IDEAS home Printed from https://ideas.repec.org/a/gam/jgeogr/v2y2022i4p43-723d969964.html
   My bibliography  Save this article

Land Suitability Evaluation of Tea ( Camellia sinensis L.) Plantation in Kallar Watershed of Nilgiri Bioreserve, India

Author

Listed:
  • S. Abdul Rahaman

    (Department of Geography, School of Earth Science, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu, India
    Department of Geography and Geoinformatics, Bangalore University, Bengaluru 560056, Karnataka, India)

  • S. Aruchamy

    (Department of Geography, School of Earth Science, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu, India)

Abstract

Nilgiri tea is a vital perennial beverage variety and is in high demand in global markets due to its quality and medicinal value. In recent years, the cultivation of tea plantations has decreased due to the extreme climate and prolonged practice of tea cultivation in the same area, decreasing its taste and quality. In this scenario, land suitability analysis is the best approach to evaluate the bio-physiochemical and ecological parameters of tea plantations. The present study aims to identify and delineate appropriate land best suited for the cultivation of tea within the Kallar watershed using the geographic information system (GIS) and multi-criteria evaluation (MCE) techniques. This study utilises various suitability criteria, such as soil (texture, hydrogen ion concentration, electrical conductivity, depth, base saturation, and drainability), climate (rainfall and temperature), topography (relief and slope), land use, and the normalised difference vegetation index (NDVI), to evaluate the suitability of the land for growing tea plantations based on the Food and Agricultural Organization (FAO) guidelines for rainfed agriculture. The resultant layers were classified into five suitability classes, including high (S1), moderate (S2), and marginal (S3) classes, which occupied 16.7%, 7.08%, and 16.3% of the land, whereas the currently and permanently not suitable (N1 and N2) classes covered about 18.52% and 29.06% of the total geographic area. This study provides sufficient insights to decision-makers and farmers to support them in making more practical and scientific decisions regarding the cultivation of tea plantations that will result in the increased production of quality tea, and prevent and protect human life from harmful diseases.

Suggested Citation

  • S. Abdul Rahaman & S. Aruchamy, 2022. "Land Suitability Evaluation of Tea ( Camellia sinensis L.) Plantation in Kallar Watershed of Nilgiri Bioreserve, India," Geographies, MDPI, vol. 2(4), pages 1-23, November.
    • Handle: RePEc:gam:jgeogr:v:2:y:2022:i:4:p:43-723:d:969964
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2673-7086/2/4/43/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2673-7086/2/4/43/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    2. Yuncheng Zhao & Mingyue Zhao & Lei Zhang & Chunyi Wang & Yinlong Xu, 2021. "Predicting Possible Distribution of Tea ( Camellia sinensis L.) under Climate Change Scenarios Using MaxEnt Model in China," Agriculture, MDPI, vol. 11(11), pages 1-18, November.
    3. Sadeeka Layomi Jayasinghe & Lalit Kumar & Janaki Sandamali, 2019. "Assessment of Potential Land Suitability for Tea ( Camellia sinensis (L.) O. Kuntze) in Sri Lanka Using a GIS-Based Multi-Criteria Approach," Agriculture, MDPI, vol. 9(7), pages 1-25, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Netrananda Sahu & Pritiranjan Das & Atul Saini & Ayush Varun & Suraj Kumar Mallick & Rajiv Nayan & S. P. Aggarwal & Balaram Pani & Ravi Kesharwani & Anil Kumar, 2023. "Analysis of Tea Plantation Suitability Using Geostatistical and Machine Learning Techniques: A Case of Darjeeling Himalaya, India," Sustainability, MDPI, vol. 15(13), pages 1-21, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Banai, Reza, 2010. "Evaluation of land use-transportation systems with the Analytic Network Process," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 85-112.
    2. Pishchulov, Grigory & Trautrims, Alexander & Chesney, Thomas & Gold, Stefan & Schwab, Leila, 2019. "The Voting Analytic Hierarchy Process revisited: A revised method with application to sustainable supplier selection," International Journal of Production Economics, Elsevier, vol. 211(C), pages 166-179.
    3. Seung-Jin Han & Won-Jae Lee & So-Hee Kim & Sang-Hoon Yoon & Hyunwoong Pyun, 2022. "Assessing Expected Long-term Benefits for the Olympic Games: Delphi-AHP Approach from Korean Olympic Experts," SAGE Open, , vol. 12(4), pages 21582440221, December.
    4. Seyed Rakhshan & Ali Kamyad & Sohrab Effati, 2015. "Ranking decision-making units by using combination of analytical hierarchical process method and Tchebycheff model in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 505-525, March.
    5. V. Srinivasan & G. Shainesh & Anand K. Sharma, 2015. "An approach to prioritize customer-based, cost-effective service enhancements," The Service Industries Journal, Taylor & Francis Journals, vol. 35(14), pages 747-762, October.
    6. Mónica García-Melón & Blanca Pérez-Gladish & Tomás Gómez-Navarro & Paz Mendez-Rodriguez, 2016. "Assessing mutual funds’ corporate social responsibility: a multistakeholder-AHP based methodology," Annals of Operations Research, Springer, vol. 244(2), pages 475-503, September.
    7. Luis Pérez-Domínguez & Luis Alberto Rodríguez-Picón & Alejandro Alvarado-Iniesta & David Luviano Cruz & Zeshui Xu, 2018. "MOORA under Pythagorean Fuzzy Set for Multiple Criteria Decision Making," Complexity, Hindawi, vol. 2018, pages 1-10, April.
    8. Paul L. G. Vlek & Asia Khamzina & Hossein Azadi & Anik Bhaduri & Luna Bharati & Ademola Braimoh & Christopher Martius & Terry Sunderland & Fatemeh Taheri, 2017. "Trade-Offs in Multi-Purpose Land Use under Land Degradation," Sustainability, MDPI, vol. 9(12), pages 1-19, November.
    9. Kumar B, Pradeep, 2021. "Changing Objectives of Firms and Managerial Preferences: A Review of Models in Microeconomics," MPRA Paper 106967, University Library of Munich, Germany, revised 13 Mar 2021.
    10. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2018. "σ-µ efficiency analysis: A new methodology for evaluating units through composite indices," MPRA Paper 83569, University Library of Munich, Germany.
    11. Anirban Mukhopadhyay & Sugata Hazra & Debasish Mitra & C. Hutton & Abhra Chanda & Sandip Mukherjee, 2016. "Characterizing the multi-risk with respect to plausible natural hazards in the Balasore coast, Odisha, India: a multi-criteria analysis (MCA) appraisal," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1495-1513, February.
    12. Chamoli, Sunil, 2015. "Hybrid FAHP (fuzzy analytical hierarchy process)-FTOPSIS (fuzzy technique for order preference by similarity of an ideal solution) approach for performance evaluation of the V down perforated baffle r," Energy, Elsevier, vol. 84(C), pages 432-442.
    13. H. S. C. Perera & W. K. R. Costa, 2008. "Analytic Hierarchy Process for Selection of Erp Software for Manufacturing Companies," Vision, , vol. 12(4), pages 1-11, October.
    14. G. La Scalia & F.P. Marra & J. Rühl & R. Sciortino & T. Caruso, 2016. "A fuzzy multi-criteria decision-making methodology to optimise olive agro-engineering processes based on geo-spatial technologies," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 15(1), pages 1-15.
    15. Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet E., 2014. "Dual criteria decisions," Journal of Economic Psychology, Elsevier, vol. 41(C), pages 101-113.
      • Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet, 2009. "Dual Criteria Decisions," Working Papers 02-2009, Copenhagen Business School, Department of Economics.
    16. Mulliner, Emma & Smallbone, Kieran & Maliene, Vida, 2013. "An assessment of sustainable housing affordability using a multiple criteria decision making method," Omega, Elsevier, vol. 41(2), pages 270-279.
    17. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    18. Majid Ebrahimi & Hamid Nejadsoleymani & Mohammad Reza Mansouri Daneshvar, 2019. "Land suitability map and ecological carrying capacity for the recognition of touristic zones in the Kalat region, Iran: a multi-criteria analysis based on AHP and GIS," Asia-Pacific Journal of Regional Science, Springer, vol. 3(3), pages 697-718, October.
    19. Zeshui Xu, 2013. "Compatibility Analysis of Intuitionistic Fuzzy Preference Relations in Group Decision Making," Group Decision and Negotiation, Springer, vol. 22(3), pages 463-482, May.
    20. Choudhary, Devendra & Shankar, Ravi, 2012. "An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India," Energy, Elsevier, vol. 42(1), pages 510-521.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jgeogr:v:2:y:2022:i:4:p:43-723:d:969964. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.