Small 'I Love Brazil' Adult's Cotton Crop Top (CO00076211)

Product Information

While only one crop per year is grown in the eastern part of the country, most producers grow two crops (1-year soybean-maize sequence called ‘safrinha') in the western region (Mato Grosso, Mato Grosso do Sul, Tocantins, Goiás, and Parana). Van Wart, J., Grassini, P., Yang, H.S., Claessens, L., Jarvis, A., Cassman, K.G., 2015 Creating long-term weather data from the thin air for crop simulation modelling. Agric. For. Meteoro. 209-210, 45-58. Table 1. Average (2015-2019) total production, harvested area, and average yield of soybean, maize, sugarcane and rice in Brazil. Source: CONAB. A weighted average yield was calculated based on the average yield reported for the municipalities located within the buffer zone and the relative contribution of each department to the total crop harvested area in the buffer zone. Reported Yw (or Yp for irrigated rice) in the Atlas are long-term averages. Yield gap (Yg) was calculated as the difference between long-term average Yw (rainfed crops) or Yp (irrigated crops) and average (2012-2017) farmer yield. Including more years before 2012 in the calculation of average actual yield would have led to a biased estimate of average actual yield due to a strong technology trend in Brazil. In the case of buffers where both safra and safrinha were common maize, average maize yield was estimated by averaging their respective average yields, weighting by the proportion of maize area under each crop system. The 1-3 dominant soil series were identified for each RWS buffer based on data from the Radambrasil project (see Cooper et al., 2005). In each buffer, dominant soils were selected to cover at least 30%. Each selected soil had at least 10% of the area. Selected soils were verified by local experts and modified as needed to ensure that simulated soils represented the most common agricultural soils.

To portray most dominant practices in sugarcane farms, 3 main cycles of ratoon crops of 12-month duration each were simulated at each location: early (April-15), mid (Aug-15), and late planting (Nov 15). Tomasella, J, Hodnett, MG, Rossato, L, 2000. Pedotransfer functions for the estimation of soil water retention in Brazilian soils. Soil Sci Soc Am J 69, 649-652. Radambrasil Project. 1973–1986. Levantamento de recursos naturais. Vol. 1–34. Inst. Brasileiro Geogr. Estatıstica, Rio de Janeiro, Brazil. Marin, F.R.; Thorburn, P.; Nassif, D.S.P.; Costa, L.G. 2015. Sugarcane model intercomparison: Structural differences and uncertainties under current and potential future climates. Environmental Modelling & Software, 72, 372-386.For each crop-RWS combination, each crop sequence x soil type combination was simulated, and then weighted by their relative proportion to retrieve an average Yw at the level of the RWS buffer zone (or Yp in the case of irrigated rice). Simulations assumed no limitations to crop growth by nutrients and no incidence of biotic stresses such as weeds, insect pests, and pathogens. Bouman, B.A.M.; Kropff, M.J.; Tuong, T.P.; Wopereis, M.C.S.; Ten Berge, H.F.M.; Laar van, H.H, 2004. Van. Oryza 2000: modeling lowland rice. Manila, Philippines: International Rice Research Institute (IRRI). 245 pp. Battisti, R.B., Sentelhas, P.C., 2017. Improvement of soybean resilience to drought through deep root systems in Brazil. Agron. J. 109, 1612–1622. Pivetta, L.A., G. Castoldi, G. Santos, and C.A. Rosolem. 2011. Soybean root growth and activity as affected by the production system. Pesquisa Agropecu. Bras. 46, 1547–1554. Most part of Brazil has a favorable climate for rainfed crop production, with total annual rainfall that ranges, across the major producing regions, from 700 mm (northeast region) to 2100 mm (south, southeast and west region). Precipitation is well distributed during the year in the south (Rio Grande do Sul, Santa Catarina, and Parana), while it exhibits strong seasonality in the rest of the producing regions, with wet summers and dry winters.

Aramburu Merlos, F., Monzon, J.P., Mercau, J.L., Taboada, M., Andrade, F., Hall, A.J., Jobbagy, E., Cassman, K.G., Grassini, P. 2015. Potential for crop production increase in Argentina through closure of existing yield gaps. Field Crops Research 184, 145-154.

Please enter your order number:

Marin, F. R. Jones, J. W. Royce, F. 2011. Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane. Agron. J. 103, 297-303. Cooper, M., Mendes, L.M.S., Silva, W.L.C., Sparovek, G., 2005. A national soil profile database for Brazil available to international scientists. Soil Sci. Soc. Am. J. 69, 649-652.