Socialsciences and Humanities: Corpus Open Access Journal
[ ISSN : 3068-0956 ]
Navigating Complexities: Implementation Challenges of Automated Fresh Fruit Bunch Ripeness Detection Systems in Oil Palm Plantations
IPOSS Jakarta, Indonesia
Corresponding Authors
Keywords
Abstract
The oil palm industry faces mounting pressures from labor shortages, quality optimization imperatives, and sustainability demands, driving interest in automated Fresh Fruit Bunch (FFB) ripeness detection technologies. While computer vision and deep learning systems achieve high accuracy (97-99.66%) in controlled environments, their widespread implementation encounters substantial complexities due to the variability of plantations and processing industries. This qualitative literature review synthesizes findings from 2020 to 2026 to examine the multidimensional challenges obstructing the practical deployment of automated FFB detection systems. Through thematic analysis of recent literature, this study identifies critical barriers spanning technical dimensions (data scarcity, hardware constraints, connectivity limitations), economic factors (capital requirements, uncertain return on investment), infrastructural inadequacies (digital divide, power instability), human capital deficits (skills gaps, digital literacy), socio-cultural resistance (trust, behavioral inertia), and institutional obstacles (regulatory fragmentation, policy-implementation gaps). Plantation environmental heterogeneity-climate variability, topographical constraints, agronomic diversity-creates unpredictable operational conditions, degrading system performance. Processing mill variations in quality standards and capacity requirements further complicate integration efforts. The analysis reveals that successful implementation requires holistic ecosystem approaches integrating technological innovation with infrastructure development, workforce capacity building, data standardization, policy incentives, and context-responsive deployment strategies. Findings underscore the need for adaptive algorithms, affordable sensor solutions, smallholder accessible business models, and comprehensive institutional support frameworks to bridge the gap between technological capability and practical viability in diverse oil palm cultivation contexts.
JEL Classification: Q16 (Production Agriculture), O33 (Technological Change: Choices and Consequences), Q55 (Technological Innovation)
