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 (1963-2009), 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.
Highlights
Livestock plays a crucial economic, social and environmental role in Brazil
Cluster analysis successfully divided Brazilian weather stations into four groups, according to herbage accumulation rate mean (HAR; kg DM ha-1 day-1) and standard deviation, and the Principal Components Analysis (PCA) allowed the characterization of the groups
For all the soil water holding capacities (SWHCs), three principal components were required to explain more than 80% of the variance and to characterize the groups properly
Summary
Livestock plays a crucial economic, social and environmental role in Brazil It was responsible for more than 30% of the agribusiness Gross Domestic Production (GDP) and about 6.6% of national GDP in 2017 (CEPEA 2018). Seasonal forage production is related to variations in products availability to industry (e.g. milk and beef) and in prices to consumers (Viana et al 2010, Gaio et al 2011). In this context, farmers are negatively affected by the seasonality of forage production, but the whole market chain
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