Abstract: The agricultural sector, a cornerstone of many economies, is undergoing a digital transformation in Latin America and the Caribbean (LAC), influencing domestic production. This study emphasizes the significance of technology readiness in agricultural production and stresses the need for comprehensive system assessments.
Technology readiness levels (TRL) are categorized into developmental (TRL₁₋₃), near operational (TRL₄₋₆), and full-scale readiness (TRL₇₋₉). Evaluations of LAC agricultural sites, involving local farmers, inform a linear mixture model estimating uncertainty (U) from binomial probability distribution P(TRLᵢ) for each TRL, representing the likelihood of achieving a specific TRL. The general mixture equation is extended and adjusted for all TRLs using newly calculated weights Wj.
Simulations involve generating random deviates (r) from a uniform distribution (0,1) and utilizing linear interpolation. Results show varying TRLs for different technologies, revealing acceptance challenges for sustainable farming practices (TRL₆), promising but cost-inefficient renewable energy sources (TRL₅), limited automation due to high upfront costs (TRL₄), and early-stage adoption for precision agriculture and smart management (TRL₂₋₄). The average TRL for the Dominican Republic is TRL₄.₂₄, indicating potentials for advancements in agriculture, with emphasis on overcoming barriers.
The digital transformation’s impact on productivity, product quality, production costs, sustainability, and environmental protection is significant. Evaluating technology readiness levels aids in assessing key techniques in sustainable farming practices, decision support, precision agriculture, and smart management. Constructing uncertainty model enhances confidence in determining technological innovations and readiness, which align with UN SDG Goal 2, addressing hunger and enhancing food security, promoting environmental sustainability for a prosperous future.