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- Grace Lhouvum
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- Pia Sethi
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Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Singh, T. P.
- Rehabilitation of Red Mud Ponds at Indal, Belgaum (Karnataka)
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Indian Forester, Vol 130, No 5 (2004), Pagination: 481-497Abstract
Bauxite residue, also known as red mud, is a by-product of the Bayer Process. Bauxite is composed principally of the monohydrate and trihydrate forms of alumina in varying proportions. The research study was conducted to rehabilitate used red mud ponds of INDAL (Indian Aluminium Company Ltd.), Belgaum, Karnataka, India, by identifying suitable trees, grasses, and legume species as well as amenders, including bacteria and mycorrhizae, to improve the physico-chemical condition of red mud deposits and convert it to a substrate. Amenders such as gypsum, FYM (farmyard manure), fly ash/vegetative dust in different proportions, forming three basic combinations, A, B, and C, were developed. These three combinations were then treated with the bacteria and mycorrhizae both alone, and in combination, to form twelve treatments and one control. The research study showed that there is remarkable change in the physical and chemical properties of red muod after amendment, which provides the platform for plantation growth. The best combination found for treating red mud ponds was: Red mud + 20% FYM + 10% Gypsum + 15% Fly ash + Bacteria + Mycorrhizae for four tree species, Prosopis julijlora, Acacia nilotica, Pangamia pinnata and Melia azedarach, and three grass/legume species Brachiaria mutica, Chloris gayana, and Sesbania sesban.- Potential of Farm Forestry in Carbon Sequestration
Abstract Views :404 |
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Indian Forester, Vol 129, No 7 (2003), Pagination: 839-843Abstract
The Kyoto Protocol allows assistance being given for sustainable development as a contribution to carry out the ultimate objective, ie. Reduction of GHG emissions. Forests act as carbon sinks, therefore, farm forestry can be immensely useful for CO2 sequestration. The article presents a case study in this context from Pilibhit District (Uttar Pradesh). The land holders, divided into three categories - small, medium and large holdings, the majority ofland being with medium landholders. Medium farmers grow more trees on their lands as compared to other categories. Usually, Eucalypts, Poplar, Teak, Kadam are being planted. It is estimated that total biomass production is likely to be 32,800 tonnes/year and the stored carbon 16,400 tonnes/year. Thus farm forestry holds tremendous potential for sequestering and storing carbon.- Resource Rehabilitation with Rural Development: the New JFM Paradigm
Abstract Views :285 |
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Indian Forester, Vol 127, No 6 (2001), Pagination: 661-670Abstract
Joint Forest Management (JFM) experiences in India have revealed the crucial role that social and economic incentives play in sustaining these efforts. JFM was conceived as a sustainable management system based on active participation of forest fringe dwellers whose opportunity cost was compensated by giving some rights and privileges on forest products. However, the definition and scope of the JFM programme is being expanded from rehabilitation of degraded forest lands to socio-economic development of resource-dependent communities; from managing resources for meeting peoples' demand for forest products to managing pressures through alternatives. The purpose of this paper is two fold: (i) to assess the extent to which the sustainability of JFM programme is dependent on rural development and (ii) to evaluate the extent of effects of already taken rural development efforts in four States under JFM namely Andhra Pradesh, Haryana, Madhya Pradesh and West Bengal. It is seen that from a forest resource management programme, States have adopted an integrated approach of rural development to supplement forest protection measures. The emphasis is now on meeting the social, economic and human development needs of communities. The village-level institutions created for natural resource management are also emerging as the focal point for rural development and each of these functions is mutually enriching and supportive. The paper traces this paradigm shift, ably supported by examples from across the country to present the crucial role for socio-economic development of communities for sustaining join forest management initiatives. It emphasises that a self-reliant community is a prerequisite for sustaining forests and should be the basic philosophy for community Forestry Programme.- Village Resource Development as an Incentive to Sustain the Joint Forest Management Programme
Abstract Views :415 |
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Indian Forester, Vol 127, No 11 (2001), Pagination: 1215-1222Abstract
Case studies from India indicate that village resource development activities may provide an important incentive for sustaining interest in the Joint Forest Management Programme apart from leading to improvements in people's livelihood status. Ensuring sustain ability of such activities , however , requires several innovative measures including the development of village funds and enhancing of inter-sectoral linkages.- Carbon Sequestration through Farm forestry: Case from India
Abstract Views :334 |
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Indian Forester, Vol 126, No 12 (2000), Pagination: 1257-1264Abstract
Forests constitute both a sink and a source of atmospheric CO2, In developing countries like India, the potential land area available for the implementation of forest management options for carbon conservation and sequestration is constrained by socio-economic circumstances. Farm Forestry involves the growth and management of trees on private lands and this provides an excellent opportunity for carbon sequestration while supplying wood and non-wood products to meet both domestic and market requirements. Under the Farm Forestry programme in the State of Uttar Pradesh in India, nearly 1906.8 million trees have been planted during the period 1979-94 of 1525.44 million are estimated to be surviving. In terms of land coverage, this works out to over one million hectares. This is significant and adds up to nearly 30% of the entire good natural forest cover in U.P. State. It is estimated that nearly 20 million tonnes of Carbon has been sequestered by these Farm Forestry plantations. Government policies and programmes that are supportive of Farm Forestry, could be the major instruments for increasing carbon sequestration from Farm Forestry, thus contributing to the implementation of the Climate Change Policy.- Quantitative Analyses of some Biochemical Constituents in Leucas Species
Abstract Views :295 |
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Indian Forester, Vol 120, No 4 (1994), Pagination: 374-375Abstract
No abstract- Comparative Analysis of the Performance of Seedlings of Some Forest Tree Species Under the Influence of Fertilisers
Abstract Views :215 |
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Indian Forester, Vol 115, No 10 (1989), Pagination: 714-723Abstract
Analysis of growth responses of seven broad-leaved tree species under various fertiliser treatments in the nursery conditions indicate that fertiliser applications lead to a marked improvement in growth response as determined by parameters like seedling height, stem girth, as well as the widlh and length of the leaves.- Comparative Analysis of the Performance of Seedlings of some Forest Tree Species under the Influence of Fertilisers
Abstract Views :312 |
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Indian Forester, Vol 114, No 8 (1988), Pagination: 417-428Abstract
The present work has been aimed at analysing the growth response of seven indigenous tree species under the various fertiliser treatments in the field conditions. The results obtained have revealed that a marked improvement in growth responses takes place by fertiliser application. However, any recommendation as to the fertiliser and its dosage for a particular species will have to take into consideration soil characteristics of the plantation site. Keeping in view the above limitation, specific recommendations of fertiliser doses have been made for the seven species investigated.- 'Warsaw Redd+ Framework' Achieved in Cop 19 of UNFCCC
Abstract Views :605 |
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Authors
Affiliations
1 Forests and Climate Change Division, Indian Council of Forestry Research and Education (ICFRE) P.O. New Forest, Dehradun
2 Forests and Climate Change Division, Indian Council of Forestry Research and Education (ICFRE) P.O. New Forest, Dehradun, IN
1 Forests and Climate Change Division, Indian Council of Forestry Research and Education (ICFRE) P.O. New Forest, Dehradun
2 Forests and Climate Change Division, Indian Council of Forestry Research and Education (ICFRE) P.O. New Forest, Dehradun, IN
Source
Indian Forester, Vol 140, No 1 (2014), Pagination: 104-105Abstract
no abstract- Innovation and Competitiveness among Small Scale Autoparts Industry of Punjab, India
Abstract Views :355 |
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Authors
Affiliations
1 School of Behavioral Sciences and Business Studies, Thapar University, Patiala (Punjab), IN
2 Symbiosis International University, Pune (M.S.), IN
3 Thapar University, Patiala (Punjab), IN
1 School of Behavioral Sciences and Business Studies, Thapar University, Patiala (Punjab), IN
2 Symbiosis International University, Pune (M.S.), IN
3 Thapar University, Patiala (Punjab), IN
Source
International Journal of Commerce & Business Management, Vol 7, No 2 (2014), Pagination: 377-387Abstract
Innovation is a key factor for survival and sustainable growth for small scale enterprises in the competitive business environment. This paper investigates the role of regional innovation system upon the factors responsible for innovation and competitiveness among smallscale autoparts Industry. The data was collected from 110 small scale Autoparts enterprises through questionnaire cum interview schedule using single source. The study revealed that regional innovation system has a strong influence on the innovativeness of Industries through enhancement in their absorptive capacity and transfer of tacit knowledge causing incremental process innovations. Further, their existence in autoparts cluster and entrepreneurship skills of the owners were also contributing factors for the innovativeness. In addition, the research found that small scale entrepreneurs with the constrained resources of organization structure and human capital was driven to think 'low cost'; 'low tech' incremental innovations to sustain in the cut throat competition.Keywords
Small Scale Auto Part Industry, Innovation, Absorptive Capacity, Regional Innovation System.References
- Asheim, B. and Isaksen, A. (2001). Regional innovation systems: the integration of local sticky and global ubiquitous knowledge. J. Technol. Transfer, 27(1) : 77-86.
- Asheim, B.T. and Coenen, L. (2006). Contextualizing regional innovation systems in a globalizing learning economy: on knowledge bases and institutional frameworks. J. Techno. Transfer, 31(1) : 163-173.
- ACMA (2012). A report of Automotive Component Manufacturers Association of India (ACMA). January, 2012.
- Beaver, G. and Prince, C. (2002). Innovation, entrepreneurship and competitive advantage in the entrepreneurial venture. J. Small Bus. & Enterprise Develop., 9(1) : 28-37.
- Bessant, J. (2003). High involvement John Wiley and Sons Ltd., Chichester.
- Cohen, W. and Levinthal, D. (1990). Absorptive capacity: a new perspective on learning and innovation. Administrative Sci. Quarterly, 35(1) : 128-152.
- Cooke, P. and Morgan, K. (1998). The associational economy : firms, regions and innovation. Oxford University Press, Oxford, UNITED KONGDOM.
- Cooke, P., Bockholt, F. and Todtling, F. (2000). The governance of innovation in Europe. London Pinter.
- Cooke, P., Heidenreich, M. and Braczyk, H.J. (2004). Regional innovation systems (2nd Ed.) (London: Routledge).
- Cornelius, Herstatt, Tiwari, Rajnish, Dieter Ernst and Stephan Buse (2008). India's national innovation system: Key elements and corporate perspectives : TIM/TUHH Working Paper 51 January 2008, pp 23-50.
- Deshpande, R., Farley, J. and Webster, F. (1993). Corporate culture, customer orientation and innovativeness in Japanese firms: a quadrat analysis. J. Mktg., 57 : 2-27.
- Dickson, P.H., Solomon, G.T. and Weaver, K.M. (2008). Entrepreneurial selection and success: does education matter? J. Small Bus. & Enterprise Develop., 15(2) : 239- 258.
- Ettlie, J. (1999). Managing innovation. John Wiley and Sons, Inc. NEW YORK, U.S.A.
- Fazizadeh, A. (2010). An investigation of innovation in small scale industries located in science park of Iran. Internat. J. Bus. & Mgmt., 5(10) : 148-155.
- Fritsch, M. (2001). Co-operation in regional innovation systems. Regional Stud., 35(4) : 297-307.
- Hayton, J.C. (2003). Strategic human capital management in SMEs: an empirical study of entrepreneurial performance.Human Resource Mgmt., 42(4) : 375-391.
- Jaehoon, R., Taekyung, P. and Lee, H. (2010). Drivers of innovativeness and performance for innovative SMEs in South Korea: Mediation of learning orientation. Technovation, 30(1) : 65-75.
- Keogh, W. and Stewart, V. (2000). Identifying the skill requirements of the workforce in SMEs: Findings from a European social fund project. J. Small Bus. & Enterprise Develop., 8(2) : 140-149.
- Kharbanda, V.P. (2001). Facilitating innovation in Indian small and medium enterprises-The role of clusters. J. Curr. Sci., 80(3) : 343-348.
- Lange, T., Ottens, M. and Taylor, A. (2000). SMEs and barriers to skills development: a Scottish perspective. J. European Industrial Training, 24(1) : 5-11.
- Laursen, K. and Foss, N.J. (2003). New human resource management practices, complementarities, and the impact on innovation performance. Cambridge J. Econo., 27 : 253-263.
- Massa, S. and Testa, S. (2008). Innovation and SMEs : Misaligned perspectives and goals among entrepreneurs, academics, and policy makers. Technovation, 28(7) : 393-407.
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- Development of a Model to Foster Innovation Culture: A Study of Small Scale Autoparts Manufacturing Industry of Punjab
Abstract Views :499 |
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Authors
Affiliations
1 School of Behavioural Sciences and Business Studies, Thapar University, Patiala (Punjab), IN
2 Symbiosis International University, Pune (M.S.), IN
3 Thapar University, Patiala (Punjab), IN
1 School of Behavioural Sciences and Business Studies, Thapar University, Patiala (Punjab), IN
2 Symbiosis International University, Pune (M.S.), IN
3 Thapar University, Patiala (Punjab), IN
Source
International Journal of Commerce & Business Management, Vol 7, No 2 (2014), Pagination: 277-283Abstract
Innovation has been the major strategic tool used by global organizations for dominating the global markets. Innovation as a process, which was earlier visible only in the big organizations, who serve high end markets, has now become a basic necessity in every organization and in all parts of their value chain. In the 21st century, it's the very nature of innovation that has changed; it's happening faster, it's more open and collaborative. In a number of countries today innovation has become one of the key factors propelling economic growth and enhancing social benefits. Innovation needs to be built into the culture of an organization to enable it to gain sustainability by involving and inspiring every process associated with the organization. Innovation is a continuous process of creating new ideas and accumulation of knowledge within an enterprise. This paper investigates the combined effect of regional innovation system and organisation culture to develop a model to foster innovation culture among small-scale autoparts industry of Punjab state. The usable data from 110 small scale Autoparts enterprises was obtained through questionnaire cum interview schedule method. Model-I was developed to assess the status of innovation culture in an organisation and the Model-II helps in analyzing the influence of regional innovation system on the innovation culture of an organisation. The study revealed that regional innovation system has a strong positive influence on innovativeness of organizations.Keywords
Innovation Culture, Auto Part Industry, Absorptive Capacity, Regional Innovation System.- Comparative Study of Feed-Forward Neuro-Computing with Multiple Linear Regression Model for Milk Yield Prediction in Dairy Cattle
Abstract Views :327 |
PDF Views:111
Authors
Affiliations
1 Symbiosis Institute of Geoinformatics, Symbiosis International University, Pune 411 016, IN
1 Symbiosis Institute of Geoinformatics, Symbiosis International University, Pune 411 016, IN
Source
Current Science, Vol 108, No 12 (2015), Pagination: 2257-2261Abstract
The main objective of this work is to compare the accuracy of artificial neural networks (ANNs) and multiple linear regression (MLR) model for prediction of first lactation 305-day milk yield (FL305DMY) using monthly test-day milk yield records of 443 Frieswal cows. We have compared four versions of feed forward algorithm with conventional statistical model. The performancre of ANN is found to be better than the MLR model for milk yield prediction. The Bayesian regularization neural network model was able to predict milk yield with 85.07% accuracy as early as 126th day of lactation. It has been found that R2 value of the models increases with increase in the number of test-day milk yield records.Keywords
Artificial Neural Network, Dairy Cattle, Milk Yielded, Multiple Linear Regression.- Soil Organic Carbon Stocks Under Different Forest Types in India
Abstract Views :280 |
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Authors
Affiliations
1 Biodiversity and Climate Change Division, Directorate of Research Indian Council of Forestry Research and Education, P.O. New Forest, Dehradun - Uttarakhand, IN
1 Biodiversity and Climate Change Division, Directorate of Research Indian Council of Forestry Research and Education, P.O. New Forest, Dehradun - Uttarakhand, IN
Source
Indian Forester, Vol 142, No 3 (2016), Pagination: 207-212Abstract
India has stabilized its forest and tree cover which is about 24.01 per cent of its total geographical area. Forests store significant amounts of carbon in its biomass, litter, dead woods and soil; and it has a major role in climate change adaptation and mitigation. Soil carbon is the largest terrestrial carbon pool and it holds a very important role in the carbon cycle. Soil samples were collected from all major forest types in different parts of the country as well as from adjoining non-forest areas for estimating the loss of soil organic carbon due to land conversion. The results of this study indicated that maximum soil organic carbon stock was under tropical moist deciduous forests (1665.65 million tonnes) followed by tropical dry deciduous forests (1572.38 million tonnes) and least under Himalayan dry temperate forests (3.85 million tonnes). The total soil organic carbon stocks i.e., 4327.36 million tonnes and 4680.25 million tonnes were estimated under the forests in the year 1995 and 2007 respectively. The estimate showed that due to increase in forest cover during the assessment period, soil in Indian forests acted as a net sink of 352.89 million tonnes of soil organic carbon. The maximum increase in soil organic carbon stock during this period was under tropical moist deciduous forests (125.91 million tonnes) and the least increase was under Himalayan dry temperate forests (0.23 million tonnes).Keywords
Soil Organic Carbon Stock, Forests, Forest Types, India.- Temporal Relations amongst 5-Methoxyindolamines in Influencing the Gonadal Activity in the Freshwater Catflsh, Clarias batrachus
Abstract Views :277 |
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Authors
Affiliations
1 Department of Zoology, Govt PG College Pratapgarh, Chittorgarh, Rajasthan, IN
2 Fish Endocrinology Laboratory, Department of Zoology, BHU, Varanasi-221 005, IN
1 Department of Zoology, Govt PG College Pratapgarh, Chittorgarh, Rajasthan, IN
2 Fish Endocrinology Laboratory, Department of Zoology, BHU, Varanasi-221 005, IN
Source
Journal of Endocrinology and Reproduction, Vol 7, No 1&2 (2003), Pagination: 62-63Abstract
Effects of melatonin (MEL), 5 methoxytryptamine (5-MT), 5-methoxytryptophan (5-MTP) and 5-methoxytrptophol (5-MTL) were studied on the circulating levels of testosterone (T), estradiol 17β (E2) and Gonadosomatic Index (GSI) during the early-preparatory and early prespawning phases of the annual reproductive cycle of the freshwater catfish, Clarias batrachus.- Forests under Paris Climate Agreement
Abstract Views :287 |
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Authors
Affiliations
1 BCC Division, ICFRE Hqs, Dehradun, IN
1 BCC Division, ICFRE Hqs, Dehradun, IN
Source
Indian Forester, Vol 142, No 5 (2016), Pagination: 513-514Abstract
No Abstract.- Forestry Sector Contribution to India's INDC to UNFCCC
Abstract Views :220 |
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Authors
Affiliations
1 Biodiversity and Climate Change Division, Indian Council of Forestry Research and Education, Dehradun (Uttrakhand), IN
1 Biodiversity and Climate Change Division, Indian Council of Forestry Research and Education, Dehradun (Uttrakhand), IN
Source
Indian Forester, Vol 142, No 7 (2016), Pagination: 711-712Abstract
No Abstract.- Comparative Studies on the Effects of Certain Treatments on the Antitryptic Activity of the Common Indian Pulses
Abstract Views :268 |
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Authors
Affiliations
1 Department of Biochemistry, Punjab Agricultural University, Ludhiana, IN
1 Department of Biochemistry, Punjab Agricultural University, Ludhiana, IN
Source
The Indian Journal of Nutrition and Dietetics, Vol 15, No 10 (1978), Pagination: 341-345Abstract
After the discovery of the antitryptic activity in the extracts of soybean, a large number of trypsin inhibitors have been isolated from the plant sources, especially from the leguminous seeds. Though these trypsin inhibitors have been found to be distributed in the different parts of the plant like seeds, leaves, cotyledons, ischolar_mains and stems; depending upon the plant species, they are mostly present in the seeds. As the legumes form an important part of the diet in the underdeveloped and the developing countries like India, a number of attempts have been made to improve their nutritional value by using heat treatments to destroy the trypsin inhibitor.- A Statistical Analysis to Evaluate the Factors Impairing Performance of the Tool and Auto-Component Industry
Abstract Views :249 |
PDF Views:0
Authors
Tarun Nanda
1,
T. P. Singh
1
Affiliations
1 Mechanical Engg. Dept., Thapar University, Patiala, IN
1 Mechanical Engg. Dept., Thapar University, Patiala, IN
Source
Manufacturing Technology Today, Vol 7, No 10 (2008), Pagination: 31-35Abstract
Small scale manufacturing industry (SSMI) is a very important sector of our economy. It contributes almost 40% of the gross industrial value added to the Indian economy and about 45% of the Indian exports. Small scale units offer high employment potential and have low capital-output and capital-labor ratios. These characteristics make small scale sector very significant in a capital scarce and labor abundant economy like India. Though there has been a conspicuous increase in the number of small scale units, industrial sickness in this sector has assumed very serious proportions. Many causes account for the sickness. The present work discusses the results of a survey conducted in 93 small scale industries. The main factors impairing the performance of machine tool, cutting tool and auto-component industry have been identified and discussed. The survey also analyzes the extent of government support to the industry in its technology development initiatives.- Development of Lifetime Milk Yield Equation Using Artificial Neural Network in Holstein Friesian Cross Breddairy Cattle and Comparison with Multiple Linear Regression Model
Abstract Views :378 |
PDF Views:114
Authors
Affiliations
1 Symbiosis Institute of Geo-Informatics, Symbiosis International University, Pune 411 016, IN
1 Symbiosis Institute of Geo-Informatics, Symbiosis International University, Pune 411 016, IN
Source
Current Science, Vol 113, No 05 (2017), Pagination: 951-955Abstract
The scope of this study was to develop lifetime milk yield (LTMY) prediction equation using different economical traits. The traits used were first lactation length, first peak yield, first lactation total milk yield,and total of three lactation milk yield of 1210 Holstein Friesian crossbred dairy cattle in India. Four variants of feed-forward back propagation algorithms were compared with the multiple linear regression model.The performance of Bayesian regularization (BR) algorithm was found to be better than the other algorithms for LTMY prediction. The BR neural network model was able to predict milk yield with 71.18% R2.Keywords
Artificial Neural Network, Cows, Lifetime Milk Yield, Multiple Linear Regression.References
- Anon., Livestock Survey Report, 2012–13, Association of Livestock Industry (CLFMA), Mumbai, Maharashtra, India.
- Anon., Department of Animal Husbandry, Dairying and Fisheries, Ministry of Agriculture, Government of India, Annual Report, 2012–13.
- Anon., International Union of Food (IUF) Dairy Industry Research, A report on Indian Dairy Industry, 2011.
- Ruhil, A. P. et al., Prediction of lactation yield based on partial lactation records using artificial neural networks. In Proceedings of the Fifth National Conference on Computing for National Development (INDIACom-2011), New Delhi, 2011.
- Sharma, A. K., Sharma, R. K. and Kasana, H. S., Empirical comparison of feed-forward connectionist and conventional regression models for prediction of first lactation 305-day milk yield in Karan Fries dairy cows. Neural Comput. Appl., 2006, 15, 359–365.
- Njubi, M. et al., Milk yield prediction in Kenyan Holstein– Friesian cattle using the computer neural network system. Livestock Res. Rural Dev., 2009, 21(4).
- Gandhi, R. S. and Dongre, V. B., Prediction of first lactation 305day milk yield based on monthly test day records using artificial neural networks in Sahiwal cattle. Indian J. Dairy Sci., 2012, 65(3), 229–233.
- Sanzogni, L. and Kerr, D., Milk production estimates using feed forward artificial neural networks, Comput. Electron. Agric., 2001, 32, 21–30.
- Gençay, R. and Min, Q., Pricing and hedging derivative securities with neural networks: Bayesian regularization, early stopping and bagging. IEEE Trans. Neural Networks, 2001, 12(4), 726–734.
- Kasthurirangan, G., Effect of training algorithms on neural networks aided pavement diagnosis. Int. J. Eng., Sci. Technol., 2010, 2(2), 83–89.
- MacKay, D. J. C., Bayesian interpolation. Neural Comput., 1992, 4, 415–447.
- Demuth, H. B. and Beale, M. H., Neural Network Toolbox – For Use with Matlab, User’s Guide, Version 4, 2002.
- Hagan, M. T., Demuth, H. B. and Beale, M., Neural Network Design. Variations on Backpropagation, Fourth Indian reprint, 2011, pp. 12–14; 19; 46.
- Beale, M. H., Hagan, M. T. and Demuth, H. B., Neural Network Toolbox – User’s Guide R2013b, 2013.
- Yegnanarayana, B., Artificial Neural Networks. Feedforward Neural Networks, Nineteenth Printing, 2012, pp. 117; 130–131.
- Khazaei, J. and Nikosiar, M., Approximating milk yield and milk fat and protein concentration of cows through the use of mathematical and artificial neural networks models. In World Conference on Agricultural Information and IT. Tokyo, Japan, 2008, pp. 91–105.
- Gandhi, R. S., Raja, T. V., Ruhil, A. P. and Kumar, A., Prediction of lifetime milk production using artificial neural network in Sahiwal cattle. Indian J. Anim. Sci., 2009, 79(10), 1038–1040.
- Gandhi, R. S., Raja, T. V., Ruhil, A. P. and Kumar, A., Artificial neural network versus multiple regression analysis for prediction of lifetime milk production in Sahiwal Cattle. J. Appl. Anim. Res., 2010, 38, 233–237.
- Bhosale, M. D. and Singh, T. P., Comparative study of feedforward neuro-computing with multiple linear regression model for milk yield prediction in dairy cattle. Curr. Sci., 2015, 108(12), 2257–2261.
- Grzesiak, W. and Blaszczyk, P., Methods of predicting milk yield in dairy cows – predictive capabilities of Wood’s lactation curve and artificial neural networks (ANNs). J. Comput. Electron. Agric., 2006, 54, 69–83.
- Dongre, V. B. and Gandhi, R. S., Comparative efficiency of artificial neural networks and multiple linear regression analysis for prediction of first lactation 305-day milk yield in Sahiwal cattle. Livestock Science, 2012, 147, 192–197.
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Authors
Sanjeev Kumar
1,
T. P. Singh
2
Affiliations
1 Department of Mechanical Engineering, Punjab Engineering College, Chandigarh-160012, IN
2 Department of Mechanical Engineering, Thapar Institute of Engineering and Technology, Patiala-147004, Punjab, IN
1 Department of Mechanical Engineering, Punjab Engineering College, Chandigarh-160012, IN
2 Department of Mechanical Engineering, Thapar Institute of Engineering and Technology, Patiala-147004, Punjab, IN