Association of spectroscopically determined leaf nutrition related traits and breeding selection in Sassafras tzumu

Abstract

Background Plant traits related to nutrition have an influential role in tree growth, tree production and nutrient cycling. Therefore, the breeding program should consider the genetics of the traits. However, the measurement methods could seriously affect the progress of breeding selection program. In this study, we tested the ability of spectroscopy to quantify the specific leaf nutrition traits including anthocyanins (ANTH), flavonoids (FLAV) and nitrogen balance index (NBI), and estimated the genetic variation of these leaf traits based on the spectroscopic predicted data. Fresh leaves of Sassafras tzumu were selected for spectral collection and ANTH, FLAV and NBI concentrations measurement by standard analytical methods. Partial least squares regression (PLSR), five spectra pre-processing methods, and four variable selection algorisms were conducted for the optimal model selection. Each trait model was simulated 200 times for error estimation. Results The standard normal variate (SNV) to the ANTH model and 1st derivatives to the FLAV and NBI models, combined with significant Multivariate Correlation (sMC) algorithm variable selection are finally regarded as the best performance models. The ANTH model produced the highest accuracy of prediction with a mean R2 of 0.72 and mean RMSE of 0.10%, followed by FLAV and NBI model (mean R2 of 0.58, mean RMSE of 0.11% and mean R2 of 0.44, mean RMSE of 0.04%). High heritability was found for ANTH, FLAV and NBI with h2 of 0.78, 0.58 and 0.61 respectively. It shows that it is beneficial and possible for breeding selection to the improvement of leaf nutrition traits. Conclusions Spectroscopy can successfully characterize the leaf nutrition traits in living tree leaves and the ability to simultaneous multiple plant traits provides a promising and high-throughput tool for the quick analysis of large size samples and serves for genetic breeding program.

Environment influences the genetic structure and genetic differentiation of Sassafras tzumu (Lauraceae)

“…The outcomes demonstrated that precipitation during the driest quarter, precipitation during the wettest month, temperature seasonality, and mean temperature during the wettest quarter chie y in uenced the distribution. Furthermore, a comparison between the simulated outcomes of the distribution range during distinct periods revealed that the suitable habitat for S. tzumu contracted and shifted from the southern to the northern regions [17]. Genotyping-by-sequence (GBS) technology represented one of the streamlined genome sequencing methodologies, aiming to reduce genome complexity through the application of restriction enzymes and the incorporation of single nucleotide polymorphisms (SNPs) [18].…”