Method for accurate fiber length determination from increment cores for large-scale population analyses in Norway spruce. Chen, Z., Abramowicz, K., Raczkowski, R., Ganea, S., Wu, H. X., Lundqvist, S., Mörling, T., de Luna, S. S., García Gil, M. R., & Mellerowicz, E. J. Holzforschung, 70(9):829–838, September, 2016.
Method for accurate fiber length determination from increment cores for large-scale population analyses in Norway spruce [link]Paper  doi  abstract   bibtex   
Abstract Fiber (tracheid) length is an important trait targeted for genetic and silvicultural improvement. Such studies require large-scale non-destructive sampling, and accurate length determination. The standard procedure for non-destructive sampling is to collect increment cores, singularize their cells by maceration, measure them with optical analyzer and apply various corrections to suppress influence of non-fiber particles and cut fibers, as fibers are cut by the corer. The recently developed expectation-maximization method (EM) not only addresses the problem of non-fibers and cut fibers, but also corrects for the sampling bias. Here, the performance of the EM method has been evaluated by comparing it with length-weighing and squared length-weighing, both implemented in fiber analyzers, and with microscopy data for intact fibers, corrected for sampling bias, as the reference. This was done for 12-mm increment cores from 16 Norway spruce ( Picea abies (L.) Karst) trees on fibers from rings 8–11 (counted from pith), representing juvenile wood of interest in breeding programs. The EM-estimates provided mean-fiber-lengths with bias of only +2.7% and low scatter. Length-weighing and length 2 -weighing gave biases of -7.3% and +9.3%, respectively, and larger scatter. The suggested EM approach constitutes a more accurate non-destructive method for fiber length (FL) determination, expected to be applicable also to other conifers.
@article{chen_method_2016,
	title = {Method for accurate fiber length determination from increment cores for large-scale population analyses in {Norway} spruce},
	volume = {70},
	issn = {1437-434X, 0018-3830},
	url = {https://www.degruyter.com/document/doi/10.1515/hf-2015-0138/html},
	doi = {10/f3rwht},
	abstract = {Abstract
            
              Fiber (tracheid) length is an important trait targeted for genetic and silvicultural improvement. Such studies require large-scale non-destructive sampling, and accurate length determination. The standard procedure for non-destructive sampling is to collect increment cores, singularize their cells by maceration, measure them with optical analyzer and apply various corrections to suppress influence of non-fiber particles and cut fibers, as fibers are cut by the corer. The recently developed expectation-maximization method (EM) not only addresses the problem of non-fibers and cut fibers, but also corrects for the sampling bias. Here, the performance of the EM method has been evaluated by comparing it with length-weighing and squared length-weighing, both implemented in fiber analyzers, and with microscopy data for intact fibers, corrected for sampling bias, as the reference. This was done for 12-mm increment cores from 16 Norway spruce (
              Picea abies
              (L.) Karst) trees on fibers from rings 8–11 (counted from pith), representing juvenile wood of interest in breeding programs. The EM-estimates provided mean-fiber-lengths with bias of only +2.7\% and low scatter. Length-weighing and length
              2
              -weighing gave biases of -7.3\% and +9.3\%, respectively, and larger scatter. The suggested EM approach constitutes a more accurate non-destructive method for fiber length (FL) determination, expected to be applicable also to other conifers.},
	number = {9},
	urldate = {2021-06-07},
	journal = {Holzforschung},
	author = {Chen, Zhi-Qiang and Abramowicz, Konrad and Raczkowski, Rafal and Ganea, Stefana and Wu, Harry X. and Lundqvist, Sven-Olof and Mörling, Tommy and de Luna, Sara Sjöstedt and García Gil, María Rosario and Mellerowicz, Ewa J.},
	month = sep,
	year = {2016},
	pages = {829--838},
}
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