# agridatasets - A Comprehensive Collection of Agricultural and Agronomic Datasets
# Version 0.1.1
# Copyright (C) 2026 Renzo Caceres Rossi
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.


#' Bamboo Growth by Geographic Location
#'
#' This dataset, bamboo_growth, is a data frame containing observations on bamboo
#' growth collected from different geographic locations. It includes information on
#' sampling compartments, locality blocks, transect numbers, and counts of old and
#' new bamboo shoots.
#'
#' The dataset name has been kept as 'bamboo_growth' to avoid confusion with other
#' datasets in the R ecosystem. This naming convention helps distinguish this dataset
#' as part of the agridatasets package and assists users in identifying its specific
#' characteristics.
#'
#' @name bamboo_growth
#' @format A data frame with 595 observations and 5 variables:
#' \describe{
#'   \item{Compartment}{Integer vector indicating the sampling compartment}
#'   \item{Locality_Block}{Integer vector indicating the locality block}
#'   \item{Transect_Number}{Integer vector indicating the transect number}
#'   \item{Old_Shoots}{Integer vector indicating the number of old bamboo shoots}
#'   \item{New_Shoots}{Integer vector indicating the number of new bamboo shoots}
#' }
#' @source Data taken from the gpk package version 1.0
#' @usage data(bamboo_growth)
#' @export
load("data/bamboo_growth.rda")
NULL

#' Crossbreeding of Cows
#'
#' This dataset, cows_insemination, is a data frame containing records of artificial
#' insemination and conception in cows collected over multiple time periods. It
#' includes insemination and conception counts for three breeding cycles labeled
#' C1, C2, and C3.
#'
#' The dataset name has been kept as 'cows_insemination' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps distinguish this
#' dataset as part of the agridatasets package and assists users in identifying its
#' specific characteristics.
#'
#' @name cows_insemination
#' @format A data frame with 10 observations and 7 variables:
#' \describe{
#'   \item{Time}{Factor indicating the time period}
#'   \item{Sillod_Insemination_C1}{Integer vector indicating the number of inseminations during cycle 1}
#'   \item{Sillod_Conception_C1}{Integer vector indicating the number of conceptions during cycle 1}
#'   \item{Sillod_Insemination_C2}{Integer vector indicating the number of inseminations during cycle 2}
#'   \item{Sillod_Conception_C2}{Integer vector indicating the number of conceptions during cycle 2}
#'   \item{Sillod_Insemination_C3}{Integer vector indicating the number of inseminations during cycle 3}
#'   \item{Sillod_Conception_C3}{Integer vector indicating the number of conceptions during cycle 3}
#' }
#' @source Data taken from the gpk package version 1.0
#' @usage data(cows_insemination)
#' @export
load("data/cows_insemination.rda")
NULL


#' Population Dynamics of Earthworms
#'
#' This dataset, earthworm_population, is a data frame containing observations on
#' earthworm population dynamics over time. It includes monthly measurements of
#' earthworm density and biomass.
#'
#' The dataset name has been kept as 'earthworm_population' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps distinguish this
#' dataset as part of the agridatasets package and assists users in identifying its
#' specific characteristics.
#'
#' @name earthworm_population
#' @format A data frame with 46 observations and 3 variables:
#' \describe{
#'   \item{Month}{Factor indicating the month of observation}
#'   \item{Density}{Numeric vector indicating earthworm population density}
#'   \item{Biomass}{Numeric vector indicating earthworm biomass}
#' }
#' @source Data taken from the gpk package version 1.0
#' @usage data(earthworm_population)
#' @export
load("data/earthworm_population.rda")
NULL


#' Earthworms in Cultivated Soils
#'
#' This dataset, earthworm_crop_soils, is a data frame containing observations on
#' earthworm populations in cultivated soils. It includes measurements of earthworm
#' density and biomass together with information on crop type, year, and soil type.
#'
#' The dataset name has been kept as 'earthworm_crop_soils' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps distinguish this
#' dataset as part of the agridatasets package and assists users in identifying its
#' specific characteristics.
#'
#' @name earthworm_crop_soils
#' @format A data frame with 12 observations and 5 variables:
#' \describe{
#'   \item{Density}{Integer vector indicating earthworm population density}
#'   \item{Biomass}{Numeric vector indicating earthworm biomass}
#'   \item{Crop}{Factor indicating the crop type}
#'   \item{Year}{Integer vector indicating the year of observation}
#'   \item{Soil}{Factor indicating the soil type}
#' }
#' @source Data taken from the gpk package version 1.0
#' @usage data(earthworm_crop_soils)
#' @export
load("data/earthworm_crop_soils.rda")
NULL


#' Body Weight in Rabbits
#'
#' This dataset, rabbit_body_mass, is a data frame containing measurements used to
#' examine the relationship between hind foot length and body weight in rabbits.
#' It includes continuous measurements of hind foot length and body weight.
#'
#' The dataset name has been kept as 'rabbit_body_mass' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps distinguish this
#' dataset as part of the agridatasets package and assists users in identifying its
#' specific characteristics.
#'
#' @name rabbit_body_mass
#' @format A data frame with 141 observations and 2 variables:
#' \describe{
#'   \item{Hind_Foot_Length}{Numeric vector indicating hind foot length}
#'   \item{Body_Weight}{Numeric vector indicating body weight}
#' }
#' @source Data taken from the gpk package version 1.0
#' @usage data(rabbit_body_mass)
#' @export
load("data/rabbit_body_mass.rda")
NULL


#' Rice and Wheat Production
#'
#' This dataset, rice_wheat_production, is a data frame containing observations on
#' rice and wheat production over multiple years. It includes information on food
#' type, year, area, production, yield, and irrigation.
#'
#' The dataset name has been kept as 'rice_wheat_production' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps distinguish
#' this dataset as part of the agridatasets package and assists users in identifying
#' its specific characteristics.
#'
#' @name rice_wheat_production
#' @format A data frame with 106 observations and 6 variables:
#' \describe{
#'   \item{Food}{Factor indicating the food type}
#'   \item{Year}{Factor indicating the year}
#'   \item{Area}{Numeric vector indicating the area}
#'   \item{Production}{Numeric vector indicating the production}
#'   \item{Yield}{Integer vector indicating the yield}
#'   \item{Irrigated}{Factor indicating irrigation}
#' }
#' @source Data taken from the gpk package version 1.0
#' @usage data(rice_wheat_production)
#' @export
load("data/rice_wheat_production.rda")
NULL


#' Timber Tree Genetic Characteristics
#'
#' This dataset, timber_genetics, is a data frame containing observations on
#' genetic and environmental components of timber tree characteristics. It includes
#' information on locality, year, replicate, subculture, elongation, multiples,
#' rooting, germination, seed length, and seed width.
#'
#' The dataset name has been kept as 'timber_genetics' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps distinguish this
#' dataset as part of the agridatasets package and assists users in identifying its
#' specific characteristics.
#'
#' @name timber_genetics
#' @format A data frame with 224 observations and 10 variables:
#' \describe{
#'   \item{Locality}{Integer vector indicating locality}
#'   \item{Year}{Integer vector indicating year}
#'   \item{Replicate}{Integer vector indicating replicate}
#'   \item{Subculture}{Integer vector indicating subculture}
#'   \item{Elongation}{Numeric vector indicating elongation}
#'   \item{Multiples}{Numeric vector indicating multiples}
#'   \item{Rooting}{Numeric vector indicating rooting}
#'   \item{Germination}{Integer vector indicating germination}
#'   \item{Seed_Length}{Numeric vector indicating seed length}
#'   \item{Seed_Width}{Numeric vector indicating seed width}
#' }
#' @source Data taken from the gpk package version 1.0
#' @usage data(timber_genetics)
#' @export
load("data/timber_genetics.rda")
NULL


#' Factorial Experiment on Corn Hybrids
#'
#' This dataset, corn_hybrid_density, is a data frame containing observations
#' from a factorial experiment comparing three corn hybrids across two sowing
#' densities. It includes information on hybrid, sowing density, and the
#' corresponding response variable.
#'
#' The dataset name has been kept as 'corn_hybrid_density' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name corn_hybrid_density
#' @format A data frame with 24 observations and 3 variables:
#' \describe{
#'   \item{A}{Character vector indicating the corn hybrid}
#'   \item{B}{Character vector indicating the sowing density}
#'   \item{Resp}{Numeric vector indicating the response variable}
#' }
#' @source Data taken from the AgroR package version 1.3.7
#' @usage data(corn_hybrid_density)
#' @export
load("data/corn_hybrid_density.rda")
NULL


#' #' Eucalyptus Grandis Progenies Height
#'
#' This dataset, eucalyptus_progenies, is a data frame containing height
#' measurements of 7-year-old Eucalyptus grandis trees. It includes
#' observations across three trials and six progenies arranged in randomized
#' blocks.
#'
#' The dataset name has been kept as 'eucalyptus_progenies' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name eucalyptus_progenies
#' @format A data frame with 72 observations and 4 variables:
#' \describe{
#'   \item{trati}{Character vector indicating the progeny}
#'   \item{bloc}{Character vector indicating the block}
#'   \item{exp}{Character vector indicating the trial}
#'   \item{resp}{Numeric vector indicating the height response}
#' }
#' @source Data taken from the AgroR package version 1.3.7
#' @usage data(eucalyptus_progenies)
#' @export
load("data/eucalyptus_progenies.rda")
NULL


#' Orange Plant Growth Under Rootstocks
#'
#' This dataset, orange_rootstocks, is a data frame containing observations
#' on orange plants grown under different rootstocks. It includes information
#' on rootstock treatment, block, and the corresponding response variable.
#'
#' The dataset name has been kept as 'orange_rootstocks' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name orange_rootstocks
#' @format A data frame with 27 observations and 3 variables:
#' \describe{
#'   \item{trat}{Character vector indicating the rootstock treatment}
#'   \item{bloco}{Character vector indicating the block}
#'   \item{resp}{Numeric vector indicating the response variable}
#' }
#' @source Data taken from the AgroR package version 1.3.7
#' @usage data(orange_rootstocks)
#' @export
load("data/orange_rootstocks.rda")
NULL


#' Soybean Cultivars Grain Yield
#'
#' This dataset, soybean_cultivars, is a data frame containing grain yield
#' evaluations of ten commercial soybean cultivars arranged in randomized
#' complete blocks. It includes information on cultivar, block, and grain
#' yield.
#'
#' The dataset name has been kept as 'soybean_cultivars' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name soybean_cultivars
#' @format A data frame with 40 observations and 3 variables:
#' \describe{
#'   \item{cult}{Factor w/ 10 levels indicating the cultivar}
#'   \item{bloc}{Factor w/ 4 levels indicating the block}
#'   \item{prod}{Numeric vector indicating the grain yield}
#' }
#' @source Data taken from the AgroR package version 1.3.7
#' @usage data(soybean_cultivars)
#' @export
load("data/soybean_cultivars.rda")
NULL


#' Alfalfa Soil Requirement for Land Evaluation
#'
#' This dataset, alfalfa_soil, is a data frame containing alfalfa soil
#' requirement information for land evaluation. It includes codes for soil
#' parameters together with values across suitability classes and weights.
#'
#' The dataset name has been kept as 'alfalfa_soil' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name alfalfa_soil
#' @format A data frame with 12 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the soil parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(alfalfa_soil)
#' @export
load("data/alfalfa_soil.rda")
NULL

#' Crop Protection Product Lethal Dose
#'
#' This dataset, toxin_lethal_dose, is a data frame containing observations
#' used to identify the lethal dose of a crop protection product. It includes
#' information on dose level together with the number of dead and alive
#' individuals.
#'
#' The dataset name has been kept as 'toxin_lethal_dose' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name toxin_lethal_dose
#' @format A data frame with 6 observations and 3 variables:
#' \describe{
#'   \item{dose}{Numeric vector indicating the dose level}
#'   \item{dead}{Integer vector indicating the number of dead individuals}
#'   \item{alive}{Integer vector indicating the number of alive individuals}
#' }
#' @source Data taken from the mcprofile package version 1.0-1
#' @usage data(toxin_lethal_dose)
#' @export
load("data/toxin_lethal_dose.rda")
NULL



#' Rice Production in Indonesia
#'
#' This dataset, idn_rice_farms, is a data frame containing observations on
#' rice production farms in Indonesia. It includes information on farm size,
#' status, rice varieties, program participation, input use, labor, wages,
#' output, price, and region.
#'
#' The dataset name has been kept as 'idn_rice_farms' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name idn_rice_farms
#' @format A data frame with 1026 observations and 20 variables:
#' \describe{
#'   \item{id}{Integer vector indicating the farm identifier}
#'   \item{size}{Numeric vector indicating the farm size}
#'   \item{status}{Factor w/ 3 levels indicating the status}
#'   \item{varieties}{Factor w/ 3 levels indicating the rice varieties}
#'   \item{bimas}{Factor w/ 3 levels indicating the bimas program participation}
#'   \item{seed}{Integer vector indicating the seed quantity}
#'   \item{urea}{Integer vector indicating the urea quantity}
#'   \item{phosphate}{Integer vector indicating the phosphate quantity}
#'   \item{pesticide}{Integer vector indicating the pesticide quantity}
#'   \item{pseed}{Numeric vector indicating the price of seed}
#'   \item{purea}{Numeric vector indicating the price of urea}
#'   \item{pphosph}{Numeric vector indicating the price of phosphate}
#'   \item{hiredlabor}{Integer vector indicating the hired labor}
#'   \item{famlabor}{Integer vector indicating the family labor}
#'   \item{totlabor}{Integer vector indicating the total labor}
#'   \item{wage}{Numeric vector indicating the wage}
#'   \item{goutput}{Integer vector indicating the gross output}
#'   \item{noutput}{Integer vector indicating the net output}
#'   \item{price}{Numeric vector indicating the price}
#'   \item{region}{Factor w/ 6 levels indicating the region}
#' }
#' @source Data taken from the plm package version 2.6-7
#' @usage data(idn_rice_farms)
#' @export
load("data/idn_rice_farms.rda")
NULL


#' Common Soil Minerals Munsell Colors
#'
#' This dataset, soil_munsell_minerals, is a data frame containing Munsell
#' color information for common soil minerals. It includes information on
#' mineral name, Munsell color notation, hue, value, and chroma.
#'
#' The dataset name has been kept as 'soil_munsell_minerals' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name soil_munsell_minerals
#' @format A data frame with 20 observations and 5 variables:
#' \describe{
#'   \item{mineral}{Character vector indicating the mineral name}
#'   \item{color}{Character vector indicating the Munsell color notation}
#'   \item{hue}{Character vector indicating the Munsell hue}
#'   \item{value}{Integer vector indicating the Munsell value}
#'   \item{chroma}{Integer vector indicating the Munsell chroma}
#' }
#' @source Data taken from the aqp package version 2.3.2
#' @usage data(soil_munsell_minerals)
#' @export
load("data/soil_munsell_minerals.rda")
NULL


#' Traditional Soil Color Names
#'
#' This dataset, soil_munsell_colors, is a data frame containing traditional
#' soil color names associated with Munsell color notation. It includes
#' information on Munsell notation and the corresponding traditional color
#' name.
#'
#' The dataset name has been kept as 'soil_munsell_colors' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name soil_munsell_colors
#' @format A data frame with 482 observations and 2 variables:
#' \describe{
#'   \item{munsell}{Character vector indicating the Munsell color notation}
#'   \item{traditional_name}{Character vector indicating the traditional color name}
#' }
#' @source Data taken from the aqp package version 2.3.2
#' @usage data(soil_munsell_colors)
#' @export
load("data/soil_munsell_colors.rda")
NULL



#' US State Soils
#'
#' This dataset, us_state_soils, is a data frame containing the official
#' state soil for each US state and territory. It includes information on
#' the state name, its abbreviation, and the corresponding soil series.
#'
#' The dataset name has been kept as 'us_state_soils' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name us_state_soils
#' @format A data frame with 52 observations and 3 variables:
#' \describe{
#'   \item{state}{Character vector indicating the state name}
#'   \item{abbreviated}{Character vector indicating the state abbreviation}
#'   \item{series}{Character vector indicating the soil series}
#' }
#' @source Data taken from the aqp package version 2.3.2
#' @usage data(us_state_soils)
#' @export
load("data/us_state_soils.rda")
NULL



#' Red Wine Characteristics and Quality
#'
#' This dataset, red_wine_quality, is a data frame containing physicochemical
#' characteristics and quality ratings of red wine samples from north
#' Portugal. It includes information on acidity, sugar, chlorides, sulfur
#' dioxide, density, pH, sulphates, alcohol, and quality.
#'
#' The dataset name has been kept as 'red_wine_quality' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name red_wine_quality
#' @format A data frame with 1599 observations and 12 variables:
#' \describe{
#'   \item{fixed_acidity}{Numeric vector indicating the fixed acidity}
#'   \item{volatile_acidity}{Numeric vector indicating the volatile acidity}
#'   \item{citric_acid}{Numeric vector indicating the citric acid content}
#'   \item{residual_sugar}{Numeric vector indicating the residual sugar}
#'   \item{chlorides}{Numeric vector indicating the chlorides content}
#'   \item{free_sulfur_dioxide}{Numeric vector indicating the free sulfur dioxide}
#'   \item{total_sulfur_dioxide}{Numeric vector indicating the total sulfur dioxide}
#'   \item{density}{Numeric vector indicating the density}
#'   \item{pH}{Numeric vector indicating the pH}
#'   \item{sulphates}{Numeric vector indicating the sulphates content}
#'   \item{alcohol}{Numeric vector indicating the alcohol content}
#'   \item{quality}{Integer vector indicating the quality rating}
#' }
#' @source Data taken from the live package version 1.5.13
#' @usage data(red_wine_quality)
#' @export
load("data/red_wine_quality.rda")
NULL



#' Cotton Response to Herbicide and Insecticide
#'
#' This dataset, cotton_pesticide, is a data frame containing observations
#' on cotton response to herbicide and insecticide treatments. It includes
#' information on plot identifier, herbicide level, insecticide level, and
#' weight.
#'
#' The dataset name has been kept as 'cotton_pesticide' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name cotton_pesticide
#' @format A data frame with 25 observations and 4 variables:
#' \describe{
#'   \item{ID}{Factor w/ 25 levels indicating the plot identifier}
#'   \item{H}{Numeric vector indicating the herbicide level}
#'   \item{I}{Integer vector indicating the insecticide level}
#'   \item{Weight}{Numeric vector indicating the weight}
#' }
#' @source Data taken from the smbdata package version 0.2.0
#' @usage data(cotton_pesticide)
#' @export
load("data/cotton_pesticide.rda")
NULL



#' Effect of Type and Size of Cutting on Willow Yield
#'
#' This dataset, willow_cutting_yield, is a data frame containing observations
#' on the effect of cutting type and size on willow yield. It includes
#' information on plot identifier, block, plot, cutting type, cutting size,
#' and yield.
#'
#' The dataset name has been kept as 'willow_cutting_yield' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name willow_cutting_yield
#' @format A data frame with 25 observations and 6 variables:
#' \describe{
#'   \item{ID}{Factor w/ 25 levels indicating the plot identifier}
#'   \item{Block}{Factor w/ 5 levels indicating the block}
#'   \item{Plot}{Factor w/ 5 levels indicating the plot}
#'   \item{Type}{Factor w/ 5 levels indicating the cutting type}
#'   \item{Size}{Factor w/ 3 levels indicating the cutting size}
#'   \item{Yield}{Numeric vector indicating the yield}
#' }
#' @source Data taken from the smbdata package version 0.2.0
#' @usage data(willow_cutting_yield)
#' @export
load("data/willow_cutting_yield.rda")
NULL




#' Plant Heights in Glasshouse
#'
#' This dataset, plant_growth_regulator, is a data frame containing plant
#' height measurements from a glasshouse experiment conducted to examine how
#' different doses of a growth regulator affect plant height under
#' controlled conditions. It includes information on pot, row, column,
#' growth regulator dose, and plant height.
#'
#' The dataset name has been kept as 'plant_growth_regulator' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name plant_growth_regulator
#' @format A data frame with 24 observations and 5 variables:
#' \describe{
#'   \item{Pot}{Factor w/ 24 levels indicating the pot}
#'   \item{Row}{Factor w/ 4 levels indicating the row}
#'   \item{Column}{Factor w/ 6 levels indicating the column}
#'   \item{Dose}{Factor w/ 6 levels indicating the growth regulator dose}
#'   \item{Height}{Numeric vector indicating the plant height}
#' }
#' @source Data taken from the smbdata package version 0.2.0
#' @usage data(plant_growth_regulator)
#' @export
load("data/plant_growth_regulator.rda")
NULL




#' Herbicide Efficacy
#'
#' This dataset, blackgrass_herbicide, is a data frame containing data from
#' a factorial experiment conducted to evaluate the efficacy of three
#' herbicides across nine different populations of black-grass. It includes
#' information on plot identifier, replicate, pot, population, type,
#' herbicide, and fresh weight.
#'
#' The dataset name has been kept as 'blackgrass_herbicide' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name blackgrass_herbicide
#' @format A data frame with 135 observations and 7 variables:
#' \describe{
#'   \item{ID}{Factor w/ 135 levels indicating the plot identifier}
#'   \item{Rep}{Factor w/ 5 levels indicating the replicate}
#'   \item{DPot}{Factor w/ 27 levels indicating the pot}
#'   \item{Population}{Factor w/ 9 levels indicating the black-grass population}
#'   \item{Type}{Factor w/ 2 levels indicating the type}
#'   \item{Herbicide}{Factor w/ 3 levels indicating the herbicide}
#'   \item{Fwt}{Numeric vector indicating the fresh weight}
#' }
#' @source Data taken from the smbdata package version 0.2.0
#' @usage data(blackgrass_herbicide)
#' @export
load("data/blackgrass_herbicide.rda")
NULL



#' Ladybird Transmission of Fungus
#'
#' This dataset, ladybird_fungus, is a data frame containing data from an
#' experiment conducted to study the transmission of fungus from ladybirds
#' to aphids on two host plant types (beans or birdsfoot trefoil). It
#' includes information on plot identifier, run, plant, host, ladybird
#' presence, number of cadavers, number of live aphids, and number of
#' infected aphids.
#'
#' The dataset name has been kept as 'ladybird_fungus' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name ladybird_fungus
#' @format A data frame with 72 observations and 8 variables:
#' \describe{
#'   \item{ID}{Factor w/ 72 levels indicating the plot identifier}
#'   \item{Run}{Factor w/ 2 levels indicating the run}
#'   \item{DPlant}{Factor w/ 36 levels indicating the plant}
#'   \item{Host}{Factor w/ 2 levels indicating the host plant type}
#'   \item{Ladybird}{Factor w/ 2 levels indicating the ladybird presence}
#'   \item{Cadaver}{Integer vector indicating the number of cadavers}
#'   \item{Live}{Integer vector indicating the number of live aphids}
#'   \item{Infected}{Integer vector indicating the number of infected aphids}
#' }
#' @source Data taken from the smbdata package version 0.2.0
#' @usage data(ladybird_fungus)
#' @export
load("data/ladybird_fungus.rda")
NULL



#' Toxicity of Nitrofen in Aquatic Systems
#'
#' This dataset, nitrofen_toxicity, is a data frame containing data from an
#' experiment to measure the reproductive toxicity of nitrofen on a species
#' of zooplankton (Ceriodaphnia dubia). Fifty animals were randomized into
#' batches of ten and each batch was put in a solution with a measured
#' concentration of nitrofen. It includes information on nitrofen
#' concentration and brood sizes across three broods along with the total.
#'
#' The dataset name has been kept as 'nitrofen_toxicity' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name nitrofen_toxicity
#' @format A data frame with 50 observations and 5 variables:
#' \describe{
#'   \item{conc}{Numeric vector indicating the nitrofen concentration}
#'   \item{brood1}{Numeric vector indicating the number of offspring in brood 1}
#'   \item{brood2}{Numeric vector indicating the number of offspring in brood 2}
#'   \item{brood3}{Numeric vector indicating the number of offspring in brood 3}
#'   \item{total}{Numeric vector indicating the total number of offspring}
#' }
#' @source Data taken from the boot package version 1.3-32
#' @usage data(nitrofen_toxicity)
#' @export
load("data/nitrofen_toxicity.rda")
NULL




#' Survival of Black Ducks
#'
#' This dataset, black_duck_survival, is a data frame containing survival
#' data on black ducks (Anas rubripes) followed by the US Fish and Wildlife
#' Service. It includes information on duck identifier, time, status, age,
#' weight, and length.
#'
#' The dataset name has been kept as 'black_duck_survival' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name black_duck_survival
#' @format A data frame with 50 observations and 6 variables:
#' \describe{
#'   \item{duck}{Integer vector indicating the duck identifier}
#'   \item{time}{Integer vector indicating the time}
#'   \item{status}{Integer vector indicating the status}
#'   \item{age}{Integer vector indicating the age}
#'   \item{weight}{Integer vector indicating the weight}
#'   \item{length}{Integer vector indicating the length}
#' }
#' @source Data taken from the collett package version 0.1.2
#' @usage data(black_duck_survival)
#' @export
load("data/black_duck_survival.rda")
NULL


#' Potato Scab Infection with Sulfur Treatments
#'
#' This dataset, potato_scab_sulfur, is a data frame containing observations
#' on potato scab infection under different sulfur treatments. It includes
#' information on infection score, treatment, row, and column.
#'
#' The dataset name has been kept as 'potato_scab_sulfur' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name potato_scab_sulfur
#' @format A data frame with 32 observations and 4 variables:
#' \describe{
#'   \item{inf}{Integer vector indicating the infection score}
#'   \item{trt}{Factor w/ 7 levels indicating the treatment}
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(potato_scab_sulfur)
#' @export
load("data/potato_scab_sulfur.rda")
NULL



#' Eelworm Fumigant Treatments
#'
#' This dataset, eelworm_fumigation, is a data frame containing counts of
#' eelworms before and after fumigant treatments. It includes information on
#' block, row, column, fumigant, dose, initial and final eelworm counts,
#' grain, straw, and weeds.
#'
#' The dataset name has been kept as 'eelworm_fumigation' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name eelworm_fumigation
#' @format A data frame with 48 observations and 10 variables:
#' \describe{
#'   \item{block}{Factor w/ 4 levels indicating the block}
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#'   \item{fumigant}{Factor w/ 5 levels indicating the fumigant}
#'   \item{dose}{Integer vector indicating the dose}
#'   \item{initial}{Integer vector indicating the initial eelworm count}
#'   \item{final}{Integer vector indicating the final eelworm count}
#'   \item{grain}{Numeric vector indicating the grain measurement}
#'   \item{straw}{Numeric vector indicating the straw measurement}
#'   \item{weeds}{Numeric vector indicating the weeds measurement}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(eelworm_fumigation)
#' @export
load("data/eelworm_fumigation.rda")
NULL




#' Apple Canker Infestation of Apple Shoots
#'
#' This dataset, apple_canker, is a data frame containing apple canker
#' infestation data across apple cultivars and inoculum levels. It includes
#' information on inoculum level, cultivar, block, number infested, and
#' total number of shoots.
#'
#' The dataset name has been kept as 'apple_canker' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name apple_canker
#' @format A data frame with 36 observations and 5 variables:
#' \describe{
#'   \item{inoculum}{Integer vector indicating the inoculum level}
#'   \item{gen}{Factor w/ 3 levels indicating the cultivar}
#'   \item{block}{Factor w/ 4 levels indicating the block}
#'   \item{y}{Integer vector indicating the number of infested shoots}
#'   \item{n}{Integer vector indicating the total number of shoots}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(apple_canker)
#' @export
load("data/apple_canker.rda")
NULL



#' Carrot Fly Infestation of Carrots
#'
#' This dataset, carrot_fly_infestation, is a data frame containing carrot
#' fly infestation data across carrot genotypes and treatments. It includes
#' information on treatment, genotype, block, total number of plants, and
#' number of infested plants.
#'
#' The dataset name has been kept as 'carrot_fly_infestation' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name carrot_fly_infestation
#' @format A data frame with 96 observations and 5 variables:
#' \describe{
#'   \item{trt}{Factor w/ 2 levels indicating the treatment}
#'   \item{gen}{Factor w/ 16 levels indicating the genotype}
#'   \item{block}{Factor w/ 3 levels indicating the block}
#'   \item{n}{Integer vector indicating the total number of plants}
#'   \item{y}{Integer vector indicating the number of infested plants}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(carrot_fly_infestation)
#' @export
load("data/carrot_fly_infestation.rda")
NULL


#' Ordered Disease Ratings of Strawberry Crosses
#'
#' This dataset, strawberry_cross_disease, is a data frame containing disease
#' ratings for strawberry crosses across parental combinations. It includes
#' information on male parent, female parent, block, disease category, and
#' count.
#'
#' The dataset name has been kept as 'strawberry_cross_disease' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name strawberry_cross_disease
#' @format A data frame with 144 observations and 5 variables:
#' \describe{
#'   \item{male}{Factor w/ 3 levels indicating the male parent}
#'   \item{female}{Factor w/ 4 levels indicating the female parent}
#'   \item{block}{Factor w/ 4 levels indicating the block}
#'   \item{category}{Factor w/ 3 levels indicating the disease category}
#'   \item{count}{Integer vector indicating the count}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(strawberry_cross_disease)
#' @export
load("data/strawberry_cross_disease.rda")
NULL


#' Cork Samples Weight on Four Sides of Trees
#'
#' This dataset, cork_tree_direction, is a data frame containing weight
#' measurements of cork samples taken from four sides of trees. It includes
#' information on tree identifier, direction, and weight.
#'
#' The dataset name has been kept as 'cork_tree_direction' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name cork_tree_direction
#' @format A data frame with 112 observations and 3 variables:
#' \describe{
#'   \item{tree}{Factor w/ 28 levels indicating the tree identifier}
#'   \item{dir}{Factor w/ 4 levels indicating the direction}
#'   \item{y}{Integer vector indicating the weight}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(cork_tree_direction)
#' @export
load("data/cork_tree_direction.rda")
NULL


#' Sample of Egg Weights on 24 Consecutive Days
#'
#' This dataset, egg_weight_daily, is a data frame containing a sample of
#' egg weights collected on 24 consecutive days. It includes information on
#' day and weight.
#'
#' The dataset name has been kept as 'egg_weight_daily' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name egg_weight_daily
#' @format A data frame with 240 observations and 2 variables:
#' \describe{
#'   \item{day}{Integer vector indicating the day}
#'   \item{weight}{Integer vector indicating the egg weight}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(egg_weight_daily)
#' @export
load("data/egg_weight_daily.rda")
NULL



#' Latin Square Experiment for Testing Fungicide
#'
#' This dataset, fungicide_latin_square, is a data frame containing data
#' from a Latin square experiment for testing fungicide. It includes
#' information on treatment, yield, row, and column.
#'
#' The dataset name has been kept as 'fungicide_latin_square' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name fungicide_latin_square
#' @format A data frame with 25 observations and 4 variables:
#' \describe{
#'   \item{trt}{Factor w/ 5 levels indicating the treatment}
#'   \item{yield}{Numeric vector indicating the yield}
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(fungicide_latin_square)
#' @export
load("data/fungicide_latin_square.rda")
NULL



#' Split-Split-Plot Experiment of Wheat
#'
#' This dataset, wheat_splitsplit, is a data frame containing wheat yield
#' data from a split-split-plot experiment. It includes information on row,
#' column, yield, inoculation, treatment, genotype, moisture condition,
#' seed treatment, and block.
#'
#' The dataset name has been kept as 'wheat_splitsplit' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name wheat_splitsplit
#' @format A data frame with 160 observations and 9 variables:
#' \describe{
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#'   \item{yield}{Integer vector indicating the yield}
#'   \item{inoc}{Factor w/ 2 levels indicating the inoculation}
#'   \item{trt}{Integer vector indicating the treatment}
#'   \item{gen}{Factor w/ 2 levels indicating the genotype}
#'   \item{dry}{Factor w/ 2 levels indicating the moisture condition}
#'   \item{dust}{Factor w/ 5 levels indicating the seed treatment}
#'   \item{block}{Factor w/ 4 levels indicating the block}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(wheat_splitsplit)
#' @export
load("data/wheat_splitsplit.rda")
NULL



#' Seed Germination with Different Temperatures
#'
#' This dataset, seed_germination, is a data frame containing seed
#' germination data under different temperatures and concentrations. It
#' includes information on temperature, replicate, concentration, number
#' germinated, and total number of seeds.
#'
#' The dataset name has been kept as 'seed_germination' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name seed_germination
#' @format A data frame with 64 observations and 5 variables:
#' \describe{
#'   \item{temp}{Factor w/ 4 levels indicating the temperature}
#'   \item{rep}{Factor w/ 4 levels indicating the replicate}
#'   \item{conc}{Numeric vector indicating the concentration}
#'   \item{germ}{Integer vector indicating the number germinated}
#'   \item{seeds}{Integer vector indicating the total number of seeds}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(seed_germination)
#' @export
load("data/seed_germination.rda")
NULL



#' Number of Lambs Born to 3 Breeds on 3 Farms
#'
#' This dataset, lamb_births, is a data frame containing lamb birth data
#' across sheep breeds and farms. It includes information on farm, breed,
#' lamb class, and number of lambs.
#'
#' The dataset name has been kept as 'lamb_births' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name lamb_births
#' @format A data frame with 36 observations and 4 variables:
#' \describe{
#'   \item{farm}{Factor w/ 3 levels indicating the farm}
#'   \item{breed}{Factor w/ 3 levels indicating the breed}
#'   \item{lambclass}{Factor w/ 4 levels indicating the lamb class}
#'   \item{y}{Integer vector indicating the number of lambs}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(lamb_births)
#' @export
load("data/lamb_births.rda")
NULL




#' Fungus Infection in Varieties of Wheat
#'
#' This dataset, wheat_bunt, is a data frame containing fungus infection data
#' for different wheat varieties. It includes information on bunt race,
#' percentage infection, replicate, and genotype.
#'
#' The dataset name has been kept as 'wheat_bunt' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name wheat_bunt
#' @format A data frame with 400 observations and 4 variables:
#' \describe{
#'   \item{bunt}{Factor w/ 20 levels indicating the bunt race}
#'   \item{pct}{Numeric vector indicating the percentage infection}
#'   \item{rep}{Factor w/ 2 levels indicating the replicate}
#'   \item{gen}{Factor w/ 10 levels indicating the genotype}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(wheat_bunt)
#' @export
load("data/wheat_bunt.rda")
NULL



#' Leaves for Cauliflower Plants at Different Times
#'
#' This dataset, cauliflower_growth, is a data frame containing cauliflower
#' leaf growth data across different growing times. It includes information
#' on year, degree days, and number of leaves.
#'
#' The dataset name has been kept as 'cauliflower_growth' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name cauliflower_growth
#' @format A data frame with 14 observations and 3 variables:
#' \describe{
#'   \item{year}{Integer vector indicating the year}
#'   \item{degdays}{Numeric vector indicating the degree days}
#'   \item{leaves}{Integer vector indicating the number of leaves}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(cauliflower_growth)
#' @export
load("data/cauliflower_growth.rda")
NULL



#' Intercropping Experiment of Maize and Cowpea
#'
#' This dataset, cowpea_maize_yield, is a data frame containing maize and
#' cowpea yield data under different nitrogen levels from an intercropping
#' experiment. It includes information on block, nitrogen level, cowpea
#' variety, maize variety, cowpea yield, and maize yield.
#'
#' The dataset name has been kept as 'cowpea_maize_yield' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name cowpea_maize_yield
#' @format A data frame with 72 observations and 6 variables:
#' \describe{
#'   \item{block}{Factor w/ 3 levels indicating the block}
#'   \item{nitro}{Factor w/ 4 levels indicating the nitrogen level}
#'   \item{cowpea}{Factor w/ 2 levels indicating the cowpea variety}
#'   \item{maize}{Factor w/ 3 levels indicating the maize variety}
#'   \item{cyield}{Integer vector indicating the cowpea yield}
#'   \item{myield}{Integer vector indicating the maize yield}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(cowpea_maize_yield)
#' @export
load("data/cowpea_maize_yield.rda")
NULL




#' RCB Experiment of Strawberry
#'
#' This dataset, strawberry_yield, is a data frame containing strawberry
#' yield data from a randomized complete block experiment. It includes
#' information on row, column, block, genotype, and yield.
#'
#' The dataset name has been kept as 'strawberry_yield' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name strawberry_yield
#' @format A data frame with 32 observations and 5 variables:
#' \describe{
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#'   \item{block}{Factor w/ 4 levels indicating the block}
#'   \item{gen}{Factor w/ 8 levels indicating the genotype}
#'   \item{yield}{Numeric vector indicating the yield}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(strawberry_yield)
#' @export
load("data/strawberry_yield.rda")
NULL



#' Density and Spacing Experiment for Turnips
#'
#' This dataset, turnip_density, is a data frame containing turnip yield data
#' under different plant densities and spacings across three blocks. It
#' includes information on yield, block, spacing, and density.
#'
#' The dataset name has been kept as 'turnip_density' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name turnip_density
#' @format A data frame with 60 observations and 4 variables:
#' \describe{
#'   \item{yield}{Numeric vector indicating the yield}
#'   \item{block}{Factor w/ 3 levels indicating the block}
#'   \item{spacing}{Integer vector indicating the spacing}
#'   \item{density}{Numeric vector indicating the density}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(turnip_density)
#' @export
load("data/turnip_density.rda")
NULL



#' Uniformity Trial in Apple
#'
#' This dataset, apple_uniformity, is a data frame containing apple yield
#' data from a uniformity trial experiment. It includes information on row,
#' column, and yield.
#'
#' The dataset name has been kept as 'apple_uniformity' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name apple_uniformity
#' @format A data frame with 198 observations and 3 variables:
#' \describe{
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#'   \item{yield}{Integer vector indicating the yield}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(apple_uniformity)
#' @export
load("data/apple_uniformity.rda")
NULL


#' Uniformity Trial of Grape
#'
#' This dataset, grape_uniformity, is a data frame containing grape yield
#' data from a uniformity trial experiment. It includes information on row,
#' column, and yield.
#'
#' The dataset name has been kept as 'grape_uniformity' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name grape_uniformity
#' @format A data frame with 155 observations and 3 variables:
#' \describe{
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#'   \item{yield}{Numeric vector indicating the yield}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(grape_uniformity)
#' @export
load("data/grape_uniformity.rda")
NULL



#' Uniformity Trial of Peach
#'
#' This dataset, peach_uniformity, is a data frame containing peach yield
#' data from a uniformity trial experiment. It includes information on row,
#' column, and yield.
#'
#' The dataset name has been kept as 'peach_uniformity' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name peach_uniformity
#' @format A data frame with 144 observations and 3 variables:
#' \describe{
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#'   \item{yield}{Integer vector indicating the yield}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(peach_uniformity)
#' @export
load("data/peach_uniformity.rda")
NULL



#' Uniformity Trial of Tomato
#'
#' This dataset, tomato_uniformity, is a data frame containing tomato yield
#' data from a uniformity trial experiment. It includes information on row,
#' column, and yield.
#'
#' The dataset name has been kept as 'tomato_uniformity' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name tomato_uniformity
#' @format A data frame with 180 observations and 3 variables:
#' \describe{
#'   \item{row}{Integer vector indicating the row}
#'   \item{col}{Integer vector indicating the column}
#'   \item{yield}{Integer vector indicating the yield}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(tomato_uniformity)
#' @export
load("data/tomato_uniformity.rda")
NULL



#' Insecticide Treatments for Carrot Fly Larvae
#'
#' This dataset, carrot_insecticide, is a data frame containing carrot fly
#' damage data for different insecticide treatments and depths. It includes
#' information on treatment, insecticide, depth, replicate, number of
#' damaged carrots, and total number of carrots.
#'
#' The dataset name has been kept as 'carrot_insecticide' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name carrot_insecticide
#' @format A data frame with 36 observations and 6 variables:
#' \describe{
#'   \item{treatment}{Factor w/ 11 levels indicating the treatment}
#'   \item{insecticide}{Factor w/ 3 levels indicating the insecticide}
#'   \item{depth}{Numeric vector indicating the depth}
#'   \item{rep}{Factor w/ 3 levels indicating the replicate}
#'   \item{damaged}{Integer vector indicating the number of damaged carrots}
#'   \item{total}{Integer vector indicating the total number of carrots}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(carrot_insecticide)
#' @export
load("data/carrot_insecticide.rda")
NULL



#' Weight Gain in Pigs for Different Treatments
#'
#' This dataset, pig_weight_gain, is a data frame containing weight gain
#' data in pigs for different treatments. It includes information on pen,
#' treatment, pig identifier, sex, initial weight, final weight, feed
#' consumption, adjusted initial weight, average daily gain, and feed
#' conversion ratio.
#'
#' The dataset name has been kept as 'pig_weight_gain' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name pig_weight_gain
#' @format A data frame with 30 observations and 10 variables:
#' \describe{
#'   \item{pen}{Factor w/ 5 levels indicating the pen}
#'   \item{treatment}{Factor w/ 3 levels indicating the treatment}
#'   \item{pig}{Integer vector indicating the pig identifier}
#'   \item{sex}{Factor w/ 2 levels indicating the sex}
#'   \item{weight1}{Numeric vector indicating the initial weight}
#'   \item{weight2}{Numeric vector indicating the final weight}
#'   \item{feed}{Numeric vector indicating the feed consumption}
#'   \item{w0}{Integer vector indicating the adjusted initial weight}
#'   \item{g}{Numeric vector indicating the average daily gain}
#'   \item{h}{Numeric vector indicating the feed conversion ratio}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(pig_weight_gain)
#' @export
load("data/pig_weight_gain.rda")
NULL



#' Broiler Chicken Daily Measurements
#'
#' This dataset, broiler_growth, is a data frame containing daily weight,
#' feed, and egg measurements for a broiler chicken. It includes information
#' on body weight, target body weight, average daily feed intake, average
#' daily gain, egg weight, and age.
#'
#' The dataset name has been kept as 'broiler_growth' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name broiler_growth
#' @format A data frame with 59 observations and 6 variables:
#' \describe{
#'   \item{bw}{Integer vector indicating the body weight}
#'   \item{targetbw}{Integer vector indicating the target body weight}
#'   \item{adfi}{Numeric vector indicating the average daily feed intake}
#'   \item{adg}{Numeric vector indicating the average daily gain}
#'   \item{eggwt}{Numeric vector indicating the egg weight}
#'   \item{age}{Integer vector indicating the age}
#' }
#' @source Data taken from the agridat package version 1.26
#' @usage data(broiler_growth)
#' @export
load("data/broiler_growth.rda")
NULL



#' Hawaii Tree Diameter Growth
#'
#' This dataset, hawaii_tree_growth, is a data frame containing diameter
#' growth increments of a tropical tree species in Hawaii. It includes
#' information on tree code, diameter at breast height, total height, crown
#' area, competition index, and current annual increment for 1986, 1987,
#' and 1988.
#'
#' The dataset name has been kept as 'hawaii_tree_growth' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name hawaii_tree_growth
#' @format A data frame with 63 observations and 8 variables:
#' \describe{
#'   \item{tree.code}{Factor w/ 63 levels indicating the tree code}
#'   \item{dbh}{Numeric vector indicating the diameter at breast height}
#'   \item{toth}{Numeric vector indicating the total height}
#'   \item{crown.area}{Numeric vector indicating the crown area}
#'   \item{comp.ind}{Numeric vector indicating the competition index}
#'   \item{cai.1986}{Numeric vector indicating the current annual increment for 1986}
#'   \item{cai.1987}{Numeric vector indicating the current annual increment for 1987}
#'   \item{cai.1988}{Numeric vector indicating the current annual increment for 1988}
#' }
#' @source Data taken from the biometrics package version 1.0.4
#' @usage data(hawaii_tree_growth)
#' @export
load("data/hawaii_tree_growth.rda")
NULL


#' Maximum Plant Size in the Hawaiian Archipelago
#'
#' This dataset, hawaii_plant_size, is a data frame containing maximum plant
#' size measurements for species in the Hawaiian archipelago. It includes
#' information on species, family, native status, sample size, 95th
#' percentile diameter, and maximum diameter of the three largest
#' individuals.
#'
#' The dataset name has been kept as 'hawaii_plant_size' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name hawaii_plant_size
#' @format A data frame with 58 observations and 6 variables:
#' \describe{
#'   \item{species}{Character vector indicating the species}
#'   \item{family}{Integer vector indicating the family code}
#'   \item{native.status}{Factor w/ 2 levels indicating the native status}
#'   \item{n}{Integer vector indicating the sample size}
#'   \item{d95}{Numeric vector indicating the 95th percentile diameter}
#'   \item{dmax3}{Numeric vector indicating the maximum diameter of the three largest individuals}
#' }
#' @source Data taken from the biometrics package version 1.0.4
#' @usage data(hawaii_plant_size)
#' @export
load("data/hawaii_plant_size.rda")
NULL


#' Biological Pest Control
#'
#' This dataset, biological_control, is a data frame containing measurements
#' related to biological pest control experiments. In a study of the
#' effectiveness of biological control of the exotic weed tansy ragwort,
#' researchers manipulated the exposure to the ragwort flea beetle on 15
#' plots that had been planted with a high density of ragwort.
#'
#' The dataset name has been kept as 'biological_control' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name biological_control
#' @format A data frame with 15 observations and 2 variables:
#' \describe{
#'   \item{Load}{Numeric vector indicating the flea beetle load (beetles/gram of ragwort dry mass)}
#'   \item{Mass}{Numeric vector indicating the average dry mass of ragwort remaining (grams/plant)}
#' }
#' @source Data taken from the Sleuth3 package version 1.0-6
#' @usage data(biological_control)
#' @export
load("data/biological_control.rda")
NULL



#' Pollen Removal
#'
#' This dataset, pollen_removal, is a data frame containing data from a
#' study investigating reproductive strategies in plants. Biologists
#' recorded the time spent at sources of pollen and the proportions of
#' pollen removed by bumblebee queens and honeybee workers pollinating a
#' species of lily.
#'
#' The dataset name has been kept as 'pollen_removal' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name pollen_removal
#' @format A data frame with 47 observations and 3 variables:
#' \describe{
#'   \item{PollenRemoved}{Numeric vector indicating the proportion of pollen removed}
#'   \item{DurationOfVisit}{Integer vector indicating the duration of visit}
#'   \item{BeeType}{Factor w/ 2 levels indicating the bee type}
#' }
#' @source Data taken from the Sleuth3 package version 1.0-6
#' @usage data(pollen_removal)
#' @export
load("data/pollen_removal.rda")
NULL



#' River Deforestation Temperatures
#'
#' This dataset, river_deforestation, is a data frame containing air and
#' water temperature measurements before and after deforestation. It
#' includes information on water temperature, air temperature, and
#' deforestation period.
#'
#' The dataset name has been kept as 'river_deforestation' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name river_deforestation
#' @format A data frame with 56 observations and 3 variables:
#' \describe{
#'   \item{Temp_water}{Numeric vector indicating the water temperature}
#'   \item{Temp_air}{Numeric vector indicating the air temperature}
#'   \item{Deforestation}{Factor w/ 2 levels indicating the deforestation period}
#' }
#' @source Data taken from the EnTraineR package version 1.0.0
#' @usage data(river_deforestation)
#' @export
load("data/river_deforestation.rda")
NULL



#' Experimental Design of Kiwifruit Cover Crops
#'
#' This dataset, kiwi_crop_design, is a data frame containing the
#' experimental design of a kiwifruit cover crop study. It includes
#' information on sample identifier and treatment.
#'
#' The dataset name has been kept as 'kiwi_crop_design' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name kiwi_crop_design
#' @format A data frame with 12 observations and 2 variables:
#' \describe{
#'   \item{SampleID}{Character vector indicating the sample identifier}
#'   \item{Treatments}{Character vector indicating the treatment}
#' }
#' @source Data taken from the easynem package version 1.0.3
#' @usage data(kiwi_crop_design)
#' @export
load("data/kiwi_crop_design.rda")
NULL



#' Hass Avocado Weekly US Sales
#'
#' This dataset, avocado_us_sale, is a data frame containing weekly Hass
#' avocado sales data in the US. It includes information on week ending
#' date, type, average selling price, total bulk and bags units, PLU 4046
#' units, PLU 4225 units, PLU 4770 units, total bagged units, small bagged
#' units, large bagged units, and extra-large bagged units.
#'
#' The dataset name has been kept as 'avocado_us_sale' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name avocado_us_sale
#' @format A data frame with 810 observations and 11 variables:
#' \describe{
#'   \item{week_ending}{Date vector indicating the week ending date}
#'   \item{type}{Character vector indicating the type}
#'   \item{avg_selling_price}{Numeric vector indicating the average selling price}
#'   \item{total_bulk_and_bags_units}{Numeric vector indicating the total bulk and bags units}
#'   \item{plu4046_units}{Numeric vector indicating the PLU 4046 units}
#'   \item{plu4225_units}{Numeric vector indicating the PLU 4225 units}
#'   \item{plu4770_units}{Numeric vector indicating the PLU 4770 units}
#'   \item{total_bagged_units}{Numeric vector indicating the total bagged units}
#'   \item{sml_bagged_units}{Numeric vector indicating the small bagged units}
#'   \item{lrg_bagged_units}{Numeric vector indicating the large bagged units}
#'   \item{xlrg_bagged_units}{Numeric vector indicating the extra-large bagged units}
#' }
#' @source Data taken from the avocado package version 0.2.0
#' @usage data(avocado_us_sale)
#' @export
load("data/avocado_us_sale.rda")
NULL


#' Insecticide Doses and Tobacco Budworm
#'
#' This dataset, budworm_pyrethroid, is a data frame containing the number
#' of tobacco budworms dying at various doses of pyrethroid. It includes
#' information on number killed, total number of budworms, dose, and
#' gender.
#'
#' The dataset name has been kept as 'budworm_pyrethroid' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name budworm_pyrethroid
#' @format A data frame with 12 observations and 4 variables:
#' \describe{
#'   \item{Killed}{Integer vector indicating the number killed}
#'   \item{Number}{Integer vector indicating the total number of budworms}
#'   \item{Dose}{Integer vector indicating the dose}
#'   \item{Gender}{Factor w/ 2 levels indicating the gender}
#' }
#' @source Data taken from the GLMsData package version 1.4
#' @usage data(budworm_pyrethroid)
#' @export
load("data/budworm_pyrethroid.rda")
NULL



#' Butterfat and Dairy Cattle
#'
#' This dataset, cattle_butterfat, is a data frame containing the average
#' butterfat content for dairy cattle. It includes information on butterfat
#' content, breed, and age.
#'
#' The dataset name has been kept as 'cattle_butterfat' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name cattle_butterfat
#' @format A data frame with 100 observations and 3 variables:
#' \describe{
#'   \item{Butterfat}{Numeric vector indicating the butterfat content}
#'   \item{Breed}{Factor w/ 5 levels indicating the breed}
#'   \item{Age}{Factor w/ 2 levels indicating the age}
#' }
#' @source Data taken from the GLMsData package version 1.4
#' @usage data(cattle_butterfat)
#' @export
load("data/cattle_butterfat.rda")
NULL


#' Food Consumption for Fish
#'
#' This dataset, fish_feeding, is a data frame containing the food
#' consumption for various fish species. It includes information on
#' species, maximum weight, temperature, aspect ratio, food type, and food
#' consumption.
#'
#' The dataset name has been kept as 'fish_feeding' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name fish_feeding
#' @format A data frame with 33 observations and 6 variables:
#' \describe{
#'   \item{Species}{Factor w/ 33 levels indicating the species}
#'   \item{MaxWt}{Integer vector indicating the maximum weight}
#'   \item{Temp}{Integer vector indicating the temperature}
#'   \item{AR}{Numeric vector indicating the aspect ratio}
#'   \item{Food}{Factor w/ 2 levels indicating the food type}
#'   \item{FoodCon}{Numeric vector indicating the food consumption}
#' }
#' @source Data taken from the GLMsData package version 1.4
#' @usage data(fish_feeding)
#' @export
load("data/fish_feeding.rda")
NULL



#' Sleep Times for Guinea Pigs
#'
#' This dataset, guinea_pig_sleep, is a data frame containing sleep times
#' for guinea pigs. It includes information on dose and sleep time.
#'
#' The dataset name has been kept as 'guinea_pig_sleep' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name guinea_pig_sleep
#' @format A data frame with 30 observations and 2 variables:
#' \describe{
#'   \item{Dose}{Numeric vector indicating the dose}
#'   \item{Sleep}{Numeric vector indicating the sleep time}
#' }
#' @source Data taken from the GLMsData package version 1.4
#' @usage data(guinea_pig_sleep)
#' @export
load("data/guinea_pig_sleep.rda")
NULL



#' Bird Abundance in Grazing Areas
#'
#' This dataset, bird_grazing, is a data frame containing the density of
#' understorey birds at a series of sites in two areas either side of a
#' stockproof fence. It includes information on time period, grazing area,
#' and bird count.
#'
#' The dataset name has been kept as 'bird_grazing' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name bird_grazing
#' @format A data frame with 62 observations and 3 variables:
#' \describe{
#'   \item{When}{Factor w/ 2 levels indicating the time period}
#'   \item{Grazed}{Factor w/ 2 levels indicating the grazing area}
#'   \item{Birds}{Integer vector indicating the bird count}
#' }
#' @source Data taken from the GLMsData package version 1.4
#' @usage data(bird_grazing)
#' @export
load("data/bird_grazing.rda")
NULL



#' World Coffee Production 2016 - 2017
#'
#' This dataset, coffee_production, is a data frame containing world coffee
#' production data. It includes information on country name, coffee
#' production in 2016, and coffee production in 2017.
#'
#' The dataset name has been kept as 'coffee_production' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name coffee_production
#' @format A data frame with 47 observations and 3 variables:
#' \describe{
#'   \item{name_long}{Character vector indicating the country name}
#'   \item{coffee_production_2016}{Integer vector indicating the coffee production in 2016}
#'   \item{coffee_production_2017}{Integer vector indicating the coffee production in 2017}
#' }
#' @source Data taken from the spData package version 2.3.5
#' @usage data(coffee_production)
#' @export
load("data/coffee_production.rda")
NULL



#' Arabica and Robusta Chemical Composition Samples
#'
#' This dataset, coffee_composition, is a data frame containing chemical
#' composition samples of Arabica and Robusta coffee. It includes
#' information on variety, country, water, bean weight, extract yield, pH
#' value, free acid, mineral content, fat, caffeine, trigonelline,
#' chlorogenic acid, neochlorogenic acid, and isochlorogenic acid.
#'
#' The dataset name has been kept as 'coffee_composition' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name coffee_composition
#' @format A data frame with 43 observations and 14 variables:
#' \describe{
#'   \item{Variety}{Factor w/ 2 levels indicating the coffee variety}
#'   \item{Country}{Factor w/ 29 levels indicating the country}
#'   \item{Water}{Numeric vector indicating the water content}
#'   \item{Bean Weight}{Numeric vector indicating the bean weight}
#'   \item{Extract Yield}{Numeric vector indicating the extract yield}
#'   \item{ph Value}{Numeric vector indicating the pH value}
#'   \item{Free Acid}{Numeric vector indicating the free acid content}
#'   \item{Mineral Content}{Numeric vector indicating the mineral content}
#'   \item{Fat}{Numeric vector indicating the fat content}
#'   \item{Caffine}{Numeric vector indicating the caffeine content}
#'   \item{Trigonelline}{Numeric vector indicating the trigonelline content}
#'   \item{Chlorogenic Acid}{Numeric vector indicating the chlorogenic acid content}
#'   \item{Neochlorogenic Acid}{Numeric vector indicating the neochlorogenic acid content}
#'   \item{Isochlorogenic Acid}{Numeric vector indicating the isochlorogenic acid content}
#' }
#' @source Data taken from the IMIFA package version 2.2.0
#' @usage data(coffee_composition)
#' @export
load("data/coffee_composition.rda")
NULL



#' Arabica Coffee Soil Requirement for Land Evaluation
#'
#' This dataset, arabica_soil, is a data frame containing arabica coffee
#' soil requirement information for land evaluation. It includes codes for
#' soil parameters together with values across suitability classes and
#' weights.
#'
#' The dataset name has been kept as 'arabica_soil' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name arabica_soil
#' @format A data frame with 11 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the soil parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(arabica_soil)
#' @export
load("data/arabica_soil.rda")
NULL


#' Arabica Coffee Temp Requirement for Land Evaluation
#'
#' This dataset, arabica_temp, is a data frame containing arabica coffee
#' temperature requirement information for land evaluation. It includes
#' codes for temperature parameters together with values across suitability
#' classes and weights.
#'
#' The dataset name has been kept as 'arabica_temp' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name arabica_temp
#' @format A data frame with 3 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the temperature parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(arabica_temp)
#' @export
load("data/arabica_temp.rda")
NULL



#' Arabica Coffee Terrain Requirement for Land Evaluation
#'
#' This dataset, arabica_terrain, is a data frame containing arabica coffee
#' terrain requirement information for land evaluation. It includes codes
#' for terrain parameters together with values across suitability classes
#' and weights.
#'
#' The dataset name has been kept as 'arabica_terrain' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name arabica_terrain
#' @format A data frame with 6 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the terrain parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(arabica_terrain)
#' @export
load("data/arabica_terrain.rda")
NULL



#' Arabica Coffee Water Requirement for Land Evaluation
#'
#' This dataset, arabica_water, is a data frame containing arabica coffee
#' water requirement information for land evaluation. It includes codes for
#' water-related parameters together with values across suitability classes
#' and weights.
#'
#' The dataset name has been kept as 'arabica_water' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name arabica_water
#' @format A data frame with 4 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the water-related parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(arabica_water)
#' @export
load("data/arabica_water.rda")
NULL



#' Robusta Coffee Soil Requirement for Land Evaluation
#'
#' This dataset, robusta_soil, is a data frame containing robusta coffee
#' soil requirement information for land evaluation. It includes codes for
#' soil parameters together with values across suitability classes and
#' weights.
#'
#' The dataset name has been kept as 'robusta_soil' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name robusta_soil
#' @format A data frame with 10 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the soil parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(robusta_soil)
#' @export
load("data/robusta_soil.rda")
NULL


#' Robusta Coffee Temp Requirement for Land Evaluation
#'
#' This dataset, robusta_temp, is a data frame containing robusta coffee
#' temperature requirement information for land evaluation. It includes
#' codes for temperature parameters together with values across suitability
#' classes and weights.
#'
#' The dataset name has been kept as 'robusta_temp' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name robusta_temp
#' @format A data frame with 3 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the temperature parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(robusta_temp)
#' @export
load("data/robusta_temp.rda")
NULL



#' Robusta Coffee Terrain Requirement for Land Evaluation
#'
#' This dataset, robusta_terrain, is a data frame containing robusta coffee
#' terrain requirement information for land evaluation. It includes codes
#' for terrain parameters together with values across suitability classes
#' and weights.
#'
#' The dataset name has been kept as 'robusta_terrain' to avoid confusion
#' with other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name robusta_terrain
#' @format A data frame with 5 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the terrain parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(robusta_terrain)
#' @export
load("data/robusta_terrain.rda")
NULL


#' Robusta Coffee Water Requirement for Land Evaluation
#'
#' This dataset, robusta_water, is a data frame containing robusta coffee
#' water requirement information for land evaluation. It includes codes for
#' water-related parameters together with values across suitability classes
#' and weights.
#'
#' The dataset name has been kept as 'robusta_water' to avoid confusion with
#' other datasets in the R ecosystem. This naming convention helps
#' distinguish this dataset as part of the agridatasets package and assists
#' users in identifying its specific characteristics.
#'
#' @name robusta_water
#' @format A data frame with 4 observations and 8 variables:
#' \describe{
#'   \item{code}{Character vector indicating the water-related parameter code}
#'   \item{s3_a}{Character vector indicating the s3_a value}
#'   \item{s2_a}{Character vector indicating the s2_a value}
#'   \item{s1_a}{Character vector indicating the s1_a value}
#'   \item{s1_b}{Character vector indicating the s1_b value}
#'   \item{s2_b}{Character vector indicating the s2_b value}
#'   \item{s3_b}{Character vector indicating the s3_b value}
#'   \item{wts}{Character vector indicating the weight}
#' }
#' @source Data taken from the ALUES package version 0.2.1
#' @usage data(robusta_water)
#' @export
load("data/robusta_water.rda")
NULL

#' Commercial Insecticides Used in Tomato Pest Control
#'
#' This dataset, tomato_insecticides, is a data frame containing a curated
#' record of 15 commercial insecticide products used for pest control in
#' tomato (Solanum lycopersicum) cultivation. Each entry documents the
#' product name, active ingredient, and target pest group (caterpillars,
#' aphids, whiteflies, mites, thrips, and nematodes).
#'
#' The dataset name has been kept as 'tomato_insecticides' to avoid
#' confusion with other datasets in the R ecosystem. This naming convention
#' helps distinguish this dataset as part of the agridatasets package and
#' assists users in identifying its specific characteristics.
#'
#' @name tomato_insecticides
#' @format A data frame with 15 observations and 4 variables:
#' \describe{
#'   \item{insecticide_id}{Character vector indicating the insecticide identifier}
#'   \item{product_name}{Character vector indicating the product name}
#'   \item{active_ingredient}{Character vector indicating the active ingredient}
#'   \item{target_pest}{Character vector indicating the target pest group}
#' }
#' @source Data taken from Zenodo: \url{https://zenodo.org/records/21611429}
#' @usage data(tomato_insecticides)
#' @export
load("data/tomato_insecticides.rda")
NULL













