Although growing mango is a profitable and viable activity in Mexico, its production is limited by the performance of the labor force. Therefore, in the present work a device to vibrate mango branches was designed and built. The mechanism consists of a 1 HP electric motor with a rotation frequency of 1,745 rev•min-1, which moves two eccentric masses with a range of 32 to 19 mm. To attach to the tree branches, a pneumatic cylinder 50 mm diameter x 305 mm career is used. The theoretical production of the equipment is 96 boxes of picked fruit per day. The dimensions of the machine in carrying position are: 4.5 x 1.8 x 2.0 m (length x width x height).

The difficulty of obtaining daily global radiation data has led to the development of models for its estimation, like the Hargreaves equation that uses maximum and minimum temperature weather variables, and the Prescott model, derived from Angström, that requires data such as sunshine hours and Angot value. Artificial neural network models are efficient tools for processing in parallel multiple input variables and estimating non-linear variables with considerable accuracy. The aim of this work was to compare the daily global radiation measured at the Santa Rosa 1 AC weather sta¬tion in irrigation district 075 in los Mochis, Sinaloa State, Mexico, with that estimated by the Hargreaves, calibrated Hargreaves, Angström-Prescott, calibrated Angström-Prescott and the feedforward backpropagation and radial basis function artificial neural network models. The Angström-Prescott model with coefficients a and b calibrated with R2 of 0.82 and RMSE of 2.33, together with the backpropagation algorithm multilayer in 3 scenarios (input variables of Julian day, minimum and maximum temperature, vapour mean pressure, relative humidity, wind speed, sunshine hours, Angot value) with R2 of 0.87 and RMSE of 1.97, were the best estimators of daily global radiation.

This research was conducted in a Plant Science Department greenhouse at the Universidad Autónoma Chapingo, located in Chapingo, Mexico State. We evaluated three irrigation frequencies (3, 4 and 5 irrigations per day), which were applied using an automated drip irrigation system at three depths (7, 14 and 25 mL•day-1) controlled by drippers; tezontle was used as substrate. A factorial arrangement of two factors, each at three levels, was used in a completely randomized design, and Steiner universal solution (90 mL•day-1) was used to provide nutrition for the production of Calla lily cv Reno. Crop behavior was analyzed in terms of number, height and development time of flowers and leaves. The crop was established from September 2010 to January 2011, and data taking was weekly from four to fifteen weeks after planting the rhizomes, when the number of developed leaves and flowers were quantified and subsequently the height of both was measured. With the data obtained, we proceeded to analyze the effect of both factors, which determined that the factor affecting the number, height and development time for Calla lily cv Reno flowers is irrigation frequency. With four and five daily irrigations, a greater number of flowers develops than with three.

A probiotic fermented milk containing Lactobacillus acidophilus, a lactic acid bacterium which can be implanted in the gastrointestinal tract, was produced. The lactic fermentation kinetic of the acidophilus milk was compared with that of the yoghurt; the corresponding curves were drawn eva¬luating pH and titratable acidity. To know the sensorial quality of both fermented milks and their difference, a control difference test and a sensorial profile were performed; to do this, eight people were trained to evaluate nine attributes of these milks. In addition, an acceptance test with potential consumers was performed. The results showed that the acidophilus milk followed a different kinetic from that of the yoghurt with respect to the processing time. Sensorially, both plain products (without sweetener) did not have any significant differences. Acidophilus milk was better accepted.