TY - DATA
T1 - Dataset: Sensing Potential in the Food Supply Chain - Mango
PY - 2025/03/04
AU - P. Mishra
AU - P. Offermans
AU - M.G.J. Mensink
AU - H.J. van de Zedde
AU - A. Chauhan
AU - L.M.J. Meesters
UR - 
DO - 10.4121/fb26fd3f-ba3c-4cf0-8926-14768a256933.v1
KW - Fruit quality
KW - Sensor
KW - Spectral
KW - NIR
KW - Ultra sound
KW - Raman
KW - Mango
KW - Brix
KW - Dry matter
KW - Firmness
N2 - <p>The overall aim of this research is to explore the feasibility of sensing technology to measure non-destructively fruit quality properties on a batch and an individual product level.</p><p><br></p><p>The specific objective for this dataset was to utilize various sensor data inputs for AI models aimed at quantifying the brix (sugar content) and firmness of mangoes. AI models were developed using data from individual sensors, as well as models based on the fusion of all sensor data. The brix and firmness were modeled using a multi-sensor approach, incorporating ultrasound and spectroscopy signals. Refractometer measurements for brix and puncture measurements for firmness served as the reference standards.</p>
ER -