Irrigation is identified as a decisive factor in Indian agriculture due to high variability and inadequacy of rainfall. Irrigation is essential for successful agriculture particularly in the area, where rainfall is inadequate uncertain, and unpredictable. These areas are prone to drought and famine condition due to partial failure and delayed arrival or early withdrawal of monsoon. Importance of irrigation has substantially increased after the adoption of High yielding varieties in developing countries. Irrigation is basic determinants of Agriculture because its inadequacies are the most powerful constraints on increase of Agricultural production. In the study region the variation of an annual rainfall from year to year is fairly large. The rainfall is irregular and uncertain in the Study region, here agriculture is gamble with monsoon. If rainfall is scare it results into crop failure. For the assure agriculture production irrigation is most important factor. There fore attempt is made here to examine the impact of irrigation on agriculture productivity in Solapur district.

Sugar industry occupies an important position on the industrial map of the state of Maharashtra. These factories played a major role in the socio-economic development of rural areas in Maharashtra. The growth of various urban centers is helping to solve the problem of unemployment by providing employment in the growing industries and business. For the present investigation Damaji co-operative Sugar Factory is selected. Mangalwedha is located in drought prone area but Bhima river flows in these region. The Bhīma river catchment are favorable for sugar cultivation. Remaining drought area is large than irrigation area, drought area sugar factory become key factor of development and employment. In this investigation primary and secondary data are used. Such type of study represents real the role of co-operative sugar factory in rural of Mangalwedha and helps to planners, agricultural scientists and research scholars.

Grain drying is a vital unit operation in many processing plants. An undesirable change associated with this operation is shrinkage of dried product which results in decreased quality. Recently many attempts have been made to decrease the shrinkage of food stuff during drying. Microwave-assisted fluidized bed drying has particularly been proposed as a potentially effective method. In the present study, at each drying operating condition, the volume of shelled corn was calculated by measuring the three principal characteristic dimensions. The variation of the ratio of mean diameter of the kernel to its initial mean diameter was investigated for different operating conditions. It has been shown that employing microwave in fluidized bed drying reduces the shrinkage of particles considerably. Also, in this study, Artificial Neural Networks (ANN) analysis was employed to predict the extent of shelled corn shrinkage. In the construction of the network, three independent variables: microwave heat source, drying air temperature and moisture content were chosen as the input parameters and shrinkage of dried sample was set as the output parameter (dependent variable). The ANN model with 5 neurons was selected for studying the influence of transfer functions and training algorithms. It has been observed that back-propagation networks with logsig transfer function and trainlm algorithm were the most appropriate ANN configuration for predicting shrinkage. Results from the experiments and modeling showed good Agreement. In order to test the ANN model the random errors were within an acceptable range of ±5% with a correlation coefficient (R2) of 98%.