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 Environmental Microbial & Food Safety Laboratory: Beltsville, MD
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ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Environmental Microbial & Food Safety Laboratory Research





- Qin, Jianwei - Tony Qin
- Pachepsky, Yakov
- Chao, Kuanglin - Kevin Chao
- Kim, Moon
- Food Safety, (Animal and Plant Products) (108)

Research Project: **Location:
                            Environmental Microbial & Food Safety Laboratory** Project Number: 8042-42000-021-012-S
                        
                        Project Type: Non-Assistance Cooperative Agreement Start Date: Jul 1, 2022
                        
                        End Date: Jun 30, 2025 **Objective:**
                        
                        Preharvest inspection of the produce fields for signs of animal intrusion and irrigation water quality monitoring is required for current and future produce operations. There is a need to develop automated drone-based sensing technologies that can aid producers to rapidly identify and mark problem sites and their surrounding areas for exclusion from harvesting. The objective of the cooperative research is to develop a new multimodal imaging-based drone system with real-time image processing and analyses capabilities to provide detection and classification of animal intrusion and fecal contamination in farm fields and for monitoring irrigation microbial water quality. **Approach:**
                        
                        ARS sensing technology team is developing an autonomous drone (or small unmanned aerial vehicle) imaging platform with multimodal imaging sensors (i.e., hyperspectral) for preharvest detection of animal intrusion and fecal contamination in produce fields. Current agricultural applications of drone-based sensing technologies lack onboard image processing and analysis capabilities and rely on post-processing of the collected image data. The proposed development of a new drone-based multimodal imaging system will incorporate an embedded single-board computer (SBC) that enables multimodal image data collection, and real-time image processing and analyses onboard the drone, and near-real-time transmission of analytical/model results to the end-user’s graphic user interface (GUI) to be used.


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