Post-harvest grain processes play a crucial role in food supply chains. Recent research focuses on how digital technologies can minimize grain losses, enhance food safety, and reduce their environmental impacts. The relationship between technologies and efficiency and sustainability needs more clarity, particularly concerning critical control points in post-harvest activities. The purpose of this article is to establish a connection between digital technologies used in food supply chains and critical control points within post-harvest systems. The research method is a bibliometric analysis. A literature survey identified thirteen digital technologies. The most published technologies are simulation, automation, and artificial intelligence. The least is augmented reality. Previous research identified nine critical control points in post-harvest engineering solutions, responsible for most losses in efficiency and environmental impacts. A framework using a sample of recent case studies was constructed to relate digital technologies and critical control points. The primary contribution of the study is a categorized list of the most influential technologies corresponding to each control point. The significance and novelty lie in providing managers and practitioners in engineering solutions for post-harvest systems with a practical guide for decision-making in the selection of technologies for future projects. Ultimately, this aids in reducing losses and environmental impact.

The purpose of this article is to identify opportunities that digital transformation in post-harvest activities offers to an engineering solution provider. The research method is a simple case study. The object is a company based in southern Brazil that provides engineering-integrated digital solutions to grain producers, including products and services. The specific objectives are to describe the company’s digital products and services, identify opportunities and players, and discuss how players can take advantage of opportunities owing to business process digitalization. The main results include separating products into three technological layers and identifying five types of opportunities (financing, commercialization, operation, logistics, traceability, and insurance), eight types of players, and the main opportunities for each player. The most significant opportunities are risk reduction in insurance contracts, improvement in grain quality, increments in food safety, and accurate information on grain movements. The main implication of the study is that grain producers and other players can explore opportunities, and solution providers can evolve toward complete digitalization by integrating service into the current offerings of post-harvest engineering solutions.

This study investigates the impact of digital transformation on a Brazilian post-harvest engineering company. The manuscript examines how digital technologies impact performance and competitive advantages, providing actionable insights for practitioners. The methodology is a twofold case study. First, it describes the company’s technology development process, examining the journey from initial implementations to its current state over the past ten years. Then, it focuses on the recommendations for future advancements, provided by a leading technology research institute located in Germany. Data collection involved observation, interviews (personnel, clients, experts), document analysis, and facility tours. The findings include qualitative (grain quality, agility) and quantitative impacts (EBITDA increase, 84% storage efficiency). Barriers included mechanical adaptation and costs. Opportunities related by BIBA include advanced technologies (such as AI and digital twins), aligning with a proposed six-level digital maturity model for post-harvest systems. Regarding practical implications, the findings emphasize the need for a strategic vision for digital technology adoption in the post-harvest industry, which is crucial for addressing labor shortages, reducing losses, and promoting sustainability, with potential annual gains of $700 million. The main novelty introduced by this study is a novel, empirically derived six-level digital maturity model. It provides comprehensive qualitative/quantitative impact analysis, highlighting advanced technologies for industry challenges.