The application of near-infrared reflectance spectroscopy (NIRS) and multivariate analysis for determining the seed germination rate of corn genotypes was assessed. Seed samples about 90 gr belong to commercial and local corn varieties at various ages were scanned with FT-NIRS on the reflectance mode from 1000 to 2500 nm wavelength. Filter paper technique showed the seed germination rates varied between 18-100% depending on the genotypes after 7 days at ±25°C. Partial least squares regression (PLSR) was applied to the reference values corresponding to the spectra. The best statistical results obtained from the pre-treatment combinations of Smooth Savitzky-Golay 9 Points (sg9), MSC full and normalization to unit length (nle). The regression coefficient of calibration (R2C) and prediction (R2P) of the created NIRS calibration via chemometric software NIRCal are realized 0.97 and 0.98 respectively for the property of corn germination rate. The standard error of both calibration (SEC) and prediction (SEP) were almost overlapping (4.17%, 4.61% respectively). The prediction accuracy of the final NIRS model was quite reasonable with the acceptable root mean standard error of prediction (RMSEP) as 8.88%. According to the residual predictive deviation (RPD) index (4.18), the accuracy of the NIRS model regarded as in the best category. Therefore, the NIRS model developed here is sufficient to predict the corn seed germination rate very fast and non-destructively without using any regents.

The level of applied microwave power is a critical parameter for the quality of the dried product in microwave drying. It is impossible to assess the applied power of the dried product with the naked eye. This work aimed to predict the applied power of black carrot powders using a chromameter and near-infrared reflectance spectroscopy with partial least squares regression. A good correlation was found between applied power, color parameters, and near-infrared reflectance. The near-infrared spectroscopy predicted the applied power with better performance (R² = 0.99) and can be utilized to appraise the applied power of black carrot powders with acceptable accuracy.

In this study, we investigated the chemical composition, antimicrobial and antibiofilm activities, and cytotoxicity of Thuja occidentalis L. (thuja) and Myrtus communis L. (myrtle) essential oils (EOs) to evaluate their potential as natural alternatives for topical applications. Thuja EOs were extracted from fresh and dried leaves and cones, while myrtle EO was extracted from fresh leaves. GC-MS analysis revealed that myrtle EO was rich in oxygenated monoterpenes (58.2%), predominantly eucalyptol (41.86%) and α-pinene (20.98%). In contrast, thuja EOs were dominated by monoterpene hydrocarbons (55–82%), with α-pinene as the major component (29–66%), and their composition varied markedly with plant organ and moisture state. Myrtle EO displayed the most potent and broad-spectrum antimicrobial activity, with MIC values as low as 3.096 µL/mL against Staphylococcus aureus and Escherichia coli, and effectively inhibited microbial adherence. Thuja EOs showed selective activity, particularly against Gram-positive bacteria and Candida parapsilosis, with EOs extracted from fresh leaves and cones exhibiting the lowest MICs (1.95–7.8 µL/mL). All EOs did not show cytotoxicity to human keratinocytes at concentrations ≤125 µg/mL and, when diluted to 0.05%, indicated excellent skin compatibility in human patch tests. This study suggests that myrtle and thuja EOs, particularly myrtle, are promising and safe natural antimicrobial agents for dermatological and cosmetic formulations.