Department of Forestry, College of Forest Resources, Mississippi State University, Mississippi State, 39762, MS, United States
Abstract: Global warming is negatively impacting life on Earth, and replacing fossil fuels with bioenergy from fast-growing, short-rotation woody poplar crops has been proposed as a promising green solution. However, the selection of high-performing genotypes has been hindered by the comparatively low heritability of productivity and its significant genotype × environment interaction. An alternative to selecting productive genotypes by measuring yield is using easily measured morphophysiological traits genetically correlated with yield. Here, we explored the feasibility of using easily measured leaf functional traits to predict Populus productivity and water use efficiency (WUE) by selecting and planting 108 genotypes from six different taxa of eastern cottonwood and hybrid poplars. Our results suggest that easily measured leaf functional traits such as leaf stomatal conductance, leaf petiole length, photosynthesis, and leaf nitrogen content per leaf mass are the most predictive parameters for Populus productivity and WUE prediction. Specifically, the weighted multiple linear regression model fitted using leaf stomatal conductance, leaf petiole length, and photosynthesis explains over 83% of the variance of Populus productivity, and the RMSE percent is 37%. The weighted multiple linear regression model fitted using leaf stomatal conductance, leaf petiole length, and leaf nitrogen content per leaf mass explains over 93% of the variance of Populus WUE, and the RMSE percent is 11.4%. Our findings provide insights for the indirect selection of highly water-use efficient and productive genotypes of Populus for bioenergy production. Predicting productivity and water use efficiency using leaf functional traits can help optimize bioenergy crop production, leading to a more sustainable alternative to fossil fuels.
