Genetic variation and genotype by environment interactions of juvenile wood chemical properties in<i>Pinus taeda</i>L.
Bibliographic record
Abstract
Genetic variation and genotype by environment interaction (G×E) were studied in several juvenile wood traits of 11 year-old loblolly pine trees (Pinus taeda L.).Wafer thin (200 µm) samples from juvenile (ring 3) and transition (ring 8) wood of 12 mm increment cores were analyzed.Transition wood had higher α-cellulose content (46.1%), longer fiber (1.98 mm), and higher coarseness (0.34), but lower lignin (29.7%) than juvenile wood (cellulose 40.9%, fiber length 1.4 mm, coarseness 0.28 and lignin 30.3%).General combining ability variance for the traits explained 2% to 10% of the total variance, whereas the specific combining ability variance was negligible, except for α-cellulose content in transition wood (2%).Specific combining ability by site interaction variance explained from 5% (fiber length) to 37% (lignin) of the total variance.Weak individual-tree heritabilities were found for all the traits, except coarseness, which was moderately high in both juvenile (0.39) and transition wood (0.30).Full-sib and half-sib family heritabilities of traits ranged 0.29 to 0.72.Genetic correlations of wood quality traits with volume and stem straightness were weak, while favorable genetic correlations of lignin with cellulose, coarseness and fiber length were observed.Implications on forest tree improvement programs were discussed.heritability / genetic correlation / α-cellulose / coarseness / lignin Résumé -Variabilité génétique et stabilité génotype-environnement pour les propriétés chimiques du bois à un stade juvénile chez Pinus taeda L. La variabilité génétique et la stabilité génotype-environnement (G×E) ont été étudiées pour plusieurs caractéristiques du bois juvénile de pins taeda (Pinus taeda L.) âgés de 11 ans.De petits échantillons de bois de 2 mm d'épaisseur ont été extraits de carottes de sondage (12 mm), dans le bois juvénile (cerne 3) et dans la zone de transition (cerne 8).Le bois de transition a une teneur en α-cellulose plus élevée, des fibres plus longues (1,98 mm) et une grosseur de grain plus élevée (0,34) mais une teneur en lignine (29,7 %) plus faible que le bois juvénile (teneur en cellulose : 40,9 %, longueur des fibres : 1,4 mm, grosseur du grain : 0,28 et teneur en lignine : 30,3 %).La variance des aptitudes générales à la combinaison (AGC) explique entre 2 et 10 % de la variance totale, tandis que la variance des aptitudes spécifiques à la combinaison (ASC) est négligeable, excepté pour la teneur en α-cellulose dans la zone de transition (2 %).La variance de du terme d'interaction SCA-site explique de 5 % (longueur de fibres) à 37 % (teneur en lignine) de la variance totale.Les héritabilités au sens strict sont faibles pour tous les caractères sauf pour la grosseur du grain.Pour ce caractère, elle est modérément élevée dans le bois juvénile (0,39) et dans la zone de transition (0,30).Les héritabilités au niveau moyennes de familles de pleins-frères et de demi-frères varient de 0,29 à 0,72 pour ces caractères.Les corrélations génétiques entre propriétés du bois d'une part et le volume et la rectitude du tronc d'autre part sont faibles ; elles sont favorables entre teneur en lignine et teneur en cellulose, grosseur du grain et longueur de fibre.Les implications pour l'amélioration génétique de l'essence sont ensuite discutées.héritabilité / corrélation génétique / α-cellulose / fibre / grosseur du grain / lignine
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".