Chitosan-coated magnetic nanoparticles (CMNP) were obtained at 50 • C in a one-step method comprising coprecipitation in the presence of low chitosan content. CMNP showed high magnetization and superparamagnetism. They were composed of a core of 9.5 nm in average diameter and a very thin chitosan layer in accordance with electron microscopy measurements. The results from Fourier transform infrared spectrometry demonstrated that CMNP were obtained and those from thermogravimetric analysis allowed to determine that they were composed of 95 wt% of magnetic nanoparticles and 5 wt% of chitosan. 67% efficacy in the Pb +2 removal test indicated that only 60% of amino groups on CMNP surface bound to Pb, probably due to some degree of nanoparticle flocculation during the redispersion. The very low weight ratio chitosan to magnetic nanoparticles obtained in this study, 0.053, and the high yield of the precipitation reactions (≈97%) are noticeable.

Aguamiel is a beverage produced by some species that is consumed in its fresh or fermented form. Despite its uses and popularity, seasonal effects on its microbial and chemical profiles are unknown. In this study, using aguamiel collected from and during different seasons, we identified microorganisms by sequencing the 16S and 18S rDNA genes and determined their chemical profiles. In total, 49 microbial strains were identified (38 bacteria and 11 yeasts). The highest richness and biodiversity were observed during winter and summer. Different lactic acid bacteria and yeast genera with potential industrial applications were identified, such as, ,, and . The analysis of the chemical profiles indicated the presence of maltooligosaccharides and fructooligosaccharides, which are associated with human health improvements, during spring in aguamiel. Aguamiel can be used in the food industry due to its microbiological and chemical profiles.

Salinity in soils is a problem that has increased in recent years, in the Mexican southeast one of the main sources associated with these effects is the oil production water, affected congenital water. Although the chemical composition changes between one site and another, it is documented that its components can cause harmful effects on health and ecosystems. To recover the vocation to use recovery areas, different treatments have been established that eliminate standardized parameters, but others that may influence soil quality are not considered. Therefore, two treatment techniques of a soil contaminated experimentally with congenital waters were evaluated, these were; cation exchange and natural attenuation, the evaluation consists in comparing the physical and chemical properties of the control soil, treated and treated after one year, some heavy metals are also determined in all of them. In the results, it is modif ied that the pollutant causes changes in the soil, such as, pH reduction (neutral to acid), porosity (20%), f ield capacity (50%) and organic matter (50%), as well as an increase in salinity (without saline to saline) and densities (10%), it is also increased that the concentrations of Pb, Zn, Ni increase. Na, Fe and V and Ca and K were reduced. Both treatments reduce salinity, but natural attenuation shows better results than cation exchange, mainly in pH, f ield capacity and textures, but with higher concentrations of sodium with respect to the witness in both cases, the metals are below the regulatory limit before and after the treatment, but when compared with control soils a level of increase in V and Pb is noted, because the area is immersed in oil activities, it is advisable to carry out long-term bioaccumulation studies.

KEYWORDSIn 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 A species. 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 resolutionalternating least squares and program stability quotients from absorbance data (SQUAD), which showed an excellent correspondence. pKa PLS PCR MCR-ALS Spectrophotometry Chemometric strategies

totales del petróleo intemperizados en suelos y sedimentos (Biodegradation modeling of sludge bioreactors of total petroleum hydrocarbons weathering in soil and sediments)