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. 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. Jones, J.W., Hoogenboom, G., Porter, C.H., Boote, K.J., Batchelor, W.D., Hunt, L.A., Wilkens, P.W., Singh, U., Gijsman, A.J., Ritchie, J.T., 2003. The DSSAT Cropping System Model. Eur. J. Agron. 18, 235–265. 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). Allen, R.G., Luis, S.P., RAES, D., Smith, M., 1998. FAO Irrigation and Drainage Paper No.56. Crop Evapotranspiration, Rome, Italy

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. 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. 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. 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.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. 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.

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. 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. 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.

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.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. Long-term(20 years) daily weather data were retrieved from Brazilian Institute of Meteorology (INMET) and include maximum and minimum temperature and precipitation for the period between years 1999 and 2018. Relative humidity, dew temperature, and ETo were estimated following Allen et al., (1998). Quality control and filling/correction of the weather data were performed based on the propagation technique developed by van Wart et al. (2014). In all cases, solar radiation was retrieved from NASA-POWER, which has shown good correlation with measured solar radiation (Bender and Sentelhas, 2018; Monteiro et al., 2018; Duarte et al., 2019). Measured weather data were not available in 20% of the buffers); hence, we used weather data (including all variables) from NASA-POWER. 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. 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. 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.