|STANSELL, ZACHARY - Cornell University|
|BJORKMAN, T - Cornell University|
Submitted to: HortScience
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/19/2017
Publication Date: 12/1/2017
Citation: Stansell, Z., Bjorkman, T., Branham, S., Couillard, D.M., Farnham, M.W. 2017. Use of a quality trait index to increase the reliability of phenotypic evaluations in broccoli. HortScience. 52(11):1490-1495. https://doi:10.21273/HORTSCI12202-17.
Interpretive Summary: Horticultural quality characteristics of mature broccoli heads have traditionally been difficult to quantify in breeding programs. The need to develop a consistent, stringent, and robust means of identifying suitable or non-suitable hybrids for the eastern United States became apparent during the course of conducting field trials at five regional test sites in South Carolina, North Carolina, Virginia, New York, and Maine. Although up to 10 attributes of heads exhibited by tested hybrids were evaluated in all regional trials, decisions to advance entries to more extensive trialing was based on assessments of mean overall-quality scores. It is problematic that this trait tends to be a subjective and difficult-to-define metric of horticultural acceptability that is hard to standardize when there are many raters evaluating multiple trials. With a goal of overcoming this dilemma, scientists at the U.S. Vegetable Laboratory in Charleston, SC, undertook broccoli field trials that were assessed by different and independent raters to determine if a quality trait index could be devised to provide a more robust measure of identifying good quality. Using multiple, more succinctly-defined traits such as head smoothness, bead uniformity and head color to model horticultural quality and compute an index, the scientists showed that the effects of rater variability and overly-subjective assessments can be minimized when employing a relative-importance index to identify superior hybrids. These results will inform future efforts by broccoli breeders to develop hybrids better adapted to the East Coast and are of great interest to horticultural scientists working to make superior hybrids available to eastern vegetable growers.
Technical 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 like head color, head smoothness, bead size, bead uniformity, and others. The head quality indices were tested for both [a] ability to reduce inter-observer rating variability, and [b] ability to emphasize specific attributes which 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, 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.