09. Module VII (Yield and production gaps) - un-fao/gaezv5 GitHub Wiki
Introduction
The Module VII (Yield and Production Gaps) carries out the final modelling step in GAEZ v5 processing. The quantitative yield gap analysis relies on both the results of crop suitability and potential yield analysis produced in Module V and the downscaling of base year agricultural area and production statistics undertaken in Module VI.
Apparent yield and production gaps have been estimated by comparing at a spatially detailed level of 5 arc-minutes the potential attainable yields and production (as estimated in GAEZ v5) and the harvested areas, actual yields and production obtained by downscaling statistical data for the year 2020.
A schematic representation of the information flow in Module VII is presented in the figure below.
Figure: Information flow in Module VII
Yield and production gaps are estimated by comparing simulated potential and downscaled statistical yield and production of main food, feed and fiber crops.
Yield and production gaps assessment procedures
As indicated in the schema above, there are two main steps involved in Module VII. First, the harvested area allocations produced when downscaling target year statistical production data, in GAEZ v5 respectively for year 2020, are combined with estimated potential attainable yields (from Module V) to generate maps of production potential consistent with historical downscaled cropping patterns. In a second step, these maps of production potential are compared with the maps of downscaled actual yield and production to quantify their discrepancies as a measure of apparent yield gaps.
For main commodities, comprising a country’s total crop production, downscaled crop area, yield and production statistics can be compared with potential crop yield and production results, for both rain-fed and irrigated cultivated land. All 26 commodities are presented in Table 9-1 below.
Table below shows the 33 crops/crop groups obtained by downscaling of statistical data into spatial rasters at 5 arc-minute resolution in GAEZ v5. It is important to note that together these 33 crop commodities represent all recorded crop production of each delineated spatial allocation unit (i.e., a country) for which crop statistics were collected. Note that for comparison of FAOSTAT statistical production (usually in harvested/fresh weight) with GAEZ simulated potential production (yield calculated mostly as dry weight of main produce) an appropriate conversion factor must be applied.
The technical conversion coefficients mainly depend on estimated moisture content (see table below) of harvested products and in a few cases are derived from technical extraction rates, such as for sugar crops, oil palm and olive. For some aggregate commodity groups (pulses, vegetables, stimulants, crops NES) a comparison with GAEZ results was not undertaken because of substantial commodity differences within the crop group (e.g. pulses, stimulants) and/or insufficient LUTs available to represent a crop group (e.g. vegetables, crops NES).
Table: Crop Names, descriptions, and moisture content.
| Name | Description | Moisture Content |
|---|---|---|
| WHE | Wheat | 13% |
| RCW | Rice | 13% |
| MZE | Maize | 14% |
| SRG | Sorghum | 13% |
| MLT | Millet | 13% |
| BRL | Barley | 13% |
| OCE | Other cereals (oats, rye, buckwheat and other minor grains) | 13% |
| POT | White potato, Sweet potato | 77% |
| CSV | Cassava | 69% |
| ORT | Yams (and other minor root crops) | 69% |
| SUB | Sugar beet | 14% sugar |
| SUC | Sugarcane | 10% sugar |
| PLS | Pulses | 10% |
| SOY | Soybean | 9% |
| RSD | Rapeseed | 8% |
| SFL | Sunflower seed | 13% |
| GRD | Groundnuts (with shell) | 67% shelled, 5% |
| SES | Sesame seed | 5% |
| OLP | Oil palm fruit | 24% oil |
| CON | Coconut | 24% copra |
| OOC | Olives and other minor oil crops | oil equivalent |
| COT | Seed cotton | 33% lint, 8% |
| TOB | Tobacco | 50% |
| BAN | Banana and Plantain | 75% |
| COF | Coffee | 10% |
| COC | Cocoa | 6.5% |
| TEA | Tea & Mate leaves | 75% |
| TOM | Tomato | 92.5% |
| OVG | Other vegetables (i.e. all except tomato) | 90% |
| FDD | Fodder crops | 70% |
| FRT | Fruits and Nuts | 85% |
| RUB | Para rubber | 70% |
| NES | All other crops not elsewhere included (mainly spices, fibre crops) | 8% |
The comparison of downscaled actual and simulated potential yields and production involves the cultivated land occurring by 5 arc-minute grid cells, separately for rain-fed and irrigated cropland. Comparisons are presented as achievement ratios (actual/potential) for yields and as absolute differences of potential and actual production. The results of yield gap analysis are stored as GIS rasters at 5 arc-minutes resolution, separately for total cropland, irrigated and rain-fed cropland.
An estimate of apparent yield gaps is then derived by comparing actual to potential yields and production. Apparent yield gaps are closely related to the calculated yield achievement factors, both summing up to 100 percent. For instance, a yield achievement factor of 75% would imply an apparent yield gap of 25%.