In the context of soil management we define resource use efficiency as the ratio between benefits generated by agricultural production processes and the amount of resources used. We distinguish between stressed resources for which there is competing demand and abundant resources for which there is no competition. Competition is context-specific and can be due to demand exceeding resource limitations or due to conflicts between resource use and other societal targets (e.g. pesticide application conflicting with biodiversity preservation or emissions of greenhouse gasses conflicting with climate change mitigation). Only the amount of stressed resources is considered in efficiency assessments (di Maio et al., 2017).

As benefit, any quantifiable, positive characteristic of a product can be chosen. This choice exerts a strong influence on calculated efficiencies and often determines efficiency rankings between production alternatives. For example, if weight of harvested biomass is considered, growing strawberries is less efficient than growing ryegrass whereas the situation is reversed if the evaluation is based on gross profits. 

As resource, any of the resources used in the production process can be chosen. Here, the system boundaries must be clearly defined because substantial resource consumption can occur in pre- or post-processes related to the process under investigation. For example, if energy efficiency is assessed, it is relevant whether or not energy used in the production of inputs or machinery is considered. Finally, leakage effects, indirect land use changes and especially rebound effects should be accounted for (Lambin & Meyfroidt, 2011).

The following figure illustrates how different categories (impact areas) of soil related resource use efficiency are based on soil functions.

Increasing agricultural resource use efficiency is a target at many policy levels.

• Globally, the Sustainable Development Goal (SDG) 12 “sustainable consumption and production” target 12.2 seeks to achieve sustainable management and efficient use of natural resources by 2030 (General Assembly, 2015).

• At the European level, a 20% reduction of resource inputs within the food chain has been set as a milestone for 2020 (European Commission, 2011). This is to be reached through measures targeting production, distribution and consumption. Increasing efficiency of agricultural production is also a priority within the EU Rural Development Act (European Union, 2013; Spicka, 2015) in which energy efficiency, greenhouse gas emissions per unit produced and water use efficiency are explicitly named.

• At German national level, the 2014 Policy Strategy on Bioeconomy seeks to improve efficiency of agricultural production by increasing productivity while protecting natural resources and minimising greenhouse gas emissions (BMEL 2014).

Farmers have always sought to optimize their efficiency in the use of limited resources. The most obvious example are efforts to optimize crop yields or revenues per hectare of land. The use of efficiency indicators in this regard is very common. However, increased awareness of the environmental consequences of resource use have extended the list of stressed resources. Today, there is an growing interest to achieve good yields with as little use of pesticides, fertilizer or greenhouse gas emissions as possible. Policy related assessment that do not focus on the individual farm or field but operate at higher spatial scales may also need to consider additional  benefits, such as calories produced in a region or energy content of harvest. This results in the need for a whole suit of efficiency indicators.

So far, only few assessments of agricultural resource use efficiency documented in scientific literature explicitly address the role of soils. However, due to the paramount role of soils for crop growth, assessment results often implicitly reflect changes in soil functions. In the context of research to support the transition from a fossil fuel based economy towards a sustainable bioeconomy, it is necessary to determine to what degree agricultural management can increase resource use efficiencies by targeting soil functions and to what degree efficiencies can be increased irrespective of soils.

Resource use efficiency is central to achieving a highly productive agricultural sector while minimising harmful externalities. However, increasing efficiencies may also lead to trade-offs. For example, reducing the amount of labour required to produce a fixed amount of biomass may have negative implications for job provision, nutrient use efficiencies greater than 100% are indicative of nutrient mining by harvest (Scholz & Wellmer, 2015), and maximising the share of biomass harvested relative to net primary production (HANPP) conflicts with biodiversity targets (BIO Intelligence Service, 2012). The potential for such trade-offs should be considered in assessments of resource use efficiency.

The resource use efficiency of agricultural soil management can be assessed by means of efficiency indicators, calculated as the ratio between the amount of benefit generated and the amount of resources used (see Equation 2 above). What type of efficiency indicator is assessed, i.e. the selection of which benefits and which resource use are to be compared, should be based on the intended result of the agricultural management, its main inputs, and the characteristics of management alternatives. More than one efficiency indicator may be required for a comprehensive assessment or to show trade-offs between different types of efficiency.

Temporal scale: Inter-annual yield variability is typical for agriculture. The use of multi-year averages for benefits and resources therefore results in indicators that are more representative of the management systems than single-year variants. Integrating production over several years is also necessary to account for perennial management effects, crop rotations and pre-crops effects (Preissel et al., 2015; Zhang et al., 2017). Where crop rotations of different length are to be compared, normalization can be achieved by dividing total benefits and resource use by the number of years in each rotation (Reckling et al., 2016). 

Spatial scale: The spatial scale most suited to the analysis of resource use efficiency depends on the intended users of the assessment results. Farm or field level efficiency is of particular interest to practitioners, especially where they affect economic performance. Typical efficiency indicators at this scale are productivity (Alam et al., 2017; Moreau et al., 2012; Zhang et al., 2016), water use efficiency (WUE) (Pascual et al., 2016; Wei et al., 2016; Zhao et al., 2010), benefit cost ratio (BCR) (Alam et al., 2017; Rehman et al., 2011), nutrient use efficiency (NUE) (nitrogen: Buckley et al., 2016; Gu et al., 2017; phosphorous: Gerber et al., 2014; Zhang et al., 2016) and energy use efficiency (Hill et al., 2006; Arodudu et al., 2017). 

Assessments with landscape or global implications are particularly relevant for policy makers. Indicators include greenhouse gas emissions per yield (Khakbazan et al., 2017; Steyn et al., 2016) or GDP contribution per domestic material consumption (European Commission, 2011; European Environment Agency, 2016). Efficiency indicators can also be tailored to assist the assessment of specific research or policy questions. Examples are efficiencies for job provision (jobs generated per hectare of farmland by different biomass usages) (BMEL, 2014) or economic risk efficiency (how does irrigation affect the amount of revenue that can be expected under a defined probability level) (Meyer-Aurich et al., 2016).  

Tables 4 and 5 gives an overview about recent studies on resource use efficiency in agricultural and on the efficiency indicators used.

Combining multiple benefits or resources
Agriculture is characterised by the production of multiple benefits such as food, feed, fibre or fuel while using multiple resources like land, water, energy and nutrients. It also generates profits, provides employment and creates habitats for plant and animal species while requiring capital and labour. For a comprehensive efficiency assessment, the appraisal of several benefits and resource uses is therefore essential. For this, assessments can either use multiple efficiency indicators, or apply a single indicator in which multiple benefits or resources are combined. 

The most common method to create combined indicators is to express all benefits or resources in monetary terms, based on their explicit or implicit market value. While practical, this approach is often criticised due to the difficulties of reflecting environmental and social consequences in monetary terms, and because values attributed to non-marketed goods vary strongly between assessments (Baveye, 2016). 

Alternative methods are often based on benchmarking. For example, Lin & Hülsbergen (2017) determine land use efficiency for a crop rotation by first calculating multiple efficiency indicators for the rotation (such as dry matter per hectare, lipid production per hectare). In a second step, each of these indicators is divided by the respective efficiency of average production in the region. This creates a set of dimensionless values. Finally, the average of these values is calculated and used as the combined indicator. Another benchmarking approach derived from economics is data envelopment analysis (DEA). Linear combinations of all enterprises or processes within in an assessment are used to calculate combinations with the highest (positive) output and smallest use of resources. These combinations constitute the so called efficiency frontier, for which an efficiency of 100% is assumed. Efficiency values of individual enterprises or processes are calculated relative to this frontier. All types of efficiencies can be combined in DEA. For example, Hoang & Alauddin (2010) used data envelopment analysis to create efficiency scores for 30 OECD countries based on agricultural production, costs, use of fertiliser and use of energy. Masuda (2016) calculated eco-efficiency of Japanese wheat production based on global warming potential, aquatic eutrophication potential and yield. 

While combined efficiency indicators allow for a quick overview and may facilitate monitoring and communication with stakeholders and policy makers, the selection and weighing of the included efficiency categories and the interpretation of the resulting indicators is challenging. In detailed impact assessment, the use of multiple efficiency indicators may be preferable because they make trade-offs between different efficiency categories directly visible whereas such relationshsips may be obscured in the values of combined indicators.  

Please note: Efficiency assessments are well suited to assess performance of agricultural production within a limited number of categories. However, they are unable to provide a holistic view of ecosystem interactions. In this regard, assessment of ecosystem services provides a well suited complementary perspective.

Table 4: Non-integrated  indicators for measuring efficiency in agriculture. Overview of studies published between 2008 and 2017 based on Web of Science Core Collection, applying search terms: “efficiency” (title) and “agriculture”, “indicator” (topic). Indicators used in three or more studies are highlighted in red. 

Table 4: Non-integrated  indicators for measuring efficiency in agriculture. Overview of studies published between 2008 and 2017 based on Web of Science Core Collection, applying search terms: “efficiency” (title) and “agriculture”, “indicator” (topic). Indicators used in three or more studies are highlighted in red. 

Table 5: Integrated indicators for measuring efficiency in agriculture. Overview of studies published between 2008 and 2017 based on Web of Science Core Collection, applying search terms: “efficiency” (title) and “agriculture”, “indicator” (topic).

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Aldanondo-Ochoaa A M, Casasnovas-Olivaa V L, Arandia-Miurab A (2014) Environmental efficiency and the impact of regulation in dryland organic vine production. Land Use Policy 36, 275– 284. doi:10.1016/j.landusepol.2013.08.010

Alluvione F, Moretti B, Sacco D, Grignani C (2011) EUE (energy use efficiency) of cropping systems for a sustainable agriculture. Energy, 36, 4468-4481. doi:10.1016/j.energy.2011.03.075

Arodudu O, Helming K, Wiggering H, Voinov A (2017) Integrating agronomic factors into energy efficiency assessment of agro-bioenergy production – A case study of ethanol and biogas production from maize feedstock. Applied Energy, 198,426-439. doi:10.1016/j.apenergy.2017.02.017

Azad A S, Ancev T (2014) Measuring environmental efficiency of agricultural water use: A Luenberger environmental indicator. Journal of Environmental Management, 145, 314-320. doi:10.1016/j.jenvman.2014.05.037

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Deike S, Pallutt B, Kustermann B, Christen O (2008b) Effects of herbicide application on energy use efficiency and carbon dioxide emissions of cereal cropping systems. Journal of Plant Diseases and Protection, Special Issue 21, 113-119

Di Maio F, Rema PC, Baldé K, Polder M (2017) Measuring resource efficiency and circular economy: A market value approach. Resources, Conservation and Recycling, 122. 163–171. doi:10.1016/j.resconrec.2017.02.009

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Gerber PJ, Uwizeye A, Schulte RPO, de Boer IJM (2014) Nutrient use efficiency: a valuable approach to benchmark the sustainability of nutrient use in global livestock production? Current Opinion in Environmental Sustainability, 9–10, 122–130. doi:10.1016/j.cosust.2014.09.007

Giambalvo D, Alfieri G, Amato G, Frenda A S, Iudicello P, Stringi L (2009) Energy use efficiency of livestock farms in a mountain area of Sicily. Italian Journal of Animal Science, 8 (2), 307-309

Godinot O, Carof M, Vertès F, Leterme P (2014) SyNE: An improved indicator to assess nitrogen efficiency of farming systems. Agricultural Systems, 127, 41–52. doi:10.1016/j.agsy.2014.01.003

Godinot O, Leterme P, Vertès F, Carof M (2016) Indicators to evaluate agricultural nitrogen efficiency of the27 member states of the European Union. Ecological Indicators, 66, 612–622. doi:10.1016/j.ecolind.2016.02.007

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Hoang VN, Alauddin M (2012) Input-Orientated Data Envelopment Analysis Framework for Measuring and Decomposing Economic, Environmental and Ecological Efficiency: An Application to OECD Agriculture. Environmental and Resource Economics, 51, 431–452. doi:10.1007/s10640-011-9506-6

Khakbazan M, Larney F J, Huang J, Mohr R, Pearson D C, Blackshaw R E (2017) Energy Use Efficiency of Conventional versus Conservation Management Practices for Irrigated Potato Production in Southern Alberta. American Journal of Potato Research, 94:105–119. doi:10.1007/s12230-016-9551-3

Korkmaz K, Ibrikci H, Karnez E, Buyuk G, Ryan J, Ulger A C, Oguz H (2009) Phosphorus use efficiency of wheat genotypes grown in calcareous soils. Journal of Plant Nutrition, 32, 2094–2106. doi:10.1080/01904160903308176

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