Climate risk and seasonal forage production of Marandu palisadegrass in Brazil

Abstract

This study aimed to characterize Brachiaria brizantha cv. Marandu seasonal production (seasonality) and its variation (climate risk) yearlong throughout Brazil. Data from weather stations in Brazil (1963Brazil ( -2009, were associated with an empirical herbage accumulation rate (HAR; kg DM ha -1 day -1 ) model which considers growing degree-days adjusted by a drought attenuation index. Simulations were performed under 20, 40, 60 and 100 mm of soil water holding capacities (SWHCs). HAR's means and standard deviations were calculated for the seasons of the year. Thereafter, cluster analysis and calculations were performed to gather similar weather stations and characterize seasonality and climate risk indexes. Cluster analysis resulted in four Groups per SWHC. The north of Brazil (Group 1) presented the lowest seasonality and climate risk indexes and low need for precautions. In the middle west (Group 2), the seasonality index ranged from medium-high to high. Winter and Summer presented the lowest and highest production, respectively. In the south of Brazil, some regions in the southeast and northeast (Group 3), Winter presented the lowest production and highest climate risk index, probably due to low temperatures. The northeast (Group 4) presented a seasonality index that ranged from medium-high to very high and low productions.

Production and Price Cycles in Beef Cattle in Rondônia State, Brazilian Amazon

“…Considering that edaphoclimatic factors have a great impact on forage production throughout the seasons, although each region has a greater or lesser intensity of these factors [21].…”

Improving the CROPGRO Perennial Forage Model for simulating growth and biomass partitioning of guineagrass

“…In this study we were also able to improve parameterization of the seasonality of production, for example, cool temperature and daylength effects, based on the Tanzânia experiment. This is important for the parameterization of guineagrass as it is usually grown year‐round in the tropics, but the decrease in forage supply to feed the animals during the winter often has to be complemented with other feeding sources (Brunetti et al., 2020). Thus, the model sensitivity to temperature and daylength is important for planning of pasture‐based systems and for model use considering diverse locations within warm‐season non‐freezing climates.…”

“…In practice, regrowth duration varies considerably despite recommendations to set optimum harvest time to avoid excess stem accumulation (Carnevalli et al., 2006; Congio et al., 2018). The forage availability for the animals varies throughout the year and between years as a consequence of edaphoclimatic conditions (Brunetti et al., 2020) and stocking rate. Adjusting the stocking rate is not an easy task and, therefore, variations in the harvest frequency occur and, thus, the pasture may be harvested during several phenological stages.…”

Productive and nutritive traits of Piatã palisadegrass after thinning the forest component of a silvopastoral system in southeastern Brazil

“…3) and the greatest water competition between the forage species and the trees in the tree line resulted in a difference in pre-grazing live forage mass between SPS1 and INT (Tian et al ., 2017; Glatzle et al ., 2021). The low precipitation in this season is typical of the experimental location (Alvares et al ., 2013) and diminishes forage production even in full sun systems (Brunetti et al ., 2020). Thus, it remains uncertain whether the differences in live forage mass between the SPS sites and INT were caused by water stress, as observed by Pezzopane et al .…”