Great attention should be paid now to simultaneously removing common pollutants, especially inorganic pollutants such as nitrate and heavy metals, as individual removal has been investigated extensively. Removing common pollutants simultaneously by iron metal is a very effective alternative method. Near neutral pH, heavy metals, such as copper and nickel, can be removed rapidly by iron metal, while nitrate removal very much slower than that of copper and nickel, and copper can accelerate nitrate removal when both are removed simultaneously. Even a little amount of copper can enhance nitrate removal efficiently. Different mechanisms of these contaminants removal by iron metal were also discussed.

No abstract

The quantification of β-glucan in oats is of immense importance for plant breeders and food scientists to develop plant varieties and food products with a high quantity of β-glucan. However, the chemical analysis of β-glucan is time consuming, destructive, and laborious. In this study, near-infrared (NIR) spectroscopy in conjunction with Chemometrics was employed for rapid and non-destructive prediction of β-glucan content in oats. The interval Partial Least Square (iPLS) along with correlation matrix plots were employed to analyze the NIR spectrum from 700–1300 nm, 1300–1900 nm, and 1900–2500 nm for the selection of important wavelengths for the prediction of β-glucan. The NIR spectral data were pre-treated using Savitzky Golay smoothening and normalization before employing partial least square regression (PLSR) analysis. The PLSR models were established based on the selection of wavelengths from PLS loading plots that present a high correlation with β-glucan content. It was observed that wavelength region 700–1300 nm is sufficient for the satisfactory prediction of β-glucan of hulled and naked oats with R2c of 0.789 and 0.677, respectively, and RMSE < 0.229.

No abstract