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Govind Ballabh Pant University of Agriculture and Technology, Pantnagar

After independence, development of the rural sector was considered the primary concern of the Government of India. In 1949, with the appointment of the Radhakrishnan University Education Commission, imparting of agricultural education through the setting up of rural universities became the focal point. Later, in 1954 an Indo-American team led by Dr. K.R. Damle, the Vice-President of ICAR, was constituted that arrived at the idea of establishing a Rural University on the land-grant pattern of USA. As a consequence a contract between the Government of India, the Technical Cooperation Mission and some land-grant universities of USA, was signed to promote agricultural education in the country. The US universities included the universities of Tennessee, the Ohio State University, the Kansas State University, The University of Illinois, the Pennsylvania State University and the University of Missouri. The task of assisting Uttar Pradesh in establishing an agricultural university was assigned to the University of Illinois which signed a contract in 1959 to establish an agricultural University in the State. Dean, H.W. Hannah, of the University of Illinois prepared a blueprint for a Rural University to be set up at the Tarai State Farm in the district Nainital, UP. In the initial stage the University of Illinois also offered the services of its scientists and teachers. Thus, in 1960, the first agricultural university of India, UP Agricultural University, came into being by an Act of legislation, UP Act XI-V of 1958. The Act was later amended under UP Universities Re-enactment and Amendment Act 1972 and the University was rechristened as Govind Ballabh Pant University of Agriculture and Technology keeping in view the contributions of Pt. Govind Ballabh Pant, the then Chief Minister of UP. The University was dedicated to the Nation by the first Prime Minister of India Pt Jawaharlal Nehru on 17 November 1960. The G.B. Pant University is a symbol of successful partnership between India and the United States. The establishment of this university brought about a revolution in agricultural education, research and extension. It paved the way for setting up of 31 other agricultural universities in the country.

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20223
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Subject: Processing and Food Engineering × End date: 2024 × Start date: 2022 × Type: Thesis ×
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    ThesisItemOpen Access
    Process standardization for the development of finger millet mix jaggery chocolate
    (G.B. Pant University of Agriculture and Technology, Pantnagar, District Udham Singh Nagar, Uttarakhand. PIN - 263145, 2022-10) Choubey, Diksha; Shahi, N. C.
    Chocolates in general are found to be poor in protein and high in fat, and excessive intake of chocolate leads to a variety of health problems due to excessive amount of refined sugar. Furthermore, chocolate does not have much nutritive value due to which it cannot be used as a supplement of nutritions. Therefore, sugar and milk powder were replaced by jaggery and finger millet flour respectively for improving the dietary contents. Jaggery is an unrefined sugar and is regarded as the healthiest sugar in the world since it has all of the minerals and vitamins found in sugarcane juice. Finger millet is a nutritionally rich nutri-cereal that is underutilized. Processing and value addition of such minor millet may help to fulfil the nutritional requirements of humans, as it is gluten-free and calcium-rich, which is advisable for stomach patients. Both jaggery and finger millet flour contain high nutritional value and are rich in fibres and minerals, so their incorporation into chocolate not only increases the nutritional value of chocolate but also improves textural properties. The present research work was, therefore, undertaken for the development of sprouted finger millet flour mixed jaggery chocolate, optimization of process parameter for quality chocolate and study of nutritional and textural characteristics of the developed chocolate. The independent variables selected were cocoa butter replaced with coconut oil (20, 25, 30 % w/w), conching time (120, 150, 180 min) and replacement of milk powder with sprouted finger millet flour (20, 30, 40% w/w). The moisture content (%), ash content (%), crude fat (%), crude protein (%), textural profile analysis (hardness, adhesiveness, cohesiveness and chewiness) and sensory characteristics were analyzed. The data from all 17 experiments were analyzed using Design Expert version 11.1.0.1 and the response functions were developed using multiple regression analysis. The optimum values of variables for maximum desirability of sprouted finger millet flour mixed jaggery chocolate were 22% cocoa butter replacement with coconut oil, 150 minutes conching time and 39 % replacement of milk powder with sprouted finger millet flour. The optimum values for responses were 5.16 % moisture, 2.66 % ash, 23.6 % crude fat, 9.87 % crude protein, , 8.12 mouthfeel, 305.6 N hardness, 2.14 N.s adhesiveness, 0.101 cohesivenesss, 4.07 N chewiness and 7.8 overall acceptability. Out of all process parameters, sprouted finger millet flour had highly significant (p<0.05) effect followed by conching time and cocoa butter replacement with coconut oil in all responses of development of sprouted finger millet flour mixed jaggery chocolate. On validation of the model for responses of developed chocolate, it was found that the developed model was accurate as an insignificant difference was observed between experimental and predicted values.
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    ThesisItemOpen Access
    Classification of potatoes into edible and non-edible by using deep learning technique
    (G.B. Pant University of Agriculture and Technology, Pantnagar, District Udham Singh Nagar, Uttarakhand. PIN - 263145, 2022-08) Singh, Nikhil Kumar; Sachin Kumar
    Potato, one of starchy vegetables, needs to be classified before entering industry for assuring the product quality. However, it is time-consuming, tedious, labor-intensive, inaccurate and expensive to assess qualitatively and classified manually. In this study, we propose an efficient and effective machine vision system based on the state-of-the-art deep learning techniques and stacking ensemble technique to offer a non-destructive and cost-effective solution for classification of ‘potatoes’ freshness and appearance. It has been trained and tested the performance of various deep learning models including ResNet, MobileNet, InceptionV3 and VGG16 to find the best model for the classification of potatoes into edible and non-edible categories. The system was trained and tested on potatoes data sets which were collected at constant distance of 20 cm for image capturing. The accuracy of used models is found to be 89 %, 68%, 95%, and 99% respectively and the precision and recall of the proposed model was best for MobileNet with uniform internet speed for each model. The experimental results show that the accuracy, precision and recall achieves with limited sample easily which tells the overall performance of the proposed model. The proposed technique for classification has less parameters and lower computation complexity than popular networks. The result proves that it can be extended to other tasks about classification.
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    ThesisItemOpen Access
    Ultrasound assisted nanocellulose extraction from microwave pre-treated rice straw to develop bio-nanocomposite for active packaging of horticultural produce
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2022-04) Bhat, Mohd Ishfaq; Shahi, Navin Chandra
    Lignocellulosic biomass (especially agricultural residue) is a sustainable feedstock for production of value-added materials through specific processing techniques and sequences as per the desired end-product. The present study aimed to utilize one such agro-residue viz. rice straw by converting it into high crystalline nanocellulose to develop a bifunctional bio-nanocomposite for active packaging of horticultural produce. The first objective involved the application of a modified microwave assisted sodium chlorite pretreatment for intensive and quick delignification of rice straw. The effect of four critical process parameters on the delignification percentage of the rice straw was studied. The delignification was manifested by characterization using Fourier transform infrared spectroscopy, x-ray diffraction and scanning electron microscopy. Using a Box-Behnken experimental design (BBD), the effect of four critical process parameters, viz. microwave power (480-800 W), microwave treatment time (4-12 min), bleaching solution concentration (0.4-3.0 %), and bleaching time (1-5 h) on the delignification (%) was investigated, and the process was optimised using response surface methodology (RSM). The experimental data best fitted a quadratic model with an R2 of 0.9964. The optimized value of process parameters in aforementioned sequence was found to be 671 W, 8.66 min, 2.67 %, and 1h respectively, for the best delignification of 93.51 percent. The absence of lignin peaks (1516 and 1739 cm-1) was corroborated by deconstructed morphological structure and higher crystallinity index in the optimised delignified sample (53.7 %). The optimized delignified rice straw powder was then subjected to ultrasound assisted acid hydrolysis for nanocellulose extraction, preceded by the removal of hemicellulose and silica. The effect of sulfuric acid concentration (40-70%), ultrasonic treatment time (30-120 min) and ultrasound power (150-250 W) on the crystallinity index (%) and the mean particle size (nm) of the nanocellulose crystals, was studied through BBD and optimized through RSM. The optimum process parameters were obtained as 51.62 % sulfuric acid concentration, 48.55 min ultrasonic treatment time and 238. 80 W ultrasound power. The mean particle size and the crystallinity index at these optimum parameters were 69.01nm and 89.72 %, respectively. The spectral characterization revealed the increased intensity of peaks corresponding to the cellulose. The transmission micrograph of the nanocellulose revealed a rod like structure with average length and width of 190 ± 6 nm and 35 ± 3 nm, respectively. The nanocellulose crystals at 1, 5 and 10% concentration levels were used for reinforcement of chitosan biopolymer along with the addition of the titanium dioxide (TiO2) nanoparticles at its 1, 3 and 5% concentration levels. The overall performance of the developed bio-nanocomposite was measured in terms of thermal, mechanical, water vapor permeability (WVP) and water sensitive properties. Thickness of the developed films varied from 0.12 to 0.17 mm. The WVP and the tensile strength were reduced and increased by 27 % and 78 %, respectively for bio-nanocomposite with 10 % cellulose nanocrystals and 3% TiO2 concentration. The thermal stability of the developed bio-nanocomposite was better as compared to neat chitosan film in terms of higher glass transition and melting temperature. The best bio-nanocomposite was used for storage study of fresh-cut apple slices. The developed bio-nanocomposite showed promising results in terms of preserving the firmness, color and the radical scavenging activity of fresh-cut apple slices for a storage study period of 11 days.