South America vs Saint Lucia: Watermelons — Gross per capita Production Index Number
South America
91.59
in 2024
Saint Lucia
130.53
in 2024
South America rank
22nd
Saint Lucia rank
25th
Watermelons — Gross per capita Production Index Number over time
- South America
- Saint Lucia
How they compare
Saint Lucia currently reports 130.53 against 91.59 in South America, a difference of 38.94.
That makes Saint Lucia's figure about 1.4 times South America's.
The two have swapped places 1 time across 21 shared years of data; in 2004 it was South America ahead.
South America ranks 22nd and Saint Lucia ranks 25th of 27 groups.
Across the 3 decades both report, South America averaged higher in 2 and Saint Lucia in 1.
Head to head by decade
| Decade | South America | Saint Lucia | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 99.63 | 44.89 | 54.73 | South America |
| 2010s | 102.25 | 93.73 | 8.52 | South America |
| 2020s | 92.75 | 116.43 | 23.69 | Saint Lucia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher watermelons — gross per capita production index number, South America or Saint Lucia?
- Saint Lucia, at 130.53 against 91.59 in South America as of 2024.
- What is the difference in watermelons — gross per capita production index number between South America and Saint Lucia?
- 38.94, with Saint Lucia ahead.
- How many years of comparable data are there for South America and Saint Lucia?
- 21 years are reported by both, from 2004 to 2024.
- How do South America and Saint Lucia rank globally for watermelons — gross per capita production index number?
- South America ranks 22nd and Saint Lucia ranks 25th of 27 groups.
- Where does this data come from?
- Food and Agriculture Organization of the United Nations, published as Watermelons — Gross per capita Production Index Number (2014-2016 = 100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. Indices for meat production are computed based on data on production from indigenous animals.