Márcia Maria Lima Duarte

Determination of quality attributes in wax jambu fruit using NIRS and PLS.

The aim of this work was to develop an analytical method to predict total anthocyanins content (TAC) and total phenolic compounds (TPC) in intact wax jambu fruit [Syzygium malaccense (L.) Merryl et Perry] using near-infrared spectroscopy (NIRS) and partial least squares (PLS). The estimation accuracy was based on parameters such as root mean square error of prediction (RMSEP), correlation coefficients [calibration (rc) and prediction (rp) set] and ratio of performance to deviation (RPD). TAC, rp = 0.98, RMSEP = 9.0 mg L(-1) and RPD = 5.19 were attained using second derivative pre-treatment. TPC, rp = 0.94, RMSEP = 22.18 (mg gallic acid equivalents (GAE)/100g) and RPD = 3.27 (excellent accuracy) were also obtained using second derivative pre-treatment. These findings suggest that the NIRS and PLS algorithms can be used to determine TCA and TPC in intact wax jambu fruit.

Solar photo-Fenton treatment of petroleum extraction wastewater

Abstract The purpose of this study is to investigate the treatment of petroleum-extraction wastewater by means of a photo-Fenton like process using sunlight as irradiation source. According to the experimental results, a reduction of the wastewater UV absorption spectral intensity indicates that polycyclic aromatic hydrocarbons and aromaticity removal of approximately 92.7 and 96.2%, respectively, were obtained after 7 h of sunlight exposure using 485.3 mmol L−1 of hydrogen peroxide. For the investigated treatment condition, the H2O2 optimum concentration was 485.3 mmol L−1 since an increment in H2O2 concentration did not promote a significant increment in treatment efficiency. H2O2 single oxidation was also important during the photo-Fenton treatment. A moderate level of mineralization was also observed. Finally, photo-Fenton process using sunlight was able to reduce sample acute phytotoxicity by about 50%.

Quantification of quality parameters in castanhola fruits by NIRS for the development of prediction models using PLS and variable selection algorithms on a laboratory scale

This paper proposes a novel methodology for the quantification of total phenolic compounds (TPCs) and total anthocyanin compounds (TACs) in castanhola fruits (Terminalia catappa Linn), using near infrared spectroscopy (NIRS) coupled with variable selection algorithms, such as interval partial least squares (iPLS) and genetic algorithm-partial least squares (GA-PLS). GA-PLS showed the best results in the prediction of both parameters. TPC parameters, Rp2 = 0.82, RMSEP = 11.3 mg GAE g−1 (mg gallic acid equivalents (GAE) per g sample), SEL 16.70 mg GAE g−1, RPD = 2.89, sensibility 2.19 × 10−7, and selectivity 0.048 were also obtained using first derivative (5 points) and MSC pretreatment. TAC parameters, Rp2 = 0.80, RMSEP = 8.70 mg L−1, SEL 6.93 mg L−1, RPD = 1.90, sensibility 6.73 × 10−6 and selectivity 0.07 were attained using second derivative (11 points) pre-treatment. From these findings, it can be concluded that NIRS coupled GA-PLS can be used as a non-destructive technique for determining TACs and TPCs in intact castanhola fruits.