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

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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.

Marin, FR, Jones, JW, Singles, A., Royce, F., Assad, E.D., Pellegrino, G.Q., Justino, F., 2012. Climate change impacts on sugarcane attainable yield in southern Brazil. Climatic Change 117, 227-239. Tomasella, J, Hodnett, 2004. Pedotransfer functions for tropical soils. In: Developments in Soil Science, pp. 415-429. Inman-Bamber, N.G., 1991. A growth model for sugarcane based on a simple carbon balance and the CERES-Maize water balance. S. Afr. J. Plant Soil 8, 93–99. 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.

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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. 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. Data from the Atlas is available for use under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Figure 1. Comparison of simulated and observed phenology (left) and grain yields (right) for rice (top), soybean (middle), and maize (bottom).The solid red line represents y = x and the dashed red lines represents ± 20% deviation from the y -x line.RMSE = mean square root of error.The phenological stages of rice, soybean and maize were based on the scales ofCounce et al.(2000), Fehr and Caviness (1977), and Ritchie et al. (1993), respectively .

Duarte, Y.C.N., Sentelhas, P.C., 2019. NASA / POWER and DailyGridded weather datasets — how good they are for estimating maize yields in Brazil ? Int. J. Biometeorol. doi: 10.1007/s00484-019-01810-1

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.

Department-level data on crop harvested area and average yields for each crop was retrieved from the IBGE – Brazilian Institute of Geography and Statistic). Statistics from the most recent six crop growing seasons (harvest years: 2012-2017) were used to calculate crop area and average yields. Radambrasil Project. 1973–1986. Levantamento de recursos naturais. Vol. 1–34. Inst. Brasileiro Geogr. Estatıstica, Rio de Janeiro, Brazil.Heinemann, A. B., Ramirez-Villegas, J., Rebolledo, M. C., Neto, G. M. F. C., & Castro, A. P., 2019. Upland rice breeding led to increased drought sensitivity in Brazil. Field Crops Research 231, 57-67. For the simulations, rooting depth was set at 2 m (sugarcane), 0.8 m (soybean and maize), and 0.4 m (upland rice) to reflect the limitation to root growth in deep horizons due to low pH and differences among crop species in rooting patterns and/or tolerance to low pH (Pivetta et al., 2011, Battisti et al., 2017; Franchini et al., 2017). Calibrated pedo-transference functions for tropical soils were used to derive soil water limits (Tomasella et al., 2000). Field capacity was set at -10 kPa following the observations for tropical soils by Reichardt (1998) and Tomasella and Hodnett (2004). Soil properties were not considered for simulation of yield potential for irrigated rice.

Management practices for each RWS buffer zone were retrieved from local EMBRAPA agronomists and other experts. Requested information include: dominant crop rotations and proportion of each of them to the total harvested area, sowing window, dominant cultivar name and maturity, and optimal plant population density (CONAB, 2019). The provided data were subsequently corroborated by other local and national experts. 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.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). Allen, R.G., Luis, S.P., RAES, D., Smith, M., 1998. FAO Irrigation and Drainage Paper No.56. Crop Evapotranspiration, Rome, Italy 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. Franchini, J.C., Antonio, A., Junior, B., Debiasi, H., Nepomuceno, A.L., 2017. Root growth of soybean cultivars under different water availability conditions Crescimento radicular de cultivares de soja em campo em diferentes disponibilidades hídricas. Ciências Agrárias, Londrina, 38, 715–724. 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.