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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:CSM-CERES-MAIZ模型在尼泊尔省赤征亚热带条件下玉米产量的季节性和多分型预测

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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:亚热带Terai和尼泊尔内部Terai的平均玉米产量非常小于其约5.0吨/公顷的潜在收益率,其逐步报告了变化的气候情景。裁剪系统模型(CSM) - 通过资源和环境综合(CERES)估计 - 嵌入在农业技术转移(DSSAT)Ver中的决策支持系统下。通过生长四种多样化玉米基因型VIZ,从现场实验数据集评估4.2。全季OPV(Rampur Composite),优质蛋白质玉米(Posilo Makai-1),混合动力(Gaurav)和Pop玉米(Pool-12)在2009 - 10年度(10月1日和11月1日)的三个不同的种植日下(9月1日和11月1日)楚尔校区,奇特湾。该实验中的两个因子因子随机完全块设计(RCBD),具有三种复制,含有低土壤(0.49%)和K(148kg / ha)和培养基(148kg / ha)和培养基( 16.3千克/公顷)状态。从M-STAT C软件分析了从现场实验获得的辅助和产量数据,并记录了Gaurav杂种在9月1日植物(5.86 T / HA)下产生了显着更高的产量,然后是Posilo Makai 1(5.55 T / HA),rampur复合(5.1t / ha)和池12(3.45 t / ha)。此外,通过使用平均基于温度的累积热单元系统,还计算了各种玉米基因型的热利用效率,并且发现只有rampur复合材料的稳定产量,用于所有种植日,其余基因型仅适用于早期种植。通过使用9月1日玉米基因型使用9月1日玉米基因型来完成模型校准,同时通过使用剩余的治疗来预测不同玉米基因型的生长和产量来实现验证。 2006年至07年,在生产玉米产量,比2009 - 10年度分别为rampur复合,Posilo Makai-1,Gaurav和Pool-12的标准玉米产量为13,18,23%和7%。此外,研究了来自2009 - 10年基本线2020,2007)所倡导的不同气候变化情景,以模拟9月1日培养日期的多样化玉米基因型的生长和产量性能,发现会有在冬季玉米玉米产量增加2020个气候变化场景,造成剧烈产量损失将在2050年至2080个情景下,在目前的农艺管理方案水平下,并敦促新的气候变化适应和减缓生产技术。

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