The complexity of assessing the irrigation performance of a solid-set sprinkler irrigation system implies analyzing factors of the sprinkler features, the spacing among sprinklers, the evaluation heights, the meteorological variables and the crop. In this research, a number of solid-set experiments with impact sprinklers were evaluated with different operating conditions and a number of models of irrigation uniformity (CUC) and losses due to drift and wind (WDEL) were assessed at different catch-can heights. Statistical analysis and predictive models were performed for each variable analyzed. The results showed that ND 5035 and SEN 4023 impact sprinklers that presented the lowest variability in water distributions patterns based on the standard deviations of the irrigation depth collected in the catch can (0.85 mm/h). These sprinklers had demonstrated the best CUC values (mean of 86%) with low WDEL averages (lower than 9%). Regarding the CUC analysis, there was a statistically significant difference in measuring the irrigation uniformity from 1 to 2 m catch-can height based on the analysis of 396 solid-set experiments of different research works. Future research could be focused on more experimental conditions analyzing the effects of the irrigation on the crop agronomic development and its yield.

The aim was to evaluate the effect of high temperature during the pollination stage on the grain corn yield in the Comarca Lagunera. The study was carried out in the spring 2023 growing season. Three corn hybrids (P3274W, H-383 and PATRIOTA) were evaluated under a subsurface drip irrigation system. The experiment was arranged as a randomized complete blocks design with three replicates. During crop development, extreme temperatures (40 °C) occurred during pollination for 11 days, starting at 74 and ending at 84 days after sowing (DAS). Due to the above, grain yields were low since they ranged between 0.76 and 2.5 t ha-1, which represented a reduction of 83 to 95% in the expected grain yield in corn.

The HortSyst model is a new discrete-time model to describe the dynamics of photothermal time (PTT), dry matter production (DMP), N uptake (Nup), leaf area index (LAI) and rate of transpiration (ETc) of greenhouse crops, it has 13 parameters. The model assumes that crops do not have water and nutrient limitations. The input variables of the model are hourly measurements of air temperature, relative humidity, and the integral of solar radiation. Two experiments were carried out in a greenhouse, with hydroponic tomato cv. "CID F1" at a density of 3.5 plants m-2, autumn-winter and spring-summer cycle, in Chapingo, Mexico. The first experiment was transplanted on August 21, 2015 and the second experiment on April 24, 2016. A weather station was installed inside the greenhouses, temperature and relative humidity were measured with a model S-TMB-M006 sensor and radiation global sensor S-LIB-M003. The objective of this research is to compare two growth models for tomato in greenhouses. According to the adjustment of its predictions against the measurements it can be of help in the supply water and nitrogen.