Magnetic solid phase extraction as a nonchromatographic method for the quantification of ultratrace inorganic arsenic in rice by inductively coupled plasma-optical emission spectrometry (ICP OES).

An alternative analytical method was developed for the quantification of inorganic arsenic (iAs) in rice by ICP OES. Iron nanoparticles modified with an organophosphorus compound were used as the solid phase for MSPE of iAs from the plant matrix. The MSPE procedure was performed using 4 mL of a buffer solution with pH 4.0, 20 mg of the nanomaterial, and a 15-min extraction time. The total As (tAs) by ICP OES was also quantified using the same MSPE procedure after solubilization of the samples by a block digester. The accuracy of tAs and iAs quantification was verified using CRM NIST 1568b (97 % and 101 % recovery, respectively). The precision (RSD < 15 %) and LOD and LOQ (1.08 and 3.70 µg kg-1, respectively) of the proposed method were satisfactory. The rice samples had tAs contents between 0.090 and 0.295 mg kg-1 and iAs mass fractions between 0.055 and 0.109 mg kg-1.

Non-chromatographic arsenic speciation analyses in wild shrimp (Farfantepenaeus brasiliensis) using functionalized magnetic iron-nanoparticles.

A new iron-magnetic nanomaterial functionalized with organophosphorus compound was used as solid-phase for arsenic speciation analysis in seafood samples by ICP-MS. The procedure was optimized using chemometric tools and the variables pH = 4.0, 15 min extraction time, and 20 mg of mass of material were obtained as the optimum point. The inorganic arsenic (iAs) extracted using nanoparticles presented concentrations between 20 and 100 µg kg-1 in the evaluated samples. The method was validated for accuracy using CRMs DOLT-5 and DORM-4. It was possible to reuse the same magnetic nanomaterial for 6 successive cycles, and we obtained a detection limit of 16.4 ng kg-1. The proposed method is suitable for the use of inorganic speciation of As, presenting good accuracy, precision, relatively low cost, and acquittance to green chemistry principles.

The concentration of polyphenolic compounds and trace elements in the Coffea arabica leaves: Potential chemometric pattern recognition of coffee leaf rust resistance.

Coffee (Coffea arabica L.) is an important commodity, involving about 500 million people from the cultivation of the coffee trees to final consumption of infusions of the ground roasted coffee beans. In contrast to a considerable amount of research performed on green coffee beans, there are relatively few studies regarding the chemical constituents of coffee leaves. Hemileia vastatrix is a parasite, specific to coffee plants and causes coffee leaf rust, which is a very destructive disease. Some coffee plants have natural resistance which is mainly linked to a gene and specific host resistance response. An increase in flavonoid production may be related to fungal disease resistance, with the levels and flavonoid types being an early physiological response to rust infection. Trace inorganic elements can be related to many roles in the defense response of higher plants and can be used as a biomarker for some diseases. To address this, coffee leaves from 16 different cultivars of Coffea arabica were harvested from Minas Gerais, Brazil (susceptible and resistant to rust) and their polyphenolic compounds were extracted using the QuEChERS technique and quantitated by HPLC-ESI-MS. The same leaves were decomposed using an acid mixture in a block digester and the content of Al, Cu, Mg, Mn, Ni, Sn and Zn was quantitated by ICP-OES. Principal component analysis (PCA) was applied and we could establish a relation between polyphenolic and trace element concentration in the leaves with resistance to rust infection. On this basis in this preliminary study we were able to separate the resistant from the susceptible cultivars. The main compounds responsible for this differentiation were the content of chlorogenic acid and magnesium in the leaves. The content of polyphenolic compounds was lower in susceptible cultivars and a diametric effect was observed between Mn and Mg concentrations. This study shows potential for the discrimination of resistant and susceptible coffee trees based on the analyses of both trace element and polyphenolic concentration.

Optimization of a cloud point extraction procedure with response surface methodology for the quantification of dissolved iron in produced water from the petroleum industry using FAAS.

The characterization of inorganic elements in the produced water (PW) samples is a difficult task because of the complexity of the matrix. This work deals with a study of a methodology for dissolved Fe quantification in PW from oil industry by flame atomic absorption spectrometry (FAAS) after cloud point extraction (CPE). The procedure is based on the CPE using PAN as complexing agent and Triton X-114 as surfactant. The best conditions for Fe extraction parameters were studied using a Box-Behnken design. The proposed method presented a LOQ of 0.010µgmL-1 and LOD of 0.003µgmL-1. The precision of the method was evaluated in terms of repeatability, obtaining a coefficient of variation of 2.54%. The accuracy of the method was assessed by recovery experiments of Fe spiked that presented recovery of 103.28%. The method was applied with satisfactory performance to determine Fe by FAAS in PW samples.