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Rajesh, M. K.
- Somatic Embryogenesis and Bioreactors
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1 Division of Crop Improvement, ICAR-Central Plantation Crops Research Institute, Kasaragod 671 124, IN
1 Division of Crop Improvement, ICAR-Central Plantation Crops Research Institute, Kasaragod 671 124, IN
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Current Science, Vol 108, No 10 (2015), Pagination: 1782-1783Abstract
No Abstract.Full Text
- A Machine Learning Approach for Prediction of Domains of DELLA Proteins, a Key Component of Gibberellic Acid Signaling in Plants
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Authors
Affiliations
1 ICAR-Central Plantation Crops Research Institute, Kasaragod - 671124, Kerala, IN
2 AIMIT, St. Aloysius College, Mangalore - 575002, Karnataka
3 ICAR-Central Plantation Crops Research Institute, Kasaragod - 671124, Kerala
1 ICAR-Central Plantation Crops Research Institute, Kasaragod - 671124, Kerala, IN
2 AIMIT, St. Aloysius College, Mangalore - 575002, Karnataka
3 ICAR-Central Plantation Crops Research Institute, Kasaragod - 671124, Kerala
Source
Indian Journal of Science and Technology, Vol 9, No 12 (2016), Pagination:Abstract
Background/Objective: For the annotation of large scale proteins, generally computational methods or tools are used. One of the drawbacks of these annotation tools is that they are not specific protein prediction programs. Methods/Analysis: In this study, we implement a machine-learning algorithm for fast and accurate prediction of DELLA proteins. Findings: We developed various modules by using conserved protein domains in DELLA proteins. To evaluate the modules classifiers like sequential minimum optimization, J48 decision tree, AD tree and logistic algorithms were used. By analyzing the results obtained from independent data set and cross-validation tests, maximum accuracy was achieved by logistic algorithm. The developed tool was tested with various inputs and it's showed that the algorithm developed in the study would be helpful in predicting plant DELLA domains. Applications: This tool will significantly contribute to deep level functional genome annotation and development of predictors.Keywords
Algorithms, Coconut, DELLA, Domains, Machine Learning, PredictionFull Text
- Biotechnology of Coconut
Abstract Views :247 |
PDF Views:125
Authors
Affiliations
1 Indian Institute of Spices Research, P. B. No. 1701, P.O. Marikunnu, Calicut- 673 012, IN
2 Central Plantation Crops Research Institute, Kasaragod-671 124, IN
1 Indian Institute of Spices Research, P. B. No. 1701, P.O. Marikunnu, Calicut- 673 012, IN
2 Central Plantation Crops Research Institute, Kasaragod-671 124, IN
Source
Journal of Horticultural Sciences, Vol 2, No 1 (2007), Pagination: 1-12Abstract
Biotechnology of coconut (Cocos nucifera L.) is a relatively recent area compared to similar work in other crops. It started as tissue culture in the eighties, which led to the development of molecular markers in late nineties with the use of RAPDs. Since then, considerable research has been carried out and protocols for tissue culture regeneration almost perfected. Embryo culture is being very successfully applied to germplasm transfer. Molecular markers such as AFLP, SSR, etc., were used to develop QTL maps. The entire gamut of coconut biotechnology is under review in this paper.Keywords
Biotechnology, Coconut, Cocos nucifera.Full Text
- Coconut Artificial Pollination Management System
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PDF Views:77
Authors
Affiliations
1 ICAR-Central Plantation Crops Research Institute, Kasaragod 671 124, IN
1 ICAR-Central Plantation Crops Research Institute, Kasaragod 671 124, IN
Source
Current Science, Vol 112, No 07 (2017), Pagination: 1325-1326Abstract
The coconut palm (Cocos nucifera) is a member of the family Arecaceae and the only species in the genus Cocos. There are two types of trees, talls and dwarfs. Talls are predominantly cross-pollinated, whereas the dwarfs are predominantly self-pollinated.Full Text
- Rejuvenating Coconut Sector for Improving Livelihood Security
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PDF Views:89
Authors
Affiliations
1 ICAR-Central Plantation Crops Research Institute, Kasaragod 671 124, IN
1 ICAR-Central Plantation Crops Research Institute, Kasaragod 671 124, IN
Source
Current Science, Vol 112, No 12 (2017), Pagination: 2359-2360Abstract
Coconut, a versatile tree crop, plays an important role in ensuring food and livelihood security to millions of people in tropical countries, in addition to providing invaluable ecosystem services. Coconut research in India began with the establishment of the Coconut Research Station in 1916 by the Madras Presidency. The milestone research achievements include discovery of hybrid vigour (1932), light interception and ischolar_main-spread studies (that resulted in the development of cropping system models), development of pest/disease management strategies, and protocols for embryo culture and cryopreservation of embryos and pollen, processing protocol for novel coconut food products, etc.Full Text
- In Vitro Regeneration of Coconut Plantlets from Immature Inflorescence
Abstract Views :274 |
PDF Views:105
Authors
Affiliations
1 ICAR-Central Plantation Crops Research Institute, Regional Station, Kayamkulam, Alappuzha 690 533, IN
2 ICAR-Central Plantation Crops Research Institute, Kudlu PO, Kasaragod 671 124, IN
1 ICAR-Central Plantation Crops Research Institute, Regional Station, Kayamkulam, Alappuzha 690 533, IN
2 ICAR-Central Plantation Crops Research Institute, Kudlu PO, Kasaragod 671 124, IN
Source
Current Science, Vol 117, No 5 (2019), Pagination: 813-820Abstract
Clonal propagation of elite, disease-free coconut palms is a promising technique for producing uniform planting material with high yield and disease resistance. Over the past few decades cloning of coconut has been attempted in a number of laboratories worldwide; however, success has been limited. In the present study, immature inflorescences of 2–12 cm size were collected from West Coast Tall variety and the rachilla segments were cultured on four different media combinations in dark condition. White translucent outgrowths were maximum in Y3 medium supplemented with 4.54 μM 2,4-dichlorophenoxyacetic acid (92%) followed by medium 72 with 41.4 μM picloram, 61.8 μM putrescine and 4.54 μM thidiazuron (TDZ) (87%). After eight weeks in dark, shoot-like outgrowth was noticed more in Y3 III (65%) followed by Y3 I. After eight months dark incubation, the cultures were transferred to 1/2 Murashige and Skoog (MS) with two hormone combinations and high frequency of multiple shoot formation was noticed in 1/2 MS with 5.37 μM naphthalene acetic acid (NAA) and 4.44 μM 6-benzylaminopurine (BAP). Maximum shoot development was observed Y3 medium fortified with 5 μM 2-isopentenyl adenine (2ip) and 5 μM BAP. The individual shoots after development of 3–4 leaves were transferred to 1/2 Y3 medium supplemented with 5.37 μM NAA and 24.6 μM indole-3-butyric acid (IBA), and ischolar_main initiation was observed in 39.28% plantlets. Start codon targeted (SCoT) profiling based on banding pattern of PCR-amplified products confirmed the clonal fidelity of in vitro regenerated coconut plantlets. The study indicates the possibility of developing an in vitro regeneration protocol for coconut using immature inflorescence explants.Keywords
Clonal Fidelity, Coconut, in vitro Regeneration, Rachillae.Full Text
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- Artificial Intelligence in Plantation Crops
Abstract Views :283 |
PDF Views:78
Authors
Affiliations
1 ICARCentral Plantation Crops Research Institute, Kasaragod 671 124, IN
1 ICARCentral Plantation Crops Research Institute, Kasaragod 671 124, IN
Source
Current Science, Vol 117, No 6 (2019), Pagination: 914-915Abstract
Agriculture plays a vital role in India’s economy with over 58% of the rural households dependent on it as their principal means of livelihood. The Indian agriculture sector, currently facing challenges of climate change, population growth and food security concerns, is progressively looking towards means to leverage innovative technologies which can substantially enhance crop productivity. Artificial Intelligence (AI) is steadily emerging as a part of the technological evolution of this sector. Plantation crops are grown in India over an area of 3.7 million hectares and provide livelihood security to around 30 million people, besides contributing Rs 250 billion to the gross domestic product (GDP). To explore the gamut of applications of AI in agriculture, with special reference to plantation crops, a two-day workshop was held last year.Full Text