Red clover (Trifolium pratense L.) seedling density in mixed pastures as predictor of annual yield

ZARZA, R.; REBUFFO, M.; LA MANNA, A.; BALZARINI, M.

FIELD CROPS RESEARCH

ELSEVIER SCIENCE BV

Lugar: Amsterdam; Año: 2020

0378-4290

Biomass predictive models can be useful tools to design management strategies for mixed pastures of red clover (Trifolium pratense) with either grasses or herbs in intensive grazing systems. This paper proposes mixed regression models to predict the annual yield of two mixtures based on red clover seedling density (CSD) and environmental effects (low, intermediate, high-yield environments). Two mixtures of red clover with either chicory (Cichorium intybus) or prairie grass (Bromus catharticus) were sown in Uruguay in a multi-environment experiment with six sowing rates to generate varying levels of species seedling densities. The CSD was recorded at 3, 7 and 12 weeks after sowing (WS). Yield prediction models in the initial establishment year (Y1) and second-year (Y2) were fitted with CSD at the three count times. CSD increased proportionally to the sowing rates in all environments. The CSD, even at 3 WS, provided a good prediction of expected annual yield (error mean