Correlação de séries históricas produtivas de grãos em sistemas de integração lavoura-pecuária com fenômenos ENOS e disponibilidade hídrica

• Autor(a) principal: Leão, Ricardo Costa
• Data de Publicação: 2022
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca de teses e dissertações da Universidade de Passo Fundo (BDTD UPF)
• Texto Completo: http://tede.upf.br:8080/jspui/handle/tede/2264
• topic: Grãos - Cultivo; Soja - Cultivo; Milho - Cultivo; Balanço hidrológico; CIENCIAS AGRARIAS::AGRONOMIA

The agricultural production of corn and soybeans in Rio Grande do Sul is characterized by the great spatial and temporal variability of grain yields, and its main cause is the fluctuation in water availability for crops. This fact is mainly due to the irregular distribution of rainfall, which is one of the outstanding characteristics of this meteorological element in the State of Rio Grande do Sul. The objective of this study was to evaluate different crop-livestock integration systems (CLS) regarding the potential to mitigate the effects of water deficits on soybean and corn grain yield between the 1996/97 and 2017/18 harvests. Temporal trends were removed from the data series and the daily water balance was calculated for each of the systems and crops. Subsequently, nine water variables were tested by parametric and non-parametric coefficients, regarding the correlation with corn and soybean grain yield. The crops were also classified by the phases of the El Niño-Southern Oscillation (ENSO) phenomenon and the deviations in grain yield from the trend-free mean were quantified. The CLS did not show differences in the grain yield of the two crops in response to the effects of the ENSO phenomenon phases. The ILP systems were not able to mitigate the effects of ENSO events on yield variability, compared to the exclusive grain production system. The CLS also did not differ from each other in terms of the correlations between grain yield and water variables, both by the linear coefficient and by the non-parametric coefficient. However, the water variables that present correlations with grain yield vary according to the prevailing meteorological phenomenon during crop development, especially those classified as La Niña and El Niño. This result indicates that when analyzing long historical series, one must take into account the prevailing meteorological conditions during the stages of crop development, in order to reduce the probability of not capturing important correlations between water variables and grain yield.