Submitted to: HortScience
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 19, 2010
Publication Date: December 8, 2010
Citation: Ledbetter, C.A., Sisterson, M.S. 2010. Carpological variability of almond (Prunus dulcis [Mill.] D.A. Webb cv Nonpareil) in a single orchard during seven consecutive harvests. HortScience. 45(12):1788-1792. Interpretive Summary: California’s 700,000+ acres of almonds represent more than 70% of the world almond crop, with approximately 35% of the California acreage being the important Nonpareil cultivar. While Nonpareil almonds are sold through their own marketing category, standards do not exist for this widely planted cultivar to distinguish it from other California almonds. By examining Nonpareil almonds grown at a single location over the course of seven consecutive harvests, a model was constructed to examine the year-to-year variation expressed by Nonpareil almond kernels. While Nonpareil almonds varied considerable among the harvest years in all measured characters, a model relating kernel surface area with kernel weight accounted for almost 95% of the expressed variation. This new information points out both strong and weak relationships among measured characteristics in Nonpareil kernels and will be useful in assisting the identification of almonds sold in the Nonpareil marketing category.
Technical Abstract: A multi-year study was conducted in California’s San Joaquin Valley to examine variability of carpological characteristics of the popular ‘Nonpareil’ almond cultivar. Samples of ‘Nonpareil’ almond fruit were collected from a single orchard during seven consecutive harvests and evaluated for 19 specific carpological characters. Harvest year significantly affected all measured variables. Of the evaluated characters, fruit weight was the most variable between years, whereas kernel percentage was one of the least variable characters. Due to year-to-year variability in carpological characters, the relationship between kernel weight and all other measured variables was investigated to determine if regression models could better describe kernels. Kernel weight best explained variability in kernel surface area (R2 = 0.943) with year-to-year variability having only a minor affect on the relationship. The results indicate that ‘Nonpareil’ almonds cannot be described using simple metrics and that definitive metrics must be able to account for differences among years.