Agri-footprint 7.0 will soon be available in the following LCA softwares: 

• openLCA
  Agri-footprint 7.0 will be available in openLCA from June 2025
• SimaPro
  Agri-footprint 7.0 will be released in SimaPro in autumn 2025

Agri-footprint 7.0 is available in various formats and license types. You can get in touch with our sales team for further information.

Agri-footprint contains Life Cycle Inventories (LCIs) of food, feed, and beverage-related ingredients. The database contains almost 4,000 agricultural products and processes, most of which are country-specific.
Agri-footprint also includes many agricultural processing LCIs such as crushing processing, dry milling, wet milling, sugar processing and oil refining. 

Download: Overview of products in Agri-footprint

The allocation method is used in Agri-footprint in all processes where there are multiple outputs (co-products). In such cases, the overall process environmental impact is subdivided between the co-products using allocation factors (with % as unit, always summing up to 100% for one specific process). The 3 Agri-footprint libraries differ in the way the allocation factors are derived:

• Economic allocation uses the price of co-products to compute the value streams of the co-products;
• Mass allocation uses the dry matter of co-products to compute the material streams of co-products;
• Energy allocation uses the gross energy content of co-products to compute the energetic streams of com-products.

We do not recommend a default allocation approach in Agri-footprint because the choice also depends on the purpose of your LCA. In our LCAs we often include a sensitivity analysis of the used allocation.

With Agri-footprint you can perform such an analysis with 3 different libraries (Economic allocation, Mass allocation, Gross Energy allocation). The economic allocation approach is most compatible with LCI databases, such as ecoinvent 3.8 cut-off by classification. In case you carry out a Feed-related study we suggest following the Feed PEFCR, which recommends economic allocation.

Yes, since the 3 libraries contain the same products, only with different allocation rules. Therefore, users can select one of the 3 pre-defined allocation LCIs. The LCIs of these 3 pre-defined allocations are exactly the same except for the allocation percentages.

Yes, emissions of active ingredients from pesticides are integrated in each cultivation LCI of Agri-footprint. We used the Pesticide Model to develop all these crop/country specific pesticide application inventories. For more details, please see Agri-footprint methodology report.

No, this version of Agri-footprint currently contains only conventional LCIs. We did include some typical processing steps for organic products such as pressing of oil crops (instead of solvent crushing). 

Yes, direct emissions from fertilizers are included as well as indirect emissions and emissions from crop residues. The Agri-footprint methodology report (part 2) provides a detailed description of how emissions from fertilizers are modelled. It also provides information on the fate of the pesticides emissions.

This is described in the methodology reports; in essence we follow the same approach as what is described in the Product Environmental Footprint guidance. This means: 90% to soil, 1% to fresh water and 9% to air.

Agri-footprint is a background database derived from many databases where data are available on a national level per crop. This information does not allow to model crop rotation more specifically, because the sequence of crop cultivation at a plot is lacking. In Agri-footprint, manure application on agricultural land in a country is equally dispatched over crops on a hectare basis. This allocation of manure is compliant to the crop rotation allocation rules as defined in the current PEF guidelines nut is not very crop specific. We might include more specific crop rotations per country/region in the near future if PEF guidelines are updated and our data sources allow.

No, indirect land use change is not taken into account.

No, Agri-footprint does not take into account carbon storage/sequestration, but users can easily include the uptake of biogenic carbon in the LCIs.

The carbon stored in crops is in most situations short-cyclical, meaning when it is used as feed, food or fuel the carbon will again be released into the atmosphere. Therefore, it is not considered. If products are studied that are not feed, food or fuel and storage of biogenic carbon in products needs to be considered in a study the user can derive data on carbon content from the meta data. 

These emissions do not change if you adapt an input because the default Agri-footprint LCIs are not parameterized. We offer detailed and tailor-made parameterized LCIs. If you wish to have parameterized models please reach out to us. 

We tried to make the data geographically as representative as possible. For cultivation and animal farming the data are specific for the countries (collected from mostly international databases). There are cultivation and animal farming data from many countries in Europe, Asia, America, and Oceania. Processing data can be either representative for countries or continents or any other supra national category. This is explained in the meta data.

No, we started Agri-footprint with the fundaments of our food which are mostly commodities.
More information about the products in Agri-footprint

Yes, you can find the documents on the Agri-footprint page. 

The data quality procedure of Agri-footprint is described in the methodology report. 
The review letter and our response is included in appendix A and B of that same report. Also several LCA food experts performed a review of the beta-version of Agri-footprint.

Data comes from several sources such as:

• Statistical databases (e.g. FAOstat),
• Primary data from companies,
• Emission models based on IPCC calculation rules (e.g. IPCC, 2019)

See methodology report for details on the data sources.

Agri-footprint 7.0: For energy and fuels and some other background data for materials and chemicals, we use ecoinvent data. Transport datasets are all modelled by MxNS|Blonk and also some other background datasets are also modelled by MxNS|Blonk. 

Agri-footprint 6.x: For energy and fuels and some other background data for materials and chemicals we use ecoinvent data. Transport datasets are all modelled by Blonk and also some other background datasets are also modelled by Blonk. 

Agri-footprint 5.0: For energy and fuels we use ELCD because these datasets are free to use. It is not possible to use other commercial databases (like ecoinvent) in your database. Transport datasets are all modelled by ourselves. Some other background datasets are also modelled by us. We hope in the future to also model energy datasets ourselves so that we are not dependent anymore on other datasets.

For the modelling of agro-food processes ecoinvent and Agri-footprint both make use of different methodologies and use different activity data. The modelling of field emission from cultivation is mostly done using similar methodologies, but there are exceptions (e.g. nitrate emissions). In general, Agri-footprint strives to build datasets based on large datasets and statistics, while ecoinvent relies more on data from specific (case) studies and reports. However, since both databases provide background datasets there is no problem in using datasets from both databases. The main challenge of using processes from both databases is in the impact assessment methodology, where Agri-footprint is directly developed to be compatible with Recipe and ILCD (as implemented in SimaPro), ecoinvent flows/substances have been mapped by PRé to match their equivalents in SimaPro.

The data quality method is aligned over all the crop datasets. So, all processes have a data quality score given their representativeness for the given crop, country, technology etcetera. For more information on our data quality procedure, please see the Agri-footprint methodology report (part 1).

Several methods are used like methods from the IPCC background documents, scientific literature for heavy metal emissions, etcetera. Detailed information can be found in the Agri-footprint methodology report (part 2).

Uncertainty distributions are defined for specific input or output data of LCI processes that incorporate some main factors defining uncertainty and variability around the average. The focus is on key parameters related to the average efficiency of processes in the regions for which average process data are derived.

For example, a crop growing process, all uncertainty modelling is concentrated in the yield per hectare. In this way, all the relationships between input of fertilizers and its emissions due to use are kept, using the efficiency (yield, in this case) of the process as description of its uncertainty.

For more details, please see the Methodology report.

Agri-footprint 6.x: Yes, the water footprint is included. For cultivation we apply the blue and green water footprint. 

Agri-footprint 5.0: Water inventories are included to calculate, for example, the ‘Water scarcity index’ according to Pfister, Koehler, & Hellweg (2009) and other water scarcity methods at midpoint or endpoint. Water polluting emissions are included in the inventory; so, you can also do impact assessments analysis on water polluting impact categories. Agri-footprint is not equipped to calculate water footprint based on the method of Hoekstra (Hoekstra & et al., 2011), because green water sources (rainwater) is not included in the water balances.

No, although this is something we wish to do. Most questions and projects we deal with are for conventional farming. It looks like organic farming is not that interested in LCA - of course due to the limitations of food LCAs (e.g. soil quality) which do not (yet) capture well enough some positive aspects of organic farming.

We aim for atleast 2 updates a year.

Typically updates are not included in the license. However, for the planned update from Agri-footprint 7.0 to 7.1, we are going to include this update in the license agreement.

All processes in Agri-footprint are modelled as unit processes. For some background processes we use the ecoinvent database, which are mainly system processes.

Waste of processing is included and accounted for. Also emissions due to crop residues on the field are accounted for. Food waste at the consumer is not included. See the Agri-footprint documents for all the data sources.

Yes, many Product Environmental Footprint (PEF) pilots have used data from Agri-footprint. For example, the following PEF-pilots: Beer, Red Meat, Animal feed, Dairy, Pasta and Pet food.

Agri-footprint data is not 100% PEF compliant because other background data are used for energy, transport, and some chemicals/materials. The difference in results of main environmental impacts such as GHG impact, fossil energy use, acidification and eutrophication is in most cases quite limited.

There is an overview of the changes we have made to improve the modeling. That is listed in our changelog. However, a detailed analysis of the changes for each dataset has not been done. The process description is listed for each dataset in each database, so a comparison can be made. If your company requires a more in-depth comparison, we can happily refer you to our consultants for more help.

Agri-footprint FLAG updated version will be released in the autumn of 2025. Please reach out to info@blonksustainability.nl if you have more questions.