Manuel Piliego
Papers
1
Total Citations
11
H-Index
1
About
Manuel Piliego is a researcher at the forefront of precision agriculture and non-destructive sensing technologies, with a primary focus on hyperspectral imaging for fruit quality assessment. His work addresses the critical challenge of determining optimal harvest timing for high-value crops, particularly table grapes. Piliego’s major contribution lies in developing on-the-go, proximal snapshot hyperspectral imaging systems that enable real-time, non-destructive ripeness estimation directly in the field—a significant advancement over traditional, time-consuming laboratory analyses. His 2024 paper on this topic has already garnered 11 citations, reflecting its immediate relevance to the agricultural technology community. By moving hyperspectral measurements from controlled lab settings to dynamic field conditions, Piliego’s research bridges the gap between high-throughput sensing and practical farming operations. His work holds promise for reducing post-harvest losses and improving fruit quality consistency, positioning him as an emerging innovator in the application of spectral imaging to sustainable agriculture and smart farming systems.
Research Focus
Key Achievements
Top Papers
- 1