Kapil Khanal
Papers
1
Total Citations
4
H-Index
1
About
Kapil Khanal’s research lies at the intersection of precision agriculture and plant phenotyping, with a focus on using spectral reflectance to improve horticultural crop management. His most cited work, “Distinguishing One Year and Two Year Old Canes of Red Raspberry Plant using Spectral Reflectance” (2018), introduces a non-destructive, remote sensing approach to differentiate between cane age classes in red raspberry—a critical task for optimizing pruning, canopy management, and pest control. By demonstrating that spectral signatures can reliably identify cane maturity, Khanal provides growers with a tool to enhance light distribution and airflow, directly reducing disease pressure and improving yield. Though his citation count is still growing (4 citations for this key paper), the work’s practical implications for sustainable berry production mark him as an emerging voice in agricultural technology. His contributions bridge field-level agronomy and sensor-based analytics, offering a scalable solution for labor-intensive tasks. For students and researchers exploring the integration of spectroscopy into crop management, Khanal’s research exemplifies how targeted spectral analysis can transform traditional horticultural practices into data-driven, efficient systems.
Research Focus
Key Achievements
Top Papers
- 1