Predicting age-age genetic correlations in tree-breeding programs: a case study of Pinus taeda L.

Abstract The Third Revolution—the application of molecular biology to plant improvement—is providing biotechnology for Pinus taeda breeding programs in the southern United States. To harness commercial value, forest biotechnology must be integrated with pine breeding. Overlaying an agriculture biotechnology template on any aspect of forestry ignores key historical, economic and biological factors unique to pine breeding programs and even to biotechnology applications. Understanding differences between forestry and agriculture will aid policy decisions about the use of genetically enhanced pines and identify numerous leverage points for directing forest biotechnology research toward commercial advantage. Integrating biotechnology into a P. taeda breeding program is illustrated using a case study approach. A molecular marker system is proposed for improving the selection efficacy of a pine breeding program. South. J. Appl. For. 25(3):116–121.

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Genetic Parameters and Genotype-by-Environment Interactions in Regional Progeny Tests of Pinus taeda L. in the Southern USA

Forest Science ◽

10.1093/forsci/fxaa035 ◽

2020 ◽

Author(s):

Edwin Lauer ◽

Andrew Sims ◽

Steven McKeand ◽

Fikret Isik

Keyword(s):

Genetic Variation ◽

Pinus Taeda ◽

Genetic Parameters ◽

Genetic Correlations ◽

Breeding Program ◽

Model Fit ◽

Genotype By Environment Interactions ◽

Genotype By Environment ◽

Progeny Tests ◽

Pinus Taeda L

Abstract Genetic parameters were estimated using a five-series multienvironment trial of Pinus taeda L. in the southern USA. There were 324 half-sib families planted in five test series across 37 locations. A set of six variance/covariance matrices for the genotype-by-environment (G × E) effect for tree height and diameter were compared on the basis of model fit. In single-series analysis, extended factor analytical models provided generally superior model fit to simpler models for both traits; however, in the combined-series analysis, diameter was optimally modeled using simpler variance/covariance structures. A three-way compound term for modeling G × E interactions among and within series yielded substantial improvements in terms of model fit and standard errors of predictions. Heritability of family means ranged between 0.63 and 0.90 for both height and diameter. Average additive genetic correlations among sites were 0.70 and 0.61 for height and diameter, respectively, suggesting the presence of some G × E interaction. Pairs of sites with the lowest additive genetic correlations were located at opposite ends of the latitude range. Latent factor regression revealed a small number of parents with large factor scores that changed ranks significantly between southern and northern environments. Study Implications Multienvironmental progeny tests of loblolly pine (Pinus taeda L.) were established over 10 years in the southern United States to understand the genetic variation for the traits of economic importance. There was substantial genetic variation between open-pollinated families, suggesting that family selection would be efficient in the breeding program. Genotype-by-environment interactions were negligible among sites in the deployment region but became larger between sites at the extremes of the distribution. The data from these trials are invaluable in informing the breeding program about the genetic merit of selection candidates and their potential interaction with the environment. These results can be used to guide deployment decisions in the southern USA, helping landowners match germplasm with geography to achieve optimal financial returns and conservation outcomes.

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Growth and Yield Following Four Reproduction Cutting Methods in Loblolly-Shortleaf Pine Stands--A Case Study

Southern Journal of Applied Forestry ◽

10.1093/sjaf/6.2.66 ◽

1982 ◽

Vol 6 (2) ◽

pp. 66-74 ◽

Cited By ~ 4

Author(s):

James B. Baker ◽

Paul A. Murphy

Keyword(s):

Pinus Taeda ◽

Growth And Yield ◽

Shortleaf Pine ◽

Advantages And Disadvantages ◽

Land Owners ◽

Second Growth ◽

Pine Regeneration ◽

Volume Production ◽

Pinus Taeda L

Abstract Four reproduction cutting methods employed on an average site (S.I. = 85 to 90 feet at 50 years) in second-growth loblolly-shortleaf pine (Pinus taeda L.--P. echinata Mill.) in south Arkansas provided adequate pine regeneration to establish or maintain well-stocked stands. During the 36-year study period, heavy seed-tree and diameter-limit cutting methods produced significantly more cubic-foot volume than selection and clearcutting, while clearcutting resulted in significantly less board-foot (Doyle) volume. Since many trees on the clearcut areas are just now reaching sawlog size, board-foot volume production among all treatments will probably equalize as time goes on. Advantages and disadvantages of the four cutting methods for large landholders and private nonindustrial land-owners are discussed.

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Fire and Fertilizer as Alternatives to Hand Thinning in a Natural Stand of Precommercial-Sized Loblolly Pine

Southern Journal of Applied Forestry ◽

10.1093/sjaf/19.1.5 ◽

1995 ◽

Vol 19 (1) ◽

pp. 5-9

Author(s):

F. Thomas Lloyd ◽

Thomas A. Waldrop ◽

David L. White

Keyword(s):

Pinus Taeda ◽

Loblolly Pine ◽

Nitrogen Fertilizer ◽

Prescribed Burning ◽

Height Growth ◽

Stem Density ◽

Economic Returns ◽

Natural Stand ◽

Pinus Taeda L

Abstract A winter backing fire thinned a natural 4-yr-old loblolly pine (Pinus taeda L.) stand from below but reduced stem density less than did hand thinning. Application of nitrogen fertilizer did not accelerate natural thinning over the 4 yr test period. Burning and fertilizing increased dbh growth of crop trees, but gains were less than those produced by hand thinning. Height growth of crop trees was increased by fertilization but may have been reduced by burning. A case study showed that economic returns from prescribed burning were comparable to those from hand thinning for a 30-yr rotation. However, additional research is needed to produce prescription guidelines that minimize the risks of burning young stands before the practice can be recommended. South. J. Appl. For. 19(1): 5-9.

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Prediction ability of genome-wide markers in Pinus taeda L. within and between population is affected by relatedness to the training population and trait genetic architecture

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab405 ◽

2021 ◽

Author(s):

Edwin Lauer ◽

James Holland ◽

Fikret Isik

Keyword(s):

Pinus Taeda ◽

Genomic Prediction ◽

Tree Breeding ◽

Strong Impact ◽

Training Population ◽

Stem Form ◽

Linkage Phase ◽

Prediction Ability ◽

Group 5 ◽

Pinus Taeda L

Abstract Genomic prediction has the potential to significantly increase the rate of genetic gain in tree breeding programs. In this study, a clonally replicated population (n = 2063) was used to train a genomic prediction model. The model was validated both within the training population and in a separate population (n = 451). The prediction abilities from random (20% vs. 80%) cross validation within the training population were 0.56 and 0.78 for height and stem form, respectively. Removal of all full-sib relatives within the training population resulted in ∼50% reduction in their genomic prediction ability for both traits. The average prediction ability for all 451 individual trees was 0.29 for height and 0.57 for stem form. The degree of genetic linkage (full sib family, half sib family, unrelated) between the training and validation sets had a strong impact on prediction ability for stem form but not for height. A dominant dwarfing allele, the first to be reported in a conifer species, was discovered via GWAS on linkage group 5 that conferred a 0.33 m mean height reduction. However, the QTL was family specific. The rapid decay of LD, large genome size, and inconsistencies in marker-QTL linkage phase suggest that large, diverse training populations are needed for genomic selection in Pinus taeda L.

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Faculty Opinions recommendation of Apparent homology of expressed genes from wood-forming tissues of loblolly pine (Pinus taeda L.) with Arabidopsis thaliana.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1015332.196410 ◽

2003 ◽

Author(s):

Guenter Theissen

Keyword(s):

Arabidopsis Thaliana ◽

Pinus Taeda ◽

Loblolly Pine ◽

Pinus Taeda L

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A Consensus Map for Loblolly Pine (Pinus taeda L.). I. Construction and Integration of Individual Linkage Maps From Two Outbred Three-Generation Pedigrees

Genetics ◽

10.1093/genetics/151.1.321 ◽

1999 ◽

Vol 151 (1) ◽

pp. 321-330 ◽

Cited By ~ 4

Author(s):

Mitchell M Sewell ◽

Bradley K Sherman ◽

David B Neale

Keyword(s):

Pinus Taeda ◽

Loblolly Pine ◽

Fragment Length Polymorphism ◽

Random Amplified Polymorphic Dna ◽

Mapping Function ◽

Genetic Maps ◽

Linkage Data ◽

Linkage Maps ◽

Consensus Map ◽

Pinus Taeda L

Abstract A consensus map for loblolly pine (Pinus taeda L.) was constructed from the integration of linkage data from two unrelated three-generation outbred pedigrees. The progeny segregation data from restriction fragment length polymorphism, random amplified polymorphic DNA, and isozyme genetic markers from each pedigree were recoded to reflect the two independent populations of parental meioses, and genetic maps were constructed to represent each parent. The rate of meiotic recombination was significantly greater for males than females, as was the average estimate of genome length for males {1983.7 cM [Kosambi mapping function (K)]} and females [1339.5 cM(K)]. The integration of individual maps allows for the synthesis of genetic information from independent sources onto a single consensus map and facilitates the consolidation of linkage groups to represent the chromosomes (n = 12) of loblolly pine. The resulting consensus map consists of 357 unique molecular markers and covers ∼1300 cM(K).

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Contrasting genotypes, soil amendments, and their interactive effects on short-term total soil CO2 efflux in a 3-year-old Pinus taeda L. plantation

Soil Biology and Biochemistry ◽

10.1016/j.soilbio.2013.10.050 ◽

2014 ◽

Vol 69 ◽

pp. 93-100 ◽

Cited By ~ 5

Author(s):

Michael C. Tyree ◽

John R. Seiler ◽

Chris A. Maier

Keyword(s):

Pinus Taeda ◽

Soil Amendments ◽

Soil Co2 Efflux ◽

Interactive Effects ◽

Co2 Efflux ◽

Soil Co2 ◽

Short Term ◽

Total Soil ◽

Pinus Taeda L

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Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Sensors ◽

10.3390/s21123971 ◽

2021 ◽

Vol 21 (12) ◽

pp. 3971

Author(s):

Gabriel Silva de Oliveira ◽

José Marcato Junior ◽

Caio Polidoro ◽

Lucas Prado Osco ◽

Henrique Siqueira ◽

...

Keyword(s):

Remote Sensing ◽

Dry Matter ◽

Pearson Correlation ◽

Genetic Correlations ◽

Remote Sensing Data ◽

Breeding Program ◽

Yield Traits ◽

Dry Matter Yield ◽

Breeding Programs ◽

Ground Truth Data

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the efficiency of forage breeding programs, to support high-throughput phenotyping (HTP), aiming to estimate parameters correlated to important traits. The main goal of this study was to propose a convolutional neural network (CNN) approach using UAV-RGB imagery to estimate dry matter yield traits in a guineagrass breeding program. For this, an experiment composed of 330 plots of full-sib families and checks conducted at Embrapa Beef Cattle, Brazil, was used. The image dataset was composed of images obtained with an RGB sensor embedded in a Phantom 4 PRO. The traits leaf dry matter yield (LDMY) and total dry matter yield (TDMY) were obtained by conventional agronomic methodology and considered as the ground-truth data. Different CNN architectures were analyzed, such as AlexNet, ResNeXt50, DarkNet53, and two networks proposed recently for related tasks named MaCNN and LF-CNN. Pretrained AlexNet and ResNeXt50 architectures were also studied. Ten-fold cross-validation was used for training and testing the model. Estimates of DMY traits by each CNN architecture were considered as new HTP traits to compare with real traits. Pearson correlation coefficient r between real and HTP traits ranged from 0.62 to 0.79 for LDMY and from 0.60 to 0.76 for TDMY; root square mean error (RSME) ranged from 286.24 to 366.93 kg·ha−1 for LDMY and from 413.07 to 506.56 kg·ha−1 for TDMY. All the CNNs generated heritable HTP traits, except LF-CNN for LDMY and AlexNet for TDMY. Genetic correlations between real and HTP traits were high but varied according to the CNN architecture. HTP trait from ResNeXt50 pretrained achieved the best results for indirect selection regardless of the dry matter trait. This demonstrates that CNNs with remote sensing data are highly promising for HTP for dry matter yield traits in forage breeding programs.

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