diff --git a/DESCRIPTION b/DESCRIPTION
index 511b1299a..2dc4faf6f 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -221,7 +221,11 @@ Authors@R:
              family = "Gegzna",
              email = "GegznaV@gmail.com",
              role = "ctb",
-             comment = c(ORCID = "0000-0002-9500-5167")))
+             comment = c(ORCID = "0000-0002-9500-5167")),
+      person(given = "Eduard", 
+             family = "Szoecs",
+             email = "eduardszoecs@gmail.com",
+             role = "ctb"))
 Description: Summarizes key information about statistical
     objects in tidy tibbles. This makes it easy to report results, create
     plots and consistently work with large numbers of models at once.
@@ -327,6 +331,10 @@ Suggests:
     tseries,
     xergm,
     zoo,
+    modeltests,
+    leaps,
+    lm.beta,
+    drc
     metafor
 VignetteBuilder: 
     knitr
@@ -353,6 +361,7 @@ Collate:
     'car-tidiers.R'
     'caret-tidiers.R'
     'data-frame-tidiers.R'
+    'drc-tidiers.R'
     'emmeans-tidiers.R'
     'ergm-tidiers.R'
     'gam-tidiers.R'
diff --git a/NAMESPACE b/NAMESPACE
index 4dc755453..96fe2b258 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -7,6 +7,7 @@ S3method(augment,clm)
 S3method(augment,coxph)
 S3method(augment,decomposed.ts)
 S3method(augment,default)
+S3method(augment,drc)
 S3method(augment,factanal)
 S3method(augment,felm)
 S3method(augment,glm)
@@ -49,6 +50,7 @@ S3method(glance,coxph)
 S3method(glance,cv.glmnet)
 S3method(glance,data.frame)
 S3method(glance,default)
+S3method(glance,drc)
 S3method(glance,durbinWatsonTest)
 S3method(glance,ergm)
 S3method(glance,factanal)
@@ -131,6 +133,7 @@ S3method(tidy,cv.glmnet)
 S3method(tidy,default)
 S3method(tidy,density)
 S3method(tidy,dist)
+S3method(tidy,drc)
 S3method(tidy,durbinWatsonTest)
 S3method(tidy,emmGrid)
 S3method(tidy,ergm)
diff --git a/NEWS.md b/NEWS.md
index a42e8eddc..9687c337d 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -86,6 +86,13 @@ TODO: sort out what happens to `glance.aov()`
 - Added `tidy.regsubsets()` for best subsets linear regression from the `leaps` package
 
 - Added method `tidy.lm.beta()` to tidy `lm.beta` class models (#545 by @mattle24)
+
+- Add feature for glance.biglm to return df.residual
+
+- Patch bug in glance.lavaan (#577)
+
+- Added tidiers for `drc::drm` models (#574 by @edild)
+
 - `tidy.prcomp()` parameter `matrix` gained new options `"scores"`, `"loadings"`, and `"eigenvalues"` (#557 by @GegznaV)
 
 - `tidy.kmeans()` now uses the names of the input variables in the output by
diff --git a/R/drc-tidiers.R b/R/drc-tidiers.R
new file mode 100644
index 000000000..f73ae752c
--- /dev/null
+++ b/R/drc-tidiers.R
@@ -0,0 +1,186 @@
+#' @templateVar class drc
+#' @template title_desc_tidy
+#'
+#' @param x A `drc` object produced by a call to [drc::drm()].
+#' @template param_confint
+#' @template param_unused_dots
+#' @param quick whether to compute a smaller and faster version, containing
+#' only the \code{term}, \code{curveid} and \code{estimate} columns.
+#' @evalRd return_tidy(   
+#'       curveid = "Id of the curve",   
+#'       "term",
+#'       "estimate",
+#'       "std.error",
+#'       "statistic",
+#'       "p.value",
+#'       "conf.low",
+#'       "conf.high"
+#' )
+#' @details The tibble has one row for each curve and term in the regression. The
+#'   `curveid` column indicates the curve.
+#' @author Eduard Szoecs, \email{eduardszoecs@@gmail.com}
+#' @examples 
+#' library(drc)
+#' mod <- drm(dead/total~conc, type, 
+#'    weights = total, data = selenium, fct = LL.2(), type = "binomial")
+#' mod
+#' 
+#' tidy(mod)
+#' tidy(mod, conf.int = TRUE)
+#' tidy(mod, quick = TRUE)
+
+#' glance(mod)
+
+#' # augment(mod)
+#' @export
+#' @seealso [tidy()], [drc::drm()]
+#' @family drc tidiers
+#' @aliases drc_tidiers
+tidy.drc <- function(x, conf.int = FALSE, conf.level = 0.95, quick = FALSE, ...) {
+  if (quick) {
+    co <- coef(x)
+    nam <- names(co)
+    term <- gsub("^(.*):(.*)$", "\\1", nam)
+    curves <- x[["dataList"]][["curveid"]]
+    if (length(unique(curves)) > 1) {
+      curveid <- gsub("^(.*):(.*)$", "\\2", nam)
+    } else {
+      curveid <- unique(curves)
+    }
+    ret <- tibble(term = term,
+                      curveid = curveid,
+                      estimate = unname(co))
+    return(ret)
+  }
+
+  co <- coef(summary(x))
+
+  nam <- rownames(co)
+  term <- gsub("^(.*):(.*)$", "\\1", nam)
+  curves <- x[["dataList"]][["curveid"]]
+  if (length(unique(curves)) > 1) {
+    curveid <- gsub("^(.*):(.*)$", "\\2", nam)
+  } else {
+    curveid <- unique(curves)
+  }
+  ret <- data.frame(term = term,
+                    curveid = curveid,
+                    co, stringsAsFactors = FALSE)
+  names(ret) <- c("term", "curveid", "estimate", "std.error", "statistic",
+    "p.value")
+  rownames(ret) <- NULL
+
+  if (conf.int) {
+    conf <- confint(x, level = conf.level)
+    colnames(conf) <- c("conf.low", "conf.high")
+    rownames(conf) <- NULL
+    ret <- cbind(ret, conf)
+  }
+
+  return(as_tibble(ret))
+}
+
+#' @templateVar class drc
+#' @template title_desc_glance
+#' 
+#' @inherit tidy.drc params examples
+#' @template param_unused_dots
+#' 
+#' @evalRd return_glance(
+#'   "logLik", 
+#'   "AIC",
+#'   "AICc" = "AIC corrected for small samples",
+#'   "BIC",
+#'   "df.residual"
+#' )
+#' @seealso [glance()], [drc::drm()]
+#' @export
+#' @family drc tidiers
+glance.drc <- function(x, ...) {
+  ret <- data.frame(AIC = AIC(x),
+                    BIC = BIC(x),
+                    logLik = logLik(x),
+                    df.residual =  x$df.residual)
+  return(as_tibble(ret))
+}
+
+#' @templateVar class drc
+#' @template title_desc_augment
+
+#' @inherit tidy.drc params examples
+#' @template param_data
+#' @template param_newdata
+#' @template param_confint
+#' @template param_se_fit
+#' @template param_unused_dots
+#'
+#' @evalRd return_augment(".conf.low" = "Lower Confidence Interval",
+#'   ".conf.high" = "Upper Confidence Interval",
+#'   ".se.fit",
+#'   ".fitted",
+#'   ".resid",
+#'   ".cooksd")
+#' 
+#' @seealso [augment()], [drc::drm()]
+#' @export
+#' @author Eduard Szoecs, \email{eduardszoecs@@gmail.com}
+#' @family drc tidiers
+augment.drc <- function(x, data = NULL, newdata = NULL,
+  se_fit = FALSE,  conf.int = FALSE, conf.level = 0.95, ...) {
+
+  if (is.null(data) && is.null(newdata)) {
+    stop("Must specify either `data` or `newdata` argument.", call. = FALSE)
+  }
+
+  # drc doesn't like tibbles
+  if (inherits(newdata, "tbl")) {
+    newdata <- data.frame(newdata)
+  }
+
+  # drc doesn't like NA in the type
+  if (!missing(newdata) || is.null(newdata)) {
+    original <- newdata
+    original$.rownames <- rownames(original)
+  }
+
+  if (!missing(newdata) && x$curveVarNam %in% names(newdata) && 
+    any(is.na(newdata[[x$curveVarNam]]))) {
+      newdata <- newdata[!is.na(newdata[[x$curveVarNam]]), ]
+  }
+
+  ret <- augment_columns(x, data, newdata, se.fit = FALSE)
+
+  if (!is.null(newdata)) {
+    if (conf.int) {
+      preds <- data.frame(predict(x, newdata = newdata, interval = "confidence",
+        level = conf.level))
+      ret[[".conf.low"]] <- preds[["Lower"]]
+      ret[[".conf.high"]] <- preds[["Upper"]]
+    }
+    if (se_fit) {
+      preds <- data.frame(predict(x, newdata = newdata, se.fit = TRUE))
+      ret[[".se.fit"]] <- preds[["SE"]]
+    }
+  }
+
+  # join back removed rows
+  if (!".rownames" %in% names(ret)) {
+    ret$.rownames <- rownames(ret)
+  }
+
+  if (!is.null(original)) {
+    reto <- ret %>% select(starts_with("."))
+    ret <- merge(reto, original, by = ".rownames", all.y = TRUE)
+  }
+
+  # reorder to line up with original
+  ret <- ret[order(match(ret$.rownames, rownames(original))), ]
+  rownames(ret) <- NULL
+
+  # if rownames are just the original 1...n, they can be removed
+  if (all(ret$.rownames == seq_along(ret$.rownames))) {
+    ret$.rownames <- NULL
+  }
+
+  as_tibble(ret)
+}
\ No newline at end of file
diff --git a/man/augment.drc.Rd b/man/augment.drc.Rd
new file mode 100644
index 000000000..03ad6f25e
--- /dev/null
+++ b/man/augment.drc.Rd
@@ -0,0 +1,117 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/drc-tidiers.R
+\name{augment.drc}
+\alias{augment.drc}
+\title{Augment data with information from a(n) drc object}
+\usage{
+\method{augment}{drc}(x, data = NULL, newdata = NULL, se_fit = FALSE,
+  conf.int = FALSE, conf.level = 0.95, ...)
+}
+\arguments{
+\item{x}{A \code{drc} object produced by a call to \code{\link[drc:drm]{drc::drm()}}.}
+
+\item{data}{A \code{\link[=data.frame]{data.frame()}} or \code{\link[tibble:tibble]{tibble::tibble()}} containing the original
+data that was used to produce the object \code{x}. Defaults to
+\code{stats::model.frame(x)} so that \code{augment(my_fit)} returns the augmented
+original data. \strong{Do not} pass new data to the \code{data} argument.
+Augment will report information such as influence and cooks distance for
+data passed to the \code{data} argument. These measures are only defined for
+the original training data.}
+
+\item{newdata}{A \code{\link[=data.frame]{data.frame()}} or \code{\link[tibble:tibble]{tibble::tibble()}} containing all
+the original predictors used to create \code{x}. Defaults to \code{NULL}, indicating
+that nothing has been passed to \code{newdata}. If \code{newdata} is specified,
+the \code{data} argument will be ignored.}
+
+\item{se_fit}{Logical indicating whether or not a \code{.se.fit} column should be
+added to the augmented output. For some models, this calculation can be
+somwhat time-consuming. Defaults to \code{FALSE}.}
+
+\item{conf.int}{Logical indicating whether or not to include a confidence
+interval in the tidied output. Defaults to \code{FALSE}.}
+
+\item{conf.level}{The confidence level to use for the confidence interval
+if \code{conf.int = TRUE}. Must be strictly greater than 0 and less than 1.
+Defaults to 0.95, which corresponds to a 95 percent confidence interval.}
+
+\item{...}{Additional arguments. Not used. Needed to match generic
+signature only. \strong{Cautionary note:} Misspelled arguments will be
+absorbed in \code{...}, where they will be ignored. If the misspelled
+argument has a default value, the default value will be used.
+For example, if you pass \code{conf.lvel = 0.9}, all computation will
+proceed using \code{conf.level = 0.95}. Additionally, if you pass
+\code{newdata = my_tibble} to an \code{\link[=augment]{augment()}} method that does not
+accept a \code{newdata} argument, it will use the default value for
+the \code{data} argument.}
+}
+\description{
+Augment accepts a model object and a dataset and adds
+information about each observation in the dataset. Most commonly, this
+includes predicted values in the \code{.fitted} column, residuals in the
+\code{.resid} column, and standard errors for the fitted values in a \code{.se.fit}
+column. New columns always begin with a \code{.} prefix to avoid overwriting
+columns in the original dataset.
+
+Users may pass data to augment via either the \code{data} argument or the
+\code{newdata} argument. If the user passes data to the \code{data} argument,
+it \strong{must} be exactly the data that was used to fit the model
+object. Pass datasets to \code{newdata} to augment data that was not used
+during model fitting. This still requires that all columns used to fit
+the model are present.
+
+Augment will often behavior different depending on whether \code{data} or
+\code{newdata} is specified. This is because there is often information
+associated with training observations (such as influences or related)
+measures that is not meaningfully defined for new observations.
+
+For convenience, many augment methods provide default \code{data} arguments,
+so that \code{augment(fit)} will return the augmented training data. In these
+cases augment tries to reconstruct the original data based on the model
+object, with some varying degrees of success.
+
+The augmented dataset is always returned as a \link[tibble:tibble]{tibble::tibble} with the
+\strong{same number of rows} as the passed dataset. This means that the
+passed data must be coercible to a tibble. At this time, tibbles do not
+support matrix-columns. This means you should not specify a matrix
+of covariates in a model formula during the original model fitting
+process, and that \code{\link[splines:ns]{splines::ns()}}, \code{\link[stats:poly]{stats::poly()}} and
+\code{\link[survival:Surv]{survival::Surv()}} objects are not supported in input data. If you
+encounter errors, try explicitly passing a tibble, or fitting the original
+model on data in a tibble.
+
+We are in the process of defining behaviors for models fit with various
+\link{na.action} arguments, but make no guarantees about behavior when data is
+missing at this time.
+}
+\examples{
+library(drc)
+mod <- drm(dead/total~conc, type, 
+   weights = total, data = selenium, fct = LL.2(), type = "binomial")
+mod
+
+tidy(mod)
+tidy(mod, conf.int = TRUE)
+tidy(mod, quick = TRUE)
+glance(mod)
+# augment(mod)
+}
+\seealso{
+\code{\link[=augment]{augment()}}, \code{\link[drc:drm]{drc::drm()}}
+
+Other drc tidiers: \code{\link{glance.drc}},
+  \code{\link{tidy.drc}}
+}
+\author{
+Eduard Szoecs, \email{eduardszoecs@gmail.com}
+}
+\concept{drc tidiers}
+\value{
+A \code{\link[tibble:tibble]{tibble::tibble()}} with columns:
+  \item{.cooksd}{Cooks distance.}
+  \item{.fitted}{Fitted or predicted value.}
+  \item{.resid}{The difference between fitted and observed values.}
+  \item{.se.fit}{Standard errors of fitted values.}
+  \item{.conf.low}{Lower Confidence Interval}
+  \item{.conf.high}{Upper Confidence Interval}
+
+}
diff --git a/man/broom.Rd b/man/broom.Rd
index aea95d46f..61c985c7f 100644
--- a/man/broom.Rd
+++ b/man/broom.Rd
@@ -79,6 +79,7 @@ Other contributors:
   \item Jason Muhlenkamp \email{jason.muhlenkamp@gmail.com} [contributor]
   \item Matt Lehman [contributor]
   \item Bill Denney \email{wdenney@humanpredictions.com} (0000-0002-5759-428X) [contributor]
+  \item Eduard Szoecs \email{eduardszoecs@gmail.com} [contributor]
   \item Nic Crane [contributor]
   \item Andrew Bates [contributor]
   \item Vincent Arel-Bundock \email{vincent.arel-bundock@umontreal.ca} (0000-0003-2042-7063) [contributor]
diff --git a/man/glance.drc.Rd b/man/glance.drc.Rd
new file mode 100644
index 000000000..a1d541e3c
--- /dev/null
+++ b/man/glance.drc.Rd
@@ -0,0 +1,64 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/drc-tidiers.R
+\name{glance.drc}
+\alias{glance.drc}
+\title{Glance at a(n) drc object}
+\usage{
+\method{glance}{drc}(x, ...)
+}
+\arguments{
+\item{x}{A \code{drc} object produced by a call to \code{\link[drc:drm]{drc::drm()}}.}
+
+\item{...}{Additional arguments. Not used. Needed to match generic
+signature only. \strong{Cautionary note:} Misspelled arguments will be
+absorbed in \code{...}, where they will be ignored. If the misspelled
+argument has a default value, the default value will be used.
+For example, if you pass \code{conf.lvel = 0.9}, all computation will
+proceed using \code{conf.level = 0.95}. Additionally, if you pass
+\code{newdata = my_tibble} to an \code{\link[=augment]{augment()}} method that does not
+accept a \code{newdata} argument, it will use the default value for
+the \code{data} argument.}
+}
+\description{
+Glance accepts a model object and returns a \code{\link[tibble:tibble]{tibble::tibble()}}
+with exactly one row of model summaries. The summaries are typically
+goodness of fit measures, p-values for hypothesis tests on residuals,
+or model convergence information.
+
+Glance never returns information from the original call to the modelling
+function. This includes the name of the modelling function or any
+arguments passed to the modelling function.
+
+Glance does not calculate summary measures. Rather, it farms out these
+computations to appropriate methods and gathers the results together.
+Sometimes a goodness of fit measure will be undefined. In these cases
+the measure will be reported as \code{NA}.
+}
+\examples{
+library(drc)
+mod <- drm(dead/total~conc, type, 
+   weights = total, data = selenium, fct = LL.2(), type = "binomial")
+mod
+
+tidy(mod)
+tidy(mod, conf.int = TRUE)
+tidy(mod, quick = TRUE)
+glance(mod)
+# augment(mod)
+}
+\seealso{
+\code{\link[=glance]{glance()}}, \code{\link[drc:drm]{drc::drm()}}
+
+Other drc tidiers: \code{\link{augment.drc}},
+  \code{\link{tidy.drc}}
+}
+\concept{drc tidiers}
+\value{
+A \code{\link[tibble:tibble]{tibble::tibble()}} with exactly one row and columns:
+  \item{AIC}{Akaike's Information Criterion for the model.}
+  \item{BIC}{Bayesian Information Criterion for the model.}
+  \item{df.residual}{Residual degrees of freedom.}
+  \item{logLik}{The log-likelihood of the model. [stats::logLik()] may be a useful reference.}
+  \item{AICc}{AIC corrected for small samples}
+
+}
diff --git a/man/tidy.drc.Rd b/man/tidy.drc.Rd
new file mode 100644
index 000000000..1d067924f
--- /dev/null
+++ b/man/tidy.drc.Rd
@@ -0,0 +1,79 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/drc-tidiers.R
+\name{tidy.drc}
+\alias{tidy.drc}
+\alias{drc_tidiers}
+\title{Tidy a(n) drc object}
+\usage{
+\method{tidy}{drc}(x, conf.int = FALSE, conf.level = 0.95,
+  quick = FALSE, ...)
+}
+\arguments{
+\item{x}{A \code{drc} object produced by a call to \code{\link[drc:drm]{drc::drm()}}.}
+
+\item{conf.int}{Logical indicating whether or not to include a confidence
+interval in the tidied output. Defaults to \code{FALSE}.}
+
+\item{conf.level}{The confidence level to use for the confidence interval
+if \code{conf.int = TRUE}. Must be strictly greater than 0 and less than 1.
+Defaults to 0.95, which corresponds to a 95 percent confidence interval.}
+
+\item{quick}{whether to compute a smaller and faster version, containing
+only the \code{term}, \code{curveid} and \code{estimate} columns.}
+
+\item{...}{Additional arguments. Not used. Needed to match generic
+signature only. \strong{Cautionary note:} Misspelled arguments will be
+absorbed in \code{...}, where they will be ignored. If the misspelled
+argument has a default value, the default value will be used.
+For example, if you pass \code{conf.lvel = 0.9}, all computation will
+proceed using \code{conf.level = 0.95}. Additionally, if you pass
+\code{newdata = my_tibble} to an \code{\link[=augment]{augment()}} method that does not
+accept a \code{newdata} argument, it will use the default value for
+the \code{data} argument.}
+}
+\description{
+Tidy summarizes information about the components of a model.
+A model component might be a single term in a regression, a single
+hypothesis, a cluster, or a class. Exactly what tidy considers to be a
+model component varies cross models but is usually self-evident.
+If a model has several distinct types of components, you will need to
+specify which components to return.
+}
+\details{
+The tibble has one row for each curve and term in the regression. The
+\code{curveid} column indicates the curve.
+}
+\examples{
+library(drc)
+mod <- drm(dead/total~conc, type, 
+   weights = total, data = selenium, fct = LL.2(), type = "binomial")
+mod
+
+tidy(mod)
+tidy(mod, conf.int = TRUE)
+tidy(mod, quick = TRUE)
+glance(mod)
+# augment(mod)
+}
+\seealso{
+\code{\link[=tidy]{tidy()}}, \code{\link[drc:drm]{drc::drm()}}
+
+Other drc tidiers: \code{\link{augment.drc}},
+  \code{\link{glance.drc}}
+}
+\author{
+Eduard Szoecs, \email{eduardszoecs@gmail.com}
+}
+\concept{drc tidiers}
+\value{
+A \code{\link[tibble:tibble]{tibble::tibble()}} with columns:
+  \item{conf.high}{Upper bound on the confidence interval for the estimate.}
+  \item{conf.low}{Lower bound on the confidence interval for the estimate.}
+  \item{estimate}{The estimated value of the regression term.}
+  \item{p.value}{The two-sided p-value associated with the observed statistic.}
+  \item{statistic}{The value of a T-statistic to use in a hypothesis that the regression term is non-zero.}
+  \item{std.error}{The standard error of the regression term.}
+  \item{term}{The name of the regression term.}
+  \item{curveid}{Id of the curve}
+
+}
diff --git a/tests/testthat/test-drc.R b/tests/testthat/test-drc.R
new file mode 100644
index 000000000..e5cc42432
--- /dev/null
+++ b/tests/testthat/test-drc.R
@@ -0,0 +1,84 @@
+context("drc")
+
+skip_if_not_installed("modeltests")
+library(modeltests)
+
+skip_if_not_installed("drc")
+library(drc)
+
+mod <- drm(dead/total~conc, type,
+  weights = total, data = selenium, fct = LL.2(), type = "binomial")
+
+test_that("drc tidier arguments", {
+  check_arguments(tidy.drc)
+  check_arguments(glance.drc)
+  check_arguments(augment.drc, strict = FALSE) 
+  # Arguments conf.int, conf.level to `augment.drc` must be listed in the argument glossary.
+})
+
+test_that("tidy.drc", {
+
+  td1 <- tidy(mod)
+  td2 <- tidy(mod, quick = TRUE)
+  td3 <- tidy(mod, robust = TRUE)
+
+  check_tidy_output(td1, strict = FALSE)
+  check_tidy_output(td2, strict = FALSE)
+  check_tidy_output(td3, strict = FALSE)
+})
+
+test_that("glance.drc", {
+
+  gl1 <- glance(mod)
+
+  check_glance_outputs(gl1, strict = FALSE)
+})
+
+test_that("augment.drc", {
+
+  expect_error(
+    augment(mod),
+    regexp = "Must specify either `data` or `newdata` argument."
+  )
+
+  check_augment_function(
+    augment.drc,
+    mod,
+    data = selenium,
+    newdata = selenium)
+})
+
+
+mod2 <- drm(rootl ~ conc, data = ryegrass, fct = W2.4())
+
+test_that("tidy.drc", {
+
+  td1 <- tidy(mod2)
+  td2 <- tidy(mod2, quick = TRUE)
+  td3 <- tidy(mod2, robust = TRUE)
+
+  check_tidy_output(td1, strict = FALSE)
+  check_tidy_output(td2, strict = FALSE)
+  check_tidy_output(td3, strict = FALSE)
+})
+
+test_that("glance.drc", {
+
+  gl2 <- glance(mod2)
+
+  check_glance_outputs(gl2, strict = FALSE)
+})
+
+test_that("augment.drc", {
+
+  expect_error(
+    augment(mod2),
+    regexp = "Must specify either `data` or `newdata` argument."
+  )
+
+  check_augment_function(
+    augment.drc,
+    mod2,
+    data = ryegrass,
+    newdata = ryegrass)
+})
\ No newline at end of file