Journal of the American Society for Horticultural Science (Sep 2022)

Genetic Variation Among 54 Eastern Black Walnut Cultivars for Phenological and Morphological Traits

  • Nicholas Meier,
  • Mark V. Coggeshall,
  • J. Bryan Webber,
  • Elias Bunting,
  • Ronald S. Revord

DOI
https://doi.org/10.21273/JASHS05242-22
Journal volume & issue
Vol. 147, no. 5

Abstract

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Eastern black walnut (Juglans nigra) is a large tree endemic to the eastern United States and is highly sought after for its timber products and uniquely flavored nuts. The University of Missouri Center for Agroforestry in New Franklin, MO, USA, hosts an eastern black walnut cultivar repository. This collection supports an ongoing breeding program to improve economic performance for nut production (kernel weight, nut quality, precocity, and yield). In 1996, 54 cultivars were grafted and planted in a series of experimental orchards for evaluation. From 2001 until 2015, trees were evaluated for 12 phenological and eight nut quality/yield traits. Economically relevant traits including kernel weight, kernel percentage, and precocity (total nuts produced age 6 to 10 years) ranged from 1.1 to 8.6 g, 5.3% to 39.3%, and 16 to 1522 total nuts per tree, respectively. Kernel percentage was positively correlated with kernel weight (r = 0.51) and precocity (r = 0.38). Precocity was negatively correlated with the first (r = −0.39) and last (r = −0.30) female bloom. Principal component analysis and biplot analyses revealed high levels of variation among the cultivars. The first two components explain 43.4% of the total variation. Nut dimensions (nut length and nut thickness), nut and kernel weight, and kernel percentage are the largest drivers of variation in the collection. Eigenvectors for precocity and kernel percentage load together and are orthogonal to kernel weight, suggesting these three important traits can be improved simultaneously. Also, nut length loads with kernel weight, providing a candidate indirect selection parameter to increase kernel weight. These data inform strategies for crossing scheme design, expectations for multitrait genetic gain, complementary hybridization, and identifying unique recombinants.

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