Santos Rafael D, Boote Kenneth J, Sollenberger Lynn E, Neves Andre L A, Pereira Luiz G R, Scherer Carolina B, Gonçalves Lucio C
Embrapa Semi-Arid, Petrolina, Brazil.
Department of Agronomy, University of Florida, Gainesville, FL, United States.
Front Plant Sci. 2017 Dec 8;8:2074. doi: 10.3389/fpls.2017.02074. eCollection 2017.
Forage production is primarily limited by weather conditions under dryland production systems in Brazilian semi-arid regions, therefore sowing at the appropriate time is critical. The objectives of this study were to evaluate the CSM-CERES-Pearl Millet model from the DSSAT software suite for its ability to simulate growth, development, and forage accumulation of pearl millet [ (L.) R.] at three Brazilian semi-arid locations, and to use the model to study the impact of different sowing dates on pearl millet performance for forage. Four pearl millet cultivars were grown during the 2011 rainy season in field experiments conducted at three Brazilian semi-arid locations, under rainfed conditions. The genetic coefficients of the four pearl millet cultivars were calibrated for the model, and the model performance was evaluated with experimental data. The model was run for 14 sowing dates using long-term historical weather data from three locations, to determine the optimum sowing window. Results showed that performance of the model was satisfactory as indicated by accurate simulation of crop phenology and forage accumulation against measured data. The optimum sowing window varied among locations depending on rainfall patterns, although showing the same trend for cultivars within the site. The best sowing windows were from 15 April to 15 May for the Bom Conselho location; 12 April to 02 May for Nossa Senhora da Gloria; and 17 April to 25 May for Sao Bento do Una. The model can be used as a tool to evaluate the effect of sowing date on forage pearl millet performance in Brazilian semi-arid conditions.
在巴西半干旱地区的旱地生产系统中,饲料产量主要受天气条件限制,因此适时播种至关重要。本研究的目的是评估DSSAT软件套件中的CSM-CERES-珍珠粟模型在巴西三个半干旱地点模拟珍珠粟[(L.)R.]生长、发育和饲料积累的能力,并使用该模型研究不同播种日期对珍珠粟饲料性能的影响。在2011年雨季,于巴西三个半干旱地点进行了田间试验,在雨养条件下种植了四个珍珠粟品种。对该模型校准了四个珍珠粟品种的遗传系数,并利用实验数据评估了模型性能。使用来自三个地点的长期历史气象数据,针对14个播种日期运行该模型,以确定最佳播种窗口。结果表明,该模型的性能令人满意,作物物候和饲料积累的模拟结果与实测数据相符。最佳播种窗口因地点而异,取决于降雨模式,尽管同一地点内的品种呈现相同趋势。博姆孔塞卢地点的最佳播种窗口为4月15日至5月15日;诺萨-塞尼奥拉-达-格洛里亚为4月12日至5月2日;圣本托-杜-乌纳为4月17日至5月25日。该模型可作为评估巴西半干旱条件下播种日期对珍珠粟饲料性能影响的工具。