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Item Ball copra production and marketing(2024-12-01) Augustine Jerard, B.; Sumitha, S.; Subramanian, P.; Jagadeesha; G.S. Chandrasekhar; Sudhrashan G.KItem Carbon Sequestration and Coconut Farming: A Sustainable Path Forward(2024-12-01) Mayalekshmi; Abdul Haris, A; Shareefa, M.; Regi J. ThomasItem Coconut inflorescence sap(2019-06) Sudha, R.; Niral, V; Hebbar, K.B; Samsudeen, KItem Diagnosis and management of soil fertility constraints in coconut (Cocos nucifera) : A review(2017-06) Malhotra, S.K.; Maheswarappa, H.P.; Selvamani, V.; Chowdappa, P.Item Diagnosis of invasive whitefly species co-occurring on coconut(2020-10) Joseph Rajkumar, A.; Chandrika Mohan; Merin Babu; Prathibha, P.S.; Vinayaka HegdeItem Integrated Pest Management in coconut based cropping systems(2024-10-01) Sujithra, M; Prathibha, V.H.; Jilu V. Sajan; Josephrajkumar, A.Item Laying out of Demonstration Plots for integrated management of coconut root (wilt) disease in Tenkasi district(2024-12-01) Josephrajkumar, A.; Regi J. Thomas; Indhuja, S.; Merin Babu; Anes, K.M.; Jilu V. Sajan; Shareefa, M.Item Nematode Management in Turmeric Intercropped Under Planation Crops(2025-09) Rajkumar; Surekha; Prathibha V,H; Vinayaka HegdeItem Nut pests of coconut(2024-08-01) Jilu V. Sajan; Prathibha, P.S.; Sujithra, M; Anes, K.M.; Merin Babu; Shareefa, M.; Josephrajkumar, A.Item An overview on water management in coconut (Cocos nucifera)(2019) Maheswarappa, H.P.; Krishnakumar, V.Item Physicochemical characterization and fatty acid profiles of testa oils from various coconut (Cocos nucifera L.) genotypes(2022-08-05) Ramesh, S.V.; Rose Mary; Shameena Beegum; Ravi Pandiselvam; Sugatha Padmanabhan; Neenu Sathyan; Sandip Shil; Niral; Manikantan Musuvadi Ramarathinam; Ankanahalli Narayanashetty Lokesha; Kodathalu Seetharamaiah Shivashankara; Dr. K. B. HebbarBACKGROUND: Cocos nucifera (L.) is an important plantation crop with immense but untapped nutraceutical potential. Despite its bioactive potential, the biochemical features of testa oils of various coconut genotypes are poorly understood. Hence, in this study, the physicochemical characteristics of testa oils extracted from six coconut genotypes – namely West Coast Tall (WCT), Federated Malay States Tall (FMST), Chowghat Orange Dwarf (COD), Malayan Yellow Dwarf (MYD), and two Dwarf × Dwarf (D × D hybrids) viz., Cameroon Red Dwarf (CRD) × Ganga Bondam Green Dwarf (GBGD) and MYD × Chowghat Green Dwarf (CGD) – were analyzed. RESULTS: The proportion of testa in the nuts (fruits) (1.29–3.42%), the proportion of oil in the testa (40.97–50.56%), and biochemical components in testa oils – namely proxidant elements Fe (34.17–62.48 ppm) and Cu (1.63–2.77 ppm), and the total phenolic content (6.84–8.67 mg GAE/100 g), and phytosterol content (54.66–137.73 mg CE/100 g) varied depending on the coconut genotypes. The saturated fatty acid content of testa oils (67.75 to 78.78%) was lower in comparison with that of coconut kernel oils. Similarly, the lauric acid (26.66–32.04%), myristic (18.31–19.60%), and palmitic acid (13.43–15.71%,) content of testa oils varied significantly in comparison with the coconut kernel oils (32–51%, 17–21% and 6.9–14%, respectively). Liquid chromatography–mass spectrometry (LC–MS) analysis revealed the presence of 18 phenolic acids in coconut testa oil. Multivariate analysis revealed the biochemical attributes that defined the principal components loadings. Hierarchical clustering analysis of the genotypes showed two distinct clusters. CONCLUSION: This study reveals the genotypic variations in the nutritionally important biochemical components of coconut testa oils. The relatively high concentration of polyunsaturated fatty acids (PUFA) and polyphenol content in testa oils warrant further investigation to explore their nutraceutical potential.Item Phytophthora diseases of arecanut in India: prior findings, present status and future prospects(2021) Patil Balanagouda; Vinayaka Hegde; Maheswarappa, H.P.; H. NarayanaswamyItem Plant based milk analogs with special emphasis on coconut milk(2024-08-01) Ajmala Rahfath; Akhina; Shameena BeegumItem Plantation Sector for Viksit Bharat: : Nutririon, Empowerment, and Livelihood(2025) Hebbar, K.B.; Ravi BhatItem Promotion of balanced fertilizer use in coconut farming(2026-08-07) Ponnusamy K; Selvamani, V.; Subramanian, P.Item Role of Nutrient Imbalance on Yellow Leaf Disease in Smallholder Arecanut Systems on a Laterite Soil in India(2016) Ravi Bhat; Sujatha, S.; Jose, C.T.Item RUGOSE SPIRALLING WHITEFLY (RSW): AN INVASIVE PEST IN INDIA(2020) PATEL S.S.; SISODIYA D.B.; PARMAR R.G.Item Status of arecanut production systems in India(2017) Sujatha, S.; Ravi Bhat; Chowdappa, P.Item Validation of suitable reference genes for gene expression studies in rugose spiraling whitefly (Aleurodicus rugioperculatus Martin) under various experimental conditions(2026) A. A. Sabana; M. K. Rajesh; Jasmin Habeeb; M. Sujithra; A. Josephrajkumarcrops, including coconut. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a fundamental and widely used technique in genomic research, particularly for analyzing gene expression levels with high sensitivity and specificity. One of the most critical factors influencing the accuracy and reliability of qRT-PCR results is the choice of internal reference genes, also known as housekeeping genes. These genes are used to normalize the expression levels of target genes. However, the lack of studies validating reference genes in A. rugioperculatus significantly restricts the accurate application of qRT-PCR for gene expression analysis. This study aims to identify suitable reference gene(s) across different biotic and abiotic conditions in A. rugioperculatus. The expression stability of 14 reference genes (18S rRNA, GST, HSP90, GAPDH, RPS17, actin, RPL13, NADH, ETF-QO, EF1α, UBQ, β-TUB, peptidylprolyl isomerase A, and Myosin L) was analyzed using five different computational programs, such as geNorm, NormFinder, BestKeeper, Comparative ΔCT, and RefFinder. The findings suggested that the optimal combinations of reference genes in A. rugioperculatus were 18S rRNA and NADH for different developmental stages, 18S rRNA and EF1α for different sexes and temperatures, and RPL13 and 18S rRNA for starvation conditions. This study presents the first report of stable reference genes for normalizing qRT-PCR analysis in A. rugioperculatus, laying the foundation for future expression studies and RNAi-based management of the rugose spiraling whitefly.Item Valorization of Fruit Waste for Bioactive Compounds and Their Applications in the Food Industry(2023) Nilesh Prakash Nirmal; Anandu Chandra Khanashyam; Anjaly Shanker Mundanat; Kartik Shah; Karthik Sajith Babu; Priyamvada Thorakkattu; Fahad Al-Asmari; Pandiselvam, R.