Carlos Arizmendi
Papers
1
Total Citations
19
H-Index
1
About
Carlos Arizmendi is a researcher whose work sits at the intersection of agricultural engineering, computer vision, and food science. His primary focus is on developing non-destructive, image-based methods for assessing fruit ripeness and quality, with a particular emphasis on coffee production. In his most-cited study, "Ripeness stage characterization of coffee fruits (Coffea arabica L. var. Castillo) applying chromaticity maps obtained from digital images" (2020), Arizmendi introduced an innovative approach that uses chromaticity maps from standard digital photographs to objectively classify coffee cherry maturity stages. This work, which has garnered 19 citations, offers a practical, low-cost alternative to subjective manual sorting, directly impacting harvest timing and bean quality for specialty coffee growers. By translating complex color data into actionable ripeness metrics, his research bridges the gap between traditional agricultural practices and modern computational analysis. Arizmendi’s contributions are particularly valuable for smallholder farmers seeking to improve yield consistency and market value without expensive equipment, making his work a notable step toward democratizing precision agriculture in the coffee sector.
Research Focus
Key Achievements
Top Papers
- 1