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Dr. Y. S. Parmar University of Horticulture & Forestry, Solan

Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Solan, was established on 1st December, 1985 with the objective to promote education, research and extension education in the fields of Horticulture, Forestry and allied disciplines. Late Dr. Yashwant Singh Parmar, the first Chief Minister and the architect of Himachal Pradesh perceived the importance of Horticulture and Forestry to develop and improve the State economy which led to the establishment of this University. Its history lies in erstwhile Himachal Agricultural College, Solan, established in 1962 and affiliated to the Panjab University. It became one of the campuses of Agriculture Complex of Himachal Pradesh University on its formation in 1970. Consequent upon the establishment of Himachal Pradesh Krishi Vishvavidyalaya in 1978, this campus became its Horticulture Complex and finally in 1985, assumed the status of a State University, being the only University in the country engaged exclusively in teaching, research and extension in Horticulture and Forestry. The University is located at Nauni in Solan District of Himachal Pradesh, 13 km from Solan on Solan-Rajgarh Road, at an elevation of 1300 metres above mean sea level. Solan town is situated on national highway (NH-22) and is well connected by train and bus services. The University has four constituent colleges, out of which, two are located at the main campus Nauni, one for horticulture and the other for forestry, having 9 and 7 departments, respectively. The third College i.e., College of Horticulture & Forestry is located at Neri in Hamirpur District on Nadaun-Hamirpur state highway, about 6 Km from Hamirpur town and is well connected with bus service. The college offers three Undergraduate Degree Programmes i.e. BSc (Hons.) Horticulture, BSc (Hons.) Forestry and B. Tech. Biotechnology and MSc degree programme in a few subjects. The fourth college i.e. College of Horticulture and Forestry, Thunag (Mandi) is located at Thunag District Mandi. This college offer BSc (Hons.) Horticulture and BSc (Hons.) Forestry degree programme. In addition, there are five Regional Research Stations, 12 Satellite Stations and five Krishi Vigyan Kendras (KVKs) situated in different zones of the State.

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Subject: Basic Sciences × End date: 2021 × Start date: 2021 ×
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    ThesisItemOpen Access
    STATISTICAL INVESTIGATION ON PREDICTION OF AREA AND PRODUCTION OF MAIZE AND BARLEY IN HIMACHAL PRADESH
    (UHF,NAUNI, 2021-11) JASWAL, ABHIMANEU; GUPTA, R K
    ABSTRACT The present investigation entitled “Statistical Investigation on Prediction of Area and Production of Maize and Barley in Himachal Pradesh” were conducted in the Department of Basic Sciences, Dr YS Parmar University of Horticulture and Forestry, Nauni, Solan (H.P.) during 2019-2021. Forecasting of agricultural production helps the government, agribusiness industries and farmers in making decisions about the future commodities prices. Secondary data on the area (thousand hectares) and production (MT) of maize and barley from (1960-61-2019-20) 60 years were collected from ASO, Directorate of Agriculture, Shimla. Different statistical models viz., linear, quadratic, compound, logistic, modified exponential and Gompertz were used for forecasting the area and production of maize and barley. Autoregressive models were also fitted to the data. Model adequacy was examined by different criterion such as significant regression coefficients, maximum value of adjusted-R square and lower values for root mean square error (RMSE) and Thiel’s U statistic. Gompertz model was found best fitted model for maize production whereas logistic and compound models were best fit for production taking area as regressor. First order autoregressive model was found best fit for prediction of area under maize. In case of barley, second order autoregressive model was found most suitable for prediction of production as well as area under barley. Quadratic model for prediction of production taking area as regressor was best fit. Annual growth rates for production and area of both the crops were also computed and it was increasing in case of production as well as area under maize but for barley it was increasing for production only when area was taken as regressor.
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    ThesisItemOpen Access
    STATISTICAL INVESTIGATION FOR VOLUME TABLE OF Toona ciliata M. Roem
    (UHF,NAUNI, 2021-10) SHARMA, SHILPA; MAHAJAN, P K
    ABSTRACT The present study entitled “Statistical Investigation for Volume Table of Toona ciliata M. Roem” was carried out in District Kangra, Himachal Pradesh. The investigation was undertaken to propose the convenient tool for foresters and researchers to obtain the estimated volume of Toona ciliata at any form without employing devastating procedures. For the study, primary data for diameter and height of toona trees was obtained from four distinct sites of District Kangra viz, Nihari, Baslag, Chauli and Kaloha. A total of 100 Toona ciliata trees were marked, with 25 trees from each site. To test the variability among different sites, the data was subjected to variability analysis. Thereafter, the homogeneity of variances in diameter, height, and volume parameters was tested using Bartlett's chi-square test.The predicted number of trees in each diameter class was calculated using probability distributions as per the cross section of data, and the significance of these results was tested using the Kolmogorov-Smirov test statistic. To estimate the number of toona trees in various diameter classes in this zone, the best fitted distributions were found to be log-normal and gamma.A two-way volume table was constructed using the best-fit power model for Toona ciliata. Finally the regression analysis was employed to predict the volume of toona trees and construction of volume tables.
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    ThesisItemOpen Access
    FORECASTING OF AREA AND PRODUCTION OF RICE AND WHEAT IN HIMACHAL PRADESH
    (UHF,NAUNI, 2021-10) DHIVYANHARSINI D; CHANDEL, ASHU
    ABSTRACT The present investigation was carried out to forecast the area and production of rice and wheat crops in Himachal Pradesh. The secondary data on area and production of rice crop for 30 years (1989-1990 to 2018-2019) and for wheat crop 50 years (1969-1970 to 2018-2019) were used for analysis. Various linear, non-linear and ARIMA models were employed. Most appropriate regression models were selected on the basis of significant regression coefficients, maximum values of adjusted , minimum values of RMSE, Theil’s U coefficient and non-significant F-statistic (chow test). The ARIMA models with different p, d and q were judged on the basis of auto correlation function (ACF) and partial auto correlation function (PACF) at various lags. ARIMA models were selected on the basis of various goodness of fit criteria viz., Akaike’s information criterion, Bayesian information criterion, RMSE, MAE, MAPE and Ljung-Box Q-statistic. Quadratic model was found to be the best fitted model for the estimation of area under rice and wheat crops. The cubic and linear models were found to be the appropriate model for the estimation of production of rice and wheat crops respectively. Among the ARIMA families of time series models for prediction of area and production of rice, ARIMA (0, 2, 1) and ARIMA (1, 1, 1) was found suitable whereas ARIMA (3, 1, 1) and ARIMA (2, 1, 2) models were found as the best model for the area and production of wheat in Himachal Pradesh. Forecasting was done up to 2019-2020. Forecasted values showed an increasing pattern in production of rice and wheat crops, whereas decreasing pattern was noticed in area of these crops. These forecasts would be helpful for policy makers to foresee ahead of time the future requirements of grain storage, import-export and adopt appropriate measures to increase production with a decrease in area by adopting improved agriculture practices in this regard.
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    ThesisItemOpen Access
    STUDIES ON POPULATION DYNAMICS OF RHIZOSPHERE AND NON RHIZOSPHERE SOIL BACTERIA IN CHIRPINE AND DEODAR FORESTS AS INFLUENCED BY DIFFERENT ALTITUDINAL RANGES OF HIMACHAL PRADESH
    (UHF,NAUNI, 2021-10) VIBHA SINGH; CHAUHAN, ANJALI
    ABSTRACT Species diversity refers to the richness of species and also balanced species distribution. Forests are essential for the availability of a variety of ecosystem services that are crucial to human well-being and also are critical habitats for the wide range of biological diversity. The high spatial variation in microbial activity is due to the spatial heterogeneity of forest soils (e.g. enzyme activity or respiration) and microbial biomass content. Coniferous trees are cosmopolitan within the world and have tremendous environmental and economic importance. Large numbers of bacteria resides in the rhizosphere or rhizoplane of their roots, and a few of those may promote tree growth through various mechanisms. Tree species like Pinus roxburghii Sarg. (chirpine) and Cedrus deodara (Roxb.) Loud (deodar) are known among the foremost magnificent conifer trees for the dynamic bacterial communities due to decomposing organic matter under these trees. Though lots of research has been done on PGPR in agricultural systems yet research on this bacterial group in forest ecosystem remains at its nascent stage. Hence, investigation entitled “Studies on population dynamics of rhizosphere and non rhizosphere soil bacteria in chirpine and deodar forests as influenced by different altitudinal ranges of Himachal Pradesh” was carried out to explore the diversity of plant growth promoting rhizosphere and non rhizosphere soil bacterial communities associated with Cedrus deodara and Pinus roxburghii and their characterization for plant growth promoting traits followed by their genetic diversity. A total of 168 rhizospheric and non rhizospheric bacteria were isolated from soil samples of Cedrus deodara and Pinus roxburghii collected from four different sites of Shimla, Kullu, Solan and Sirmour valleys of Himachal Pradesh. A significant variation was recorded in rhizosphere and non rhizosphere bacterial population in deodar and chirpine which increases from lower to higher altitude. All these bacterial isolates were screened for multifarious plant growth promoting traits i.e. P-solubilzation shown by 76.78% , siderophore production shown by 79.16%, IAA shown by 69.04% of isolates and zinc solubilization was shown by 76.78% of total isolates. Maximum plant growth promoting traits were shown by rhizosphere soil samples of deodar. After this, they were subjected to test for various antagonistic traits (HCN, Chitinase, Protease, Amylase) and also test for antifungal against Fusarium sp. and Phytophthora sp. Fifty seven isolates exhibiting maximum PGP traits were subjected to study their biochemical tests. Then, a total of 19 representative isolates were selected to study genetic diversity among them using 16S rDNA sequencing. In silico analysis grouped these isolates into three major genera i.e. Bacillus and Pseudomonas being predominant while other is Alcaligenes. Overall, present study conclude that, isolates from rhizosphere soil exhibit higher multifarious PGP traits than non-rhizosphere soil. Also the soil under deodar is well enriched by various soil nutrients which supports the proliferation of large number of beneficial bacteria as compared to chirpine forests.
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    ThesisItemUnknown
    FORECASTING OF AREA AND PRODUCTION OF PEACH AND APRICOT IN HIMACHAL PRADESH
    (UHF,NAUNI, 2021-10) THAKUR, PARUL; CHANDEL, ASHU
    ABSTRACT The present investigation entitled “Forecasting of area and production of Peach and Apricot in Himachal Pradesh’’ were conducted in the Department of Basic Sciences, Dr YS Parmar University of Horticulture and Forestry, Nauni, Solan (H.P.) during 2019-2021. Forecasting of agricultural production helps the government, agribusiness industries and farmers in making their decisions about the future commodities prices. Secondary data on the area (ha) and production (MT) of peach and apricot from 1996-2019 (24 years) were collected from Directorate of Horticulture, Shimla. Different statistical models viz., linear, quadratic, cubic, compound, modified exponential, power and Gompertz were used for forecasting the area and production of peach and apricot. Autoregressive model was also fitted based on significance of autocorrelation coefficients. Annual growth rates were also calculated for area and production. Model adequacy was examined by different criterion such as, significance of regression coefficients, maximum value of adjusted-R square and lower values for root mean square error (RMSE) Theil’s U statistic. Power and quadratic were found to be best fitted models to forecast the area and production of peach. First order autoregressive model and power model were found to be best fitted model to forecast the area and production of apricot. Linear and compound growth rate showed that, production of peach and apricot has been increased over the time.
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    ThesisItemOpen Access
    EVALUATION OF STATISTICAL MODELS FOR PREDICTION OF AREA AND PRODUCTION OF POTATO (Solanum tuberosum. L) IN HIMACHAL PRADESH
    (UHF,NAUNI, 2021-10) KAUR, SUKHDEEP; GUPTA, R K
    ABSRACT The Present Investigation entitled “Evaluation of Statistical models for Prediction of Area and Production of Potato (Solanum tuberosum. L) in Himachal Pradesh.” was undertaken in the Department of Basic Science, Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan 173230 (H.P.) during 2019-2021. Last 31 years of secondary data based on area (1000 ha) and production (1000 MT) of potato for H.P was used and various prediction models viz. linear, quadratic, cubic, compound, exponential, modified exponential, power, gompertz, logistic, autoregressive and autoregressive integrated moving average were applied and tested. All the six prediction models namely: linear, quadratic, compound, exponential, power, gompertz, 1st order autoregressive and ARIMA (1,2,2) fitted well to the area under potato but among all the models, quadratic model was found to be best model for area under potato with highest value of , lowest value of RMSE, C.V, Theil’s inequality coefficient (U) and non significant F value (chow test). The linear, compound, exponential, logistic, 1st order autoregressive and ARIMA (1,1,2) fitted well to the potato production. ARIMA (1,1,2) was fitted well to the production of potato, but on the basis of , RMSE, C.V, Theil’s inequality coefficient (U) and nonsignificant F value (chow test) linear model was found to be best fitted for potato production. An annual increase in Production growth rate in Potato was obtained during the studied period.
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    ThesisItemOpen Access
    ISOLATION AND SCREENING OF INDUSTRIALLY IMPORTANT MICROBES FOR THE PRODUCTION OF BIOMOLECULES WITH AN EMPHASIS ON BIOSURFACTANTS
    (UHF,NAUNI, 2021-01) SHARMA, PUSHPINDER; SHARMA, NIVEDITA
    ABSTRACT Biosurfactant research as well as its development and commercialization have beheld a great significance in recent years. Biosurfactants are considered as amphiphilic surface-active compounds produced by various microbes that harbor numerous unique properties. Oil contaminated sites are highly probable source of oil degrading microorganisms and was utilized as a source for isolation of biosurfactant producing microorganisms. In present study, 40 strains were isolated from biosurfactant producing bacteria from various oil-contaminated sites of Himachal Pradesh. Among them, four strains PS9, PS23, PS26 and PS37 were selected for the further study which were identified as B. tequelensis PS9 |MN 197768|, B. cereus PS23 |197769|, B. subtilis PS26 |197770| and Escherichia fergusoni PS37 |1997771|. Antibacterial and antifungal activity of the strain was also examined. Optimization of culture conditions was done on the basis of various process parameters and medium components viz. media types, temperature, pH, carbon sources, nitrogen sources and media additives firstly using classical One Variable at a Time (OVAT) approach followed by statistical optimization by utilizing Central Composite Design (CCD) of Response Surface Methodology (RSM). Hydrophobicity was found to be maximum at 40°C temp in 1% carbon and nitrogen source in both the strains but at 7.0 and 9.0 pH in B. tequelensis and B. subtilis respectively. Furthermore, 283mg of dried biosurfactant was produced. The extraction and purification was done followed by quantitification of biosurfactant formed by B. tequelensis PS9 which was done by using High Performance Liquid Chromatography (HPLC). The quantity of the biosurfactant came out to be 85.657ppm. Further characterization of purified biosurfactant was done and it was found to be effective at 40°C temperature, 7.0 pH, 1% NaCl concentration and quite stable at 4°C for 9 days while at room temperature upto 5 days. The maximum of 98.25μg/ml protein content was observed. In oildisplacement activity, an impressive zone of 2.6cm was observed and emulsification index was equal to 37.5%. Molecular and structural compositions of the purified biosurfactant were then evaluated by FTIR, NMR and MS/MS and a cyclic lipopeptide {C14 Surfactin (L/I4, D6), [M+H]+ and C15 Surfactin (V4,D6), [M+H]+} by Bacillus tequelensis PS9 were identified. In case of other analytical techniques, FTIR data revealed lactone and peptide form of surfactin, NMR showed glycosidic linkage of sugar moiety and methoxy functional groups indicating the surfactin. The study has a great implication as the biosurfactants are considered safer alternative to synthetic or chemical surfactants as they are less toxic, eco-friendly and of course have low ecological impact. The present study provides further evidence that biosurfactant produced from Bacillus tequelensis PS9 has undoubtedly turned out to be a potential candidate in bioremediation as well as can be recommended for industrial use as a laundry detergent