In the present study the relationships between apple texture and rheological parameters were evaluated by means of multivariate analysis. In particular, reference apple cultivars were used to assess fruit crispness of two new apple breeding populations. Principal Component Analysis and Linear Discriminant Analysis were initially applied to the rheological data collected on reference cultivars for which experimental crispness scores were determined. Principal Component Analysis enhanced the interpretation of the relationships between crispness and rheological variables, while Linear Discriminant Analysis showed a clear trend of separation among the different apple cultivars according to their crispness score. Finally, the new apple populations were projected in the multivariate model in order to predict their crispness. These predicted scores of apple crispness are expected to have a relevant impact to the further investigation of apple quality, since they can be exploited to better describe the general fruit quality as well as the detection of genomic regions and causal genes involved in the control of fruit texture in apple.

Ballabio, D.; Consonni, V.; Costa, F. (2012). Relationships between apple texture and rheological parameters by means of multivariate analysis. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 111 (1): 28-33. doi: 10.1016/j.chemolab.2011.11.002 handle: http://hdl.handle.net/10449/20737

Relationships between apple texture and rheological parameters by means of multivariate analysis

Costa, Fabrizio
2012-01-01

Abstract

In the present study the relationships between apple texture and rheological parameters were evaluated by means of multivariate analysis. In particular, reference apple cultivars were used to assess fruit crispness of two new apple breeding populations. Principal Component Analysis and Linear Discriminant Analysis were initially applied to the rheological data collected on reference cultivars for which experimental crispness scores were determined. Principal Component Analysis enhanced the interpretation of the relationships between crispness and rheological variables, while Linear Discriminant Analysis showed a clear trend of separation among the different apple cultivars according to their crispness score. Finally, the new apple populations were projected in the multivariate model in order to predict their crispness. These predicted scores of apple crispness are expected to have a relevant impact to the further investigation of apple quality, since they can be exploited to better describe the general fruit quality as well as the detection of genomic regions and causal genes involved in the control of fruit texture in apple.
Apple
Fruit quality
Texture parameters
Crispness
Principal component analysis
Discriminant analysis
2012
Ballabio, D.; Consonni, V.; Costa, F. (2012). Relationships between apple texture and rheological parameters by means of multivariate analysis. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 111 (1): 28-33. doi: 10.1016/j.chemolab.2011.11.002 handle: http://hdl.handle.net/10449/20737
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