Use of a quality trait index to increase the reliability of phenotypic evaluations in Broccoli

Abstract

Selection of superior broccoli hybrids involves multiple considerations, including optimization of head quality traits. Quality assessment of broccoli heads is often confounded by relatively subjective human preferences for optimal appearance of heads. To assist the selection process, we assessed five candidate head quality indices that make use of a set of individual and distinct ratings for traits such as head color, head smoothness, bead size, bead uniformity, and others. The head quality indices were tested for both a) the ability to reduce interobserver rating variability and b) the ability to emphasize specific attributes that display the greatest associations with overall horticultural quality of heads. Index development was based on datasets generated from quality evaluations by three independent raters of two replicated variety trials in Spring 2014. Relative-importance analysis was used to identify specific traits most associated with overall quality. Developed models were subsequently tested and compared using data collected by three raters evaluating two similar trials in Spring 2015. Head smoothness, bead uniformity, head color, and holding ability were found to account for 78% of the model variation in overall head quality. Intraclass correlation coefficients (ICCs), which measure the degree of concordance among raters, were increased from 0.71 to 0.88 (P < 0.05) in one 2015 trial and from 0.67 to 0.80 (P < 0.05) in the second when comparing the simple overall quality assessment to the use of the index weighted by the most important individual head attributes. Thus, results showed that a quality index taking into account the relative importance of individual traits should enhance the identification of the best hybrids adapted to target conditions. This method can be used to improve concordance for subjective ratings in general.