Evaluation of DSSAT CROPGRO model on growth and yield of pigeonpea cultivars under different fertigation levels

Q4 Immunology and Microbiology
R. Jeyajothi, S. Pazhanivelan, M. Saravana Kumar, N. Vinothini, A. Indhushree, S. Ramadass, S. Marimuthu
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Abstract

Crop modelling can make it easier for researchers to comprehend and describe experimental results and pinpoint yield disparities. In this competition, the impact of pigeonpea growth and yield under various fertigation levels was examined using the Decision Support Systems for Agrotechnology Transfer 4.6 (DSSAT) and CROPGRO pigeonpea models. Under drip fertigated levels, the cultivars received various nutrient doses. The pigeonpea model developed by DSSAT-CROPGRO successfully simulated measured pigeonpea grain yield. The field trials took place in Coimbatore at the millet breeding facility of the Tamil Nadu Agricultural University. The study ran the GLUE coefficient estimator to estimate the cultivar coefficients until it had a good match between the predicted and observed seed yield. The accuracy of the model was measured by calculating its R-squared, RMSE, NRMSE, and Agreement percentage. According to model simulation and field measurements, drip fertigation at 125% RDF via WSF + Azophosmet and foliar spray of 1% PPFM resulted in the highest seed output of 1875 kg ha-1(V1F5) over both years. The increase in seed yield with drip fertigation at 125% RDF via WSF + Azophosmet and foliar spray of 1% PPFM (V1F5) was 8.0 - 11.0% when compared to drip fertigation at 100% RDF via WSF + Azophosmet and foliar spray of 1% PPFM (V1F4)12.9 - 16.1 % compared to drip fertigation at 100% RDF through WSF; and 68.0 - 74.3 % compared to conventional fertilizer. It was indicated that the DSSAT v.4.6 can be a helpful tool for determining and forecasting pigeonpea growth yield if it is appropriately calibrated. Simulation models substantially facilitated maximizing crop growth and generating management advice.
DSSAT CROPGRO模型对不同施肥水平下鸽豆品种生长及产量的评价
作物模型可以使研究人员更容易理解和描述实验结果,并查明产量差异。在本次竞赛中,利用DSSAT和CROPGRO鸽豆模型研究了不同施肥水平下鸽豆生长和产量的影响。在滴灌施肥水平下,品种接受不同的营养剂量。利用DSSAT-CROPGRO软件建立的鸽子豆模型成功地模拟了鸽子豆实测值。田间试验在哥印拜陀的泰米尔纳德邦农业大学的谷子育种设施进行。本研究利用GLUE系数估计器对品种系数进行估计,直至预测产量与实测值吻合。通过计算模型的r平方、RMSE、NRMSE和一致性百分比来衡量模型的准确性。根据模型模拟和田间测量,通过WSF + Azophosmet滴灌施肥125% RDF和叶面喷施1% PPFM,两年的最高种子产量为1875 kg ha-1(V1F5)。经WSF + Azophosmet滴施125% RDF和叶面喷施1% PPFM (V1F5)的种子产量比经WSF + Azophosmet滴施100% RDF和叶面喷施1% PPFM (V1F4)12.9 ~ 16.1%经WSF滴施100% RDF的种子产量增加8.0 ~ 11.0%;与常规肥料相比,提高68.0 ~ 74.3%。结果表明,如果DSSAT v.4.6进行适当的校准,可以成为确定和预测鸽豆生长产量的有用工具。模拟模型极大地促进了作物生长最大化和产生管理建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Applied and Natural Science
Journal of Applied and Natural Science Immunology and Microbiology-Immunology and Microbiology (all)
CiteScore
0.80
自引率
0.00%
发文量
168
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