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concerned that though India is the largest producer of milk in the world had an insignificant share in the global export market. The large quantity of milk stills remains unprocessed (or is handled by the unorganised sector as given in Fig.1). India is surrounded by milk deficient countries like China, Japan, Banglades... | D4239118419.pdf | Agriculture business |
should be given at a subsidized rate to the small farmer. Secondly, credit facilities at a concessional rate with a more extended moratorium period and the longer repayment schedule should be arranged for the rural entrepreneur. Thirdly high-quality local breed cattle with high lactation yield must be made available to... | D4239118419.pdf | Agriculture business |
& Industry, GOI. Retrieved August 29, 2018, from http://apeda.gov.in/apedawebsite/ 3. Avhad, S. R., Kadian, K. S., Verma, A. K., & Kale, R. B. (2015). Entrepreneurial behaviour of dairy farmers in Ahmednagar district of Maharashtra, India. Agricultural Science Digest A Research Journal, 35(1), 56. https://doi.org/10.59... | D4239118419.pdf | Agriculture business |
Asian Journal of Management Sciences, 02(March), 170–172. 12. Kumar, A., & Parappurathu, S. (2014). Trends in the consumption of milk and milk products in India: implications for self-sufficiency in milk production. Food Security: The Science, Sociology and Economics of Food Production and Access to Food, 6(August). ht... | D4239118419.pdf | Agriculture business |
Manmeet Singh Junior Research Fellow (JRF) Department Of Economics Punjabi University, Patiala,India P: ISSN No. 2394-0344 RNI No. UPBIL/2016/67980 VOL.IX , ISSUEII May 2024 E: ISSN No. 2455-0817 Remarking An Analisation Dairy Farming In India: A Theoretical Review Paper Id : 18920 Submission Date : 09/05/2024 Acceptan... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
positive aspects dairy farming too had various problems including inadequate infrastructure, lack of quality control, inefficient supply chain, absence of adequate policies and untrained manpower. Keywords Dairy farming, Supply chain, Marketing Chain, Food Safety Measures, Entrepreneurial behavior, Efficiency. Introduc... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
The livestock sector helps ease inequality and poverty in the country’s rural areas and creates jobs for farmers. Dairy is an important sub-sector in India’s rural economy within the livestock sector (Parida et al., 2022). The Indian dairy farming system is witnessing a gradual transformation from traditional productio... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
Many research studies related to the overview of dairy farming in India have been reviewed. The contribution of dairy sector in respect of women empowerment, supply chain and marketing chain, food safety measures in dairy sector, entrepreneurial behavior and sources of information utilized by dairy farmers and efficien... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
facilities. Brar et al., (2018) explored the factors influencing choice of milk marketing channel among small and medium dairy farmers in Punjab. The study used a binomial logistic regression model for the analysis. The study categorized marketing channels into organized and unorganized and revealed that age of househo... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
in enhancing the performance of the dairy companies in the form of an increase in performance matrix indicators. The study suggested the dairy firms to shift their business from the traditional approach to ICT enabled supply chain system as it enables the dairy firms to support with the various business functions along... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
Measures Ruegg, (2003) explored the practical interventions that can enhance the safety of dairy products and dairy farm environment. The study reviewed other works and revealed that safety of dairy products can be enhanced by minimizing the sources of microbial contamination of milk by adopting adequate hygienic stand... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
study used two-stage residual inclusion method for the analysis. The study revealed that on an average dairy farmer adopted only 29 percent of the recommended FSM. The herd size, experience in dairy farming, caste of farmers and share of milk consumed at home were found to influence adoption of FSM positively. The econ... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
export potential. In a recent study Nyokabi et al., (2024) empirically invested the adoption of Food Safety Measures (FSM) in small holder dairy systems. The study used the cross sectional survey including 159 farming households and 18 participant observations from participating farms. The study considered 36 different... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
behavior of dairy farmers in Punjab” to ascertain these needs of dairy farmers of state Punjab in India. The study revealed that 23.52 percent dairy farmers had attended training programmes organized by universities, dairy development board, cooperatives; animal husbandry department etc at some point of time, the remai... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
maximum utilization with Mean Rank Score (MRS) of 5.31 and Mean Score (MS) of 1.063 followed by mass media sources with MRS of 6.41 and MS of 0.802, followed by personal cosmopolite channel with MRS of 7.61 and MS 0.755 and the least used were personal localite sources with MRS of 1.28 and MS 0.517. The regression anal... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
positive and significant relationship between education, annual income, training, scientific orientation, group cohesion and creativity with entrepreneurial behavior. The variables such as age and credit orientation exhibited non-significant correlation coefficients and thus indicated no significant relationship with e... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
industry. For total asset turnover ratio and inventory turnover ratio the p value was 0.000 which was less than 0.05 resulting in rejection of null hypothesis, revealing significant differences between total asset turnover ratios and inventory turnover ratio in Indian dairy industry. George et al., (2022) tried to exam... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
cost was found positively significant to milk production whereas labor cost was negatively significant. The determinants of technical inefficiency estimates revealed that the education, marketed surplus and distance from milk sale place had negative association with technical inefficiency. Yadaveni et al., (2023) inves... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
in the literature relevant to the dairy sector including inadequate infrastructure, lack of quality control, inefficient supply chain, absence of adequate policies and untrained manpower. Despite of this, the dairy sector has awesome potentials for development in the coming decades and requires proper policy initiative... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
entrepreneurs in dairying enterprise of Mathura district on the basis of social participation. 8. Gayathri, S. L., Bhakat, M., & Mohanty, T. K. (2023). An outlook on commercial dairy farming in India: A review. Indian Journal of Animal Production and Management, 37(1), 45-56. 9. George, S., Saseendran, P. C., Anil, K. ... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
243-254. 15. Kumar, A., Wright, I. A., & Singh, D. K. (2011). Adoption of food safety practices in milk production: Implications for dairy farmers in India. Journal of International Food & Agribusiness Marketing, 23(4), 330-344. 16. Kumar, R. (2022). Information and communication Technology (ICT) effect on supply chain... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
Evidence from Indian States. International Journal of Innovative Research in Engineering & Management, 9(2), 196-206. 24. Paul, U. K. (2024). Estimation of technical efficiency of chemical-free farming using data envelopment analysis and machine learning: evidence from India. Benchmarking: An International Journal, 31(... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
Sciences, 189, 285-291. 31. Tamang, R., Chutia, P., Talukdar, D., Swargeary, B. D., & Kalita, D. J. (2023). Study on socio economic status of dairy farmers and its impact on environment at Topatoli village of Kamrup Metropolitan district of Assam, India. In Report of the ICSSR Sponsored National Seminar on (Vol. 13, p.... | Dairy Farming In India A Theoretical Review.pdf | Agriculture business |
AI-Based Teat Shape and Skin Condition Prediction for Dairy Management Yuexing Hao *†, Tiancheng Yuan *, Yuting Yang *, Aarushi Gupta, Matthias Wieland, Ken Birman, Parminder S. Basran Ithaca NY, USA {yh727, ty373, yy354, ag2288, mjw248, psb92, kpb3}@cornell.edu Abstract Dairy owners spend significant effort to keep th... | Dairy science.pdf | Agriculture business |
changes that might be early precursors of animal health issues. Our work focuses on dairy cow teat health assessment through the 1) automated and accurate teat shape assessment, and 2) creation and deployment of computer vision. There has been limited research on machine-learning techniques for solving this problem eve... | Dairy science.pdf | Agriculture business |
at low cost. Accordingly, this paper focuses on three questions: 1. Can we obtain high quality still images (keyframes) from fixed video cameras in a rotary milking parlor? 2. Given a choice of images for one cow, can we select the image that best visualizes the stall-id and the cow’s teats? 3. Can we accurately classi... | Dairy science.pdf | Agriculture business |
standard laptops because we based our solutions on existing open-source, off-the-shelf AI vision tools. This contrasts with past approaches that required data-center scale computing resources and were environmentally problematic. Moreover, we expose trade-offs that other researchers with similar goals might encounter b... | Dairy science.pdf | Agriculture business |
Virkler 2017). To create a ground-truth data set for teat condition classification, our team works with veterinarians and veterinary assistants, who supervise certain milking sessions, manually scoring each cow’s teats with respect to shape and skin condition. The scoring metrics used for teat shape assessment are base... | Dairy science.pdf | Agriculture business |
learning techniques for tasks that include overall farm management (nutrition, hydration, animal activity), herd reproduction management, and animal behavior analysis (Slob, Catal, and Kassahun 2021a; Cockburn 2020; M R, N K, and V 2022a). Many in the field are arguing that the future dairy farm could be reconceived as... | Dairy science.pdf | Agriculture business |
and behavioral analysis (Rutten et al. 2013) to assist dairy management. For example, (Fauvel et al. 2019) utilized cow’s activity and temperature data in their LCE algorithm that enables automatic estrus detection. (FadulPacheco, Delgado, and Cabrera 2021) integrated data from cow’s health records to develop machine l... | Dairy science.pdf | Agriculture business |
DeLaval) Milking Statistics (Powered by DeLaval) Milking Statistics (Powered by DeLaval) Time-Series of Milking Statistics Stall ID Keyframes (Lower Angle) Timepoint + (Parallel) Timepoint Match Match Figure 2: Overall System Workflow As noted earlier, most prior research on the use of ML in dairy animal health assessm... | Dairy science.pdf | Agriculture business |
and McDaniel 1985a; Mein et al. 2001) guidelines. Although a GoPro captures video, the video data stream itself consists of a series of still images called keyframes separated by zero or more delta frames. For our work, we limited consideration to the key frames. We disable GoPro data compression and automated image to... | Dairy science.pdf | Agriculture business |
collected from the farm. This selection process discards images where teats are difficult to distinguish, with blurring or poor lighting and motion effects. For training purposes, our veterinary experts considered only the selected data, annotating a portion that we used to refine the vision model’s ability to detect t... | Dairy science.pdf | Agriculture business |
shows an individual cow for approximately 3 seconds each. Data selection proves to be surprisingly challenging. As an example, consider the identification of the stall ID. Even if an image contains an ID tag, it could be out of focus, the tag may be obstructed, or the frame may capture half of it as the parlor rotates.... | Dairy science.pdf | Agriculture business |
obtains frame-by-frame access using the OpenCV package 2. To perform teat localization,, we trained an ML model which entails identifying each of the cow’s teats and segmenting them using bounding boxes. Similar to the process used for stall ID identification, line 8 uses the function Loc(teat segments) to check two th... | Dairy science.pdf | Agriculture business |
end if 14: else if is teat key then 15: Store teat segments to folder name 16: end if 17: end while (Ren et al. 2015) model as a baseline. The foundational vision models in this project utilize either convolutional layers or multi-head attention blocks, and sometimes both. These models are benchmarked in our dataset wi... | Dairy science.pdf | Agriculture business |
Networks (RPN) to propose many potential regions of interest (RoI) and then applies a classifier backbone. YOLO-F (Chen et al. 2021), a modified version of YOLO, is a single-stage detector. We then consider the State-Of-TheArt (SOTA) models often observed to have end-to-end transformer architecture. DINO (Zhang et al. ... | Dairy science.pdf | Agriculture business |
a modified version of YOLO (Joseph Redmon 2015), YOLO-F (Chen et al. 2021). Over the past few years, transformers have achieved great success in the vision domain. We select DINO (Zhang et al. 2022) (a modified version of the first end-to-end object detector, DETR (Carion et al. 2020)) as a candidate transformer-based ... | Dairy science.pdf | Agriculture business |
41.364 million parameters, and it requires 0.208 TFLOPs (tera floating-point operations per second). For YOLO-F, using the same input shape, the model consists of 42.409 million parameters and requires 98.808 GFLOPs (giga floating point operations per second) to execute. For DINO, we have a model with 47.546 million pa... | Dairy science.pdf | Agriculture business |
around 0.133 when deployed. Such a finding indicates that the baseline model is prone to overfitting to the training set, becoming a “narrow specialist” on training data and yet giving weaker results in actual deployment. DINO is slightly slower than other models, but not significantly so. Indeed, the sub-second perfor... | Dairy science.pdf | Agriculture business |
a different angle, that same teat might have been clearly visible. A keyframe is much smaller then a full video clip, and the segmented portion of the frame containing the cow teats even more so. From our collected data, the measured average size per image frame that contains full image with four teats is 800KB on disk... | Dairy science.pdf | Agriculture business |
the improved quality and quantity of data we collected. We consider a multi-phase setup, where the deliverable for each stage would be deployed to help with further improvement that happens during the next stage. In particular, we started with a low-data paradigm, where we have quite a limited amount of data, but with ... | Dairy science.pdf | Agriculture business |
current skin condition dataset, our ratio between normal C1 labels and abnormal C3 labels is 925:44. The unbalanced dataset limits the model to learn from the abnormal situations and impacts model performance. Through largescale, long-term data collection efforts, we anticipate that our models will demonstrate improved... | Dairy science.pdf | Agriculture business |
objects from 4 distinct classes. For teat skin conditions, we generate 946 labels to train ML models for teat health analysis. In this paper, we explore different object detectors across various architectures and found that DINO performs best overall. Our automated digital-twin approach has been shown to yield accurate... | Dairy science.pdf | Agriculture business |
End-to-end object detection with transformers. In European conference on computer vision, 213–229. Springer. Chen, Q.; Wang, Y.; Yang, T.; Zhang, X.; Cheng, J.; and Sun, J. 2021. You only look one-level feature. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 13039–13048. Cockburn,... | Dairy science.pdf | Agriculture business |
Body Shape and Automation of Condition Scoring. Journal of Dairy Science, 91(11): 4444–4451. Hillerton, J. E. 2005. Teat condition scoring-an effective diagnostic tool. In Proc. of National Mastitis Council Regional Meeting, 37–43. Hogeveen, H.; Pyorala, S.; Waller, K. P.; Hogan, J. S.; Lam, T. J.; Oliver, S. P.; Schuk... | Dairy science.pdf | Agriculture business |
S.; N K, V.; and V, K. 2022a. Teat and Udder Disease Detection on Cattle using Machine Learning. In 2022 International Conference on Signal and Information Processing (IConSIP), 1–5. M R, S.; N K, V.; and V, K. 2022b. Teat and Udder Disease Detection on Cattle using Machine Learning. 1–5. Mein, G.; Neijenhuis, F.; Morg... | Dairy science.pdf | Agriculture business |
on dairy farms. Journal of Dairy Science, 96(4): 1928–1952. Schreiner, D.; and Ruegg, P. 2003. Relationship between udder and leg hygiene scores and subclinical mastitis. Journal of dairy science, 86(11): 3460–3465. Seykora, A.; and McDaniel, B. 1985a. Heritabilities of Teat Traits and their Relationships with Milk Yie... | Dairy science.pdf | Agriculture business |
and Shum, H.-Y. 2022. Dino: Detr with improved denoising anchor boxes for end-to-end object detection. arXiv preprint arXiv:2203.03605. | Dairy science.pdf | Agriculture business |
arXiv:2006.12387v3 [cs.CY] 15 Sep 2020 Leveraging traditional ecological knowledge in ecosystem restoration projects utilizing machine learning BOGDANA RAKOVA, Accenture, Responsible AI, USA ALEXANDER WINTER, California Institute of Integral Studies, USA Ecosystem restoration has been recognized to be critical to achie... | Ecological Restoration_Resource Management.pdf | Agriculture business |
actors. Furthermore, framing ML projects as open and reiterative processes can facilitate access on various levels and create incentives that lead to catalytic cooperation in the scaling of restoration efforts. ACM Reference Format: Bogdana Rakova and Alexander Winter. 2020. Leveraging traditional ecological knowledge i... | Ecological Restoration_Resource Management.pdf | Agriculture business |
for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is per... | Ecological Restoration_Resource Management.pdf | Agriculture business |
indigenous cultural practices, world views, and ways of life which offer myriad epistemological and ontological approaches, including mythologies passed down as songs and stories, embedded in geographic representations, and more [5]. It is a field of study in anthropology defined as the cumulative body of knowledge, pract... | Ecological Restoration_Resource Management.pdf | Agriculture business |
real-world applications there is often no possibility of having many feedback loops due to the high cost of failures. In the context of environmental sustainability unintended consequences of ML algorithms might have irreversible impacts. An interdisciplinary worldview can help practitioners recognize the need for mult... | Ecological Restoration_Resource Management.pdf | Agriculture business |
ecological knowledge systems. We provide an overview of how ML is currently used in the planning, execution, and monitoring stages of forest ecosystem restoration 2 Leveraging traditional ecological knowledge in ecosystem restoration projects utilizing machine learning ACM Knowledge Discovery and Data Mining (KDD) 2020... | Ecological Restoration_Resource Management.pdf | Agriculture business |
skills towards a broad range of sustainability challenges. Gomes et al. call for transformative synthesis by incorporating a combination of techniques from (1) data and ML, (2) optimization and dynamic models simulation, and (3) multi-agent crowdsourcing and citizen science [16]. Levy et al. go on to investigate the li... | Ecological Restoration_Resource Management.pdf | Agriculture business |
for ML governance in regenerative ecosystem practices could make use of a framework proposed by Suresh and Guttag which identifies the following biases: (1) historical bias, (2) representation bias, (3) measurement bias, (4) aggregation bias, (5) evaluation bias, and (6) deployment bias [53]. Margins of error can arise ... | Ecological Restoration_Resource Management.pdf | Agriculture business |
and the 2015 Paris Agreement. These can be considered as distinct climate governance models which have been studied by policymakers and other scholars. Held and Roger (2019) provide a comparative analysis of these models [20], while other scholars bring political economy perspectives to the increasing but uneven uptake... | Ecological Restoration_Resource Management.pdf | Agriculture business |
levels in this model are: (1) the local knowledge of animals, plants, solids, and landscapes; (2) resource management, composed of local environmental knowledge, practices, and tools; (3) community and social organizing offering coordination, cooperation, and governance; and (4) worldviews involving general ethics and b... | Ecological Restoration_Resource Management.pdf | Agriculture business |
and multi-crop field historically employed in Latin America. These shifting cultivation systems, referred to as swiddens, comprise lands which are transformed for cultivation by means of skilled slashing and burning of vegetation. The Milpa woodland ecosystems are shaped without the use of fertilizers and pesticides, in... | Ecological Restoration_Resource Management.pdf | Agriculture business |
ancestormind, and pattern-mind, which can be mapped onto the five fingers of a hand and made to interact. We suggest such processes could be incorporated into ML and data science approaches in the context of ecosystem regeneration [55]. In what follows, we provide a brief analysis of how ML is used in the planning, execu... | Ecological Restoration_Resource Management.pdf | Agriculture business |
suggest that ML practitioners will benefit from new organizing principles allowing for and incentivizing teaming up with people from interdisciplinary fields during all stages of an ecosystem restoration project. In order to partner with IPLCs, a technical ML team might employ qualitative research methods while collabora... | Ecological Restoration_Resource Management.pdf | Agriculture business |
of necessary resources for ongoing ML efforts and the consideration of ML applications toward and beyond a threshold for ecosystemic self-sufficiency. 5 ACM Knowledge Discovery and Data Mining (KDD) 2020 Conference Workshop "Fragile Earth: Data Science for a Sustainable Planet", August 23–27, 2020, Virtual Conference Bogd... | Ecological Restoration_Resource Management.pdf | Agriculture business |
selective logging [22], high-resolution land cover mapping [45], and predicting forest wildfire spread [41]. Monitoring is also an important stage in the lifecycle of any ML model which is deployed in a real-world system. Continuous monitoring, integration, re-training and tuning of model parameters is part of a more ge... | Ecological Restoration_Resource Management.pdf | Agriculture business |
each project stakeholder. For the ML research team, this could include establishing practical ethical guidelines, adopting an impact assessment framework, involving impacted communities in active participation rather than passive acceptance to ensure cultural relevance to the community, as well as building community ca... | Ecological Restoration_Resource Management.pdf | Agriculture business |
action [20], we could make more informed decisions about the organizing and governance principles that could enable positive results, reducing the negative impacts of ML-based ecosystem restoration efforts. The problem of reducing environmental degradation has the characteristics of joint products, preference heterogene... | Ecological Restoration_Resource Management.pdf | Agriculture business |
which recognizes that: • Good intentions are not good enough. Acknowledging the fallacy of technological solutionism, there’s a need to stimulate incremental action within academia, the private sector, civil society, etc. Frameworks can facilitate measurability, which helps actionability and adds to the conceptual tool... | Ecological Restoration_Resource Management.pdf | Agriculture business |
as a major asset in local restoration efforts. By bringing interdisciplinary perspectives to the work of data science and machine learning scholars, we aim to highlight 7 ACM Knowledge Discovery and Data Mining (KDD) 2020 Conference Workshop "Fragile Earth: Data Science for a Sustainable Planet", August 23–27, 2020, Vir... | Ecological Restoration_Resource Management.pdf | Agriculture business |
of mind: Collected essays in anthropology, psychiatry, evolution, and epistemology. University of Chicago Press. [4] Fikret Berkes. 1993. Traditional ecological knowledge in perspective. Traditional ecological knowledge: Concepts and cases 1 (1993). [5] Fikret Berkes. 2017. Sacred Ecology: Traditional Ecological Knowle... | Ecological Restoration_Resource Management.pdf | Agriculture business |
ecosystems. Island Press. [13] European Commission High-Level Expert Group on AI. 2019. Trustworthy AI Assessment List. Technical Report. https://ec.europa.eu/newsroom/dae/document.cfm?doc_id=60440 [14] Toby A Gardner, Magnus Benzie, Jan Börner, Elena Dawkins, Stephen Fick, Rachael Garrett, Javier Godar, A Grimard, Sar... | Ecological Restoration_Resource Management.pdf | Agriculture business |
tropical selective logging. Remote sensing of environment 221 (2019), 569–582. [23] Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (2019), 900–915. [24] IPCC. 2014. Fifth Assessment Report Summary for Policyma... | Ecological Restoration_Resource Management.pdf | Agriculture business |
and beyond: the crucial role of interaction strength in the complexity– stability debate. Adaptive food webs (eds Moore JCM, de Ruiter PC, McCann KS, Wolters V.) (2017), 31–44. [34] Ronald Nigh and Stewart AW Diemont. 2013. The Maya milpa: fire and the legacy of living soil. Frontiers in Ecology and the Environment 11, ... | Ecological Restoration_Resource Management.pdf | Agriculture business |
Rico. 1998. Gender, the environment and the sustainability of development. (1998). [45] Caleb Robinson, Anthony Ortiz, Kolya Malkin, Blake Elias, Andi Peng, Dan Morris, Bistra Dilkina, and Nebojsa Jojic. 2020. Human-Machine Collaboration for Fast Land Cover Mapping.. In AAAI. 2509–2517. [46] Pedro Rodriguez-Veiga, Jame... | Ecological Restoration_Resource Management.pdf | Agriculture business |
A framework for understanding unintended consequences of machine learning. arXiv preprint arXiv:1901.10002 (2019). [54] Yadav Uprety, Hugo Asselin, Yves Bergeron, Frédérik Doyon, and Jean-François Boucher. 2012. Contribution of traditional knowledge to ecological restoration: practices and applications. Ecoscience 19, ... | Ecological Restoration_Resource Management.pdf | Agriculture business |
1. Introduction The Indian Journal of Animal Science (IJAS) is one of the most popular scientific journals in the areas of animal breeding, diseases, physiology, nutrition, dairying, animal production and fisheries. It is a peerreviewed and open access journal. It is being published by the Indian Council of Agricultura... | ICALUC_2022.pdf | Agriculture business |
of collaboration was also found 0.92 which is considered to be a weak collaboration between the authors. To cite this paper: Rohila, N.S., Singh, B.P., and Bankar, R.S.“Indian Journal of Animal Science: A Scientometric Assessment and Application of Lotka ’s Law (2015 -2020 ).” In Innovation , Growth and Sustainability ... | ICALUC_2022.pdf | Agriculture business |
Research Institute, Bareilly. During the study period the highest research publications were also found from India. Keywords: Scientometrics, Bibliometrics, biblioshiny, Web of Science (WoS), Indian Journal of Animal Science (IJAS), Lotka’s Law. Indian Journal of Animal Science: A Scientometric Assessment… 245 Bankar a... | ICALUC_2022.pdf | Agriculture business |
the minimum 262 in the year 2018. Graph 1: Yearwise production of research publications. 2. Yearwise citations of publications: Graph 2 reflects the yearwise citations received by the publisher of IJAS as per Web of Science citation database. It is evident from the graph that the maximum (522) citations received were o... | ICALUC_2022.pdf | Agriculture business |
c=2575 2n * 574 = 2575 2n = 2575/574 = 4.486 Indian Journal of Animal Science: A Scientometric Assessment… 247 Taking log both Sides n log 2 = log 4.486 n * 0.301 = 0.651 Therefore, [log2 = 0.301] n = 0.651/0.301 n = 2.16 Table 2: Observed values of y and calculated value of y when n=2.16 No. of Articles (x) No. of Aut... | ICALUC_2022.pdf | Agriculture business |
Research Institute, Bareilly 266 2. ICAR-National Dairy Research Institute, Karnal 245 3. Guru Angad Dev Veterinary Animal Science University 125 4. ICAR-National Bureau of Animal Genetic Resources 94 5. ICAR-Central Avian Research Institute 72 6. Tamil Nadu Veterinary Animal Sciences University 65 7. ICAR Central Inst... | ICALUC_2022.pdf | Agriculture business |
research papers It is clear from graph 4 that maximum number of papers (1501) authored by Indian authors followed by Iran (40), China (35), Turkey (31), Mexico (20), South Korea (19), Egypt (9), Canada (8), Malaysia (8) and Pakistan (8). These data also witness a good reputation of IJAS among the abroad countries. Indi... | ICALUC_2022.pdf | Agriculture business |
Patra, Swapan K, Bhattacharya, Partha and Verma, Neena (2005). Bibliometric Study of Literature on Bibliometrics. DESIDOC, 26(1), pp. 27-32. Rajendran, P., Jayashanker, R. and Elango, B (2011). Scientometric Analysis of Contributions to Journal of Scientific and Industrial Research. International Journal of digital Lib... | ICALUC_2022.pdf | Agriculture business |
www.ijcrt.org © 2018 IJCRT | Volume 6, Issue 2 April 2018 | ISSN: 2320-2882 IJCRT1892619 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt.org 751 DAIRY INDUSTRY IN INDIA: DEVELOPMENT AND CHALLENGES Sonwane Rajkumar Sopanrao Assistant professor of dairy science, Dept. of Dairy Science, Yeshwant Maha... | IJCRT1892619.pdf | Agriculture business |
to private dairies with metropolitan cities such as Bombay, Calcutta and Delhi and some other larger townships could claim of making available processed milk, table butter and ice cream, though not on large scale. In India, market milk industry started in 1950-51when central dairy and AERY milk colony was commissioned ... | IJCRT1892619.pdf | Agriculture business |
using secondary data collected from the various published reports, books and internet source. From the websites of NDDB.The collected data is analyzed to arrive at logical conclusions. III. RESULTS AND DISCUSSION: Dairy development under-operation flood programme: As a result of Operation Flood (OF) project more villag... | IJCRT1892619.pdf | Agriculture business |
science and technology. A multitiered www.ijcrt.org © 2018 IJCRT | Volume 6, Issue 2 April 2018 | ISSN: 2320-2882 IJCRT1892619 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt.org 752 co-operative structure was established under the operation with primary village co-operative societies at the base,... | IJCRT1892619.pdf | Agriculture business |
dairy co-operative societies had been organized in 170 milk sheds involving over 9.4 million farmer members. Thus Operation Flood has helped to establish a White revolution in the country. It is started in 1985 and came to an end in April 1996. Dairy development through following: Key village scheme ↓ Intensive cattle ... | IJCRT1892619.pdf | Agriculture business |
by Government for the development of dairy sectors of India. After Independence, the first organized attempt to develop village cattle on an effective scale was initiated with the launch of key village scheme (KVS) in 1950 during the first five-year plan. KVS is a general comprehensive scheme drawn up by Government of ... | IJCRT1892619.pdf | Agriculture business |
KVS. In 1968, 479 village blocks were functioning in various states and they covered 5 million cows and she-buffaloes which were about 6.5% of the total breedable female cattle of the country. On review of the functioning of key village scheme, it was revealed that it did not produce results according to the expectatio... | IJCRT1892619.pdf | Agriculture business |
government of Indian extended 100 percent central assistance for the project during the 3rd five-year plan. After implementation and on completion of 2 years, these protect were transferred to plan scheme of the state government. This change led to reduced financial assistance from central government. In some of the St... | IJCRT1892619.pdf | Agriculture business |
been growing. Agricultural sector (including crops, livestock, fisheries, forestry) contributed about 40 percent to the GDP in the 1960s. This gradually decreased to 36.5. Table 3 Milk production and per capita availability of milk in India Milk production and per capita availability of milk in India Year Production (M... | IJCRT1892619.pdf | Agriculture business |
for more animal proteins including milk. Table 4. Livestock population (2012 Livestock census): Sr. No Species Number(in millions) Ranking in the world population 01 Cattle 190.9 Second 02 Buffaloes 108.7 First Total (including Mithun and Yak) 300 First 03 Sheep 65.0 Third 04 Goats 135.2 Second 05 Pigs 10.3 06 Others 1... | IJCRT1892619.pdf | Agriculture business |
2018 IJCRT | Volume 6, Issue 2 April 2018 | ISSN: 2320-2882 IJCRT1892619 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt.org 755 2014-15 114,81,794 20,68,958 18.0 5,10,020 4.4 2015-16 124,58,642 21,75,547 17.5 5,60,613 4.5 Source: National Accounts Statistics-2016, Central Statistical Organization... | IJCRT1892619.pdf | Agriculture business |
India is a country that consumes its own milk production. India is neither considered an active importer or an exporter of dairy products. Yet the country provides a share in the global market still remains at small rates of 0.3 and 0.4 percent for exports and imports respectively. This is because of people who directl... | IJCRT1892619.pdf | Agriculture business |
through the organized sector. The milk processing industry of India is small compared to the huge amount of milk produced every year. Only 10% of all the milk is delivered to some 400 dairy plants. A specific Indian phenomenon is the unorganized sector of milkmen, vendors who collect the milk from local producers and s... | IJCRT1892619.pdf | Agriculture business |
that without increasing productivity, efficiency is difficult the age of globalization. 4.1 Challenges by dairy units: 1. Quality a big concern: More than 70% of the marketable surplus goes through an informal channel where quality is a big concern. Sometimes quality is an issue in the formal channel as well. Quality o... | IJCRT1892619.pdf | Agriculture business |
of middleman who reaps the actual benefit depriving the producers of their due share. 4.1.2 The practical dairy farming challenges in India: 1. Small dairy farms: Dairy animals are kept by small farmers and the number can vary from 1 to 5 animals per farm. Not be suitable to call them as dairy farms. 2. Feeding of anim... | IJCRT1892619.pdf | Agriculture business |
perishable nature of milk , the value addition such as processing, packaging, and conversion to long life products, such as sterilized milk (UHT), dahi, paneer, chhachh, lassi, shrikhand and so on, is more a necessary, while imposing GST and imperative to create a special class for dairy products with minimum value-add... | IJCRT1892619.pdf | Agriculture business |
201718, as per estimates released by CSO. India can be rated as among the best performing economies in the world on this parameter. India has become the largest producer of milk in the world and is the largest consumer of milk. This huge success in dairy development through Operation Flood largest rural development pro... | IJCRT1892619.pdf | Agriculture business |
and Rural Development: Challenges and Prospectus, Indian dairyman, April 2018, 70 (4):129-131. [7] Mario Gabriele Miranda and S. Ramachandran (2014) A Study on the Dairy Industries in India, Indian Journal of Science and Technology.7 (S5): 1–2, ISSN (Print): 0974-6846 ISSN (Online): 0974-5645. [8] Mathur B. N .2000. Cu... | IJCRT1892619.pdf | Agriculture business |
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