干旱区生态环境知识资源中心(Arid): Predictive Modeling for Chickpea Blight (Ascochyta rabiei) Occurrence in the Semi-Arid Zone Using Meteorological Data from Faisalabad, Pakistan

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	Predictive Modeling for Chickpea Blight (Ascochyta rabiei) Occurrence in the Semi-Arid Zone Using Meteorological Data from Faisalabad, Pakistan
	Ahmad, Salman 1; Khan, Muhammad Aslam 2; Ahmad, Irfan 3; Ashraf, Ejaz 1; Aatif, Hafiz Muhammad 4; Ali, Amjad 1; Safdar, Muhammad Ehsan 1; Anjum, Muhammad Zohaib 1; Raza, Waqas 1
通讯作者	Ahmad, Salman
来源期刊	PHILIPPINE AGRICULTURAL SCIENTIST
ISSN	0031-7454
出版年	2019
卷号	102 期号:4 页码:330-339
英文摘要	Chickpea blight is the most destructive disease in the semi-arid zone of Punjab and is mainly controlled through fungicides. However, in this area, the use of fungicides is excessive and non-judicious which could be rationalized through the use of a predictive model based on meteorological variables. The aim of the current research was to develop a disease predictive model of chickpea blight based on temperatures (maximum and minimum), rainfall, relative humidity (RH), and wind speed. Relationship of meteorological variables with disease severity was determined through correlation analysis, and stepwise regression was used to develop the model. For this purpose, 2 yr (2011-12) data of meteorological variables and chickpea blight severity was used. A significant correlation was found between all environmental variables and blight severity. A model based on weekly meteorological variables fit the data well (R-2 = 0.82). Predictions of the model were evaluated on two statistical indices, root mean square error (RMSE) and error (%), which were <= +/- 20, indicating that the model was good. The model was validated with 5 yr (2006-10) independent data set. Homogeneity of the regression equations of the two models, 2 yr (2011-12) and 5 yr (2006-10), showed that they validated each other. Scatter plots showed that blight severity was high at maximum (20-24 degrees C) and minimum (12-14 degrees C) temperatures, 65-70% RH, 5-6 mm rainfall and 5-6.5 km/h wind speed). The chickpea blight model developed during this study is the first meteorological variable model in the semi-arid zone of Punjab and will help to make the predictions of chickpea blight well before the occurrence of the disease; thus, the model can make early an prediction of the time of fungicide application, lessen the use of fungicides, curtail input cost of farmers, and help to mitigate environmental pollution.
英文关键词	chickpea blight meteorological model predictive modeling
类型	Article
语种	英语
国家	Pakistan
收录类别	SCI-E
WOS记录号	WOS:000501348700006
WOS关键词	DIDYMELLA-RABIEI ; RELATIVE-HUMIDITY ; INFECTION ; RESISTANCE ; TEMPERATURE ; POPULATIONS ; TELEOMORPH ; DIVERSITY ; WHEAT ; RUST
WOS类目	Agriculture, Multidisciplinary
WOS研究方向	Agriculture
EI主题词	2019-12-01
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/311058
作者单位	1.Univ Sargodha, Coll Agr, Sargodha 40100, Pakistan; 2.Univ Agr Faisalabad, Dept Plant Pathol, Faisalabad 38000, Pakistan; 3.Univ Agr Faisalabad, Dept Forestry & Range Management, Faisalabad 38000, Pakistan; 4.Bahauddin Zakariya Univ, Layyah Campus, Multan 60000, Pakistan
推荐引用方式 GB/T 7714	Ahmad, Salman,Khan, Muhammad Aslam,Ahmad, Irfan,et al. Predictive Modeling for Chickpea Blight (Ascochyta rabiei) Occurrence in the Semi-Arid Zone Using Meteorological Data from Faisalabad, Pakistan[J],2019,102(4):330-339.
APA	Ahmad, Salman.,Khan, Muhammad Aslam.,Ahmad, Irfan.,Ashraf, Ejaz.,Aatif, Hafiz Muhammad.,...&Raza, Waqas.(2019).Predictive Modeling for Chickpea Blight (Ascochyta rabiei) Occurrence in the Semi-Arid Zone Using Meteorological Data from Faisalabad, Pakistan.PHILIPPINE AGRICULTURAL SCIENTIST,102(4),330-339.
MLA	Ahmad, Salman,et al."Predictive Modeling for Chickpea Blight (Ascochyta rabiei) Occurrence in the Semi-Arid Zone Using Meteorological Data from Faisalabad, Pakistan".PHILIPPINE AGRICULTURAL SCIENTIST 102.4(2019):330-339.