DIEBACK DISEASE PREDICTIVE MODEL FOR SEXUALLY AND ASEXUALLY PROPAGATED DALBERGIA SISSOO (SHISHAM)

 

IRFAN AHMAD¹, M. ATIQ², SADAF GUL^3*, ABDUL HANNAN⁴, M.T. SIDDIQUI¹,

M. FARRAKH NAWAZ¹, M. ASIF¹ AND SALMAN AHMED⁵

 

¹Department of Forestry and Range Management, University of Agriculture, Faisalabad, Pakistan

²Department of Plant Pathology, University of Agriculture, Faisalabad, Pakistan

³Department of Botany, University of Karachi, Karachi, Pakistan

⁴Assistant Land Reclamation Officer, Directorate of Land Reclamation, Punjab, Pakistan

⁵Department of Plant Pathology, University College of Agriculture, University of Sargodha, Pakistan

^*Corresponding author’s e-mail: sadafgpk@yahoo.com

 

Abstract

 

Dieback disease is a potential threat to Dalbergia sissoo (Shisham) which is a multipurpose tree of the Indian subcontinent. Different factors have been found associated with inciting shisham dieback. Fungal pathogens have been recognized as the major causal organism but changing climate is a main threat to forest dieback. Sexually (seedlings) and asexually (cuttings) propagated shisham were inoculated with the different fungi (Fusarium solani, Botryodiplodia theobromae, Curvularia lunata and Ganoderma lucidum). As environmental factors play critical role in the development of the disease, so the present study was designed to observe the impact of rainfall, temperature, relative humidity and wind velocity on the disease and for the management of disease predictive model was developed. A significant negative correlation was observed between disease and relative humidity both for seedlings (r = - 0.97) and cuttings (r = -0.487), respectively while maximum temperature expressed significant positive correlation with seedlings and cuttings with coefficient of correlation r = 0.734 and r = 0.629, respectively. Path analysis expressed that with one unit increase in rainfall the disease would rise by 7.58 and 15.04 and for maximum temperature it was 2.47 and 5.27 units in seedlings and cuttings, respectively. Multiple regression analysis showed that coefficient of determination (R²) value was 0.62 and 0.48 for cuttings and seedlings, respectively. Normed fit index (NFI) and comparative fit index (CFI) values indicate that model is quite a good fit. Similarly comparison of observed and predicted data also validated the model for forecasting the disease.

 

Key words: Dalbergia sissoo; Dieback; Seedlings and cuttings; Environmental variables; Path model.