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ThesisItem Open Access Models for Migration of Agricultural Labourers in Belgaum District(UAS, Dharwad, 2012) Suvarna M. Agasara; S.N. MegeriMigration is an important feature of human civilization. It reflects, human endeavour to survive in the most testing conditions both natural and manmade. There are several reasons for the migration, thus the study was carried out based on the primary data, collected from the three taluks of Belgaum district viz., Bailhongal, Chikkodi and Gokak based on highest labour force. Totally 153 samples were selected from three taluks. Tabular analysis showed that out of sample households, around 78 per cent of people migrate from Chikkodi and Gokak taluks. It also showed that more than 50 per cent individuals migrate from the family when compared with the entire family migration and the individuals belonging to the age group of 15-30 years migrate more. Correlation coefficients for the variables viz., land/capita, size of the family, education, income and caste revealed that there was significant relation between the land per capita and migration. The significant relation also existed even with family income and migration. The gravity model revealed that the people migrate more to places located near to their origin and as distance of destination increases the volume of migration decreases. Logistic regression model was fitted for the migration data of Belgaum district. It revealed that land per capita was negatively significant with the odd ratios greater than unit, by this we can interpret that lower the land per capita influenced more migration. Considering the other features viz., size of the family, it was positively significant for few villages and negative for the others with the odd ratio unit or less than unit. The positive significance indicates that the migration was influenced more as the size of the family was big and the negative significance indicates that even when the size of the family was small people migrated due to different reasons. The other aspect such as the education; the model showed that illiterates migrate more than that of literates.ThesisItem Open Access Small Area Estimation Techniques in Wheat Production - An Empirical Study(UAS, Dharwad, 2012) Najeer Ahmad D.G.; Ashalatha K.V.The study was attempted to estimate the number of farmers engaged in wheat production activities in the villages of Bagalkot and Dharwad using small area techniques . In the present study, the Bagalkot and Dharwad taluks are considered as broad area and villages in this area are considered as small area. The Bagalkot district is selected under irrigated area and Dharwad district is selected under rainfed area. From each selected district, one taluk was selected randomly, from each taluk four villages were selected and from each selected village twenty five farmers were selected randomly. The total sample size was 200 farmers. The primary data was collected from the Wheat growing farmers by personal interview method. The schedule used for collection of data included information on socio-economic status of the farmers, information on agricultural and animal husbandry activities and other farm activities undertaken by the farmers. The Analytical tools used under this research study were Small area estimation techniques which include Broad area ratio estimation (BARE) to know the percentage of farmers involved in wheat growing activity. The percentage of wheat growing farmers in Bagalkot district is more (68 per cent) than Dharwad district (57.7 per cent). Multiple regressions models to know the relationship between wheat production and different weather parameters used and also to find out the significances of the all variables. There was a significant effect between wheat production and the variables like total area under wheat crop, fertilizer consumption as well as rainfall. The estimates of wheat yield by SRSWOR sampling per unit method were used to assess the more precise estimates of wheat yield by sample survey and lastly the researcher has concluded the efficacy of the smaller areas to larger areas by different estimators and their efficiencies.ThesisItem Open Access Regional Disparity in Sericulture Development in Karnataka - A Statistical Analysis(UAS, Dharwad, 2012) Veena L.V.; P.A. KatarakiSericulture has a special place among the agro-based cottage industry of our country. Sericulture industry supported millions of rural people in our country by way of providing employment. Sericulture in India has turned out to be a highly remunerative enterprise with minimum capital base and yielding reasonably good returns vis-à-vis other enterprises. The development of sericulture and the factors affecting regional disparity with respect to sericultural development studied in detail using ten important sericultural development indicators. The study pertained to Karnataka state and its component districts. The secondary data were collected for a period of 20 years depending on the availability of the data starting from 1990-1991 to 2009-2010, pertaining to ten important sericultural development indicators like area under mulberry, egg production, cocoon production, raw silk production, number of mulberry producing villages, number of markets, number of grainage centers, number of chalky centers, number of reeling centers, rainfall. The Mahalanobis D2 analysis (distance statistics) was employed to know the extent of regional disparity, factors affecting regional disparity and to classify the districts based on sericulture development. The results revealed that districts were highly despair with respect to sericultural development and the area under mulberry production, egg production, cocoon production and raw silk production were the major factors affecting regional disparity followed by number of mulberry producing villages, number of grainage centers and number of markets. All the 20 districts were grouped into three clusters and the three clusters were categorized into three groups as highly developed, moderately developed and low developed using the sericultural development index formed. With this optimistic scenario, priority should be given to major development indicators and there is need to undertake developmental measures in low developed and moderately developed districts to reduce regional disparity in the state.ThesisItem Open Access Statistical Models on Poultry Egg Production(UAS, Dharwad, 2012) Mala M.; P.A. KatarakiPoultry is one of the fastest growing segments of the agro based industry in India. The behavioral trends in production, time of peak and decline as well as the persistency of lay can also be studied from such egg production curves, keeping all these in view the present study was envisaged. Experimental data were collected from Manjunatha poultry farm at Davanagere. MLR models was used for 2 strains viz. Suguna and Babcock hen age, hen house consumption, temperature and vaccination were used as an independent variables for different age groups viz. 19-29, 30-45, 46-60 and 61-72 weeks and dependent variable as egg production. Results of the study revealed that age showed significant effect for egg production and egg weight. As age increases there was increased in egg weight indicates that age contributing significantly as compared to other variable. The linear and nonlinear models viz., quadratic, cubic, logarithmic, power, exponential models were tried. Results of the study revealed that polynomial models viz., fourth (for Suguna) and fifth (for Babcock) degree polynomial models were of much informative in explaining the relation between age of the hen and egg production. Two way ANOVA for two factor was used and the factors are strains viz., strain1, strain2 for 12 season (months) for egg production and also for age groups. Result revealed that strain1 was less in production as compared to strain2, interaction of strains and seasons were showed non-significance. August was high yielding month followed by June followed by September and July. For egg production 2nd followed by 3rd age groups were showed highest yield in egg production, that showed average of 5 to 6 eggs in numbers per bird per week in that farm.ThesisItem Open Access Development of Decision Supporting System for Fertilizer Recommendation for Selected Zones of Karnataka(UAS, Dharwad, 2012) Vishwajith K.P.; A.R.S. BhatNutrient Management plays a vital role in increasing crop production, soil upgradation and healthy crop and as such is of great importance. Taking these things into consideration a Decision Support System on fertilizer recommendation in Crops (DSS) for selected zones of Karnataka has been designed and developed at University of Agricultural Sciences, Dharwad. DSS is developed using Visual Basic 06 as a plat form. DSS is a console application and provides decision to farmers on amount of fertilizer application in crops. The system will have great importance in agriculture as Experts are not always available to answer farmer’s queries. The system is based on STCR approach. The procedure provides a scientific basis for balanced fertilization and balance between applied nutrients and nutrients available in the soil. The system has been developed total for 6 zones viz., Zone-3, Zone-4, Zone-5, Zone-6, Zone-7 and Zone-8. Herein, the user gets an advice for fertilizer application based on the information provided for soil test values and targeted yield. The testing and validation of the system for the zone-8 was done. The developed decision support system is onpar with the farmers field condition in both the crops i.e., for maize and chilli. If the farmer applied the fertilizer according to the developed decision support system, they will get the same yield with a standard deviation of 7 quintals/ha and C.V 12.75 per cent in maize and standard deviation of 2 quintals/ha and C.V 11.53% in chilli. Fertilizer is not only the factor influencing the yield of a crop. There are many factor which influence like management, rainfall, quantity and method of irrigation, soil fertility, temperature, etc. Therefore, if we apply the fertilizer according to these DSS or in any other approach the yield may vary.ThesisItem Open Access Statistical Models for Insect Pests in Sorghum [Sorghum bicolor (L.) Moench](UAS, Dharwad, 2012) Pavana Kumars S.T.; Y.N. HavaldarSorghum [Sorghum bicolor (L.) Moench] is one of the most important cereal crop in the world, because of its adaptation to a wide range of ecological conditions. It is the fifth major cereal crop of world following wheat, rice, maize and barley in terms of production and utilization. Sorghum adversely affected by shoot fly in northern Karnataka, in considering the importance of the pest present study was envisaged. Experimental data were collected from AICSIP at Dharwad and meteorological data were collected from meteorological observatory of Main Agricultural Research Station of Dharwad. The linear and nonlinear models viz., quadratic, cubic, logarithmic, inverse, exponential models were tried. Results of the study revealed that simple linear and nonlinear models viz., cubic and quadratic models were of much informative in explaining the relation between dates of sowing and the shoot fly. The Correlation analysis was carried out to know the relationship existing between weather parameters and shoot fly. In kharif season high rainfall was negatively correlated with the egg population and high temperature (Max and Min), high relative humidity (RH1 and RH2) were positively correlated with the egg as well as dead heart of shoot fly in both the season. But the minimum temperature less than 20°C and low humidity had negative correlation during Rabi season. By considering the significance of the weather parameters stepwise regression analysis was carried out, these models were having high R square value. During kharif season in the year 2003 models for 14 days after emergence of the crop produced high R square value 0.986 and During rabi season model in 2005 for 14 days after emergence of the crop produced high R square value of 0.999 and hence it was best fit, in explaining the effect of weather parameters in the development of shoot fly.ThesisItem Open Access Statistical Analysis of Export of Grapes From India(UAS, Dharwad, 2012) Vijayakumar S.; S.N. MegeriThe export data on fresh and dried grapes (raisins) were collected for the period of 1987-2011. The parameters of logistic distribution and logistic model were estimated using the total export values for the period of 1987-2011, and future export values were predicted. The country wise export data was available from 1995-2011. The data was used to find out the transitional probability matrix and for comparing different growth models. The important statistical tools used for the purpose were, logistic distribution using method of moments, logistic model using Levenberg- Marquardt method, Markov-chain analysis, Co-efficient of Variation, monomolecular model, exponential model and Gompertz model. The logistic distribution and model were fitted and the year wise estimated values had calculated, further to test for the presence of autocorrelation in the residuals, the Durbin–Watson statistic was used. The transitional probability matrix showed, the Netherlands was one of the most reliable importer of Indian fresh grapes whereas, Egypt Arab Republic was most reliable importer of raisins. The results for both, fresh and dried grapes, ‘other country’ showed more reliable importer. The results from the instability analysis, UK were stable importer and Saudi Arabia is the most unstable importer of Indian fresh grapes. Instability analysis found highly unstable for exporting raisins from India. The results found in comparing growth models, Gompertz model showed better fit to the Netherlands, Bangladesh and Saudi Arabia, as the MSE value showed less. For United Arab Emirates and UK, monomolecular model was better fit. For ‘other country’ category, exponential model shows better fit model. For raisins, Gompertz model showed better fit as MSE is less among the other two models and this has taken to estimate the predicted values for five years in advance.ThesisItem Open Access Application of Small Area Estimation Technique in Estimating the Number of Households Engaged in Income Generating Farm Activities(UAS, Dharwad, 2011) Santhosh N. Shanbhag; A.R.S. BhatIn the present study the Coastal Area under Arabian Sea is considered as broad area and villages in the Coastal Area are considered as small area. The sampling units (non-farm households) are selected by the method of two stage samplings. Villages are considered as first stage units and farming households are considered as second stage units. The coastal area was separated into two parts namely Udupi and Dakshina Kannada. Small area estimates were obtained for the villages by fitting regression based models considering each of the above as broad area. Small area estimates were also obtained considering all these areas together as one broad area. The estimates were obtained by fitting Poisson regression model and Logistic regression models. For fitting Poisson and Logistic regression models, the explanatory variables used are family size, education level of household (number of years of schooling), total land holding (in acres), total annual non-farm income (in thousand rupees). The fitted models are then used to estimate the number of households engaged in non-farm activities for non-sampled villages in the broad area. The present investigation indicates that Logistic estimator and Composite estimator are the best small area estimators. The information on household’s farm activities at village level has a greater importance to the government and NGO’s in policy formulation, fund allocation for socio-economic development of a region and for establishment of small scale industries at the village level.ThesisItem Open Access Use of Statistical Tools in Organic Farming Practices in Northern Zones of Karnataka(UAS, Dharwad, 2011) Manjunatha G.R.; Ashalatha K.V.The study was attempted to estimate the crop preferences under organic farming, to asses the effect of number of years of organic farming practices and to test the efficacy of organic farming on crop productivity. Multistage purposive random sampling was employed for the selection of sample respondents. Wherein three zones viz, Hilly zone, Northern Transitional zones and northern dry zones were selected from Northern Karnataka. From each zones one district viz., Uttar Kannada, Dharwad and Bijapur were selected based on the maximum area under organic farming. From each district one taluk and two villages were chosen. The total sample size of 150 comprising 75 each of organic and inorganic farmers was chosen. Organic soil sample of about 27 were collected from respective zones. Optimal scaling technique, ANOVA technique and Regression models were employed for analysis of data. The results of correspondence analysis revealed a stronger association between crops and zones and organic farming practices and selected zones. While ANOVA technique signaled a significant influence of years of farming and zonal organic practices on various soil indicators viz., organic carbon, nitrogen, phosphorus and potassium. Exponential growth in productivity level was observed over the period of practicing organic farming in selected zones. The significant difference was noticed on yield levels of performing organic and inorganic farming for different crops in selected zones of Karnataka.