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Relationship between Weather Variables and the Corynespora Leaf Spot Disease in Soybean
Author(s) -
G. Amith,
H. Venkatesh,
Shamarao Jahagirdar
Publication year - 2022
Publication title -
international journal of environment and climate change
Language(s) - English
Resource type - Journals
ISSN - 2581-8627
DOI - 10.9734/ijecc/2022/v12i830718
Subject(s) - abiotic component , kharif crop , leaf spot , context (archaeology) , biology , agriculture , crop , environmental science , toxicology , agronomy , ecology , paleontology
The present investigation on weather and diseases relationships in soybean to establish forewarning procedures for timely preventive measures was conducted at the Main Agricultural Research Station (MARS), University of Agricultural Sciences, Dharwad during kharif 2017. Due to changing climatic scenario, biotic and abiotic threats are more prominent. It is well known that the biotic stress factors like insect pests and diseases are affected by abiotic factors. Further, the severity and degree of virulence of diseases over a geographical area is dependent on weather factors. Hence, in this context, there is need to study the role of weather parameters in diseases. In this endeavour, the present study has been undertaken with a new concept called lead-time concept for plant disease forecasting helps controlling early before they reach to economic injury level (EIL), and reducing cost of cultivation in use of low use of pesticides and insecticide. Corynespora leaf spot (CLS) is a disease of soybean, which infects mainly to leaves. The weather data was collected from the MARS Dharwad observatory and micrometeorological data collected in crop field and they are collected at three days interval. The Correlation coefficients between disease grade of Corynespora Leaf Spot and 29 weather variables were presented in the data show that the disease grade ratings were positively correlated, with r =0.69 for PRHT (X14), r = 0.69 for PRHM (X17), r = 0.69 for PRHB (X20), and r = 0.28 for PRHO (X26). And remining were negative correlated. Hence, the weather plays an important role in the disease incidence and development. 

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