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University of Agricultural Sciences, Bengaluru

University of Agricultural Sciences Bangalore, a premier institution of agricultural education and research in the country, began as a small agricultural research farm in 1899 on 30 acres of land donated by Her Excellency Maharani Kempa Nanjammanni Vani Vilasa Sannidhiyavaru, the Regent of Mysore and appointed Dr. Lehmann, German Scientist to initiate research on soil crop response with a Laboratory in the Directorate of Agriculture. Later under the initiative of the Dewan of Mysore Sir M. Vishweshwaraiah, the Mysore Agriculture Residential School was established in 1913 at Hebbal which offered Licentiate in Agriculture and later offered a diploma programme in agriculture during 1920. The School was upgraded to Agriculture Collegein 1946 which offered four year degree programs in Agriculture. The Government of Mysore headed by Sri. S. Nijalingappa, the then Chief Minister, established the University of Agricultural Sciences on the pattern of Land Grant College system of USA and the University of Agricultural Sciences Act No. 22 was passed in Legislative Assembly in 1963. Dr. Zakir Hussain, the Vice President of India inaugurated the University on 21st August 1964.

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2010 - 201526
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Subject: Agricultural Statistics and Informatics × End date: 2015 × Start date: 2010 × Thesis Type: M.Sc ×
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Now showing 1 - 9 of 26
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    ThesisItemOpen Access
    STATISTICAL EVALUATION OF AGRICULTURAL DEVELOPMENT AT DISTRICT LEVEL IN KARNATAKA
    (University of Agricultural Sciences GKVK, Banglore, 2010-08-31) RAVI, SHANKAR, N; H.CHANDRA SHEKAR
    No Abstract
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    ThesisItemOpen Access
    STATISTICAL ANALYSIS OF DEVELOPMENT PATTERN IN KARNATAKA
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-11-11) RAMESH; Gowda, D. M
    There exists a variation in the level of development across nations, be it developed or developing. The development pattern is influenced by different sectors of the economy like the primary sector, secondary sector and the tertiary sector. The primary sector predominantly covers agriculture, animal husbandry, forestry etc. the secondary sector include the industry and manufacturing sector. The services sector comprises of banking, education, insurance, etc. Countries across the globe have concentrated on these three sectors in varying proportion to realize the growth potential of the economy. The primary focus of the Governments of the day is the total maximum welfare of its citizens. After independence, the Indian economy was characterized by not only stagnation but also wide regional disparities. The successive five year plans in India have focused on addressing this issue of regional disparity. The third five year plan (1961-66) document devoted a separate chapter on balanced regional development, identification of backward areas, indicators for development for different sectors and policies for the development of backward areas. Even the finance commission appointed by government of India have addressed to regional inequalities across states especially while exercising resource transfer from the center to the States.
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    ThesisItemOpen Access
    IMPACT OF CLIMATE CHANGE ON CASHEW CROP AT SELECTED LOCATIONS OF KARNATAKA –A STATISTICAL ANALYSIS
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-10-28) ANITHA, R; Gowda, D.M
    The weather data for the period 1992 – 2011 was consider to study the impact of climate change on cashew crop productivity at Puttur and Chintamani stations. The significant difference was noticed in the mean of two-decades with respect to rainfall and sunshine hours at Puttur, minimum and maximum temperature at Chintamani stations. Higher variation was found in sunshine hours(43%) at Puttur and rainfall(36%) at Chintamani. From the result of cubic trend, minimum temperature and number of rainy days shows declining trend and rainfall shows, increasing trend in both the stations. Rainfall and number of rainy days showed the significant correlation with the yield in both the stations. In stepwise-regression, the number of rainy days found to be significant on yield in both flowering and overall period at Puttur and humidity(PM) and rainy days found to be significant in flowering and overall period at Chintamani. Regression model was fitted for the significant variables to obtain the expected yield, maximum yield can be obtained when the maximum temperature is at 37 ºC and number of rainy days is 12 in overall period. During flowering period, when sunshine hours is at 8 and number of rainy days is 10 at Puttur station. In chintamani location, the expected maximum yield can be obtained at humidity(AM) is 85 percent and the number of rainy days is 14 during overall period and during flowering period, when minimum temperature is 12 ºC and humidity(AM) is 80 percent. 5.93 and 8.30 percent of variations in the mean yield was noticed for a given varying interval of climatic factors during overall and flowering period respectively at Puttur In Chintamani, 11.10 and 11.4 percent variations in the mean yield was observed for a given climatic factors during overall and flowering period.
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    ThesisItemOpen Access
    ASSESSMENT OF CROP AREA AND PRODUCTION OF MAJOR CROPS OF SEDAM TALUK OF GULBARGA USING REMOTE SENSING AND GIS
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-10-10) SHALINI, M N; Munirajappa, R
    Remote sensing is the art and science of making measurements of the earth using sensors on airplanes or satellites. These sensors collect data in the form of images and provide specialized capabilities for manipulating, analysing, and visualizing those satellite images. Remote sensed imagery is integrated within a Geographic Information System (GIS). Several methods exist for remote sensing image classification. They include supervised and unsupervised approaches. In supervised classification, the classifier is trained to identify the classes using training data set where as in an unsupervised classification, the classifier itself develops the spectral classes. For statistical comparisons of different image classification methods test imagery obtained through IRS (Indian Remote Sensing) P6 LISS-III on 22nd December, 2011 for Sedum Taluk of Gulbarga district of Karnataka state were used. Maximum likelihood classification, Mahalanobis distance classification, Minimum distance to means classification under supervised classification approach were performed for the test imagery using ERDAS imagine 9.1 version software. Accuracy assessment was found important to evaluate the final output of remote sensing. Accuracy of the classification of each data set and their classifiers were expressed as an error matrix from which overall accuracy, users accuracy, producers accuracy, mapping accuracy, F-measures, Kappa coefficients and sample variance of Kappa coefficients were estimated. The test of significance of Kappa coefficients were performed using Z-test. Pairwise comparison of Kappa coefficients of different classification methods were performed. Maximum likelihood classification was found to be the best with highest overall accuracy of 93.38 per cent for Sedum Taluk, Gulbarga district of Karnataka.
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    ThesisItemOpen Access
    STATISTICAL MODEL FOR FORECASTING ARRIVAL AND PRICE BEHAVIOR OF POTATO IN MAJOR REGULAR MARKETS OF KARNATAKA
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-09-30) PRADEEP, M; Gowda, D.M
    Potato is the most important vegetable crop in the world used for human consumption. In order to study the arrival and price behavior of potato in major regulated markets of Karnataka, eleven years data (April, 2003 to May, 2014) on monthly arrivals and prices of potato at five regulated markets viz., Bangalore, Belgaum, Chikkaballapur, Hassan and Kolar were considered for the study. The findings reveal that the arrivals and prices of potato have registered significant increase in trend for all the markets. All the markets have shown seasonal pattern in their arrivals and the current month prices was influenced by the previous month price except Bangalore being a terminal market. ARIMA model (0,1,0)×(1,1,1)12 was found to be ideal among the different forecast models fitted. This model was used to forecast the prices of potato in all the above markets for a duration of seven months through a lagged series. ARCH and GARCH models for prices of potato indicated no volatility. The values at risk and instability index were computed due to the absence of volatility. These were found to be high for Chikkaballapur market and low for Belgaum market.
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    ThesisItemOpen Access
    CROP MODELING ON AREA AND YIELD OF SUGARCANE IN SELECTED DISTRICTS OF KARNATAKA
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-09-23) MADHUSHREE, C. S; Surendra, H.S
    A modest attempt has been made to obtain model for the area and yield of sugarcane along with weather parameters for Mandya and Mysuru districts of Karnataka. For the present study secondary data for a period of 18 years from 1994 to 2011 were utilized on area and yield of sugarcane. Information on weather parameters were used to assess the impact of climatic factors on the sugarcane yield. Various models such as linear and non-linear models were fitted on the data sets for both area and yield of sugarcane. Among the models, cubic model based onEstimates of climate change on crop production could be biased depending upon uncertainties in climate variation or change scenarios, regions of study, crop models used for impact assessment studies and level of management. The yield of agricultural crops is limited by the amount of water received and stored in the soil than by air temperature. It also depends on how much of the rainfall is retained in the soil, how much is lost through evaporation from the soil surface, and how much remains in the soil that the crop cannot extract. The amount of water transpired by the crop is also determined by air humidity, with generally less dry matter produced in a drier atmosphere. Thus, changes in both rainfall and air humidity, would be likely to have significant effects on different crop yields. Important effect from changes of climate need not only stem from changes in average temperature and rainfall, but also from changes in frequency of extreme climatic events that can be damaging and costly for agriculture. The balance between profit and loss in commercial farming often depends on the relative frequencies of favorable and adverse weather
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    ThesisItemOpen Access
    STATISTICAL STUDY OF LONG TERM FERTILIZER EXPERIMENTS
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-09-02) CHANDANA, S; Manjunath, V
    Long term field experiments provide a vehicle for scientific investigation of structural relationship that governs the variability of specified crop over a period of time. The experimental data on grain yield of maize (q/ha) and various soil characteristics for a period of 25 years laid out in four replicate randomized block design with eleven treatments were procured. The study period data is split into three periods having eight years data in first two periods (1986-1994 and 1995-2002) and nine years data in the period three (2003-2011). Split plot and principal component analysis were carried out to know the effect of treatment on a grain yield over a period of time. Principal component analysis found to be more appropriate as year, treatment and interaction effect in split plot analysis was significant. The results of principal component analysis clearly showed that the variance explained by the first principal component is greater than 40 percent in all the treatment in all the three periods under study. The component scores were obtained by multiplying standardised values with an eigen vector. The two way table involving the index scores of the treatments in three replicates so obtained analysed as in randomised block design. The status of the soil nutrients were analysed using multiple linear regression analysis. The individual contribution of available N, P, K and its interactions were observed to have influence on the grain yield. Polynomial regression analysis to identify the response curves over a time indicated considerable variation in growth pattern in all fertilizer treatment for grain yield of maize.
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    ThesisItemOpen Access
    STATISTICAL EVALUATION OF AGROFORESTRY SYSTEM WITH FINGERMILLET
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-07-10) SOUMYA, S. DESAI; Mallikarjuna, G. B.
    Correlation analysis, Path analysis, ANOVA and ANCOVA were employed in this study. Fingermillet grain yield was noticed to be higher when grown with Madhuca latifolia, same tree species has recorded higher finger millet yield grown in its southern direction and at a 5 m distance compared to 2.5 m against other tree species. If a farmer wants grain and straw yield in the initial days he can think of intercropping with Madhuca latifolia, if he needs wood in the initial period Melia dubia may be preferred as it provides less yield for finger millet. Correlation analysis between wood volume and tree characters revealed that there was significant correlation between wood volume and GBH followed by bole height. Path analysis revealed that higher directs effects of GBH and bole height on wood volume. These two characters can be considered for selection of tree species for intercropping with fingermillet. Lower residual effect indicated better association with the tree characters on wood volume when grown with fingermillet as intercrop. ANCOVA carried out using tree characters as covariates (GBH and bole height) had less error mean sum of squares than ANOVA. Relative efficiency of ANCOVA over ANOVA was >1. This indicated that, adjustment to covariates ANCOVA will minimize the error component of analysis and is more precise than ANOVA in identifying actual fingermillet yield differences when grown as intercrop
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    ThesisItemOpen Access
    EVALUATION OF STATISTICAL MODELS FOR CLIMATIC CHARACTERIZATION OF GKVK STATION
    (UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU, 2015-07-10) BHOOMIKA RAJ, R; Krishnamurthy, K. N
    Agro-climatic characters play an important role in deciding the cropping pattern of a region. The distribution of rainfall is one such climatic character essential to plan farm activities in a given region. The present study was conducted to know the climatic characterization of GKVK station. The secondary data of weather parameters over a period of 38 years (1976-2013) and Finger millet (GPU 28) crop yield (qtl/ha) data during kharif season for a period of 16 years (1998-2013) was collected from AICRP on Agro Meteorology and AICSMIP, UAS, GKVK, Bengaluru respectively. Among the weather parameters, amount of maximum daily rainfall (mm) was considered to fit appropriate probability distributions. The probability distributions viz., Normal, Log- normal, Gamma (1P, 2P, 3P), Generalized Extreme Value (GEV), Weibull (1P, 2P, 3P), Gumbel and Pareto were used to evaluate the best fit for maximum daily rainfall (mm). Kolmogorov-Smirnov test for the goodness of fit of the probability distributions showed that for majority of the data sets on rainfall at different study periods, Weibull (3P) distribution was found to be the best fit. However, all the data sets were scale dominated which indicated large variation in the distribution of rainfall. Simple and multiple linear regression analysis showed that none of the weather parameters influenced the finger millet crop yield significantly. The path coefficient analysis indicated that among all the weather parameters, direct effect of PET on rainfall was found to be highly negative, while evaporation had the highest positive direct effect on rainfall. Further, vapor pressure and evaporation had positive and negative indirect contributions through the other weather parameters respectively.