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Typology of Irrigation Technology Adopters in Oil Palm Production: A Categorical Principal Components and Fuzzy Logic Approach

Author

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  • Diana Martínez-Arteaga

    (Colombian Oil Palm Research Center-Cenipalma, Bogotá 11121, Colombia
    Department of Agronomy, Faculty of Agricultural Sciences, Universidad Nacional de Colombia, Bogotá 11132, Colombia)

  • Nolver Atanasio Arias Arias

    (Colombian Oil Palm Research Center-Cenipalma, Bogotá 11121, Colombia)

  • Aquiles E. Darghan

    (Department of Agronomy, Faculty of Agricultural Sciences, Universidad Nacional de Colombia, Bogotá 11132, Colombia)

  • Carlos Rivera

    (Department of Agronomy, Faculty of Agricultural Sciences, Universidad Nacional de Colombia, Bogotá 11132, Colombia)

  • Jorge Alonso Beltran

    (Colombian Oil Palm Research Center-Cenipalma, Bogotá 11121, Colombia)

Abstract

Oil palm is the second most cultivated oilseed crop in the world after soybeans, with more than 23 million hectares cultivated worldwide; it has become crucial for the economy of many countries. In Colombia, it is one of the most developed agricultural sectors, and every year the sector promotes the development of technologies that lead to greater sustainability of agricultural and food systems and address the challenges and opportunities of agribusiness. In this research, the central focus was the adoption of irrigation technologies, which is limited despite significant efforts and investments in physical and human capital. On many occasions, the typology of farmers has been associated with low technology implementation. Thus, linking the typology of farmers according to certain commonalities or differences is an essential step in exploring the factors that explain the adoption. In addition, the ranking also helps in the understanding of existing adoption constraints, as well as finding opportunities for change. This study aimed to determine the socioeconomic and demographic typology of those who adopt irrigation technologies. The analysis was performed using categorical principal component analysis to reduce dimensionality and fuzzy cluster analysis to classify the groups. As a result, four groups of producers that differ in terms of their demographic and socioeconomic characteristics were obtained, where the groups “population with female leadership” and “diversified population” were the adopters of irrigation technologies. The most outstanding characteristics of these two groups were the profitability of the harvest and the age of the producers. Determining the typology of farmers is a fundamental step in expanding the technology adoption process through agricultural extension services, which represent a way of reaching producers directly. In addition, these results allow decision makers to participate in this dynamic reflectively and intentionally (such as governments, researchers, and technology transferors).

Suggested Citation

  • Diana Martínez-Arteaga & Nolver Atanasio Arias Arias & Aquiles E. Darghan & Carlos Rivera & Jorge Alonso Beltran, 2023. "Typology of Irrigation Technology Adopters in Oil Palm Production: A Categorical Principal Components and Fuzzy Logic Approach," Sustainability, MDPI, vol. 15(13), pages 1-11, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9944-:d:1176735
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    References listed on IDEAS

    as
    1. Nuzhat Khan & Mohamad Anuar Kamaruddin & Usman Ullah Sheikh & Yusri Yusup & Muhammad Paend Bakht, 2021. "Oil Palm and Machine Learning: Reviewing One Decade of Ideas, Innovations, Applications, and Gaps," Agriculture, MDPI, vol. 11(9), pages 1-26, August.
    2. Kaliba, Aloyce R. & Mushi, Richard J. & Gongwe, Anne G. & Mazvimavi, Kizito, 2020. "A typology of adopters and nonadopters of improved sorghum seeds in Tanzania: A deep learning neural network approach," World Development, Elsevier, vol. 127(C).
    3. Mpanga, Isaac K. & Idowu, Omololu John, 2021. "A Decade of Irrigation Water use trends in Southwestern USA: The Role of Irrigation Technology, Best Management Practices, and Outreach Education Programs," Agricultural Water Management, Elsevier, vol. 243(C).
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    6. Diana Martínez-Arteaga & Nolver Atanacio Arias Arias & Aquiles E. Darghan & Dursun Barrios, 2023. "Identification of Influential Factors in the Adoption of Irrigation Technologies through Neural Network Analysis: A Case Study with Oil Palm Growers," Agriculture, MDPI, vol. 13(4), pages 1-13, April.
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