Calculate agrometeorological variables for crops
             including growing degree days (McMaster, GS & Wilhelm, WW
             (1997) <doi:10.1016/S0168-1923(97)00027-0>), cumulative
             rainfall, number of stress days and cumulative or mean
             radiation and evaporation. Convert dates to day of year
             and vice versa. Also, download curated and interpolated
             Australian weather data from the Queensland Government
             DES longpaddock website
             <https://www.longpaddock.qld.gov.au/>. This data is
             freely available under the Creative Commons 4.0 licence.

Implements the Changepoints for a Range of Penalties (CROPS) algorithm of Haynes et al. (2017) <doi:10.1080/10618600.2015.1116445> for finding all of the optimal segmentations for multiple penalty values over a continuous range.

Interface to easily access Cropland Data Layer (CDL) data for any area of interest via the 'CropScape' <https://nassgeodata.gmu.edu/CropScape/> web service.

Calculates daily climate water balance for irrigation purposes and 
  also calculates the reference evapotranspiration (ET) using three methods,
  Penman and Monteith  (Allen et al. 1998, ISBN:92-5-104219-5);
  Priestley and Taylor (1972) <doi:10/cr3qwn>; or Hargreaves and Samani (1985)
  <doi:10.13031/2013.26773>.  Users may specify a management allowed depletion
  (MAD), which is used to suggest when to irrigate.  The functionality allows
  for the use of crop and water stress coefficients as well.

Climate crop zoning based in minimum and maximum air temperature. The data used in the package are from 'TerraClimate' dataset (<https://www.climatologylab.org/terraclimate.html>), but, it have been calibrated with automatic weather stations  of National Meteorological Institute of Brazil.  The climate crop zoning of this package can be run for all the Brazilian territory.

Analyze data from a crossover design using generalized estimation equations (GEE), including carryover effects and various correlation structures based on the Kronecker product. It contains functions for semiparametric estimates of carry-over effects in repeated measures and allows estimation of complex carry-over effects. Related work includes: a) Cruz N.A., Melo O.O., Martinez C.A. (2023). "CrossCarry: An R package for the analysis of data from a crossover design with GEE". <arXiv:2304.02440v1>. b)  Cruz N.A., Melo O.O., Martinez C.A. (2023). "A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures". <doi:10.1007/s00362-022-01391-z> and c) Cruz N.A., Melo O.O., Martinez C.A. (2023). "Semiparametric generalized estimating equations for repeated measurements in cross-over designs". <doi:10.1177/09622802231158736>.