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Application of csm- ceres-maize model for seasonal and multi-decadal predictions of maize yield in under subtropical condition of Chitwan, Nepal

机译:cscerceres-maize模型在尼泊尔奇旺亚热带条件下的季节和多年代玉米产量预报中的应用

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The average maize yield of 2.5 t/ha in sub-tropical terai and inner terai of Nepal has been very less than its potential yield of about 5.0 t/ha, for which changing climatic scenarios have been reported the critical factors. Cropping system Model (CSM)-Crop Estimation through Resource and Environment Synthesis (CERES)-Maize, embedded under Decision Support System for Agro-technology Transfer (DSSAT) ver. 4.2 was evaluated from a datasets of field experimentation by growing four diverse maize genotypes viz. full season OPV (Rampur Composite), Quality Protein Maize (Posilo Makai-1), Hybrid (Gaurav) and Pop corn (Pool-12) under three different planting dates (September 1, October 1 and November 1) in 2009-10 at Rampur Campus, Chitwan. The experiment was laid out in two factor factorial randomized complete block design (RCBD) with three replications in slightly acidic (pH 6.7) sandy loam soil having low soil available N( 0.49%) and K (148 kg/ha) and medium P (16.3 kg/ha) status. The ancillary and yield data obtaining from field experiment was analyzed from the M-Stat C software and recorded that Gaurav hybrid produced significantly higher yield under September 1 planting (5.86 t/ha) followed by Posilo Makai 1 (5.55 t/ha), Rampur Composite (5.1t/ha) and the least with Pool-12 (3.45 t/ha). Further, the heat use efficiency of diverse maize genotypes were also calculated by using the mean temperature based accumulative heat unit system and found the stable yields only with Rampur Composite for all planting dates and the rest genotypes were suitable only to the early winter plantings. Model calibration was done by using September 1 planting date for all 4 maize genotypes while validation was accomplished by using the remaining treatments for predicting growth and yield of different maize genotypes. The year 2006- 07 was found 13, 18, 23 and 7% higher in producing the maize yield than the standard year 2009-10 for Rampur Composite, Posilo Makai-1, Gaurav and Pool-12, respectively. Further, the different climate change scenarios as advocated by IPCC (2007) for 2020, 2050 and 2080 from base line of 2009-10 was studied to simulate the growth and yield performance of diverse maize genotypes with September 1 planting date and found that there would be increment in winter maize yield up to 2020 scenario of climate change and the drastic yield loss would be on 2050 to 2080 scenarios under the present levels of agronomic management options and urged for the new climate change adaptation and mitigation production technologies.
机译:尼泊尔亚热带和内地的玉米平均产量为2.5吨/公顷,远低于其潜在的产量约5.0吨/公顷,据报道,气候变化是关键因素。种植系统模型(CSM)-通过资源和环境综合评估(CERES)-玉米,嵌入在农业技术转让决策支持系统(DSSAT)中。通过种植四种玉米基因型,从田间试验数据集中评估4.2。在2009-10年度的三个不同播种日期(9月1日,10月1日和11月1日)进行全季OPV(Rampur复合材料),优质蛋白玉米(Posilo Makai-1),杂种(Gaurav)和爆米花(Pool-12)。奇旺拉姆布尔校园。该实验采用两因子分解随机完全区组设计(RCBD),在弱酸性(pH 6.7)砂壤土中进行了三组重复试验,土壤有效氮含量低(0.49%)和钾含量(148 kg / ha),中等磷含量( 16.3千克/公顷)状态。使用M-Stat C软件分析了从田间试验获得的辅助数据和产量数据,并记录了Gaurav杂交种在9月1日播种(5.86吨/公顷)之后,其次是Posilo Makai 1(5.55吨/公顷),Rampur,产生了更高的产量。复合(5.1t / ha),最少的是Pool-12(3.45 t / ha)。此外,还通过使用基于平均温度的累积热量单位系​​统计算了不同基因型的玉米的热利用效率,发现仅Rampur Composite在所有播种日期均具有稳定的产量,其余基因型仅适用于初冬。通过使用所有4个玉米基因型的9月1日播种日期进行模型校准,同时通过使用其余处理来预测不同玉米基因型的生长和产量来完成验证。发现2006-07年度的玉米产量分别比Rampur Composite,Posilo Makai-1,Gaurav和Pool-12的标准年度2009-10高13、18、23和7%。此外,研究了IPCC(2007)倡导的2009-10年基准的2020年,2050年和2080年的不同气候变化情景,以模拟9月1日播种日期不同玉米基因型的生长和产量表现,发现到2020年气候变化情景下冬季玉米单产增加,在目前的农艺管理方案水平下,大幅度的单产损失将发生在2050至2080年情景下,并敦促采用新的气候变化适应和减缓生产技术。

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