TY - JOUR
T1 - Quality parameters of six cultivars of blueberry using computer vision.
AU - Matiacevich, Silvia
AU - Celis Cofré, Daniela
AU - Silva, Patricia
AU - Enrione, Javier
AU - Osorio, Fernando
N1 - Publisher Copyright:
© 2013 Silvia Matiacevich et al.
PY - 2013
Y1 - 2013
N2 - Background. Blueberries are considered an important source of health benefits. This work studied six blueberry cultivars: "Duke," "Brigitta", "Elliott", "Centurion", "Star," and "Jewel", measuring quality parameters such as °Brix, pH, moisture content using standard techniques and shape, color, and fungal presence obtained by computer vision. The storage conditions were time (0-21 days), temperature (4 and 15°C), and relative humidity (75 and 90%). Results. Significant differences (P<0.05) were detected between fresh cultivars in pH, °Brix, shape, and color. However, the main parameters which changed depending on storage conditions, increasing at higher temperature, were color (from blue to red) and fungal presence (from 0 to 15%), both detected using computer vision, which is important to determine a shelf life of 14 days for all cultivars. Similar behavior during storage was obtained for all cultivars. Conclusion. Computer vision proved to be a reliable and simple method to objectively determine blueberry decay during storage that can be used as an alternative approach to currently used subjective measurements.
AB - Background. Blueberries are considered an important source of health benefits. This work studied six blueberry cultivars: "Duke," "Brigitta", "Elliott", "Centurion", "Star," and "Jewel", measuring quality parameters such as °Brix, pH, moisture content using standard techniques and shape, color, and fungal presence obtained by computer vision. The storage conditions were time (0-21 days), temperature (4 and 15°C), and relative humidity (75 and 90%). Results. Significant differences (P<0.05) were detected between fresh cultivars in pH, °Brix, shape, and color. However, the main parameters which changed depending on storage conditions, increasing at higher temperature, were color (from blue to red) and fungal presence (from 0 to 15%), both detected using computer vision, which is important to determine a shelf life of 14 days for all cultivars. Similar behavior during storage was obtained for all cultivars. Conclusion. Computer vision proved to be a reliable and simple method to objectively determine blueberry decay during storage that can be used as an alternative approach to currently used subjective measurements.
UR - http://www.scopus.com/inward/record.url?scp=84940930387&partnerID=8YFLogxK
U2 - 10.1155/2013/419535
DO - 10.1155/2013/419535
M3 - Article
AN - SCOPUS:84940930387
SN - 2356-7015
VL - 2013
JO - International Journal of Food Science
JF - International Journal of Food Science
M1 - 419535
ER -