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Pinus taeda L. (loblolly pine) dominates 13.4 million ha of US southeastern forests and contributes over $30 billion to the economy of the region. The species will also form an important component of the renewable energy portfolio as the United States seeks national and energy security as well as environmental sustainability. This study employed NIR-based chemometric models as a high throughput screening tool to estimate the chemical traits and bioenergy potential of 351 standing loblolly pine trees representing 14 elite genetic families planted on two forest sites. The genotype of loblolly pine families affected the chemical, proximate and energy traits studied. With a range of 36.7% to 42.0%, the largest genetic variation (p-value < 0.0001) was detected in the cellulose content. Furthermore, although family by site interactions were significant for all traits, cellulose was the most stable across the two sites. Considering that cellulose content has strong correlations with other properties, selecting and breeding for cellulose could generate some gains.

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