Thumbnail Image

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.

Browse

2014 - 20173
Reset filters
Subject: Biostatistics × Start date: 1984 ×
Reset filters

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    ThesisItemOpen Access
    Statistical study on pre-harvest forecasting of apple yield
    (2014) PROMILA, DEVI; CHAUDHARY, V.K.
    The present study entitled “Statistical study on pre-harvest forecasting of apple yield” was undertaken in the Department of Basic Science, Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan 173230 (H.P.) during 2012-2014. The primary data were collected on the S yield and biometrical characters of apple trees of five blocks (Kullu, Nagar, Banjar, Anni and Nirmand) of Kullu district of H.P. Maximum yield was observed in Nagar block & minimum in Banjar block during the study. Yield was found to be significantly and positively correlated with age, height, girth, diameter, canopy (N-S), canopy (E-W) and number of branches biometrical characters of apple tree. In Kullu block, cubic model was best fitted for tree age to predict apple yield. S- curve model was best fitted for height, girth, diameter and volume to predict apple yield. Quadratic model best fitted for canopy (N-S), canopy (E-W) and number of branches to predict apple yield. In Nagar block, power model was best fitted for tree age to predict apple yield. S model was best fitted for height, girth, diameter and volume to predict apple yield. Exponential model was best fitted for canopy (N-S) and canopy (E-W) to predict apple yield. Growth model was best fitted for number of branches to predict apple yield. In Banjar block, cubic model fitted best for tree age to predict apple yield. Logarithmic model fitted best for girth, diameter and volume to predict apple yield. Quadratic model fitted best for height, canopy (E-W) and number of branches to predict apple yield. Linear model fitted best for canopy (N-S) to predict apple yield. In Anni block, power model was best fitted for girth, diameter, canopy (N-S) and volume to predict apple yield. Quadratic model was best fitted for height and number of branches to predict apple yield. Cubic model was best fitted for tree age to predict apple yield. S model was best fitted for canopy (E-W) to predict apple yield. In Nirmand block, cubic model was best fitted for tree age, height and diameter to predict apple yield. Linear model fitted best for girth, canopy (N-S) and canopy (E-W) to predict apple yield. Quadratic model fitted best for volume and number of branches to predict apple yield. Whereas, forecasting model based on multiple regression analysis for Kullu district is Y=1.1272+0.9638X1+2.6485X2+3.5237X3+0.2138X4+0.4467X5+0.8395X6+1.3490X7+1.0280X8 found to be fitted well based on R 2 , adjusted R 2 , SSE and RMSE in the data of biometrical characters of apple tree
  • Thumbnail Image
    ThesisItemOpen Access
    SOME CONTRIBUTIONS IN THE THEORY OF CONSTRUCTION OF STRATA
    (UHF,NAUNI, 2016) THAKUR, ASHU; MAHAJAN, P.K.
    ABSTRACT The method of choosing the best boundaries that make strata internally homogeneous, given some sample allocation, is known as optimum stratification. To achieve this, the strata are constructed in such a way that the strata variances should be as small as possible for the characteristic under study. Present study considers the problem of finding optimum strata boundaries to optimize the estimation of sensitive/stigmatized characters when sample sizes from different strata are selected with simple random sampling with replacement (SRSWR) and probability proportional to size sampling with replacement (PPSWR) and the data are collected by scrambled randomized response technique on the sensitive study variable. Assuming the form of the regression of the estimation variable y on the auxiliary variable x as y = ƞ(x) + e and the form of the conditional variance V (Y/X), the minimal equations giving optimum strata boundaries by minimizing the variance of the estimator of the population mean have been obtained. Due to implicit nature of these equations, the approximate solutions to these minimal equations have been found to give approximate optimum strata boundaries (AOSB). The total four rules have been proposed to have AOSB i.e. for Neyman allocation with SRSWR, equal and proportional allocation in PPSWR and for ratio and regression method of estimation. Limiting expressions for the variance of the estimator of population mean have also been suggested. Numerical investigation into the relative efficiency of stratification under all considered allocations with respect to no stratification have also been made for three usually encountered distributions namely rectangular, right triangular and exponential.
  • Thumbnail Image
    ThesisItemOpen Access
    “Statistical investigations on kinnow mandarin (Citrus reticulate Blenco.) production in Himachal Pradesh”,
    (UHF,NAUNI,SOLAN, 2017) VERMA, GEETA; MAHAJAN, P.K.
    ABSTRACT The study was carried out in Kangra and Sirmour districts of Himachal Pradesh with special reference to comparison of different sample allocation methods in combination with various stratification rules for determination of optimum strata boundaries. For this purpose, four methods of construction of strata boundaries viz., equalization of strata total, equalization of cum. , equalization of cum. {r(y)+f(y)} and equalization of cum. rules were used and it was observed that variance term worked out to be least in Neyman allocation and hence this allocation method was retained for further investigation. The critical examining of the results also revealed that for varying sample size, equalization of cum. provided the least variance, therefore, the study inferred that sampling methodology for estimation, “Statistical investigations on kinnow Mandarin (Citrus reticulata Blenco.) production in Himachal Pradesh” should be in conjunction with cum. can be used for estimation of kinnow production. To assess the relative contribution of various morphological characters in increasing the kinnow yield, 104 trees from location-1 and 96 trees from location -2 were randomly selected in the year 2014-15. F-test suggested that there was significant variation among all the characters between these two locations except fruit weight and LD ratio. It was also observed that number of flowers per branch, number of fruits per branch, plant girth and fruit weight contributes significantly towards the kinnow yield. In relation to the socio- economic status of kinnow orchardists, it was observed that the contribution of fruit crops towards the gross farm income had shown an increasing trend, while the contribution of field crops had shown a declining trend with the increase in farm size. At overall level, fruits crop accounted for 62.68 percent while field crops accounted only 37.32 percent of the total gross farm income. In relation to the price spread of kinnow under different marketing channels in the Himachal Pradesh indicated that producers’ share in consumers’ rupee was highest in channel-IV (81%), followed by channel-III (51%) and channel-I (43%), therefore, the marketing efficiency was found maximum (4.35) when farmers sold their produce directly to consumers.