Appropriate quantification of nitrogen availability in soil is the prerequisite for proper implementation of soil-test based fertilizer-application scheme. But, most of the soil testing laboratories use soil organic carbon level to suggest fertilizer dose for nitrogen and hence, the present study has been initiated to develop prediction equation for estimating available nitrogen content of soil from its organic carbon content to facilitate the implementation of soil test based on nitrogen fertilizer application in mulberry garden. A total of 300 soil samples comprising 100 locations from each of Malda, Murshidabad and Birbhum districts have been analyzed for estimation of organic carbon as well as corresponding available nitrogen content. Analytical data was further subjected to regression analysis and district wise working equations were developed to predict nitrogen availability in soil from its organic carbon content. All the equations registered quite higher R 2 values, significant at 1% level and thus, considered viable to predict nitrogen availability in soil. Moreover, comparison between predicted and observed values of available nitrogen content in some selected soil samples of each of the districts was done to ascertain accuracy of these equations. The accuracy was found reasonable in terms of ±10% variation and thus, the developed equations are competent enough to predict nitrogen availability in soil under mulberry vegetation of the districts under investigation.

Brown leaf rust (BLR) caused by Peridiopsora mori is one of the major foliar diseases of mulberry (Morus sp.) in the subtropical hills of eastern India. The disease appeared in first week of August and continued up to September with maximum severity in second and third week of September. The disease symptoms appeared at atmospheric temperature (27.00-20.078C), relative humidity (92.14-82.43%), rainfall (11.20 cm) and rainy days (7) of the preceding week. Disease severity (450 PDI) was observed at temperature (26.29-19.298C), relative humidity (94.14-80.14%), rainfall (4.12 cm) and number of rainy days (2-3 days). Apparent rate of infection was found high at temperature (27.00-19.838C), relative humidity (94.67-85.00%), rainfall (4.6 cm) and rainy days (2) of the preceding week. The correlation coefficient between disease severity and average meteorological factors of the preceding 7 days revealed that BLR disease severity showed significant negative correlation with minimum temperature. It was also revealed that contribution of maximum and minimum temperature 42.23% and 35.21%, maximum and minimum relative humidity (RH) 11.23% and 10.69% and rainfall and number of rainy days 0.11% and 0.50%, respectively towards development of BLR disease severity. Multiple regression analysis revealed that average of maximum and minimum temperatures and minimum RH of preceding 7 days were found to maximally influence BLR disease severity.