Weather stations often have incomplete records for a certain period, due to the absence or replacement of the operator, recording device failures or operational negligence, thereby limiting the carrying out of agro-climatic and hydrological studies. Therefore, the aim of this study was to compare the deductive rational (DR), normal ratio (NR) and US National Weather Service’s inverse square distance (ISD) methods, and then select the best for estimating missing daily precipitation and maximum and minimum temperature records of the weather stations located in San Luis Potosi, Mexico. Six stations were analyzed, of which 15 % of the precipitation (1,489 of 9,862) and 25 % of the maximum and minimum temperature (1,489 of 5,844) information was eliminated. Missing data were generated with the ISD, DR and NR methods, and their evaluation was performed using the RMSE and Willmott index of agreement, d, statistical indices, which indicated that the ISD method has the Willmott index close to one and the mean standard error close to zero; consequently, it was the one used to estimate the missing data from 108 weather stations in San Luis Potosí.

   Cooling is an important practice that extends the shelf life of fruit and vegetable products. The arrangement of these products for cooling is similar to a macroporous bed, where a cold fluid circulates between packed particles. The study of these systems is essential to estimate characteristic operation variables so that they can be suitably designed. The aim of this study was to evaluate the use of the Ergun equation in estimating the pressure drop in a forced-air cooling unit. As study geometry, a pipe 30.0 cm long and 15.5 cm in diameter, which was filled with Styrofoam spheres and subjected to experimental evaluation of pressure drop (ΔPexp) with various sphere diameters and mass air flux, was used. Void fraction, temperature and air density and viscosity were evaluated in each condition. The pressure drop was calculated with the Ergun equation (ΔPest) and the parameters of this model were calibrated through the MatLab® lsqnonlin.m subroutine, with which the adequate estimation of the packed bed was obtained. Based on geometry of packed objects, the results are applicable to fruit such as apples, oranges, peaches, lemons and plums, among others.

Corn is the basic input of the Mexican diet. It is grown in one-third of the country, with Sinaloa being the leading producer of irrigated corn in Mexico, mainly by surface irrigation. It has become increasingly urgent to optimize the use of water due to competition from non-agricultural sectors for water resources, as well as the high spatial and temporal variability of annual volumes available for irrigation, . An alternative in dry years is to apply regulated deficit irrigation. Therefore, the aim of this study was to evaluate this technique in surface-irrigated corn, with three deficit treatments and a control, to which the water requirement demanded by the crop was applied. The water deficit levels applied were: 10, 20, 30 and 0 %, for T1, T2, T3 and C (control), respectively. An irrigation scheduling system based on the concept of degree days was used. The effect of water deficit levels was evaluated in terms of application efficiency, water productivity and yield. The treatment with the highest deficit generated the best application efficiency and water productivity. Yields were statistically similar in the treatments and the control. Results indicated that using the deficit irrigation technique is a viable option in critical water availability conditions, by having a reduced effect on yields obtained in relation to conventional methods.