Eleven-year Correlation of Physical Fruit Texture Traits between Computerized Penetrometers and Sensory Assessment in an Apple Breeding Program

Abstract

Fruit texture is a major target of apple (Malus domestica) breeding programs due to its influence on consumer preference. This multitrait feature is typically rated using sensory assessment, which is subjective and prone to biases. Instrumental measurements have predominantly targeted firmness of the outer region of fruit cortex using industry standard Magness–Taylor-type penetrometers, while other metrics remain largely unused. Additionally, there have been limited reports on correlating sensory attributes with instrumental metrics on many diverse apple selections. This report is the first to correlate multiyear historical fruit texture information of instrumental metrics and sensory assessment in an apple breeding program. Through 11 years of routine fruit quality evaluation at the Washington State University apple breeding program, physical textural data of 84,552 fruit acquired from computerized penetrometers were correlated with sensory assessment. Correlations among various instrumental metrics are high (0.63 ≤ r ≤ 1.00; P < 0.0001). In correlating instrumental outputs with sensory data, there is a significant correlation (r = 0.43; P < 0.0001) between the instrumental crispness value and sensory crispness. Additionally, instrumental hardness traits are significantly correlated (0.61 ≤ r ≤ 0.69; P < 0.0001) with sensory hardness. Outputs from two versions of computerized penetrometers were tested and shown to have no statistical differences. Overall, this report demonstrates potential use of instrumental metrics as firmness and crispness estimates for selecting apples of diverse backgrounds in a breeding program. However, in testing a large number and diversity of fruit, experimenters should perform data curation and account for lower limits/thresholds of the instrument.

Trends in Fruit Quality Improvement From 15 Years of Selection in the Apple Breeding Program of Washington State University

“…In the PCA variable factor map, juiciness and crispness were highly correlated. Similarly, previous studies reported sensory juiciness to be moderately (Evans et al, 2010;Zdunek et al, 2010;Teh et al, 2020b) to highly correlated (Cliff and Bejaei, 2018) with sensory crispness. In correlating sensory juiciness with instrumental Cn, correlation coefficients ranged from low to moderate, with r values of 0.36 (Evans et al, 2010), 0.72 (Cliff and Bejaei, 2018), and 0.33 (Teh et al, 2020b).…”

“…Similarly, previous studies reported sensory juiciness to be moderately (Evans et al, 2010;Zdunek et al, 2010;Teh et al, 2020b) to highly correlated (Cliff and Bejaei, 2018) with sensory crispness. In correlating sensory juiciness with instrumental Cn, correlation coefficients ranged from low to moderate, with r values of 0.36 (Evans et al, 2010), 0.72 (Cliff and Bejaei, 2018), and 0.33 (Teh et al, 2020b). The range in coefficients could be partially explained by the diversity of germplasm used, wherein the lower correlation coefficients are expected in a more diverse set of germplasm.…”

“…From 2014 to 2019, Mohr TM Digi-Test Model 2 (MDT-2) was used in replacement of MDT-1. No statistical difference was detected in fruit textural outputs between two sequential models of the computerized penetrometers during the transition of WABP from MDT-1 to MDT-2 (Teh et al, 2020b). Mathematical interpretation of texture analysis outputs is based on a two-region anatomy model of peeled apple fruit.…”

“…In addition, tools and instruments for evaluation may change, potentially rendering results/outputs more difficult to compare. Fortunately, the technological transition from computerized penetrometer Mohr TM Digi-Test Model 1 (MDT-1) to Mohr TM Digi-Test Model 2 (MDT-2) was determined to be statistically insignificant (Teh et al, 2020b); however, no data exist to make a similar comparison between the TA-XT2 Texture Analyzer and the MDT-1. Slight changes in the protocol are inevitable over this time span.…”

Modelling and Classification of Apple Textural Attributes Using Sensory, Instrumental and Compositional Analyses

“…Simple apple flesh firmness puncture tests can be conducted using different instruments. For example, penetrometers (i.e., Effegi) could be mounted on a drill press in older versions [ 15 ] or performed by more sophisticated instruments (i.e., MTS traction machine [ 9 ] and Mohr Digi-Test-2 [ 16 , 17 ]) that allow researchers to have a continuous record of the force with penetration [ 17 ]. Care must be taken when comparing determinations taken from the different fruit-firmness instruments, because they generate a unique set of data and sample preparation may not be same.…”