Human digital twins for agriculture 5.0: A systematic literature review and taxonomy

• It analyzes 52 selected articles from 2,039 works published between 2014 and 2025 across seven scientific databases. • The article proposes two taxonomies: one focused on applications and another on challenges. • The identified applications include well-being, safety, optimization, adaptive systems, and knowledge sharing. • The challenges involve heterogeneous data integration, framework standardization, privacy, and infrastructure limitations. • The study supports the alignment of HDTs with the principles of Agriculture 5.0, emphasizing adaptive and human-centered approaches. Human Digital Twins (HDTs) are emerging as a promising concept in the context of Agriculture 5.0, offering new perspectives for ergonomics, decision-making, and the integration of humans into digital agricultural systems. This paper presents a systematic literature review covering the period from 2014 to October 2025, aiming to consolidate the current state of knowledge and identify gaps in the application of HDTs in agriculture. The methodology followed established systematic review protocol with searches conducted in major scientific databases, applying defined inclusion and exclusion criteria. Fifty-two articles were selected and analyzed according to two taxonomies: one addressing applications of HDTs and another focused-on implementation challenges. Results highlight that HDTs in agriculture are associated with categories of well-being, safety, optimization, knowledge sharing , and worker-adaptive systems . Challenges identified include data integration, standardization of frameworks, ethical aspects, and validation in real scenarios. The study contributes by providing a structured overview of HDTs in agriculture, mapping current trends, and suggesting directions for future research and development.