Crop models can aid the synthesis and application of knowledge, planning of experiments and forecasting in agricultural systems. Few studies have reviewed the uses and applications of these models for tropical forages. The purpose of this study was to review the information available in this scientific area, highlighting the main models, their applications and limitations. Several empirical models have been developed to predict the growth and biomass accumulation of tropical forages, especially for the genera Cynodon, Paspalum, Panicum and Brachiaria. Their application, however, is often location or region specific. The adaptation of mechanistic models to accurately predict biomass accumulation in tropical grasses is still limited. Recent advances have been made on the plot‐scale and farm‐scale process‐based models ALMANAC, CROPGRO Perennial Forage and agricultural production systems simulator (APSIM), with promising results. In addition, global‐scale process‐based models, such as the Century Agroecosystem Model and the Orchidee Grassland Management Model, have been tested for tropical grassland areas. A greater number of region‐specific calibrations of empirical models can enhance their use, and improved databases and model parameterizations for a wide range of tropical grasses will enable the continuous improvement of mechanistic models.

Two cultivars of Brachiaria brizantha (Hochst ex. A. Rich) Stapf. (Syn. Urochloa) were evaluated for their adaptation to water deficit and the stress response mechanisms in a greenhouse experiment. The experimental design was in completely randomized blocks with a 2 × 2 × 4 factorial arrangement. The Marandu and BRS Piatã cultivars were evaluated under two water availability conditions, with or without water restriction. The harvests were carried out 0, 7, 14 and 28 days after the start of water restriction. For both cultivars, the water deficit stress caused a reduction in shoot biomass and leaf area and an increase in the percentage of roots in the deeper soil layers. The B. brizantha cv. Marandu reached critical levels of leaf water potential in a shorter period of water restriction than did the B. brizantha cv. BRS Piatã. The osmoregulation and deepening of the root system are mechanisms of adaptation to water stress observed in both Marandu and BRS Piatã cultivars. Besides that, the Marandu cultivar also increases its leaf senescence and, consequentially, decreases its leaf area, as a response to water deficit

The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry‑field conditions in São Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree‑days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in São Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree‑days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.

Climate, soil and management are the main drives for growth and production of tropical pastures. Thus, a better understanding of the effects of these factors and their interactions under climate conditions is required to obtain effective management options. Here, we used data from two field trials to research on climate and management interactions on the production seasonality of Panicum maximum Jacq. Treatments included four sampling times (250, 500, 750, and 1000 °C accumulated) during eight regrowth period, under irrigated and rainfed conditions and, cuts were made to simulate grazing intensity. All treatments were arranged in a completely randomized block design with four replications. At each sampling time, basal tillers were sampled to observe meristematic differentiation and were linked with the respective daylength. Soil moisture was determined, and the water availability index (WAI) was calculated. The dry matter production (DMP) was taken and relative productivity was calculated. Soil moisture was the key seasonal drive in spring-summer and the WAI could be used to adjust the maximum production for that season. The major drive for DMP in fall was the daylength, which was found at 11.81 h. For all seasons, DMP correlated better with the residues in early regrowth phase (r = 0.82 and p < 0.0001) and with degree-days at final regrowth phase (r = 0.73 p < 0.01). Applying these critical values to management guidelines should make Guinea grass DMP more efficient on tropical farms.