Development of agro-climatic grape yield model with future prospective

IF 1.6 4区 农林科学 Q2 AGRONOMY
S. J. Kadbhane, V. Manekar
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引用次数: 3

Abstract

Agriculture sector is most vulnerable to climate change. To predict the crop yield in accordance with the changing climate is a need of hour than choice. To know the climate in advance is crucial for grape growing farmers and grape export agencies for its better planning and security of grape industries from climate change perspective. In the present study, the Agro-Climatic Grape Yield (ACGY) model is developed on monthly scale climatic parameters using correlation, significance and multi-regression analysis approach. The developed model is statistically tested for its predictive ability. The discrepancy ratio, the standard deviation of discrepancy ratio, mean percentage error and standard deviation of mean percentage error for the developed model is obtained as 1.03, 0.19, 0.03% and 0.19 respectively. Sensitivity analysis is carried out for the developed ACGY model using the parametric sensitivity method. In order to know the grape yield for future using developed ACGY model, climate scenarios are generated under Canadian Earth System Model (CanESM2) for three emissions Representative Concentration Pathways (RCP) as RCP2.6, RCP4.5, and RCP8.5. Model response variability is carried out to understand the variation of grape yield. It is observed that grape yield is showing adverse variation with the increase in minimum temperature in January and November months, and precipitation in August and November months. Whereas, minimum temperature in April and sum of monthly mean evapotranspiration showing accordance effect on the grape yield. It is recommended the use of ACGY model for grape yield estimations applicable for the present and future climate of the study area based on the predictive capability of developed model.
农业气候葡萄产量模型的开发与展望
农业部门最容易受到气候变化的影响。根据气候变化预测作物产量是一项紧迫的任务。提前了解气候变化对葡萄种植户和葡萄出口机构从气候变化的角度更好地规划和保障葡萄产业至关重要。本文采用相关性、显著性和多元回归分析方法,建立了月尺度气候参数的农业气候葡萄产量(ACGY)模型。该模型的预测能力得到了统计检验。所得模型的差异比、差异比标准差、平均百分比误差和平均百分比误差标准差分别为1.03、0.19、0.03%和0.19。采用参数灵敏度法对所建立的ACGY模型进行了灵敏度分析。在加拿大地球系统模型(CanESM2)下,以RCP2.6、RCP4.5和RCP8.5三种典型排放浓度路径(RCP)为研究对象,对未来葡萄产量进行了预测。通过模型响应变率来了解葡萄产量的变化。随着1月和11月最低气温的增加,8月和11月降水量的增加,葡萄产量呈负向变化。4月最低气温与月平均蒸散量对葡萄产量的影响呈一致。建议在已有模型预测能力的基础上,采用ACGY模型对研究区当前和未来气候条件下的葡萄产量进行估算。
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
CiteScore
2.10
自引率
8.30%
发文量
6
期刊介绍: Among the areas of specific interest of the journal there are: ecophysiology; phenology; plant growth, quality and quantity of production; plant pathology; entomology; welfare conditions of livestocks; soil physics and hydrology; micrometeorology; modeling, simulation and forecasting; remote sensing; territorial planning; geographical information systems and spatialization techniques; instrumentation to measure physical and biological quantities; data validation techniques, agroclimatology; agriculture scientific dissemination; support services for farmers.
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