Stable isotope ratios (SIRs) of C, N, H and O have been exensively used in fruit juices quality control (ENV and AOAC methods) to detect added sugar and the watering down of concentrated juice, practices prohibited by European legislation (EU Directive 2012/12). The European Fruit Juice Association (AIJN) set some reference guidelines in order to allow the judging of the genuiness of a juice. Moreover, various studies have been carried out to determine the natural variability of SIRs in fruit juices, but none of these has investigated SIRs extensively in authentic citrus juices from Italy. In this work, about 500 citrus juice samples were officially collected in Italy by the Italian Ministry of Agricultural and Forestry Policies from 1998 onwards. (D/H)(I) and (D/H)(II) in ethanol and δ(13) C(ethanol), δ(13) C(pulp), δ(13) C(sugars), δ(18) O(vegetalwater), δ(15) N(pulp), and δ(18) O(pulp) were determined using Site-Specific Natural Isotope Fractionation-Nuclear Magnetic Resonance and Isotope Ratio Mass Spectrometry, respectively. The characteristic ranges of variability in SIRs in genuine Italian citrus juice samples are here presented as well as their relationships and compliance with the limits indicated by the AIJN and others proposed in the literature. In particular, the Italian range of values was found to be not completely in agreement with AIJN guidelines, with the risk that genuine juices could be judged as not genuine. Variety seems not to influence SIRs, whereas harvest year and region of origin have some influence on the different ratios, although their data distribution shows overlapping when principal component analysis is applied.
A simple and reliable high-performance liquid chromatographic method that uses photodiode array detection was developed for the simultaneous determination of 12 native and synthetic plant hormones, i.e., plant growth regulators (PGRs), in fertilizers, such as 1-naphthol, 2,4-dichlorophenoxyacetic acid, 4-(2,4-dichlorophenoxy)butyric acid, 4-chlorophenoxyacetic acid, indole-3-acetic acid, 4-(3-indolyl)butyric acid, dichlorprop, (4-chloro-2-methylphenoxy)acetic acid, -naphthaleneacetic acid, 1-naphthaleneacetamide, -naphthoxyacetic acid, and thidiazuron. The method was experimentally validated for routine regulatory application, and the following analytical parameters were assessed for all PGRs studied: linearity; specificity; precision (relative standard deviation) and accuracy, both measured at 3 concentration levels (0.1, 0.05, and 0.01, w/w); ruggedness; limit of detection; and limit of quantification. Results were satisfactory for all method validation parameters tested and for all PGRs studied, demonstrating the suitability of the method for the determination of PGRs in fertilizers. The uncertainty of measurement was also estimated at 3 concentration levels for all PGRs by using the approach of the International Organization for Standardization, described in its Guide to the Expression of Uncertainty in Measurement. The method was applied to 20 samples of liquid fertilizer with declared biostimulant properties.
The influence of the wine distillation process on methanol content has been determined by quantitative analysis using gas chromatographic flame ionization (GC-FID) detection. A comparative study between direct injection of diluted wine and injection of distilled wine was performed. The distillation process does not affect methanol quantification in wines in proportions higher than 10%. While quantification performed on distilled samples gives more reliable results, a screening method for wine injection after a 1:5 water dilution could be employed. The proposed technique was found to be a compromise between the time consuming distillation process and direct wine injection. In the studied calibration range, the stability of the volatile compounds in the reference solution is concentration-dependent. The stability is higher in the less concentrated reference solution. To shorten the operation time, a stronger temperature ramp and carrier flow rate was employed. With these conditions, helium consumption and column thermal stress were increased. However, detection limits, calibration limits, and analytical method performances are not affected substantially by changing from normal to forced GC conditions. Statistical data evaluation were made using both ordinary (OLS) and bivariate least squares (BLS) calibration models. Further confirmation was obtained that limit of detection (LOD) values, calculated according to the 3σ approach, are lower than the respective Hubaux-Vos (H-V) calculation method. H-V LOD depends upon background noise, calibration parameters and the number of reference standard solutions employed in producing the calibration curve. These remarks are confirmed by both calibration models used.
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