A review of agroforestry, precision agriculture, and precision livestock farming—The case for a data-driven agroforestry strategy

Abstract

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Agroforestry can be defined as an agroecosystem whereby soil is used holistically and synergistically by various stakeholders including farmers, livestock, and plants. As such, agroforestry offers numerous benefits that include conservation of biodiversity, regulation of pests and diseases, increased quality of soil, air and water, efficient cycling of nutrients, and resilience to climate change. Review of published studies in agroforestry shows however that research in this area could benefit from increased real-time, spatial and temporal measurements. This situation is to be contrasted with that of precision agriculture in monocultures and precision livestock farming where progress made in sensor systems has attracted considerable research interest. It is advocated in this review article that wireless sensor networks could also significantly impact agroforestry through the monitoring of the local real-time interactions that occur between the various components constituting agroforestry systems. This review article proposes therefore the new field of data-driven agroforestry which lies at the intersection of precision agriculture, precision livestock farming, permaculture, and agroforestry. Data-driven agroforestry has the potential to not only help farmers harness the interactions between the different components of an agroforestry system to their advantage but also shine light on fundamental interactions between soil, plants, trees, and livestock while offering a sustainable agricultural method beneficial to all agroforestry stakeholders.

Keywords

• data-driven agroforestry
• agroforestry
• precision agriculture
• precision livestock farming
• sensors
• wireless sensor networks