Fábio R. Marin

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Reliable predictions of sugarcane response to climate change are necessary to plan adaptation strategies. The objective of this study was to assess the use of global climate models (GCMs) and a crop simulation model for predicting climate change impacts on sugarcane production. The Canegro model was used to simulate growth and development of sugarcane crops(More)
In some of the traditional areas growing sugarcane and in most of the expanding regions in Brazil, water deficit stress is a limiting factor and irrigation is usually needed to assure economically viable sugarcane yields. This research evaluated the water requirements of a drip-irrigated second ratoon sugarcane crop based on three different spatial scales:(More)
Historically, trash has been burnt in Brazil. Recently, increasingly crops are being harvested green with trash retailed as blanket (GCTB) due to environmental restrictions, and because of the trash use as a feedstock for bioenergy. The presence of a trash blanket affects sugarcane crops, by conservation of soil moisture and a potential to increase soil(More)
Sugarcane is one of the world's main carbohydrates sources. We analysed the APSIM-Sugar (AS) and DSSAT/CANEGRO (DC) models to determine their structural differences, and how these differences affect their predictions of crop growth and production. The AS model under predicted yield at the hotter sites, because the algorithm for computing the degree-days is(More)
Global climate changes are now well accepted to happen and can likely impact agriculture. Process-based dynamic crop models are able to estimate a range of crop responses to the environment and to assess the biophysical effects of future climate scenarios on crop growth and yield. They are hence scientifically accepted as a predictor of future agricultural(More)
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