Economic Feasibility and Water Footprint Analysis for Smart Irrigation Systems in Palm Oil Industry

The Malaysian palm oil industry is the second largest global producer of palm oil products in the world after Indonesia. However, oil palm plantation activities are typically very labour-intensive and inefficient. The rapid development of technologies, especially Industry Revolution 4.0 technologies, has brought forward a variety of advanced smart technologies and systems that can be adapted in the palm oil industry to improve the efficiency and yields in the industry as well as create better economic performance. This work aims to explore and quantify the potential of adaption and implementations of smart irrigation system in oil palm plantations. The proposed approach considers economic performance (return of investment, ROI) and water footprint (additional water usage) of smart irrigation. In addition, the analysis also includes the consideration of different server setup options and plantation sizes. The results show that smart irrigation is a feasible method to be implemented in oil palm plantations with positive economic performance for plantation with land size more than 1.5 ha. The findings also show a significant reduction in water footprint and costs in the smart irrigation system to achieve optimal moisture conditions in a plantation. This paper provides insight for oil palm stakeholders to understand the feasibility and performance of smart irrigation systems as a feasible option to transform oil palm plantations with Industrial Revolution 4.0 technologies.

[1]  S. Abd Aziz,et al.  Design considerations of variable rate liquid fertilizer applicator for mature oil palm trees , 2022, Precision Agriculture.

[2]  S. Mukhtar,et al.  Effects of Some Weather Parameters on Oil Palm Production in the Peninsular Malaysia , 2021 .

[3]  R. Wardhani,et al.  Sustainability strategy of Indonesian and Malaysian palm oil industry: a qualitative analysis , 2021 .

[4]  Yuvaraja Teekaraman,et al.  Implementation of Cognitive Radio Model for Agricultural Applications Using Hybrid Algorithms , 2021, Wirel. Pers. Commun..

[5]  Paula Fraga-Lamas,et al.  Design, Implementation, and Empirical Validation of an IoT Smart Irrigation System for Fog Computing Applications Based on LoRa and LoRaWAN Sensor Nodes † , 2020, Sensors.

[6]  Tristan Perez,et al.  Performance improvements of a sweet pepper harvesting robot in protected cropping environments , 2020, J. Field Robotics.

[7]  Francisco Rovira-Más,et al.  From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management , 2020, Agronomy.

[8]  Brooke E. Mason,et al.  Intelligent urban irrigation systems: Saving water and maintaining crop yields , 2019 .

[9]  A. Thakur,et al.  Automatic drip irrigation scheduling effects on yield and water productivity of banana , 2019, Scientia Horticulturae.

[10]  Lars Grimstad,et al.  An autonomous strawberry‐harvesting robot: Design, development, integration, and field evaluation , 2019, J. Field Robotics.

[11]  Rokhedi Priyo Santoso,et al.  Competitiveness analyses of Indonesian and Malaysian palm oil exports , 2019, Economic Journal of Emerging Markets.

[12]  S. Ahirwar,et al.  Application of Drone in Agriculture , 2019, International Journal of Current Microbiology and Applied Sciences.

[13]  Muhammad Imran,et al.  Technology-Assisted Decision Support System for Efficient Water Utilization: A Real-Time Testbed for Irrigation Using Wireless Sensor Networks , 2018, IEEE Access.

[14]  Balu Nambiappan,et al.  MALAYSIA: 100 YEARS OF RESILIENT PALM OIL ECONOMIC PERFORMANCE , 2018 .

[15]  Mehmood Ali Noor,et al.  Smart Farming: An Overview , 2020 .

[16]  Um Rao Mogili,et al.  Review on Application of Drone Systems in Precision Agriculture , 2018 .

[17]  Prashant M. Ambad,et al.  Industry 4.0 – A Glimpse , 2018 .

[18]  C. Chow The effects of season, rainfall and cycle on oil palm yield in Malaysia. , 1992 .