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Dr. Rajendra Prasad Central Agricultural University, Pusa

In the imperial Gazetteer of India 1878, Pusa was recorded as a government estate of about 1350 acres in Darbhanba. It was acquired by East India Company for running a stud farm to supply better breed of horses mainly for the army. Frequent incidence of glanders disease (swelling of glands), mostly affecting the valuable imported bloodstock made the civil veterinary department to shift the entire stock out of Pusa. A British tobacco concern Beg Sutherland & co. got the estate on lease but it also left in 1897 abandoning the government estate of Pusa. Lord Mayo, The Viceroy and Governor General, had been repeatedly trying to get through his proposal for setting up a directorate general of Agriculture that would take care of the soil and its productivity, formulate newer techniques of cultivation, improve the quality of seeds and livestock and also arrange for imparting agricultural education. The government of India had invited a British expert. Dr. J. A. Voelcker who had submitted as report on the development of Indian agriculture. As a follow-up action, three experts in different fields were appointed for the first time during 1885 to 1895 namely, agricultural chemist (Dr. J. W. Leafer), cryptogamic botanist (Dr. R. A. Butler) and entomologist (Dr. H. Maxwell Lefroy) with headquarters at Dehradun (U.P.) in the forest Research Institute complex. Surprisingly, until now Pusa, which was destined to become the centre of agricultural revolution in the country, was lying as before an abandoned government estate. In 1898. Lord Curzon took over as the viceroy. A widely traveled person and an administrator, he salvaged out the earlier proposal and got London’s approval for the appointment of the inspector General of Agriculture to which the first incumbent Mr. J. Mollison (Dy. Director of Agriculture, Bombay) joined in 1901 with headquarters at Nagpur The then government of Bengal had mooted in 1902 a proposal to the centre for setting up a model cattle farm for improving the dilapidated condition of the livestock at Pusa estate where plenty of land, water and feed would be available, and with Mr. Mollison’s support this was accepted in principle. Around Pusa, there were many British planters and also an indigo research centre Dalsing Sarai (near Pusa). Mr. Mollison’s visits to this mini British kingdom and his strong recommendations. In favour of Pusa as the most ideal place for the Bengal government project obviously caught the attention for the viceroy.

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2019 - 20204
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Subject: Soil and Water Engineering × End date: 2020 × Start date: 2019 × Type: Thesis × Thesis Type: M.Tech. ×
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Now showing 1 - 4 of 4
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    ThesisItemOpen Access
    Development of drainage plan for waterlogged areas of Darbhanga district using remote sensing and GIS approach
    (DRPCAU, Pusa, 2020) D, Sudhakar Raj; Bhagat, I. B.
    In India, rainfall is variable which causes flood and drought frequently. In Bihar, out of 38 districts, 28 districts will become flooded and 15 districts among them will get extremely affected in every consecutive year. Nearly, 73.63% of the geographical area of North Bihar is considered to be prone to floods. Next to flood, congestion in drainage of surface water resulting into water-logging is another major serious problem in the Bihar state. The combined use of remotely-sensed images and GIS based environmental applications in this work is needed for systematic ideas and scientific planning in the Darbhanga district of Bihar. Image processing and water-logged area assessment was done using ArcGIS and eCognition software. The index-based classification method was followed in an ArcGIS software and as a result, various indices such as NDVI, NDWI, MNDWI (Esri), MNDWI (IHS) had been obtained to assess the water-logged portions. Among the various indices used in different months False Colour Composite image, it was found that the month of September (2017) is the best month to indicate, assess and delineate the water-logged areas. Comparison with the other indices, MNDWI was highlighting the water-logged portions in the better way. The object-based classification was carried out in eCognition software which will convert the pixels into objects. The water-logged boundary layer was extracted by using the threshold value of -0.175 in the September month MNDWI raster. The total area subjected to water-logging in the Darbhanga district was found to be 42,282 ha. The area of water-logging was found in the two sub-divisions of the Darbhanga district. The blocks of Darbhanga and Biraul sub-division, holding the water-logging area of 21,899 ha and 20,383 ha respectively. The maximum expected rainfall at 60 per cent, 70 per cent and 80 per cent probability levels were found using Weibull’s formula and 70 percent maximum rainfall of consecutive days was considered for the drainage characteristics which have been analysed with the formula of volume-balance method. The average pan evaporation loss was estimated as 0.385 cm per day. The average percolation loss was found based on the previous research works and considered for analysis of drainage characteristics. The drainage coefficient of consecutive days i.e., 1-,2-,3-,4-,5-,6- and 7- days for the blocks of Darbhanga sub-division was found to be 27.71, 16.93, 12.57, 10.42, 9.19, 8.35 and 1.60 cm per day respectively and for the blocks of Biraul sub-division it was computed as 18.12, 10.94, 8.07, 6.66, 5.85, 5.31 and 4.79 cm per day respectively. The surface drainage plan for the blocks of Darbhanga and Biraul sub-divisions have been expressed by showing the main drain lines and outlets which was based on the comparison of different thematic maps. The useful measures also have been suggested to execute the drainage plan in an active manner.
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    ThesisItemOpen Access
    Standardization of Irrigation and fertigation schedule for Tomato cultivation under soil less media
    (DRPCAU, Pusa, 2020) Umashanker; Nirala, S. K.
    The research work entitled “Standardization of Irrigation and Fertigation schedule for Tomato cultivation under Soil Less Media” was conducted with eighteen treatments. The treatments comprised with different soil less media like Cocopeat, Perlite,Vermiculite,Vermicompost and sand along with three levels of RDF and two levels of irrigation. The tomato plants planted in grow bags irrigation and fertigation applied with drip irrigation system. Tomato crop of variety Avinash-2 was selected for experiment. The field layout done by using CRD with three replications. The seasonal crop water requirement of tomato plants in soilless media in grow bages cultivation varies from 12.72 to 15.90 cm under irrigation level 80% and 100% Etc.The best growing media was foundCocopeat + Perlite + Vermicompost (3:1:1). The composite effect of growing media, irrigation and fertigation on vegetative growth and yield parameters (fruit length, fruit diameter, numbers of fruit per plant, fruit weight, yield per plant) was found better in treatment M1I2F1 (Cocopeat + Perlite + Vermicompost + 0.80 ETc + 125 % RDF). The maximum average vegetative growth was recorded as 102.12 cm, fruit length 5.55 cm, maximum diameter 5.29 cm, average numbers of fruit per plant 63.73, average fruit weight 90.82 g, and maximum yield 5.23 kg per plant was recorded. However, the minimum yield was (2.88 Kg) under M1F3I2 treatment. The B: C ratio of 3.12 and maximum net income of Rs 211211/- per 1000 m2 in treatment M1I2F1 and minimum B: C ratio of 1.46 in treatment M1F3I2 (control).
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    ThesisItemOpen Access
    Drought assessment and impact of land use land cover change on surface water extent of Bihar using remote sensing and GIS
    (Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, 2019) Bhawana; Prasad, Sudarshan
    The captured satellite datasets using advanced techniques such as remote sensing (RS) and its processing to extract the information using geographic information system (GIS) have been used for detection of droughts and its mapping for the Bihar state. Meteorological droughts over various places of Bihar during monsoon season were identified using standard precipitation index (SPI) through software for SPI computation. The daily rainfall estimates of time duration of 67 years from 1951 to 2017 extracted from satellite datasets viz. Asian Precipitation Highly Resolved Observational Data Integration towards evaluation of water resources (APHRODITE) of duration 47 years from 1951 to 1997 and Tropical Rainfall Measuring Mission (TRMM) of duration 20 years from 1998 to 2017 were used for the purpose. The whole area of the state was divided into total number of 301 grid points of 0.25° × 0.25° resolutions and monthly time series of rainfall (mm) estimates were obtained for each grid points from daily rainfall estimates obtained from TRMM and APHRODITE. These datasets of monthly time series were validated with rainfall data of monthly time series of 20 years duration from 1998 to 2017 observed at rain gauge station, Pusa using statistical techniques Thus, spatio-temporal maps of SPI based meteorological drought were developed for the years 2000 to 2017 for the area under study. Vegetation condition index (VCI) estimated through MODIS NDVI products obtained from USGS Earth Explorer for Bihar state were composited for Kharif and Rabi season from year 2000 to 2017. Spatio-temporal maps of NDVI and VCI for Kharif as well as Rabi season were developed based on vegetation indices for the years from 2000 to 2017. Using LANDSAT-5 (TM) and LANDSAT-8 (OLI/TIRS) imageries unsupervised image classification was performed. The Land use-land cover maps were generated for the years 2008 and 2018 with six feature classes namely agricultural land, settlement, vegetation, waste land, water body and sand were identified. Analysis of SPI revealed that the year 2006 experienced moderate dry conditions in the districts like Kishanganj, Araria, Purnea, Katihar and Gopalganj. In the year 2013 districts like West Champaran, Saran, Gopalganj Sheohar, Vaishali, Muzaffarpur and Samastipur faced moderately dry conditions repeating the trend in 2016. In all the years from 2000-2017 majority of the study area experienced mild drought. However, in case of 2007, almost all the districts of the study area having the extreme wet condition because of high rainfall during monsoon season. The temporal variation of NDVI in the year from 2000 to 2017 showed that most of the south-western districts of the state noticed the low value of NDVI ranging from 0.2 to 0.4 during Kharif season of almost all years. During the wet year of 2007, the high value of NDVI (>0.5) was noticed in almost every district except Samatipur, Darbhanga and Khagaria which experienced highly wet condition. During entire period of analysis lush vegetation with high value NDVI of more than 0.6 was noticed except for Banka and Jamui districts which experienced moderately dry condition in almost every year from 2000 to 2017. Spatio-temporal maps with varying VCI, showed the moderate to no drought conditions in the study area. In the year 2000, extremely good vegetation condition was observed decreasing in each year especially in the year 2005 in which almost entire area experienced low value of VCI ranging from 0.5 to 0.2 indicating fair vegetation condition. During Rabi season districts like Banka and Jamui show consistent poor vegetation condition in the years from 2000 to 2016. Analysis of Land use-land cover map for the years 2008 and 2018 depicted that there was drastic change in most of the feature classes. The water body shrinked to 2.13 % with areal loss of water body by 35.74 km2.
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    ThesisItemOpen Access
    Impact assessment of change in land use land cover and rainfall pattern on soil erosion potential of Irga river catchment (Jharkhand) using remote sensing and GIS techniques
    (Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, 2019) Yadav, Shankar; Sahu, R.K.
    Soil erosion is a major form of land degradation and has been recognized as a severe environmental problem. The present study was conducted in Irga catchment situated in Giridih district of Jharkhand. Image processing and soil erosion assessment is done using eCognition and ArcGIS softwares. The land use land cover map of 1997, 2007 and 2017 were prepared using LANDSAT images by object-based image classification technique having better accuracy than traditional pixel based image classification. The Land use land cover maps were classified into six classes viz. agricultural land, settlement, vegetation, waste land, water body and river. Using RUSLE integrated with RS and GIS, soil erosion map was prepared for the study area. For preparing soil erosion map, R factor was derived from TRMM rainfall data of ten years (2008 to 2017), K factor from DSMW prepared by UN FAO and LS factor from SRTM DEM. The C and P factor values were assigned according to LULC map based on reviewed works. The overall accuracy of classified images are computed to be 88%, 83% and 91 % while kappa coefficients are found to be 0.8455, 0.7706 and 0.8796 for year 1997, 2007 and 2017 respectively. The results indicate that waste land greatly reduced and converted into settlement and agricultural land. In application of RUSLE model for Irga catchment, R factor varied from 499.834 to 538.049 MJ mm h-1 ha-1 yr-1and K factor varied from 0.0159 to 0.0191 t ha h ha-1 MJ-1 mm-1 for year 2017. The generated LS factor map of the study area showed that it varied from 0.03 to 41.09. C and P factor varied from 0 to 1. The estimated value of soil loss from the catchment varies from 0 to 36.1185 t /ha/yr with mean value as 0.2814 t/ha/yr. The results indicate that the study area has very slight and slight erosion class. Further, using 10 year rainfall data of 1998 to 2007 and LULC map of 2007, the soil erosion potential map for the year 2007 was also generated. The value of soil loss varies from 0 to 44.2149 t/ha/yr for this year with mean value as 0.3057 t/ha/yr. The mean value of the soil erosion potential has decreased by 8.6049 % over the period of 10 years (2007-2017) which reveals that the changes in LULC and rainfall pattern greatly affect the soil erosion potential. The results of the present study also reveal that object-based image classification technique gives higher accuracy for image classification as compared to pixel-based classification. Further, integrated use of RUSLE with RS and GIS technique is effective and powerful tool for estimation of soil erosion.