Juan Acosta Jaramillo

Martins, G. S., Yuliarto, M., Yong, W. C., Melia, T., Maretha, M. V., Sharma, M., … Hodge, G. (2024, February 10). Estimation of Additive and Dominance Effects in an Acacia crassicarpa Multi-Environment Progeny Trial Using Genomic Pedigree Reconstruction. FOREST SCIENCE, Vol. 2. https://doi.org/10.1093/forsci/fxae004

Castillo, M. S., Acosta, J. J., Hodge, G. R., Vann, M. C., & Lewis, R. S. (2023, January 16). Analysis of alkaloids and reducing sugars in processed and unprocessed tobacco leaves using a handheld near infrared spectrometer. JOURNAL OF NEAR INFRARED SPECTROSCOPY, Vol. 1. https://doi.org/10.1177/09670335221148594

Ibarra, L., Hodge, G., & Acosta, J. J. (2023). Quantitative Genetics of a Hybrid Population of Eucalyptus nitens x Eucalyptus globulus: Estimation of Genetic Parameters and Implications for Breeding Strategies. FORESTS, 14(2). https://doi.org/10.3390/f14020381

Mostert-O'Neill, M. M., Tate, H., Reynolds, S. M., Mphahlele, M. M., Berg, G., Verryn, S. D., … Myburg, A. A. (2022, July 2). Genomic consequences of artificial selection during early domestication of a wood fibre crop. NEW PHYTOLOGIST, Vol. 7. https://doi.org/10.1111/nph.18297

Perek, M., Hodge, G., Tambarussi, E. V., Biernaski, F. A., & Acosta, J. (2022). Predicted genetic gains for growth traits and wood resistance in Pinus maximinoi and Pinus tecunumanii. CROP BREEDING AND APPLIED BIOTECHNOLOGY, 22(2). https://doi.org/10.1590/1984-70332022v22n2a23

Rocha, L. F., Benatti, T. R., Siqueira, L., Souza, I. C., Bianchin, I., Souza, A. J., … Tambarussi, E. V. (2022). Quantitative trait loci related to growth and wood quality traits in Eucalyptus grandis W. Hill identified through single- and multi-trait genome-wide association studies. TREE GENETICS & GENOMES, 18(6). https://doi.org/10.1007/s11295-022-01570-x

Kropat, M., Laleicke, P. F., & Acosta, J. J. (2022). Towards Inline Prediction of Color Development for Wood Stained with Chemical Stains Using Near-Infrared Spectroscopy. FOREST PRODUCTS JOURNAL, 72(2), 130–139. https://doi.org/10.13073/FPJ-D-22-00021

Jackson, C., Christie, N., Reynolds, S. M., Marais, G. C., Tii‐kuzu, Y., Caballero, M., … Myburg, A. A. (2021). A genome‐wide SNP genotyping resource for tropical pine tree species. Molecular Ecology Resources, 22(2), 695–710. https://doi.org/10.1111/1755-0998.13484

Mostert-O'Neill, M. M., Reynolds, S. M., Acosta, J. J., Lee, D. J., Borevitz, J. O., & Myburg, A. A. (2021). Genomic evidence of introgression and adaptation in a model subtropical tree species,Eucalyptus grandis. MOLECULAR ECOLOGY, 30(3), 625–638. https://doi.org/10.1111/mec.15615

Lu, Y., Payn, K. G., Pandey, P., Acosta, J. J., Heine, A. J., Walker, T. D., & Young, S. (2021). HYPERSPECTRAL IMAGING WITH COST-SENSITIVE LEARNING FOR HIGH-THROUGHPUT SCREENING OF LOBLOLLY PINE (PINUS TAEDA L.) SEEDLINGS FOR FREEZE TOLERANCE. TRANSACTIONS OF THE ASABE, 64(6), 2045–2059. https://doi.org/10.13031/trans.14708

Pandey, P., Payn, K. G., Lu, Y., Heine, A. J., Walker, T. D., Acosta, J. J., & Young, S. (2021). Hyperspectral Imaging Combined with Machine Learning for the Detection of Fusiform Rust Disease Incidence in Loblolly Pine Seedlings. REMOTE SENSING, 13(18). https://doi.org/10.3390/rs13183595

Nel, A., Acosta, J. J., & Hodge, G. R. (2021, September 28). Initial growth results comparing first generation F1 and advanced-generation F2 Pinus patula x Pinus tecunumanii interspecific hybrid families. SOUTHERN FORESTS-A JOURNAL OF FOREST SCIENCE, Vol. 9. https://doi.org/10.2989/20702620.2021.1926370

Lu, Y., Walker, T. D., Acosta, J. J., Young, S., Pandey, P., Heine, A. J., & Payn, K. G. (2021). Prediction of Freeze Damage and Minimum Winter Temperature of the Seed Source of Loblolly Pine Seedlings Using Hyperspectral Imaging. FOREST SCIENCE, 67(3), 321–334. https://doi.org/10.1093/forsci/fxab003

Whittier, W. A., Hodge, G. R., Lopez, J., Saravitz, C., & Acosta, J. J. (2021, July 8). The use of near infrared spectroscopy to predict foliar nutrient levels of hydroponically grown teak seedlings. JOURNAL OF NEAR INFRARED SPECTROSCOPY, Vol. 7. https://doi.org/10.1177/09670335211025649

Caballero, M., Lauer, E., Bennett, J., Zaman, S., McEvoy, S., Acosta, J., … Isik, F. (2021). Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome. APPLICATIONS IN PLANT SCIENCES, 9(6). https://doi.org/10.1002/aps3.11439

Hodge, G. R., & Acosta, J. J. (2020). An Algorithm for Genetic Analysis of Full-Sib Datasets with Mixed-Model Software Lacking a Numerator Relationship Matrix Function, and a Comparison with Results from a Dedicated Genetic Software Package. Forests, 11(11), 1169. https://doi.org/10.3390/f11111169

Acosta, J. J., Castillo, M. S., & Hodge, G. R. (2020). Comparison of benchtop and handheld near-infrared spectroscopy devices to determine forage nutritive value. CROP SCIENCE, 60(6), 3410–3422. https://doi.org/10.1002/csc2.20264

Bekewe, P. E., Castillo, M. S., Acosta, J. J., & Rivera, R. (2020). Defoliation management effects on nutritive value of ‘performer’ switchgrass. Crop Science, 60(3), 1682–1689. https://doi.org/10.1002/csc2.20036

Tyrmi, J. S., Vuosku, J., Acosta, J. J., Li, Z., Sterck, L., Cervera, M. T., … Pyhäjärvi, T. (2020). Genomics of Clinal Local Adaptation in Pinus sylvestris Under Continuous Environmental and Spatial Genetic Setting. G3#58; Genes|Genomes|Genetics, 10(8), 2683–2696. https://doi.org/10.1534/g3.120.401285

Martins, G. S., Yuliarto, M., Antes, R., Sabki, Prasetyo, A., Unda, F., … Acosta, J. J. (2020). Wood and Pulping Properties Variation of Acacia crassicarpa A.Cunn. ex Benth. and Sampling Strategies for Accurate Phenotyping. Forests, 11(10), 1043. https://doi.org/10.3390/f11101043

Acosta, J. J., Fahrenkrog, A. M., Neves, L. G., Resende, M. F. R., Dervinis, C., Davis, J. M., … Kirst, M. (2019). Exome Resequencing Reveals Evolutionary History, Genomic Diversity, and Targets of Selection in the Conifers Pinus taeda and Pinus elliottii. Genome Biology and Evolution, 11(2), 508–520. https://doi.org/10.1093/gbe/evz016

de Moraes, B. F. X., dos Santos, R. F., de Lima, B. M., Aguiar, A. M., Missiaggia, A. A., da Costa Dias, D., … Muñoz, P. R. (2018). Genomic selection prediction models comparing sequence capture and SNP array genotyping methods. Molecular Breeding, 38(9). https://doi.org/10.1007/s11032-018-0865-3

Hodge, G. R., Acosta, J. J., Unda, F., Woodbridge, W. C., & Mansfield, S. D. (2018). Global near infrared spectroscopy models to predict wood chemical properties of Eucalyptus. Journal of Near Infrared Spectroscopy, 26(2), 117–132. https://doi.org/10.1177/0967033518770211

Naidoo, S., Christie, N., Acosta, J. J., Mphahlele, M. M., Payn, K. G., Myburg, A. A., & Külheim, C. (2018). Terpenes associated with resistance against the gall wasp, Leptocybe invasa, in Eucalyptus grandis. Plant, Cell & Environment, 41(8), 1840–1851. https://doi.org/10.1111/pce.13323

Albert, V. A., Barbazuk, W. B., dePamphilis, C. W., Der, J. P., Leebens-Mack, J., Ma, H., … Tomsho, L. (2013). The Amborella Genome and the Evolution of Flowering Plants. Science, 342(6165), 1456–1457. https://doi.org/10.1126/science.1241089

Resende, M. F. R., Jr, Muñoz, P., Acosta, J. J., Peter, G. F., Davis, J. M., Grattapaglia, D., … Kirst, M. (2011). Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments. New Phytologist, 193(3), 617–624. https://doi.org/10.1111/j.1469-8137.2011.03895.x

Stability of Genomic Selection prediction models across ages and environments. (2011). BMC Proceedings. https://doi.org/10.1186/1753-6561-5-s7-o14

Echavarría, H., Correa, G., Patiño, J. F., Acosta, J. J., & Rueda, J. A. (2006). Evaluación de métodos estadísticos utilizados en trabajos de grado y tesis en los programas de la facultad de ciencias agropecuarias, en un período de tres años. Revista Facultad Nacional De Agronomía, 59(2), 3565–3580. Retrieved from https://www.redalyc.org/articulo.oa?id=179914075012

Echavarría Sánchez, H., Correa Londoño, G., Patiño Díez, J., Acosta Jaramillo, J., & Rueda Restrepo, J. (2006). Evaluación de métodos estadísticos utilizados en trabajos de grado y tesis en los programas de la facultad de ciencias agropecuarias, en un período de tres años. Revista Facultad Nacional De Agronomía, Medellín., 59(2), 3465–3580. Retrieved from https://revistas.unal.edu.co/index.php/refame/article/view/24349

Ruiz Suescún, O. A. (2005). Escorrentía superficial en bosques montanos naturales y plantados de Antioquia, Colombia. Revista Facultad Nacional De Agronomía, Medellín., S.l.], v. 58, n. 1, 2635–2649, Retrieved from https://revistas.unal.edu.co/index.php/refame/article/view/21509/22498

Ruiz, O. A., Acosta, J. J., & León, J. D. (2005). Escorrentía superficial en bosques montanos naturales y plantados de Antioquia, Colombia. Revista Facultad Nacional De Agronomía, 58(1), 2635–2649. Retrieved from http://www.bdigital.unal.edu.co/24359/1/21509-73485-1-PB.pdf