10 samples. Spectra of aphid samples were measured using a Nicolet iN10 MX microspectrometer, which has a deuterated triglycine sulphate (DTGS) detector and KBr beam splitter (Thermo Fisher Scientific, Waltham, MA, USA) with Nicolet iZ10 module, coupled with a Smart Orbit ATR one-bounce diamond crystal (diamond 30.000–200 cm⁻¹) accessory. Measurements were controlled using OMNIC software (Thermo Fisher Scientific). Spectra for both background and aphid sample measurements were recorded at a resolution of 4 cm⁻¹ and 64 scans in the range of 500–4000 cm⁻¹. For each spectrum, baseline correction and vector normalization were made using OPUS 7.0 software (Bruker Optik GmbH, Ettlingen, Germany).

For the analysis of cellulose organization in leaves of M. giganteus and maize plants, the cell wall was isolated from frieze-dried leaves and purified from starch. The mid-infrared spectra were collected using Fourier transform infrared spectrometer (FTIR) Nicolet iZ 10 module (Thermo Fisher Scientific) and the ATR accessory equipped with a diamond crystal. Interferograms (256) were gathered at the resolution of 4 cm⁻¹ and co-added within the wavelength range between 4000 and 400 cm⁻¹ using OMNIC (v. 8.1, Thermo Fisher Scientific) software. The spectra were normalised to the unit area (1800–900 cm⁻¹) after the baseline correction and processed for analysis using the ChemoSpec (Hanson 2017 (link)) and the hyperSpecc (Beleites and Sergo 2018 (link)) packages in the R (R Core Team 2018 (link)).

Mid-infrared spectroscopy measurements were performed on cell wall material ground into a fine powder with an agate mortar and pestle and washed successively with 70% ethanol, 1:1 (v/v) mixture of chloroform and methanol, and acetone. Spectral data were collected using Fourier Transform Infrared (FTIR) spectrometer (Nicolet iZ 10 module, Thermo Fisher Scientific Inc., United States) equipped with a deuterated triglycine sulfate (DTGS) detector, KBr beam splitter, and a diamond single bounce Attenuated total reflectance (ATR) accessory. Two-hundred and fifty-six interferograms were recorded and added together between 4,000 and 400 cm^-1 at 2 cm^-1 resolution. The spectra were baseline corrected, normalized to a constant area between 1,760 and 880 cm^-1, and smoothed at a final resolution of 4 cm^-1 by apodization using the Blackman–Harris 3-term function and a zero-filling factor of 2. Collection, pre-processing, and analysis of spectral data were performed by means of OMNIC software (v. 9.0, Thermo Fisher Scientific Inc.). The spectra were subjected to multiple univariate and multivariate analysis. The latter was performed by unsupervised principal component analysis (PCA) (Unscrambler X, v.10.1, CAMO, Norway).