Smart Sensing and Digital Twin Technology for Yield Estimation and Phenomics Prediction in Strawberries

Strawberry is a popular and economically significant fruit worldwide, with a substantial volume produced and consumed globally. However, it faces various production challenges including labor shortages, weather uncertainties, competition from imports, disease outbreaks, and insect infestations. This chapter explores the use of smart sensing for yield estimation, phenomics prediction for trait analysis, and digital twin technology for virtual simulation to enhance strawberry production. The implementation steps for each technique are discussed and examples of successful applications in strawberry production are given. These digital techniques provide a perspective of crop conditions, assisting in optimizing management practices, improving productivity and profitability, and promoting sustainable agriculture. However, their adoption also brings about certain challenges like high costs and the necessity for standardized data collection and analysis protocols. Additionally, the chapter emphasizes the importance of collaborative efforts among industry stakeholders for fostering innovation and encouraging the adoption of these technologies.