Determining constraints in medicinal plants adoption: A model geospatial study in the Indian state of Punjab

2021 
Abstract Understanding the constraints involved in the adoption of medicinal plant cultivation is the most important step to design future policies and action plans for effective outcomes. Keeping this in view, a model survey-based study involving medicinal plant cultivators by using a purposing sampling technique was carried out. Additionally, farmers identified via exploration of various channels from public and personal sources were geo-tagged using Geographic Information System (GIS). The digital maps shall act as a platform to establish linkage between concerned stakeholders viz. policymakers, traders, industries, regulatory agencies, and farmers. The scope of the study was limited to progressive farmers cultivating commercially important medicinal plants i.e. Curcuma longa L. (Haldi), Aloe vera (Linn.) Burm.f (Ghritkumari), Phyllanthus emblica L. (Amla), Ocimum sanctum L. (Tulsi), Rauvolfia serpentina (L.) Benth. ex Kurz (Sarpgandha). The survey questionnaire was developed through the expert advisory method, followed by statistical validation based on achieving Chronbach’s alpha value of 0.6. Statistical analysis of the responses by applying Mean Percentage Score (MPS) and significance determination using Chi-square test indicated prominent correlation among small and large farmers in context to technical, trade, social, and awareness aspects. The study highlighted the non-availability of quality planting material, lack of awareness about good agricultural and packaging practices, less knowledge about agro-climatic suitability, and commercialization avenues acted as one of the major constraints. The study will act as a basis to frame policies for promoting medicinal plant cultivation as a commercially successful crop diversification model in the region.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    48
    References
    0
    Citations
    NaN
    KQI
    []