scispace - formally typeset
V

Valentin Picasso

Researcher at University of Wisconsin-Madison

Publications -  48
Citations -  1123

Valentin Picasso is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Forage & Perennial plant. The author has an hindex of 14, co-authored 43 publications receiving 819 citations. Previous affiliations of Valentin Picasso include Iowa State University & Wageningen University and Research Centre.

Papers
More filters
Journal ArticleDOI

Crop Species Diversity Affects Productivity and Weed Suppression in Perennial Polycultures under Two Management Strategies

TL;DR: On average, increasing species richness in perennial herbaceous polycultures increased productivity and weed suppression, but well-adapted species produced high biomass yield regardless of richness.
Journal ArticleDOI

Land use change and ecosystem service provision in Pampas and Campos grasslands of southern South America

TL;DR: Moher et al. as discussed by the authors synthesised 242 references from peer-reviewed and grey literature published between 1945 and mid-2015 and analysed secondary data to examine the evidence on the ecosystem services provided by this grassland biodiversity hotspot and the way they are affected by land use changes and their drivers.
Journal ArticleDOI

Diverse perennial crop mixtures sustain higher productivity over time based on ecological complementarity.

TL;DR: It is concluded that choosing a single well-adapted species for maximizing productivity may not be the best alternative over the long term and that high levels of species diversity should be included in the design of productive and ecologically sound agricultural systems.
Journal ArticleDOI

Sustainability of meat production beyond carbon footprint: a synthesis of case studies from grazing systems in Uruguay

TL;DR: This analysis of fifteen beef grazing systems in Uruguay quantifies the range of variation of carbon footprint, and the trade-offs with other relevant environmental variables, using a partial life cycle assessment (LCA) methodology.