Nitrogen fertiliser use efficiency ‘rules of thumb’ - how reliable are they?
Take home messages
- An assessment of current ‘rules of thumb’ (RoT) for predicting nitrogen (N) fertiliser requirements in the southern region cropping systems has identified the need to update current assumptions.
- Deep soil N testing prior to (or just after) sowing is critical for good fertiliser N management.
- Current RoTs and other decision support systems for in-crop N mineralisation do not provide predictions at an adequate time step or scale.
- Crop utilisation of fertiliser and soil N varied markedly in response to seasonal rainfall distribution. Across all major cropping zones in Victoria, the average crop recovery of fertiliser N in the year of application is about 35% and this is recommended to replace the RoT of 50%.
- 15N fertiliser mass balance studies revealed significant losses of fertiliser N, with an average of 25%, 32% and 41% of applied N in the low-medium rainfall, high rainfall and irrigated cropping systems, respectively.
- The important N loss pathways remain unknown, but identification is critical if appropriate N management strategies to minimise losses and maximise crop uptake are to be developed.
Nitrogen (N) fertiliser is a key determinant of grain yield and the ability of cereal crops to achieve water limited yield potential in western Victoria (Armstrong et al. 2018). Because N fertilisers are one of the largest variable cost inputs (in both the southern region and nationally), accurate predictions of N fertiliser requirements are critical for grower profitability.
A national survey of more than 300 growers and advisers conducted in 2015 across a broad range of rainfall/productivity zones, including South Australia (SA) and Victoria (Vic) assessed how they made decisions and the underlying assumptions used to arrive at N management recommendations (UQ00179). The survey found that most of these busy advisers and growers utilised nutrient budgeting and general ‘rules of thumb’ (RoT) adjusted with localised information (experience) and specific data such as results from pre-sowing soil N testing. Many did not use elaborate decision support systems (DSS) or tools including simulation models such as Yield Prophet®, and where they did, it tended to act as a backup (validation) of the RoT. Another report (Unkovich et al. 2016) of adviser and grower practices in the southern region suggest a greater use of more elaborate DSS. However, these growers and advisers indicated concern about the accuracy of both simple N decision methods and the more elaborate DSS given the major changes in soil fertility and cropping systems since these tools were developed. Some expressed concern about using a DSS ‘black box’ especially without evidence of the embedded assumptions and caveats underpinning these procedures.
The basic components (assumptions) of most of the RoT approaches are from several assessments made each season of the estimated yield (demand) and the efficiency of N uptake by the crop from the soil and fertiliser inputs. Soil N supply depends on (i) available mineral N at sowing, (ii) within season N mineralisation from organic matter (iii) the efficiency of recovery of soil and applied N by the crop and (iv) net off-site losses of N or immobilisation by microbes. Differences between soil N supply and anticipated crop demand are then met by fertiliser application. In general, there is a supply shortfall to account for seasonal risk e.g. growers rarely fertilise to achieve yield potential because of the uncertainty of spring conditions and the risks of frost, drought or heat shock. Variability in any of these N supply and demand components can significantly influence fertiliser decision-making, and therefore alter the return on investment.
Nitrogen management is influenced by a range of factors, many which are logistical in nature. It is argued, however, that the current lack of confidence by many growers and advisers in existing N management approaches at a biophysical level stems from uncertainty surrounding the magnitude and seasonal variability of these key processes at a local scale and across soil types, and the inability to readily access relevant data used in these determinations. This paper reviews the assumptions underpinning the key components used to predict soil and fertiliser N supply in current RoTs used to guide fertiliser N management decisions for the current season. Biophysical data from recent studies focused on western Victoria is used, but this data is likely to be applicable to the whole southern region. Recent publications are referenced such as Unkovich et al. (2020) that have reviewed both published and grey literature relating to previous research into the processes underlying these assumptions.
Data used for assessments of assumptions (available N at sowing, within season net N mineralisation, the efficiency of recovery of soil and applied N by the crop and net off-site losses of N or immobilisation) were obtained primarily from two PhD studies (A. Wallace and K. Dunsford). The first study was based on data collected in two Australian Government funded Projects (Action on Ground (AonG), ‘Reducing on-farm nitrous oxide (N2O) emissions through improved nitrogen use efficiency in grains’) and the ‘Filling the Research Gap’ NANORP program. Both assessed crop response to and utilisation of N fertiliser applied to cereal crops (mainly wheat) in growers’ paddocks across a broad range of environments and soil types encompassing the key grain production areas of western Victoria: high rainfall > 550mm annual (HRZ), medium rainfall 400-550mm (MRZ), low rainfall < 400mm (LRZ) and irrigated cropping systems of northern Victoria. The AonG data comprised nine sites undertaken between 2014 and 2016 equating to a total of 29 site by year comparisons (Figure 1). The trials were located in grower paddocks (i.e., using grower management of the crop). At each site, a simple N rate response trial was established using a randomised complete block design with plot sizes of approximately 18m2. Three N treatments were applied at each of the nine sites based on industry standard practice relevant to each region and the seasonal conditions. Sites received a small rate of N in the starter fertiliser across all plots at sowing (0-20kg N/ha), typically in the form of Mono-Ammonium Phosphate (MAP) or Di-Ammonium Phosphate (DAP) depending on grower management. Treatments included two rates of N fertiliser applied during the growing season plus a control which received no additional N during the season. The NANORP data comprised a total of six site by years experiments conducted between 2012 to 2014 in the Wimmera (Wallace et al. 2020). These experiments tested a range of different N management strategies. The utilisation and recovery in the soil: plant system of N fertiliser applied to wheat crops in both data sets was assessed using a 15N mass balance approach to develop crop utilisation coefficients. Differences in the amount of labelled N applied and that recovered in the soil were assumed to represent losses. In the AonG trials, 15N labelled urea was top-dressed during the vegetative or stem elongation growth stages when a rainfall event was anticipated in the following two to three days, although in higher yielding situations (especially the HRZ and irrigated sites) a second application later in the year was made in favourable seasons.
Nitrogen mineralisation data was collected from 73 grower paddocks (including those used in the AonG project) in the LRZ, MRZ and HRZ, between 2013 and 2016. Data was also collected from the SCRIME long-term rotation/tillage experiment at Longerenong (Armstrong et al. 2019). The contribution of net in-crop N mineralisation (net ICM – the balance of N mineralised from soil organic matter and crop residues minus N immobilised by soil microbes) to crop N supply was assessed in all studies. Net ICM of N was estimated as the difference between measurable N supply (mineral N measured at sowing plus fertiliser inputs minus the sum of mineral N measured and crop N uptake at maturity) based on the procedure used by Armstrong et al. (1997):
Net ICM (kg N/ha) = Crop N x 1.1 + SNM – (SNS + Nfert)………….Equation 1
Where Crop N is the total amount of N contained in the shoots of the crop at maturity multiplied by 1.1 to estimate the fraction of N allocated to roots (Angus 2001; Gan et al. 2011). SNM and SNS are soil nitrate (0 – 1.2m) at maturity and at sowing, respectively, and Nfert is applied fertiliser N. Only nitrate data was used for this calculation and not ammonium, since most mineral N in dryland cropping soils is rapidly converted to nitrate.
Results and discussion
Available N at sowing
The amount of mineral N in the profile prior to or just after sowing is a crucial indicator of soil N supply for the coming season. In some circumstances, sufficient N can mineralise over the preceding summer/autumn fallow, to meet crop requirements, without the need to add additional N (Dunsford 2019; Harris et al. 2016). At present, only a minority of paddocks are tested for mineral N in deeper profile layers (‘deep N’), due principally to logistical challenges (Sean Mason 2020 pers. comm; project 9176604) such as access to a suitable soil sampler. As an alternative to direct measurement, estimates of likely mineral N can potentially be made by considering the previous rotation and rainfall. As data from SCRIME shows (Table 1), pre-sowing mineral N can be influenced equally by fallow summer/autumn rainfall (Figure 1) as by previous rotation (Armstrong et al. 2019). As such, delaying direct assessment of mineral soil N supply until after sowing may provide growers with increased confidence in both the starting point of N supply to a crop and potential grain yields.
Table 1. Profile (0-120cm) soil nitrate-N (kg/ha) prior to sowing of the wheat phase in response to different rotation/tillage treatments in SCRIME (2001 to 2017). n.d. = not determined. n.s. = not significant (P < 0.05).
1 W=wheat; P=pulse; =barley; Gm=vetch green manure; ZT=zero tillage; RT=reduced tillage; CT=conventional tillage; C=canola; F=fallow; L=lucerne (Source: Armstrong et al. (2019)).
Figure 1. Relationship between rainfall (December of preceding year to March, inclusive in mm) and the amount of nitrate-N (kg/ha) in the profile (0-120cm) prior to sowing at SCRIME for 2001 to 2017. Analysis omits the value for 2011 when 375mm was received during this period.
Within season net N mineralisation
Studies of in-crop N mineralisation in southern region cropping systems indicate that this source of N potentially represents a significant proportion of a crop’s requirement (Dunsford 2019). A comprehensive review of DSS tools including simple RoTs for estimating in-crop N mineralisation has recently been published (Unkovich et al. 2020). Many of these tools were developed in an era when pasture legume-leys dominated cropping systems or on acid soils in southern NSW rather than current continuous cropping, reduced tillage/stubble retention practices and alkaline soils that dominate cropping in the southern region (Dunsford 2019). Dunsford (2019) found that the ‘Ridge Approach’, provided a fair estimate (R = 0.46) of net in-crop N mineralisation across a large section of cropping systems in western Victoria, based on soil organic carbon (SOC) of the topsoil and actual growing season rainfall (GSR, Table 2). The Ridge method is calculated as:
N mineralisation (k/ha) = 0.15 × SOC (%) × GSR (mm)………….Equation 2
If long-term average rainfall is used in the calculation, however, the reliability of the prediction is reduced considerably (data not presented). The recent extensive review of soil mineralisation by Unkovich et al. (2020) concluded that ‘none of the currently available tools appear to provide field and season-specific information (prediction) of N mineralisation on a useful time step’, or where more complex models existed (e.g., Yield Prophet), ‘they required detailed parameterisation unlikely to be conducted at an appropriate spatial scale‘.
Table 2. Correlation coefficients (r) of the relationships between net in-crop nitrogen mineralisation (net ICM) against growing season rainfall (GSR: April to October) and methods of predicting ICM, including soil tests and a simple calculator. Values are presented as r with significance indicated by *** P<0.001, ** P<0.01, and * P<0.05.
Net positive ICM data
Soil organic carbon (SOC) (%)
Total N (mg/g)
Pre-sowing profile nitrate (kg N/ha)
Ridge Method (kg N/ha)
Anaerobic NH4+ (kg/ha)
Hot KCl Gross NH4+ (kg/ha)
The efficiency of recovery of soil and applied N by the crop
A range of methods have been used to estimate fertiliser efficiency, and in particular, the quantity of fertiliser recovered by the crop. Traditionally, especially in the southern region, this was determined by measuring the difference between the quantity of N in the fertilised crop and a paired unfertilised treatment, expressed as a percentage, and referred to as the ‘difference measure’ (Strong 1995). Fertilised crops, however, frequently take up more soil N than unfertilised crops in a phenomenon referred to as the ‘added N interaction’ or a ‘priming effect’. As a result, difference measure generally overestimates the efficiency of use of fertiliser N. In contrast to difference methods, the efficiency of recovery of soil and fertiliser N can be assessed using 15N tracers. 15N is a stable (i.e., non-ionising) form of N that occurs ‘naturally’ at low levels in the environment (0.00367% of all N) and effectively behaves similarly at a chemical and physiological level to 14N. Although the applied 15N is subject to isotopic discrimination during mineralisation-immobilisation (MIT) (Strong 1995), it is considered a better method to assess fertiliser N utilisation (and losses), especially when measurements are made of residual 15N remaining in the soil after harvest. This is due to its ability to accurately detect crop uptake of a relatively small amount of fertiliser N (e.g., 25-100kg N/ha) against a much larger background quantity of soil N (e.g. 2,200kg N/ha assuming soil total N = 0.2% and bulk density of 1.1g/cm3).
A generalised value of 50% recovery of the fertiliser and available soil N within the season of application by the crop is widely assumed (Unkovich et al. 2020). This value is based on experimental data from field trials undertaken in the 1980s cited in Chen et al. (2008) in southern Australia and Strong (1995) in southern Queensland, which indicate that wheat crops recover 25 to 60% of the applied N. More recent publications cite fertiliser N recoveries by wheat of 49 and 57% in an acid chromosol in southern NSW (Smith et al. 2019).
Data on crop utilisation of 15N labelled urea collected from western Victoria using current grower management practices and rates across a range of environments and seasons indicate a wide range of fertiliser N recoveries (2 to 75%) depending on the zone/cropping system (Table 3). The average crop recovery of fertiliser N (34 to 35%) was surprisingly similar between environments and cropping systems. The key determinant of crop recovery was rainfall (or irrigation) following application. Very low recovery of fertiliser N was measured where GSR post application was <66mm, a common occurrence in low and medium rainfall situations during the seasons tested. Crop recovery was also sensitive to the rate of application (as expected), with higher crop recovery at lower application rates. However, there was no statistical evidence (P > 0.05) that applying fertiliser produced an added N interaction (i.e., inducing an increased utilisation of soil N; data not presented), a finding that contrasts with the NANORP study where the interaction was relatively large (Wallace et al. 2020).
Table 3. Mean (and range) of crop recovery of fertiliser N using both 15N labelling and difference methods, errors between these methods and losses of fertiliser N from the crop:soil system within the season of application using pooled data from nine sites (2014 to 2016). N was applied as top-dressed urea during vegetative/early tillering stage.
Zone/ cropping system
Crop recovery using 15N approach
Crop recovery using difference approach*#
Crop recovery error when using the difference approach*
Loss of top-dressed N using 15N approach*
Low-medium rainfall dryland
(2 to 75%)
(-29 to 226%)
(-52 to +172%)
(2 to 47%)
(22 to 50%)
(-13 to 102%)
(-40 to +64%)
(4 to 53%)
(12 to 60%)
(-13 to 64%)
(-39 to +48%)
(26 to 57%)
Data from a smaller spatial scale study (three experiments, all in the Wimmera) indicated a narrower range of crop fertiliser N recoveries, ranging from 12 to 56% (Table 4). This study highlighted the strong effect of seasonal conditions on the effectiveness of different N management strategies. For example, in 2012, N management had no significant effect on crop recovery of fertiliser N (range 49 to 55%), although it did affect grain yield response. In contrast, in 2014, maximum fertiliser recovery by the crop occurred when N was applied early whereas later applications (topdressing) resulted in very low crop recoveries and a trend to poorer grain yield responses due to very low rainfall received from August onwards. A positive finding, however, was that the low crop recovery under these dry conditions generally corresponded to high rates of recovery in the soil at harvest, rather than being lost. In contrast to the AonG survey data, significant interactions were recorded, indicating that utilisation of soil N was stimulated by fertiliser treatment (Wallace et al. 2020).
Table 4. Crop total N uptake at maturity, N uptake from fertiliser, total N uptake, recovery of fertiliser N in crop (grain + straw) and estimated loss of fertiliser N from crop:soil system (0-40 cm) using different N management strategies in the Wimmera from 2012 to 2014. (Source: Wallace et al. 2020).
Total N uptake from soil (kg/ha)
N uptake from fertiliser
Total N uptake (kg/ha)
Grain yield (kg/ha)
Crop recovery of 15N fertiliser (%)
Fertiliser loss using 15N approach (%)
50 N DMPP
0:50 N NBPT
50 N DMPP
0:50 N NBPT
50 N DMPP
0:50 N NBPT
0N = no N applied. 50N = urea incorporated at sowing; 50 N DMPP = urea + nitrification inhibitor incorporated at sowing; 0:50 N: urea top dressed at early-mid tillering; 0:50 N NBPT = urea + urease inhibitor top-dressed at early-mid tillering. Fertiliser N applied at equivalent of 50 kg N/ha.*Superscripts indicate significant differences (P <0.05) compared with other treatments within a given year.
Net off-site losses of N or immobilisation
Significant losses of N can occur from the soil by a range of pathways, including gaseous losses of ammonia (via volatilisation), denitrification (predominantly as dinitrogen- N2) and leaching (of nitrate) below the root zone.
The use of a 15N labelled fertiliser mass balance approach allowed a quantitative assessment of the potential irretrievable loss of N derived from fertiliser. In our field studies, losses of fertiliser N ranged from 2 to 47% in low and medium rainfall zones (mean = 25%), 4 to 53% (mean = 32%) in the HRZ and 26 to 57% (mean = 41%) in irrigated cropping sites in northern Victoria (Table 3). Similar to crop recoveries, N management strategy significantly affected losses of fertiliser N depending on seasonal conditions, with nitrification inhibitors (DMPP) reducing losses in above average rainfall conditions and urease inhibitors (NBPT) producing significant benefits in reducing losses of top-dressed urea under dry seasonal conditions (Table 4). While the data directly estimated the loss of N derived from the labelled fertiliser applied to the crop:soil system, it could not unfortunately identify the primary N loss processes responsible. Measurements following harvest indicated little movement of 15N below the topsoil (0-10cm and occasionally 10-20cm), suggesting that gaseous loss (denitrification or volatilisation) was most likely responsible rather than leaching. Furthermore, total losses of N from the system are likely to be greater than our data indicate, as our procedure only accounted for fertiliser N and not for losses of ‘background’ soil mineral N which was not labelled with 15N.
Despite its importance to on-farm profitability, N management remains problematic for most growers and advisers. The guiding ‘4R’ principles of the right source, rate, time and place of fertiliser requires knowledge of both crop demand and soil N supply. Seasonal conditions remain the primary driver of crop demand for N in dryland cropping systems and to a significant extent also fertiliser use efficiency. Similarly, seasonal conditions also strongly influence the underlying assumptions of soil N supply, via its effect on both the rate of N mineralisation during the summer/autumn fallow and the rate of N mineralisation in-crop, as well as crop utilisation and losses/immobilisation of fertiliser N.
Although no one can control seasonal conditions, seasonal forecasting is steadily improving and it is thought that growers/advisers can significantly reduce uncertainty of potential N supply through measuring both soil profile N prior to or just after sowing and in-crop N mineralisation using currently available procedures. The previous widely held assumption of 50% recovery of fertiliser and soil N was reputedly based on higher recovery of soil mineral N (70%) and 30% of fertiliser N (Mike Bell, quoting Wayne Strong and Chris Dowling). This value was formulated, however, in a period when soil N supplied most of the crop’s N. In current cropping systems, however, where there is less legume/pasture leys and tillage, and organic matter levels have declined, fertiliser N is the dominant source of crop N supply, a more appropriate figure for crop utilisation of fertiliser and soil of 35% is suggested for the southern region. This revised figure appears to be consistent across diverse cropping systems, although this may reflect differing influences. For example, better soil moisture in higher rainfall environments allowing for greater crop access to fertiliser being balanced by lower losses of N in drier environments.
Similarly, losses of fertiliser and presumably soil N appear to be an inherent feature of current cropping systems and based on the data appear to have been underestimated. Although many advisers in the 2015 survey were aware of the mechanisms by which N could be lost from the cropping system, most had difficulty in identifying rates of losses occurring in their environments. Furthermore, because the emphasis of many previous field-based experiments has been on greenhouse gas emissions (N2O), where total quantities of N in terms of kg/ha are relatively low (Wallace et al. 2018), there was a lack of awareness that N2 losses from denitrification could be of much greater ‘agronomic significance’, as suggested by the 15N mass balance data. ‘Unaccounted for’ N which was assumed to be lost averaged 25, 32 and 41% in low-medium, high rainfall and irrigated cropping systems, respectively, but instances of losses of > 50% were recorded across all these systems. These losses occurred at agronomically relevant rates and could be expected to become relatively larger at higher application rates. Previous research (also using 15N mass balances) has found large losses (up to 90% depending on application strategy) of applied fertiliser N from HRZ cropping systems in western Victoria (Harris et al. 2016). In the AonG study, fertiliser N was applied via topdressing of urea (mostly during tillering to first node), so an assumption was that volatilisation was the main loss mechanism. However, there were circumstances, especially in the HRZ and irrigated cropping trials and on sodic soils in the MRZ, that background soil conditions may have been conducive to denitrification losses driven by anaerobic waterlogged conditions. Knowing the mechanism of this N loss is important, as the NANORP study clearly showed that use of an appropriate fertiliser management strategy can significantly reduce losses of N and enhance supply to the target crop if applied in the correct situation.
Growers can potentially improve their fertiliser N management by (i) undertaking deep N soil testing, (ii) using current RoT predictions of in-crop N mineralisation and (iii) reducing the assumed crop utilisation of soil + fertiliser N to approximately 35 rather than current 50%.
Large losses of N appear to occur regularly across low and medium rainfall and irrigated cropping systems, not just in the HRZ as previous thought. However, the ability to mitigate these losses is hampered by uncertainty as to the loss pathways. Knowledge of this information would facilitate the identification of appropriate fertiliser management strategies, which have been shown to significantly reduce losses and improve yields.
Much of the original data used in this project originated from the Australian Department of Agriculture and Water Resources (AOTGR2- 0073) project ‘Reducing on-farm nitrous oxide (N2O) emissions through improved nitrogen use efficiency in grains’ and Filling the Research Gap’ NANORP program. We wish to acknowledge the invaluable discussions and insights provided by our colleagues Murray Unkovich, Mike Bell, Louise Barton and Sean Mason. Katherine Dunsford’s PhD was co-funded by Agriculture Victoria, LaTrobe University and GRDC through Project DAN00168. We wish to acknowledge the significant contributions of the many grain growers of western Victoria who assisted us with conducting these experiments on their properties.
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Prof. Roger Armstrong
Grains Innovation Park, 110 Natimuk Rd, Horsham VIC 3400.
0417 500 449
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