2,4,6- Ttrichloroanisol:a consumer panel evaluation

“Cork taint” is a major problem in wine industry and is caused by contamination of wines. This contamination is usually attributed to wine cork stoppers and 2,4,6-trichloroanisole (2,4,6-TCA) is one of the compounds mostly associated to this off-flavour. In this work, a consumer panel performed “forced choice” triangular tests in order to measure Odour Detection Thresholds (ODT) and Taste Detection Thresholds (TDT) of 2,4,6-TCA in water, hydro-alcoholic solutions (11.5% and 18% ethanol) and white and red wines. A paired preference test was also performed by the panel in order to measure Odour Rejection Threshold (ORT) in white and red wine spiked with 2,4,6-TCA. Results obtained show that the ODT and the TDT for 2,4,6-TCA in water were 0.2 and 0.3 ng/L, respectively. In hydro-alcoholic solutions with 11.5% and 18% ethanol the ODT were 4 and 10 ng/L respectively. In red wine the ODT and the TDT were 0.9 and 1.7 ng/L and in white wine were 1.5 and 1.0 ng/L respectively. ORT for white was 10.4 ng/L and for red wines 16.0 ng/L. These results suggest that although this group of consumers detected very low concentrations of 2,4,6-TCA in wines, they did not reject the wine at these low concentration values.

Evaluation of uv spectrophotometry for estimation of nitrite and nitrate in nitrified urine

Water is a limited resource for which demand is growing. Contaminated water from inadequate wastewater treatment provides one of the greatest health challenges as it restricts development and increases poverty in emerging and developing countries. Therefore, the connection between wastewater and human health is linked to access to sanitation and to human waste disposal. Adequate sanitation is expected to create a barrier between disposed human excreta and sources of drinking water. Different approaches to wastewater management are required for different geographical regions and different stages of economic governance depending on the capacity to manage wastewater. Effective wastewater management can contribute to overcome the challenges of water scarcity. Separate collection of human urine at its source is one promising approach that strongly reduces the economic and load demands on wastewater treatment plants (WWTP). Treatment of source-separated urine appears as a sanitation system that is affordable, produces a valuable fertiliser, reduces pollution of water resources and promotes health. However, the technical realisation of urine separation still faces challenges. Biological hydrolysis of urea causes a strong increase of ammonia and pH. Under these conditions ammonia volatilises which can cause odour problems and significant nitrogen losses. The above problems can be avoided by urine stabilisation. Biological nitrification is a suitable process for stabilisation of urine. Urine is a highly concentrated nutrient solution which can lead to strong inhibition effects during bacterial nitrification. This can further lead to process instabilities. The major cause of instability is accumulation of the inhibitory intermediate compound nitrite, which could lead to process breakdown. Enhanced on-line nitrite monitoring can be applied in biological source-separated urine nitrification reactors as a sustainable and efficient way to improve the reactor performance, avoiding reactor failures and eventual loss of biological activity. Spectrophotometry appears as a promising candidate for the development and application of on-line nitrite monitoring. Spectroscopic methods together with chemometrics are presented in this work as a powerful tool for estimation of nitrite concentrations. Principal component regression (PCR) is applied for the estimation of nitrite concentrations using an immersible UV sensor and off-line spectra acquisition. The effect of particles and the effect of saturation, respectively, on the UV absorbance spectra are investigated. The analysis allows to conclude that (i) saturation has a substantial effect on nitrite estimation; (ii) particles appear to have less impact on nitrite estimation. In addition, improper mixing together with instabilities in the urine nitrification process appears to significantly reduce the performance of the estimation model.