Present experiment was conducted at College of Horticulture, Bengaluru (KA) during year 2017–18 to study the cultural, morphological and biochemical variations among the isolates of the pathogen Alternaria solani, the causal agent of early blight disease in tomato. The results revealed variation among the isolates collected from different regions of Karnataka state, India with regard to the colony characteristics viz., colony colour, mycelial growth pattern, margin of the colony and zonations whereas the maximum mycelial growth in terms of diameter (90 mm) was observed in the isolates Bagalkot (BaBG) and Chikkamagaluru (CMH) on Czapek’s (Dox) agar medium while the least growth (36.33) was noticed in Bidar (BiHH) isolate. The isolate could grow better on Czapek’s (Dox) agar medium as among the 3 media tested Czapek’s (Dox) agar medium produced maximum growth of 80.70 mm and the least growth (63.70 mm) was noticed in V-8 juice agar. The morphological studies revealed that all the conidia of various isolates varied in length (25.07–42.90 µm), breadth (10.53–21.52 µm) and number of horizontal septa (2–7), longitudinal septa (0–4). Biochemical studies among the isolates revealed significant variation in their enzyme activities. The peroxidase activity was more in Chikamagaluru (CMH) isolate (81.80 Unit g-1 FW) least activity was found in Bidar (BiHH) isolate 11.78 Unit g-1 FW whereas the esterase activity was more Bengaluru (BYC) isolate (69.01 Unit g-1 FW) least activity was found in Bagalkot (BaBG) isolate 11.78 Unit g-1 FW. Existence of variation among the isolates of Alternaria solani evident from the results obtained.

Computational grids are becoming increasingly vital in organizations with ever growing IT infrastructure and the need to increase the productivity of the computing infrastructure by ensuring optimal throughput for their computational jobs. Key to computational grids in the load balancer and job scheduler that is involved in decision making about when and which node to basically use to execute a job/task submitted to the grid. Most of the existing grids use a load function that evaluates the existing resources on the nodes, accesses the resource requirements of the task submitted and decide whether to withhold the job in the queue or schedule it on a node where the resources are available for the job. This decision making process becomes more challenging with jobs that are long duration, I/O intensive and resource requirements vary at different times during the task execution. Most current grid engines factor in the maximum requirement as stated at the time of job submission and are not good at analyzing the variation in resource requirements based on past history of the same job execution and use the information gathered in the decision making process. In this paper, we try to analyze how we can change the load balancing function to introduce more statistical analysis of history of past jobs in the scheduling decision process thereby ensuring we do not end up in trashing situations for I/O intensive jobs while at the same time utilize the available resources as efficiently as possible.

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A study on entrepreneurial behaviour of pomegranate growing farmers in Bagalkot district of Karnataka was carried out to analyze the pomegranate growers' entrepreneurship behaviour. The study revealed that majority of the farmers had medium entrepreneurial behaviour. Further the variables viz., education, land holding, annual family income, mass media participation, extension participation and scientific orientation showed significant relationship, while remaining variables viz., age, occupation and extension contact showed non-significant relationship with entrepreneurial behaviour of pomegranate farmers.

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