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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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Subject: Mathematics × End date: 2025 × Start date: 2020 × Type: Thesis ×
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    ThesisItemOpen Access
    STATISTICAL APPRAISAL OF PRODUCTION TRENDS IN MAJOR PULSES GROWN ACROSS KARNATAKA STATE
    (University of Agricultural Sciences, Bangalore, 2021-12-31) SAHANA, N; SAHANA, N; SAHANA, N; . MANJUNATH, V; . MANJUNATH, V; . MANJUNATH, V
    In order to assess the trend in area, production and productivity of major pulses (red gram, bengal gram, horse gram, green gram and black gram) across Karnataka, 22 years secondary data were used. To know growth trends different polynomial linear models (linear, quadratic, cubic), intrinsically linear models (logarithmic, inverse, compound, power) and non-linear models (log-logistic, exponential) were fitted. Appropriate models were selected on the basis of important model adequacy tests. All the characteristics in red gram showed an exponentially increasing trend, while in bengal gram productivity was linearly increasing whereas area and production showed exponential trend. Cubic and linear models was performed well in majority of situation for green gram and black gram. Quadratic model was well suited for productivity of horse gram, while different modelswere found to be best fit for other characteristics. By trend analysis it can be inferred that different growth trends were observed in each of the crops studied. Further to study the spatial variations in area, production and productivity across major pulses growing districts of the State in different study period, Coefficient of variation (CV%), Coppock’s instability index (CII) and Cuddy Della Valle index (CDI) were adopted. Bengal gram and black gram showed high instability during Period II. More instability in area, production and productivity was noticed in Vijayapura, Gadag, Mysuru, Bagalkot and Bidar districts for red gram, bengal gram, horse gram, green gram and black gram respectively, it may be due to these crops are grown in these districts under rainfed conditions.
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    ThesisItemOpen Access
    MODEL BASED STATISTICAL EVALUATION OF MAJOR CEREALS PRODUCED IN KARNATAKA STATE
    (University of Agricultural Sciences, Bangalore, 2021-12-31) APOORVA RAJ; APOORVA RAJ; APOORVA RAJ; MANJUNATH, V; MANJUNATH, V; MANJUNATH, V
    An attempt has been made to study the trend in area, production and productivity of major cereals (rice, maize, jowar, ragi and bajra) grown in Karnataka state. For this study 22 years secondary data were collected on area, production and productivity for the selected cereals. In order to study the temporal variation, linear, quadratic, cubic, logarithmic, inverse, compound, power, logistic, log-logistic and exponential models were utilized. An appropriate model chosen based on the model adequacy criteria R2, AIC, RMSE and MAPE. Log-logistic model was the best fit model in majority of situation for rice and maize which indicated a steady increase during initial periods and reaching stagnation, whereas linear and exponential model was best fit for most of the characteristic in case of jowar, ragi and bajra indicating steady increase or decreasing trend. Rice and maize were mainly grown in kharif season so same trend was observed for pooled data over all the season whereas in case of jowar and ragi were mainly grown in rabi season so same was depicted in pooled data. Further the spatial variations in area, production and productivity across districts during the study period were analysed by computing Coefficient of variation (CV%), Coppock’s instability index (CII%) and Cuddy Della Valle index (CDI%). It was observed that instability was more for production of all the cereals than area and productivity in their respective districts. Larger instability was seen in period III for all the cereals except bajra which showed highest stability during period II.
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    ThesisItemOpen Access
    A STATISTICAL EVALUATION OF SHIFT IN CROPPING PATTERN IN SELECTED AGRO-CLIMATIC ZONES OF KARNATAKA
    (University of Agricultural Sciences, Bangalore, 2021-12-31) SUMAN, V; SUMAN, V; Mr. SURENDRA, H. S; Mr. SURENDRA, H. S
    In this research, an effort was made to analyse the trends in area and production of major cereal crops (Paddy, Maize, Ragi and Jowar) in selected four agro-climatic zones of Karnataka state, using linear, quadratic, cubic, exponential and logistic model for the time period of 2000-2019. The best fit model was selected based on the minimum value RMSE. Linear and exponential models were found to be best fit for most of the crops in the study area. In this study an attempt was made to evaluate the shift in cropping pattern in selected four agro-climatic zones of Karnataka, using Herfindahl index (HI), Simpson index (SI)and Entropy index (EI). In all the three types of analysis conducted Central Dry zoneshowed highest diversification followed by Southern Dry zone, Southern transition zone and Eastern Dry zone for the time period 2000-2004, 2005-2009, 2010-2014 and 2015-2019 respectively. Further, an attempt was made to identify the suitable weather parameters influencing the production of selected major crops, considering production as dependent variable and using area, rainfall, maximum temperature, minimum temperature and relative humidity as independent variables. Multicollinearity was not seen among the independent variables. Multiple linear regression (MLR) model and stepwise multilinear regression (SMLR) model, were tried to identify the weather parameters. It is observed that area had the significant positive influence on production for most of the crops and less significant influence was seen from the weather parameter for most of the crops