Article title: The New Cranberry Wisconsin Research Station: Renovation Priorities of a ‘Stevens’ Cranberry Marsh Based on Visual Mapping, Genetic Testing, and Yield Data
Authors: Daniel Matusinec, Andrew Maule, Eric Wiesman, Amaya Atucha, Mura Jyostna Devi & Juan Zalapa
Journal: International Journal of Fruit Science
Bibliometrics: Volume 22, Number 01, pages 121 - 132
DOI: http://dx.doi.org/10.1080/15538362.2021.2014016
When the article was initially published, the caption for Figure 4 was “Scatter plot showing a negative correlation (r2 =0.476, p <.039) between 2017 cranberry yield data and percentage genetic contamination, detected using nine microsatellite markers, in the production beds of the Wisconsin Cranberry Research Station.” Based on the regression outlier analysis, the caption for Figure 4 was updated and reposted online as below,
Figure 4. Scatter plot showing a negative correlation (r2 =0.476, p <.039) between 2017 cranberry yield data and percentage genetic contamination, detected using nine microsatellite markers, in the production beds of the Wisconsin Cranberry Research Station. One point was removed based on a regression outlier analysis implemented with the lm() function in R. Point 8 was removed based on 95% confidence interval and corresponded to value of 287.36 for the 2017 yield. However, the Grubbs test for outliers was not significant based on the grubbs.test() function in R, p-value = 0.2852, alternative hypothesis: highest value 287.36 is an outlier.