grd = spsample(data_n, type = "regular",n=10000)

n_yield = sapply(1:length(grd), function(pt) {
  d = spDistsN1(data_n, grd[pt,])
  return(mean(data_n[d < 5,]$yield_n))
  })
n_dat = data.frame(coordinates(grd), n_yield)
datNoNas <- na.omit(object = n_dat)

# mapping in ggplot
ggplot(aes(x = x1, y = x2,fill = n_yield), data = datNoNas) +
geom_tile() +
scale_fill_gradientn(colours = rainbow(4)) +
coord_equal()