Kinetic study of nordihydroguaiaretic acid recovery from Larrea tridentata by microwave-assisted extraction

Nordihydroguaiaretic acid (NDGA) is a powerful antioxidant that can be found in plants like Larrea tridentata (Zygophyllaceae), also known as creosote bush, which grows in semidesert areas of Southwestern United States and Northern Mexico [1]. Several studies have demonstrated that NDGA has important biological activities with great interest in the health area, such as antiviral, cancer chemopreventive, and antitumorgenic activities [2]. Extraction of bioactive compounds from plants is conventionally performed using a heat‐reflux extraction method. However, different techniques have been developed in order to decrease extraction time and solvent consumption, as well as to increase the extraction yield and enhance the extracts quality [3]. The objective of this study was to develop a microwave‐assisted extraction (MAE) method for NDGA recovery from Larrea tridentata leaves, and compare the obtained results with those found by using the conventional heat‐reflux extraction (HRE)

New chemometric strategies in the spectrophotometric determination of pKa

In this work, principal component regression and partial least squares regression were used for the estimation of acid dissociation constants through UV-Vis spectrophotometric measurements, considering five well-known acid-base indicators as well as two herbicides as analytes. In each case, an acid-base titration was carried out. Then, the multivariate calibration model was constructed with a few absorption spectra of the series at extreme pH values, to which values of the dissociation fraction (α) of 1 or 0 were assigned, in the case of HA or Aspecies. After that, the prediction step consisted in the estimation of α for the rest of the series. Then, distribution diagrams were built up with α vs pH, to find α = 0.5 where pH = pKa. The results were compared with those obtained through multivariate curve resolution-alternating least squares and program stability quotients from absorbance data (SQUAD), which showed an excellent correspondence