Data acquisition

Data were primarily collated from meta-analyses found in scientific literature. Terms used in Ovid (https://ovidsp.ovid.com/), CAB Abstracts (https://www.cabdirect.org/) and Google Scholar (https://scholar.google.com/) were: (crop) AND (“nutrient concentration” OR “nutrient content” OR “harvest index”) across any time. This search resulted in over 245,000 results. These results were refined to include studies that purported to represent crop nutrient concentration and/or harvest index of crops for geographic regions of the world, as opposed to site-specific field experiments. Given the range in different crops grown globally, preference was given to acquiring datasets that included multiple crops. In some cases, authors of meta-analyses were asked for raw data to aid the standardisation process. In addition, the International Fertilizer Association (IFA), and the Food and Agriculture Organization of the United Nations (UN FAO) provided data used for crop nutrient balances (FAOSTAT 2020). The request to UN FAO yielded phosphorus and potassium crop nutrient concentrations in addition to their publicly available nitrogen concentration values (FAOSTAT 2020). In total the refined search resulted in 26 different sources of data.

Data files were converted to separate comma-delimited CSV files for each source of data, whereby a unique ‘source’ was a dataset from an article from the scientific literature or a dataset sent by the UN FAO or IFA. Crop nutrient concentrations were expressed as a percentage of dry matter and/or the percentage of fresh weight depending on which units were reported and whether dry matter percentages of crop fresh weight were reported. Meta-data text files were written to accompany each standardized CSV file. The standardized CSV files for each source of data included information on the name of the original region, the crop coefficients it purported to represent, as well as the original names of the crops as categorised by the authors of the data. If the data related to a meta-analysis of multiple sources, information was included for the primary source of data when available. Data from the separate source files were collated into one file named ‘Combined_crop_data.csv’ using R Studio (version 4.1.0) (hereafter referred to as R) with the scripts available at https://github.com/ludemannc/Tier_1_2_crop_coefficients.git.

Processing of data

When transforming the combined data file (‘Combined_crop_data.csv’) into representative crop coefficients for different regions (available in ‘Tier_1_and_2_crop_coefficients.csv’), crop coefficients that were duplicates from the same primary source of data were excluded from processing. For instance, Zhang et al. (2021) referred to multiple primary sources of data, and the data requested from the UN FAO and the IFA referred (in many cases) to crop coefficients from IPNI (2014). Duplicate crop coefficient data that came from the same primary source were therefore excluded from the summarised dataset of crop coefficients.

Two tiers of data

The data were sub-divided into two Tiers to help overcome the challenge of using these data in a global nutrient balance when data are not available for every country. This follows the approach taken by the Intergovernmental Panel for Climate Change-IPCC (IPCC 2019). Data were assigned different ‘Tiers’ based on complexity and data requirements.

·         Tier 1: crop coefficients at the world level.

·         Tier 2: crop coefficients at more granular geographic regions of the world (e.g. at regional, country or sub-country levels).  

Crop coefficients were summarised as means for each crop item and crop component based on either ‘Tier 1’ or ‘Tier 2’.

One could also envision a more detailed site-specific level (Tier 3). The data in this dataset did not meet the required level of complexity or data requirements for Tier 3, unlike, say, the site-specific data being collected as part of the Consortium for Precision Crop Nutrition (CPCN) (www.cropnutrientdata.net)-which could be described as being Tier 3. No data from the current dataset were therefore assigned to Tier 3. It is expected that in the future, site-specific data will be used to improve the crop coefficients further with a Tier 3 approach.

The ‘Tier_1_and_2_crop_coefficients.csv’ file includes mean crop coefficients for the Tier 1 data, and mean crop coefficients for the Tier 2 data. The Tier 1 estimates of crop coefficients were mean values across Tier 1 data that purported to represent the World.

Crop coefficients found in the data sources represent quite different geographic areas or regions. To enable combining data with different spatial overlaps for Tier 2, data were disaggregated to the country level. First, each region was assigned a list of countries (which the regional averages were assumed to represent, as listed in the ‘Original_region_names_and_assigned_countries.csv’ file). Countries were assigned alpha-3 country codes following the ISO 3166 international standards (https://www.iso.org/publication/PUB500001.html). Second, for each country mean, crop coefficients were calculated based on coefficients from regions listed for each country. For Australia for example, the mean values for each crop coefficient were calculated from values that represented sub-country (e.g. Australia New South Wales South East), country (Australia), and multi-country (e.g. Oceania) regions.  For instance, if there was a harvest index value of 0.5 for wheat for the original region ‘Australia New South Wales South East’, a value of 0.51 for the original region named ‘Australia’ and a value of 0.47 for the original region named ‘Oceania’, then the mean Tier 2 harvest index for wheat for the country Australia would be 0.493, the unweighted mean. Using our dataset, a user can assign different weights to each entry.

To aid analysis, the names of the original categories of crop were converted into UN FAO crop ‘item’ categories, following UN FAO standards (FAOSTAT 2022) (available in the ‘Original_crop_names_in_each_item_category.csv’ file). These item categories were also assigned categorical numeric codes following UN FAO standards (FAOSTAT 2022). Data related to crop products (e.g. grain, beans, saleable tubers or fibre) were assigned the category “Crop_products” and crop residues (eg straw, stover) were assigned the category “Crop_residues”.

Dry and fresh matter weights

In some cases nutrient concentration values from the original sources were available on a dry matter or a fresh weight basis, but not both. Gaps in either the nutrient concentration on a dry matter or fresh weight basis were given imputed values. If the data source mentioned the dry matter percentage of the crop component then this was preferentially used to impute the other missing nutrient concentration data. If dry matter percentage information was not available for a particular crop item or crop component, missing data were imputed using the mean dry matter percentage values across all Tier 1 and Tier 2 data.

Global means for the UN FAO Cropland Nutrient Budget.

Data were also summarised as means for nitrogen (N), elemental phosphorus (P) and elemental potassium (K) nutrient concentrations of crop products using data that represented the world (Tier 1) for the 2023 UN FAO Cropland Nutrient Budget. These data are available in the file named World_crop_coefficients_for_UN_FAO.csv.

R scripts to produce these data  are available at: https://github.com/ludemannc/Tier_1_2_crop_coefficients.git.

README_LUDEMANN_CROP_DATA_2024.txt

Provides details of all the data files in this DRYAD submission.

Data_diagram_25102022.csv

Illustrates the general process for standardisation of data into the final formats.

Combined dataset (Combined_crop_data.csv)

This dataset includes the combined crop coefficient data from all sources before it was summarised by Tier category. Two metadata files accompany the Combined_crop_data.csv file. The Meta_data_Combined_crop_data_1.csv file describes the header parameters, while the Meta_data_Combined_crop_data_2.csv file describes units for each variable used in the file.

Data summarised at Tier 1 and 2 level (Tier_1_and_2_crop_coefficients.csv)

This dataset includes a summary of the data from the Combined_crop_data.csv file. Data were summarised into mean values across sources that purported to represent the World (indicated as being Tier 1) and across sources that purported to represent different regions of the world (Tier 2). The Tier 2 crop coefficients excluded duplicated data from the same primary source (e.g. secondary sources that used data from IPNI (2004)). Tier 2 data were summarised for each UN-recognised country based on mean values from regions that were applicable for each country where data were available. In the absence of any better country or sub-country-specific survey data, it is envisioned that preference be given to using the Tier 2 country estimates of crop coefficients in any global analyses. If any countries do not have Tier 2 crop coefficients then Tier 1 values can be used.

A metadata file accompanies this file and is named Meta_data_Tier_1_and_2_crop_coefficients.csv. This describes the header parameters.

Data summarised for UN FAO Cropland Nutrient Budget (World_crop_coefficients_for_UN_FAO.csv)

This file contains a summary of Tier 1 data from the Tier_1_and_2_crop_coefficients.csv file, and it was used in the 2023 update of the UN FAO Cropland Nutrient Budget.  A metadata file accompanies this file and is named Meta_data_World_crop_coefficients_for_UN_FAO.csv. This describes the header parameters.

Crop category data file (Original_crop_names_in_each_item_category.csv)

This file includes information on the UN FAO crop item categories, crop item codes and original crop names assigned to each item in this dataset. The parameter named item indicates the United Nations crop type ‘item’ name, item_code indicates the United Nations item code number, and original_crop  indicates the name of the crop category originally used in the source of data.

Region data file (Original_region_names_and_assigned_countries.csv)

This file includes information on countries and alpha-3 country codes assigned to each original region category (used in the sources of data). The parameter named country indicates the official United Nations English name of the country, iso3_code indicates the 3-letter ISO 3166 United Nations code (https://www.iso.org/publication/PUB500001.html) to signify country or region.

Related works

These data are used as part of the United Nations Food and Agriculture Organization Cropland Nutrient Budget https://www.fao.org/faostat/en/#home 

Versions

In March 2023.

-Data were updated by excluding outliers from India. Data from Roy et al (2004) (Table 29) for India were actually total uptake of nutrient per unit of crop product, rather than nutrient concentration. These (high) values were therefore excluded from the dataset and the github repository was updated accordingly. 

In November 2023 data were updated for the 2023 version of the FAO Cropland Nutrient Budget. Key changes included: 

-There was a change in the assumption used for converting nitrogen to protein concentrations for the Unkovich raw data. The original source  (Sinclair and De Wit 1975) mentioned they used a N:protein ratio of 6.67 instead of the 6.25 ratio originally assumed in the previous version of this dataset.

-Code was updated to better utilize nutrient concentration data on a dry matter basis for filling in gaps in nutrient concentration on a fresh weight basis. 

-Overcome double up in Carrots data from the FAO (2020) raw data file. 

-Updated Cassava values in Fao (2020) raw data file as there was an error. Values for N,P and K removal for 20t of fresh weight cassava yield were used from http://nutrien-ekonomics.com/tools-to-calculate-fertilizer-needs/calculators/nutrient-removal/

-In regular expression function to convert original crop names to item_code, "Grain, mixed" was given code 103 "Mixed grain" rather than 108 "Cereals, nes". 

-An error in the filter code (used to avoid double ups on data from the same primary source) was fixed. This resulted in more species being available while still avoiding duplicates of values from the same original source of data. 

In September 2024 this repository had an article DOI linked to it from Nutrient Cycling in Agroecosystems (https://doi.org/10.1007/s10705-024-10381-6). No changes were made to the data. 

References

FAOSTAT. 2020. FAOSTAT Domain Cropland Nutrient Budget Metadata, release December 2020. Rome, Italy.  https://fenixservices.fao.org/faostat/static/documents/ESB/ESB_e.pdf 

FAOSTAT. 2022. FAOSTAT. Retrieved 18 May 2020 from: http://www.fao.org/faostat/en/#country.

IPCC. 2019. Overview: 2019 refinements to the 2006 IPCC guidelines for national greenhouse gas inventories. https://www.ipcc.ch/site/assets/uploads/2019/12/19R_V0_01_Overview.pdf.

IPNI. 2014. IPNI Estimates of Nutrient Uptake and Removal. Retrieved 11 July 2022  http://www.ipni.net/ipniweb/portal.nsf/0/CBDC9962624CDFCD85257AC60050BBD2/$FILE/Metric%204_1%20&%204_5%200115.pdf.

Sinclair, T., and De Wit, C. T. (1975). Photosynthate and nitrogen requirements for seed production by various crops. Science 189, 565–567.

Zhang X, Zou T, Lassaletta L, Mueller ND, Tubiello F, Lisk MD, Lu C, Conant RT, Dorich CD, Gerber J, Tian H, Bruulsema T, McClellan-Maaz T, Nishina K, Leon B, Bodirsky LB, Popp A, Bouwman L, Beusen A, Chang J, Havlík P, Leclère D, Canadell JG, Jackson RB, Billen G, Heffer P, Wanner N, Zhang W, Davidson EA. 2021. Quantification of global and national nitrogen budgets for crop production. Nature Food: 1-14.