diff --git a/README.Rmd b/README.Rmd
index cca2494..e37c966 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -6,7 +6,7 @@ output: github_document
 
 Plant breeders typically use multi-environment datasets that are unbalanced with respect to individuals over time and often within year as well. Experimental designs and the best models for micro-environmental variation may also vary with environment, defined as a location x year combination. These complexities can be handled efficiently with a two-stage analysis, in which best linear unbiased estimates (BLUEs) of genotypic value are computed for each environment in Stage 1 and then used as the response variable in Stage 2. To fully utilize the data, however, the variance-covariance matrix of the estimates from Stage 1 should be included in Stage 2 ([Piepho et al. 2012](https://doi.org/10.1002/bimj.201100219); [Damesa et al. 2017](https://doi.org/10.2134/agronj2016.07.0395)), which is not possible with most software packages for genomics-assisted breeding. 
 
-R package StageWise was developed to provide a simple interface for genomic selection and GWAS based on a fully efficient, two-stage analysis. Each phenotypic record is associated with a single genotype id, which is suitable for clonal and inbred lines but not hybrid crops. The ASReml-R package is used for variance component estimation, which requires a license from [VSN International](https://www.vsni.co.uk/software/asreml-r).
+R package StageWise was developed to provide a simple interface for genomic selection and GWAS based on a fully efficient, two-stage analysis [(Endelman 2023)](https://doi.org/10.1007/s00122-023-04298-x). Each phenotypic record is associated with a single genotype id, which is suitable for clonal and inbred lines but not hybrid crops. The ASReml-R package is used for variance component estimation, which requires a license from [VSN International](https://www.vsni.co.uk/software/asreml-r). 
 
 Software development has been supported by USDA Hatch Project 1013047 and the USDA National Institute of Food and Agriculture (NIFA) Award 2020-51181-32156. The potato datasets were generated with support from NIFA Awards 2016-34141-25707 and 2019-34141-30284, Potatoes USA, the Wisconsin Potato and Vegetable Growers Association, and the University of Wisconsin-Madison.
 
diff --git a/README.md b/README.md
index 44da8e2..f00c419 100644
--- a/README.md
+++ b/README.md
@@ -18,10 +18,11 @@ possible with most software packages for genomics-assisted breeding.
 
 R package StageWise was developed to provide a simple interface for
 genomic selection and GWAS based on a fully efficient, two-stage
-analysis. Each phenotypic record is associated with a single genotype
-id, which is suitable for clonal and inbred lines but not hybrid crops.
-The ASReml-R package is used for variance component estimation, which
-requires a license from [VSN
+analysis [(Endelman 2023)](https://doi.org/10.1007/s00122-023-04298-x).
+Each phenotypic record is associated with a single genotype id, which is
+suitable for clonal and inbred lines but not hybrid crops. The ASReml-R
+package is used for variance component estimation, which requires a
+license from [VSN
 International](https://www.vsni.co.uk/software/asreml-r).
 
 Software development has been supported by USDA Hatch Project 1013047
diff --git a/inst/CITATION b/inst/CITATION
index 6b44bf3..2e0f4f1 100644
--- a/inst/CITATION
+++ b/inst/CITATION
@@ -3,8 +3,9 @@ citHeader("To cite the StageWise package in publications, please use")
 citEntry(entry="Article",
 	title="Fully efficient, two-stage analysis of multi-environment trials with directional dominance and multi-trait genomic selection",
 	author=personList(as.person("J. B. Endelman")),
-	year=2022,
-	journal="bioRxiv",
-    pages="BIORXIV/2022/509884",	
-    textVersion="Endelman JB (2022) Fully efficient, two-stage analysis of multi-environment trials with directional dominance and multi-trait genomic selection. BIORXIV/2022/509884"
+	year=2023,
+	journal="Theoretical and Applied Genetics",
+	volume="136",
+    pages="65",	
+    textVersion="Endelman JB (2023) Fully efficient, two-stage analysis of multi-environment trials with directional dominance and multi-trait genomic selection. Theoretical and Applied Genetics 136:65"
 )