Josefina Barrera-Cortés

TEMPERATURE AND CONCENTRATION EFFECTS OF OSMOTIC MEDIA ON OD PROFILES OF SWEET POTATO CUBES

A study was conducted to evaluate the effects of temperature and sucrose osmotic solution concentrations on osmotic dehydration profiles of sweet potato (Ipomea batata) cubes (3.5 cm sides). Two temperatures (26 and 50°C) and three concentrations (30:100, 50:100 and 70:100 w/w) were studied for various exposition times, up to 168 hours. Main influence was observed at higher temperature (50°C) due the fact that water loss (WL) and solids gains (SG) are faster and more intense. At 26°C no appreciable change in solids concentration was observed at distances deeper than 0.5 cm from the cubes surfaces even at 168 hours. At 50°C all the layers are affected even at shorter times (8 hours).

Neural prediction of hydrocarbon degradation profiles developed in a biopile

Abstract The biochemical and physical nature of the degradation process in biopile systems is very complex and difficult to describe analytically, thus, neural network modeling and simulation can be of great help. Predictive feedforward neural models (FFNMs) have been commonly used to capture the dynamic phenomena of biological systems by a learning process, but the large number of input/output variables and the vast connectivity of the neural network makes it very time consuming. This paper proposes the use of a recurrent neural network model (RNNM) to predict biodegradation profiles of hydrocarbons contained in an aged polluted soil. The proposed multi-input multi-output RNNM has eight inputs, five outputs, 13 neurons in the hidden layer, and global and local feedbacks. The weight update learning algorithm is a version of dynamic backpropagation. The approximation error for the last epoch of learning is below 1.25% and the total time of learning is about 101 epochs. The learning process is applied to the kinetics of residual hydrocarbons, pH, carbon dioxide, oxygen consumption and moisture obtained with different operational conditions of air flow, and temperature; the kinetics are analyzed at four heights of the columns. The low learning error approximation makes the RNNM interesting to facilitate the study of complex biological processes in a short time.

Reducing the microcapsule diameter by micro-emulsion to improve the insecticidal activity of Bacillus thuringiensis encapsulated formulations

ABSTRACT The emulsion/internal gelation method is highly effective to produce microcapsules of Bacillus thuringiensis (Bt) in a short time; however, it has the limitation to produce microcapsules within a wide range of diameters (1–1000 µm). The aim of this study was to reduce the range of small microcapsule diameters by using a water/corn-oil (W/CO) micro-emulsion as the dispersing medium and the mixture Tween 80–Span 80 as the surfactant. It involved the development of the W/CO micro-emulsion and the determination of the suitable agitation time to disperse the gelling medium (sodium alginate) through the micro-emulsion. A micro-emulsion formulation that allowed reduction of the microcapsule diameter was composed of 82% corn oil, 12% alginate solution and 6% surfactant mixture Tween80–Span80 (31:69). Evaluation of four dispersing times showed that 45 min was suitable to produce 75% of microcapsules of an average diameter of 3.1 ± 1 µm containing the spore–protein complex (SPC) produced by Bt. Bioassays carried out at low concentrations of microencapsulated formulations of cry proteins allowed determination of how its insecticidal effect increased if the range of microcapsule diameters was reduced in the range 1–9 µm. Furthermore, the SPC formulation in alginate microcapsules showed high resistance to extreme irradiation (2.9 ± 0.5 × 108 erg) of a long wavelength (365 nm), which made the microencapsulated formulation profitable and of high yield since repeated applications of the biopesticide during the same harvest period may not be necessary.

A soft sensor based on online biomass measurements for the glucose estimation and control of fed-batch cultures of Bacillus thuringiensis

On bioprocess engineering, experimental measurements are always a costly part of the modeling effort; therefore, there is a constant need to develop cheaper, simpler, and more efficient methodologies to exploit the information available. The aim of the present work was to develop a soft sensor with the capacity to perform reliable substrate predictions and control in microbial cultures of the fed-batch type, using mainly microbial growth data. This objective was achieved using dielectric spectroscopy technology for online monitoring of microbial growth and hybrid neural networks for online prediction of substrate concentration. The glucose estimator was integrated to a fuzzy logic controller to control the substrate concentration in a fed-batch experiment. Dielectric spectroscopy is a technology sensitive to the air volume fraction in the culture media and the turbulence generated by the agitation; however, the introduction of a polynomial function for the calibration of the permittivity signal allowed biomass estimations with an approximation error of 2%. The methodology presented in this work was successfully implemented for the glucose prediction and control of a fed-batch culture of Bacillus thuringiensis with an approximation error of 6%.

Encapsulation of Trichoderma harzianum conidia as a method of conidia preservation at room temperature and propagation in submerged culture

ABSTRACT The objective of the present work was to develop a method for the preservation of T. harzianum conidia at room temperature and the immobilised conidia propagation in submerged culture. This was accomplished by immobilising the strain in sodium alginate capsules (white capsules) and subsequently propagating them in a column bubble reactor (green capsules). Three capsule diameters were tested (micro, medium and large capsules), which were produced by emulsion internal gelation and dripping methods. Tested variables were the immobilised conidia propagation in submerged culture for free conidia production, the immobilised conidia viability throughout the time (two years), the resistance of the encapsulated conidia to the UV irradiation of short and long wavelength, and the antagonistic effect of the encapsulated T. harzianum against four phytopathogenic fungi. It was found that the medium capsules (1.5 ± 0.3 mm) favoured the massive production of released conidia in submerged culture and that the higher the density of conidia per capsule, the greater the protection against the ultraviolet irradiation. Regarding the conidia preservation in calcium alginate, a viability loss of around 30% was observed two years after storage at environmental temperature in both white and green capsules; along the two years that the viability of conidia was analyzed, the purity of the formulation was corroborated. The results presented here show the efficacy of the green and white capsules for T. harzianum preservation at room temperature for a long period of time.

Remediation of Hydrocarbon-Contaminated Soil by Washing with Novel Chemically Modified Humic Substances

In this work, humic (HA) and fulvic acid (FA) were chemically modified by esterification and etherification with alkanes under microwave (MW) irradiation to improve their surfactant properties for the remediation of total petroleum hydrocarbons (TPHs)-contaminated soil. Humic acid and FA were evaluated as surfactant for the remediation of soil by means of washing an aged highly TPH-contaminated soil (50,000 mg TPH kg) sampled from a Mexican petrochemical area. The efficiency of chemical modification of HA and FA was increased and accelerated under MW irradiation with respect to that of conventional heating. Results showed that modified HA and FA were able to considerably reduce the contamination of TPH-polluted soils. The best results were obtained with HA modified by esterification with -dodecanol and FA modified with -decanol, which increased the hydrocarbon removal by 24 and 18%, respectively, with respect to amounts removed by the unmodified derivatives.