Novel field-based approaches reveal wheat genotypic differences in nitrogen use efficiency and grain protein dynamics

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Swarbreck, Alek Ligeza, Susie Roques, Daniel Kindred, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8261533/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Achieving high yield and grain quality in wheat typically requires the application of substantial amounts of nitrogen (N) fertiliser. However, given economic and environmental constraints, it is critical to understand whether growers can reduce N inputs without compromising performance, and whether existing varieties differ in their ability to cope with lower N availability. Using a novel field-based experimental platform, we assessed the performance of fifteen registered wheat varieties under six N regimes and over two seasons with contrasting weather patterns. As expected, yields and grain protein contents both increased with N application, although protein content plateaued at a higher N threshold than yield. We noted higher genotypic differences in N use efficiency (NUE; defined as yield per unit of available N) under zero- N fertiliser applications, revealing intrinsic variation in low-N resilience. N-driven yield increase was more strongly associated with spike number rather than spike weight. Two varieties selected in Denmark where tight regulations on N applications are applied were included for comparison and could achieve high yield with contrasting strategies; one with low and the other with high spike weight. In addition, using a novel stable isotope field-based method, we could show that under higher N levels, the post-anthesis N uptake was decreased and this trait is critical to achieving positive grain protein deviation (higher increase in grain protein content than expected given its yield). Our findings highlight the necessity of evaluating commercial and pre-breeding wheat germplasm under reduced N conditions to identify genotypes suited to sustainable, lower-input agricultural systems in a changing climate. Biological sciences/Genetics Biological sciences/Plant sciences Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Nitrogen (N) is an essential macronutrient for plant growth and tends to be limiting plant primary productivity in all ecosystems except deserts (LeBauer and Treseder 2008 ). The widespread availability of synthetic N fertiliser, made possible through the development of the Haber-Bosch process, has sustained crop yields in many production regions across the globe over the last century (Erisman et al. 2008 ). This industrial and chemical innovation and accompanying innovative agronomic practises, have been particularly important for cereal crops such as wheat ( Triticum aestivum L.), which has a high N requirement. Concurrent advances in plant breeding led to the selection of short-strawed cultivars which were tolerant to lodging (physical displacement of stems) and more likely to allocate biomass towards the grain. Since then, wheat varieties have tended to be selected under high N inputs, which has driven increases in yield. In the UK, these have plateaued since the 1990s (Hawkesford 2014 ) FAOSTAT, 2025). Agronomic N use efficiency (NUE), the ratio of yield produced per unit of available N, is often used to describe the impact of additional N fertilization on yield. However, the usefulness of the NUE term has been questioned (Swarbreck et al 2019 ), since under recommended N application levels, NUE continues to remain quite low (Voss-Fels et al. 2019 ), and is high under lower N availabilities (which also limit yield). Also, NUE does not account for the economic cost of increasing N applications, relative to yield, and it has recently been suggested that research should focus on N responsiveness: maximising yield relative to reduced N inputs (Swarbreck et al., 2019 ). Soil available N is mostly taken up in the form of nitrate by wheat grown in temperate climates since it is the most available N source under those conditions (Kindred et al. 2012 ). Assessing soil N availability to ensure optimal supply to the crop is difficult because of seasonal fluctuations due to soil microbial activity, leaching and denitrification. However, it is essential that growers adjust their fertiliser application rate while taking into account available N. The UK RB209 Nutrient Management Guide issued by the Agricultural and Horticultural Developmental Board (AHDB) in the UK provides information on how to estimate soil available N based on soil type and previous cropping regimes. Applications of higher levels of N fertiliser are often used to maximise yield, and in some cases to increase grain protein content. In the UK, wheat grown for bread making (belonging to the UK Flour Millers Group 1) tends to require higher N applications to achieve the requisite 13% grain protein content (GPC) which is accompanied by a price premium (N. S. Fradgley et al. 2022 ; N. Fradgley et al. 2023 ). In order to reduce N inputs and losses due to run-off and volatilisation, studies are required to determine whether commercially available varieties could maintain yield quantity and quality at lower applied N levels (Swarbreck et al. 2019 ). Tools are available to growers to adjust N application during the season such as measurements using NDVI (normalised difference vegetation index), or low-cost chlorophyll meters. In addition, the leaf colour chart which was developed initially at the International Rice Research Institute (IRRI) has been applied to in-season N recommendations for rice cultivation in India (Irri 1996 ) and adapted for wheat (Varinderpal-Singh et al. 2012, 2017 ). In North West Europe (especially France and the UK), many studies have evaluated the performance of winter wheat varieties under contrasting N levels over the past 5 decades. Some studies report differences amongst commercial varieties (Barraclough et al. 2010 ; Barraclough, Lopez-Bellido, and Hawkesford 2014 ) though varieties tend to respond more similarly (Morris N., Clarke S., Swarbreck S.M., Peters C. and Hague B. 2024; Morris, N., Hoad, S., Roberston, D. and Charlton, M. 2022 ). Recently released elite genotypes tend to be less efficient in acquiring soil N in the absence of supplementation from N fertiliser, (Foulkes, Sylvester-Bradley, and Scott 1998 ), and may be better adapted to acquire N dispensed at specific stages in large doses and perhaps less dependent on microbial activities. For UKFM group 1 varieties, the requirement for high GPC adds to the N requirement although post-anthesis N uptake can lead to higher GPC (Bogard et al. 2010), providing a specific timepoint for intervention. In Europe, a total of 225 winter wheat varieties released between 1969 and 2010 (mostly released between 1985 and 2010) were tested under two N rates in four experiments (Cormier et al. 2013 ). This uncovered significant Genotype (G) x N rate interactions for grain yield, GPC and NUE. The year of registration had a significant effect on G x N rate interaction for yield and NUE. Modern varieties had a G x N rate interaction that increased yield under high N, with a corresponding decrease under low N. These G x N rate interactions could be explained by variations in quality classes (more recent varieties tended to be higher yielding but had lower GPC and earlier flowering times). In a follow up study, tolerance indices were defined and used to identify specific QTL regions underpinning tolerance to low N (Mini et al. 2023). Overall, reports of varietal differences in yield under varied N levels have been noted. Farmers cannot simply assume that the performance of a wheat variety will be maintained at lower N and understanding the biological basis for these differences can inform selection of cultivars better suited to low input agriculture, and reduce N losses and emissions from more intensive systems or late fertiliser applications (Swarbreck et al. 2019 ). Additionally, accounting for changing climatic conditions (winter flooding or low water recharge, summer drought) requires additional research to inform farmers on timing for optimal N fertilisation schedules. The aim of this study was to investigate the responses of modern elite wheat varieties, released between 1989 and 2014, selected across the 4 UKFM milling groups under contrasting N inputs. The set include varieties issued from Danish breeding programmes, which have been conducted under lower N availability compared to the UK. The use of a novel Opti-plot design allowed 6 contrasting N concentrations to be delivered to a specific variety within a single plot, across a replicated field experiment, with a modified combined harvester quantifying yields for each variety at each N level. The field trial was repeated over two contrasting growing seasons, 2016–2018 with measurements of canopy development, chlorophyll content and soil N content, as well as 15 N uptake and utilisation post-anthesis. Materials & Methods Opti-plot field trials A total of 15 winter wheat commercial varieties were selected for field testing, representing UK commercially available lines from each of the four UK Flour Millers groups as well as varieties selected for the Danish market, where restrictions on N applications are in place (Petersen et al. 2021 ), Table 1 ). Table 1 List of winter wheat varieties included Varieties UK/Denmark UKFM Group Year of registration 1,2 Claire UK 3 1997 Cordiale UK 2 2002 Crusoe UK 1 2010 Evolution UK 4 2012 Grafton UK 4 2007 Hereward UK 1 1989 JB Diego UK 4 2006 Robigus UK 3 2001 Santiago UK 4 2009 Siskin UK 2 2014 Skyfall UK 1 2012 Belgrade Denmark 2014 Benchmark Denmark 2014 Mariboss Denmark 2008 Torp Denmark 2013 1 Year of registration indicates year of completion of the statutory National Listing. Two field experiments were conducted in Stetchworth (Suffolk, UK) on different fields on the same farm in 2016/2017 (52°2180’ N, 0°3707’ E) and 2017/2018 (52°2125’ N, 0°3721’ E). The trial was drilled on 28th September 2016 and on 5th October 2017. Soil types were sandy loams. Climatic conditions throughout the growth period, including rainfall and temperature patterns, are presented in Fig. S1 . The total rainfall from 1st January until the 31st August was lower in 2017 (215.8 mm) compared to 2018 (387.4 mm). However, during the grain filling period post-anthesis (1st June- 15th August), the total amount of rainfall was much higher in 2017 (126.2 mm) compared to 2018 (54.8 mm). Trials in both years used the experimental field design (Fig. 1 A), that held four blocks, each containing variety mainplots of 2m x 32m each, plus 2m x 32m ‘uniformity plots’ at each end and in the centre of each block, flanked by 2m x 32m discard plots. Varieties were grouped and the groups were randomised in each block. N treatments ran across blocks in 4m strips, so that each 32m plot is split into eight 4m subplots. The central six N subplots included six N treatment (0, 70, 140, 210, 280 and 350 kg N ha − 1 ) achieved through the application of ammonium nitrate granules (Fig. 1 A), the subplot at each end of the plot were treated at 210 kg N ha − 1 rate and discarded because it contained a tractor wheeling. The order of N treatments in each block was randomised, with the randomisation restricted such that adjacent N treatments did not differ by more than 2 N levels. All plots were planted at a seed rate of 350 seeds m − 2 and replicated in each block. A total of 52 winter wheat genotypes including 15 commercial varieties were tested and we present here the data from the commercial varieties only (Table 1 ). In the first trial year, soil mineral N was measured on 26th January 2017 to be 75 kg N ha − 1 (soil analysis was completed at a commercial lab following BS EN 13652:200). Polysulphate was applied at a rate of 101.5 kg ha − 1 across the trial on the 10/03/17 to avoid S limitation (48.7 kg ha − 1 SO 3 , no N). In the second year, soil mineral content was measured on 30th January 2018 to be 25 kg N ha − 1 . A rate of 100 kg ha − 1 ammonium sulphate was applied across the trial 20/03/18 to avoid S limitation (21 kg N ha − 1 N, 60 kg ha − 1 SO 3 ). In each season, N was applied in three splits (details of the dates and N applied at each split is shown in Table S1 ). Field trials were managed following typical practices including application of fungicides, herbicides and pesticides. Grain yield for each individual N application level was measured by plot harvester (Sampo 2010) and expressed at 85% dry matter. Grain protein and moisture contents were measured using Near-Infrared Spectroscopy at a commercial lab. NDVI measurements NDVI measurements were conducted using a RapidScan CS-45 (Holland Scientific) on 2nd November 2016, 27th January 2017, 1st March 2017, 25th April 2017 and 1st of June 2017. Shoot number at GS31 The number of shoots per plant was counted on ten uprooted plants from each sub-plot at GS31. Grab samples Pre-harvest samples of 30 whole shoots were cut at ground level from each subplot at two N rates (0 and 210 kg N ha − 1 ). Samples were split into ears and straw and oven-dried at 80 o C for 24 hours before weighing. The ears threshed to separate grain and chaff, and the grain re-dried and weighed. Samples of straw + chaff were analysed by Dumas for %N content. Plot yields were used to calculate grain, chaff and straw biomass (t ha − 1 ) and N content (kg ha − 1 ). Chlorophyll content and leaf measurements Chlorophyll contents were estimated using a portable chlorophyll content meter (CCM-200 plus, Opti-Sciences, Hudson, USA) on 12 flag leaves from individual plants per sub-plot between 1st June 2017 and 21st June 2017 and on 8 plants per sub-plot between 5th June 2018 and 21st June 2018, around flowering time (after GS61). Assessments using the leaf color chart (LCC) were conducted over the same period in 2018 (Varinderpal-Singh et al. 2012, 2017 ). Post anthesis nitrogen measurements For a subset of varieties (Claire, Crusoe, Evolution and Siskin), post-anthesis nitrogen uptake was estimated using a 15 N isotopic method. In the field, a volume of 10mL of a 1mM 15 NH 4 15 NO 3 ( 15 N 2 98%, Cambridge Isotope Lab Inc.) solution was added to the base of one plant at milk stage (GS75) and one tiller of the targeted plant was collected after 2 days. Additional tillers from untreated plants were collected from each plot as control. Tillers were then dried at 75°C for 48h or until no further loss of weight could be measured. All samples were weighed, ground to a fine powder and analysed for isotopic ratio of 14 N/ 15 N. Post-anthesis N uptake was estimated as the capacity of plants to take up 15 N over the 2-day labelling period. In a separate pot experiment, plants (varieties Claire, Crusoe and Siskin) were grown under controlled conditions with 16h photoperiod, 20°C day/18°C night, light intensity (200 µmol m − 2 s − 1 ), in 1L pots on a 1:1 (v/v) mixture of sand and terragreen, supplemented with a modified Hoagland solution (Taulemesse et al. 2015 ). Nutrient solution including 1mM KH 2 PO 4 , 1.5mM KNO 3 , 0.25mM Ca(NO 3 ) 2 , 4H 2 O, 2mM MgSO 4 , 7H 2 O, 3.25mM CaCl 2 , 3,5 mM 2H 2 O, 3.5mM KCl, 1mM NH 4 NO 3 , 10µM H 3 BO 3 , 0.7µM ZnCl 2 , 0.4µM CuCl 2 , 2H 2 O, 4.5µM MnCl 2 , 4H 2 O, 0.2µM MoO 3 and 50µM EDFS-Fe, was supplied every 2–3 days. At GS75, a volume of 10mL of a 1mM 15 NH 4 15 NO 3 was provided to each pot. Samples were then collected. Roots were washed from the sand and terragreen. Grains were collected from the middle of the spike from the main tiller. Flag leaves were also collected from the main tiller. Plant material was dried at 75°C for 48h, before grinding to a fine powder using a Tissue Lyser (Qiagen). Samples sealed in tin capsules were analyzed for percentage carbon, percentage nitrogen, 12 C/ 13 C (δ 13 C) and 14 N/ 15 N (δ 15 N) using a Costech Elemental Analyzer attached to a Thermo DELTA V mass spectrometer in continuous flow mode. The dried sample was carefully weighed (0.5mg) into a tin capsule, sealed and loaded into the auto-sampler (analyses conducted at the Godwin Laboratory, Department of Earth Sciences, University of Cambridge). Precision of analyses is better than 0.1‰ for 12 C/ 13 C. Data are presented as 15 N excess, which was calculated based on measurements of δ 15 N and tissue N% as described in (Bandyopadhyay et al. 2024 ). Statistical analysis Statistical analysis of the field trial data was conducted in R and using the lme4 package. A linear mixed model was used to analyse the data: lmer(variable ~ Year * Variety * N Treatment + (1| Year:Block) + (1| Year:Block:Plot) + (1| Year:Block:Subplot). The term “(1| Year:Block)” was included to account for the block as a random effect, while “(1| Year:Block:Plot)” was included to account for plot within blocks as random effect (as each varieties is one plot) while “(1| Year:Block:Subplot)” was included to account for the fact that all N levels are on the same strip. Best Linear Unbiased Estimates and confidence intervals were calculated using the emmeans function from the emmeans package in R. Results All tested winter wheat varieties respond to increased N availability Data are presented for the 15 wheat commercial varieties included in the trial grown, at six N levels (0, 70, 140, 210, 280 and 350 kg ha − 1 ) in an opti-plot field trial system (Fig. 1 A) over two seasons (2016–2017, 2017–2018), with contrasting weather conditions (Fig. S1 ). All varieties showed a typical response to the provision of N fertiliser, with an initial clear increase in yield from 0 to 70 or 140 kg N ha − 1 (Table S2). (Fig. 1 B). For most varieties, the yield tended to plateau above 140 kg N ha − 1 , except for Cordiale which plateaued at 70 kg N ha − 1 . The yield achieved in harvest year 2018 tended to be lower (reaching a maximum of 8.8 t ha − 1 ) than that achieved in harvest year 2017 (reaching, a maximum of 11.7 t ha − 1 , Fig S2). While all varieties responded to the provision of N fertiliser, there were significant difference in yield amongst varieties at different N levels (Fig. S3A). Under no additional N supply, Siskin and Santiago showed significantly higher yield compared to Cordiale, Robigus, Crusoe and Hereward. Siskin remained a high yielding variety maintained at high N availability. Danish derived varieties, Belgrade, Torp and Mariboss were the top performers at low (70 kg N ha − 1 ) N level. While there was overall good correlation between performance at 70 kg N ha − 1 and 140 kg N ha − 1 , the varieties Claire and Siskin produced significantly higher yields under 140 kg N ha − 1 than predicted for their performance at 70 kg N ha − 1 yields (Fig. 1 C). These appear as clear outliers relative to the regression line, which reflects a higher N responsiveness than observed for the remaining varieties. NUE decreases with increasing N application rate NUE was calculated as the ratio of yield per unit of available N (i.e. estimated as the sum of residual soil N and applied N). Overall, there was no significant difference between 2017 and 2018 (Fig. 2 , lmer n.s.). The differences amongst varieties were significant at the lowest N rate (lmer, p < 0.01), and there was a significant interaction between variety and N treatment (lmer, p < 0.05). Santiago and Siskin showed the highest NUE, while Crusoe showed the lowest (Fig. 2 ). NUE decreased with increased N availability (lmer, p < 0.01). NUpE (defined as the ratio of total N uptake per unit of N available) also declined with the addition of N fertiliser (lmer, p < 0.01) and no significant differences amongst varieties could be measured (Fig. S4A) while the Nitrogen Harvest Index (proportion of N in the grain to the total N) remained similar between 0 and 210 kg N ha − 1 treatments (Fig. S4B, lmer, n.s. ). Grain yield increased with the date of variety registration with more recent varieties showing higher yield overall (Fig. S5). However, in the absence of N fertiliser, the slope was lower (0.04 t ha − 1 per year, compared to 0.06 t ha − 1 per year under 70kg N ha − 1 ) and the correlation was not significant ( p = 0.07), compared to the other N application rates. With applied N rates above 210 kg N ha − 1 , the correlation tended to be greater than 0.6. NDVI is an indicator of N dependent yield increase NDVI measurements were conducted at five timepoints throughout the first trial season (November- GS13, January- GS23, March- GS25, April- GS31, and June- GS61) and identified significant differences between varieties at all time points except late in the season (June). NDVI values increased throughout the season indicating increased ground coverage (Fig. 3 A). In April, a significant response to an increase in N availability was detected from 70 to 140 kg N ha − 1 (Fig. 3 A). At this timepoint, there was a significant correlation between NDVI measurements and yield (Fig. 3B, R 2 = 0.48, p < 0.01). Overall, there was no significant interaction between varieties and N treatment. While most varieties showed a positive correlation between yield and NDVI measured in April, this was not the case for Cordiale (Fig. S6). It is worth noting that the correlation between yield and NDVI was strongest under lower N levels (Fig. S7). Leaf greenness was measured using SPAD at flowering in both 2017 and 2018, and clearly increased with additional N availability (Fig. S8). The LCC was also used in 2018 to capture visible changes in leaf greenness (Fig. S8). Overall, there was good correlation between SPAD and LCC measurements ( R 2 = 0.9, p < 0.01). Nitrogen dependent yield increase is linked to increased shoot number when rainfall is sufficient Wheat yield is the product of grain number (grain number per spike and spike number) and grain weight. The number of shoots was higher in 2018 (ranging from a mean of 2.98 shoots per plant for Claire to a mean of 5 shoots per plant for Mariboss), compared to 2017 (mean of 2.21 shoots per plant for Hereward to a mean of 3.88 shoots per plant for Cordiale, Fig. 4 ). There were significant differences in shoot number amongst varieties in both years (lmer, p < 0.05) and differences amongst varieties. These were generally higher in the wetter winter of 2018 (Fig. S1 ), with Hereward and Claire showing a lower shoot number compared to other varieties (Fig. 4 ). There was a positive, though weak, correlation between shoot number at GS31 and yield but only in the harvest year 2017 (R 2 = 0.08, p < 0.05) and not in harvest year 2018 ( n.s. ), when there was a late drought following anthesis (Fig. S1 ). Spike weight does not respond to increased nitrogen availability Ear weight was not significantly affected by N level (lmer, n.s.) in both 2017 and 2018 (Fig. 5 ). There were significant differences amongst varieties in both years (Fig. 5 ). While Mariboss generally showed lower spike weight compared to all other varieties (lmer, p < 0.01), Torp showed significantly higher spike weight (Fig. S9). The spike weight for Crusoe was also significantly higher compared to other varieties (lmer, p < 0.01). Wheat grain protein content plateaus at higher N availability than yield. All varieties showed a clear response to the provision of N fertiliser, with an increase in GPC (Fig. 6 A). For most varieties, GPC tended to plateau at 210 kg N ha − 1 , which is a higher N level than the yield plateau. The overall GPC achieved in 2017 tended to be higher (range of 7.19–14.39%) than that achieved in 2018 (range of 4.54–12.15, Fig S2), again showing the impact of the late drought. While the N dependent yield and GPC increase showed a positive correlation (2017: R 2 = 0.26, p < 0.01; 2018 R 2 = 0.43, p < 0.01) overall, at each N level we observe the expected negative correlation between yield and GPC (Fig. S11). Positive grain protein deviation is linked to post-anthesis N uptake There was significant differences grain protein content amongst varieties (Fig. S10) as expected given their UKFM group. Some varieties showed positive grain protein deviation (GPD, representing an increase in grain protein content relative to yield, and hence positioned above the regression line in Fig. 6 B) including Siskin (also higher yielding) and Crusoe (lower yielding), while others showed a negative GPD (Claire and Evolution, Fig. 6 B). Positive GPD has been linked to increased post-anthesis N uptake (Bogard et al. 2010), and this was measured in the field using 15 N labelling (Fig. 6 C). While there were no significant differences amongst varieties, there was increased post-anthesis N uptake under lower N supply (70 kg N ha − 1 ) compared to higher N supply (280 kg N ha − 1 , lmer p < 0.01). A negative correlation between kernel N content and kernel 15 N excess was measured in the field, suggesting higher PANU potential in lower N-containing grains. In a separate experiment, PANU was measured in plants grown in pots under controlled conditions following a similar method of application of 15 NH 4 15 NO 3 to the growth substrate. Under these conditions, roots could be washed and analysed as well as the flag leaves and grains. Grains represented the largest store of 15 N post-anthesis while very little 15 N remained in the flag leaf (Fig. 7 A). Under these conditions, a significant difference was recorded, with positive GPD varieties (Crusoe and Siskin) showing higher PANU compared to Claire which has negative GPD (Fig. 7 A). Overall, there was also a negative correlation between grain N content at the time of analysis and PANU as measured through 15 N excess (Fig. 7 C), consistent with the field data. Discussion Balancing the need for wheat production for food and feed with environmental impact associated with modern fertiliser inputs is a challenge that requires continued investigation, especially in the context of seasonal variations in water supply and drought associated with climate change. Here we report the response of elite winter wheat cultivars from Northern European breeding programmes (all released in the last 25 years) to N rates ranging from 0 to 350 kg N ha − 1 . There was a clear positive effect of N application on the yield of all cultivars tested, while some varietal differences could be measured. NUE showed a strong decline under even modest N application for all varieties. We show that the N-dependent yield increase is linked to an increased spike number, rather than spike weight, thus identifying a possible mechanism for N responsive yield increase and a target for crop breeders. Field trials across the broad range of N application rates used here are unusual because of the technical complexity. Unless wheat is grown under organic farming practices (Przystalski et al. 2008 ), some level of N is added which makes the level 0 in our study unique. At the other end of the spectrum, applying 350 kg N ha − 1 is not economically viable for farmers (except where fertiliser is heavily subsidised) and results in environmental losses. However, assessing diverse wheat cultivars under this range of N applications rate is valuable as it allows precise quantification of their N responses. The opti-plot testing approach used here allows for testing of 6 N levels with sufficient plot sizes to allow for reliable agronomic assessment of crop growth and grain yield. The plots and treatment are arranged to ensure some level of randomisation and reduces the likelihood of impact from high N sub-plots onto low N sub-plots. Yield of all varieties tested tended to plateau at 140 kg N ha − 1 , in both 2017 and 2018 even though climatic conditions (late drought) which probably limited yield in 2018. All varieties tested here showed a clear increase in yield under higher N availability. Since the varieties had all been selected for and commercialised in the last 25 year, this is expected. Modern wheat cultivars tend to show higher yield responses under high N availability compared to older (and taller) varieties (Ortiz-MonasterioR et al. 1997 ). We also noted increases in yield at all N levels related to the year of registration which, and this is in-line with similar analyses conducted on German wheat germplasm (Voss-Fels et al. 2019 ). We also found that the positive correlation was more apparent under higher N level (Fig.S5), suggesting that perhaps selecting under lower N levels would lead to greater genetic gains for performance under lower N. While all varieties tended to respond to the same level, selected varieties (Siskin and Claire, Fig. S3) showed a greater than expected N responsiveness suggesting that this is a trait that has not yet been maximised for all commercially released varieties. N responsiveness is the capacity of plants to respond to increased N availability. We argued that varieties showing higher N responsiveness should be a selection marker, as this trait is linked to the molecular signalling associated with plant N uptake and mobilisation (Swarbreck et al. 2019 ). The response for Cordiale to higher N was lower, and we propose this to be linked to its early flowering phenology (Fig. S12), which may have resulted in mis-timed N fertiliser application. It is worth noting that Danish varieties performed well under 70 kg N ha − 1 , though their overall NUE was not particularly improved compared to varieties selected through breeding programmes in the UK (Fig. 2 C). However, they are able to achieve high yields using different strategies as Mariboss showed a very low spike weight that was compensated by greater spike numbers. Although NUE does not effectively capture the economic costs associated with N application (which makes N responsiveness such a useful metric), we confirmed that it was much greater under lower N availability, in line with other studies (Voss-Fels et al. 2019 ). The higher NUE under no fertiliser application can be associated with either increased NUpE (the ratio of total N uptake per unit of N available) or NUtE (yield per unit of N taken up by the plant). Higher NUpE can be achieved under no additional N application when microbial dependent N sources become more important (King et al., 2001). Under no additional N application, soil processes can be improved or increase recruitment of beneficial microbes, which tend to be inhibited at elevated N availability (Oldroyd and Leyser 2020). In our study, we could see a similar pattern of increase NUpE under low N but no change in NHI (grain N content relative to above-ground plant N) suggesting that increased uptake efficiency underpins the higher NUE without any fertiliser application. This supports the finding that in a study of French wheat varieties (historical, pre-Green Revolution and more recent varieties) grown under two levels of N (no addition, and 170 kg ha − 1 addition), NUpE accounted for more of the variation of NUE for grain yield at N0 than under N fertilisation (Le Gouis et al. 2000 ). Under low N, wheat plants can develop more extensive root systems to explore and exploit a larger soil volume and access a higher proportion of soil available N (Smith and De Smet 2012; Aziz et al. 2017 ; Finch et al. 2017 ). It is interesting that differences in grain yield, hence NUE, amongst varieties are very strong at N0. It is often thought that plants need to be grown under optimal/high N rate to see differences amongst varieties and enable efficient breeding. However here, the strongest differences were seen at lower N level. Perhaps it is because these varieties were selected under generally higher N levels that no differences amongst variety specific NUE can be observed at high N levels. This raises the potential of including reduced N level screening in selection of germplasm in breeding and assessment of commercial varieties in the UK (Morris N., Clarke S., Swarbreck S.M., Peters C. and Hague B. 2024) as is done in other countries such as France. Yield is a complex trait that includes grain size and grain number (which itself is dependent on spike number and number of grains per spike). Here we show that spike number varies amongst varieties and is correlated with grain yield, although only under sufficient moisture (2017). Our data show a similar pattern to data from foxtail millet (Bandyopadhyay et al. 2022 ) where N-dependent yield increased is underpinned by increases in grain number rather than grain size. This lack of increase in grain weight under increasing N level is also noted as spike weight remained stable at all six N levels in both trial years of the experiments. It remains to be seen whether improving individual grain size response to increased N may lead to further yield increase under higher N availability. Danish varieties Torp and Mariboss adopted contrasting strategies to achieve high yield. Torp showing higher spike weight compared to Mariboss under all N levels, and lower spike numbers. In our study, N dependent GPC tended to plateau at higher N application rates than yield. GPC of varieties was also negatively correlated with their yield. However, when yield increase is driven by increasing N, there is an overall positive correlation between yield and GPC. It is only at each N level, that a negative varietal correlation was noted. From this analysis, we could identify varieties with higher yield such as Evolution and Siskin, and varieties with lower yield such as Claire and Crusoe. In terms of grain protein content relative to yield (GPD), both Crusoe and Siskin showed positive GPD while Claire and Evolution showed negative GPD. Such data provides a basis for crop breeders to select varieties with enhanced yields in association with more sustainable N inputs. Post-anthesis N applications are often used to enhance GPC and nudge grain quality towards UKFM bread-making requirements. Using an 15 N based method we were able to measure post anthesis N uptake (PANU) at a specific time point and showed overall a lower PANU (expressed as 15 N kernel excess) at higher N rates. This is a novel method for measuring PANU, as previous reports included estimating the total N content in the grain and straw at maturity in comparisons with the total plant N at anthesis (Nehe et al. 2020 ). Our 15 N based measurement is useful as it allows temporal resolution of PANU. This trait remains quite poorly understood and somewhat goes again the general concept that N in the grain is derived from the remobilisation from vegetative tissues. However, it was shown to be particularly relevant to the improvement of GPC (Bogard et al. 2010). While no varietal differences could be noted in the field, under controlled conditions (well watered) there was significant differences, with varieties showing positive GPD also showing higher PANU. Our findings that under higher N availability PANU declines are in agreement with a previous report (Taulemesse et al. 2015 ), which also suggested a key role for the high affinity nitrate transporter TaNRT2.1 . There is a need for further exploration of the genetic basis for PANU, especially in terms of regulation by plant-N status and contribution from remobilisation of existing N assimilates. Our data suggest that grain N content itself is correlated with PANU but the nature of the signalling mechanism from grain N status to root uptake is not known currently. From an agronomic and crop breeding perspective, the novel opti-plot approach, combining a wide range of N availabilities across two contrasting years in the field has provided insights for the traits that underpin higher performance in these conditions. Given the low level of genetic diversity amongst commercial wheat varieties in the UK, evaluating these under an extensive range of N level enables resolution of their N response differences, with a view to the selection of varieties which sustain yield and grain quality at lower N inputs. Our work also demonstrated that measurements of NDVI (and other low technology solutions, such as the LCC) throughout the season, and especially at GS31, provided a good indication of overall yield. However, climatic conditions in both years contributed to overall yield and grain quality, whether in terms of lower tillering in a dry winter (2017) or a reduction in spike productivity in a late season drought. These findings are a step towards providing farmers with a clearer understanding of how changing climatic conditions can alter the effectiveness of late N applications, whether in terms of enhancing GPD or recovering the financial cost of the additional inputs. In future, such an economic N optimum will need to be associated with individual crop varieties, and more sustainable farming practices, which minimise N losses and maximise grain yield and quality. Declarations Competing interest The authors declare that they have no competing interests. Funding We thank BBSRC (BB/N013441/1: Cambridge-India Network in Translational Nitrogen CINTRIN), the Newton-Bhabha Trust Fund and Department of Biotechnology (India) for funding (Grant No.: BT/IN/UK-VNC/42/RG/2014-15). Author Contribution DK, RSB, HG and AB acquired the funding and designed the experiments. AL, SR and SMS acquired and analysed the data. SMS conducted further data analysis and interpreted the data together with AB and HG. SMS, AB and HG wrote the manuscript with contributions from RSB. Acknowledgements Rainfall and temperature data were provided by KisanHub. The authors would like to thank members of the CINTRIN project for interesting discussions. The authors would also like to acknowledge Dr Tally Wright and Dr Greg Deakin for support in statistical analyses, and the trial team at ADAS. References Aziz, Moyassar M., Jairo A. Palta, Kadambot H. M. Siddique, and Victor O. 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06:59:41","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11689,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/2c2a13ef17b6c0f0c912c970.png"},{"id":97765126,"identity":"fda3b8fc-c3e9-4550-937f-87d8c02c4921","added_by":"auto","created_at":"2025-12-09 06:59:41","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12901,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinegroupimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/8375469f54b942e88470092c.png"},{"id":97765130,"identity":"63b09997-79ba-4c80-a9be-a3fd9e438173","added_by":"auto","created_at":"2025-12-09 06:59:42","extension":"xml","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":111573,"visible":true,"origin":"","legend":"","description":"","filename":"be4b7032785445f1b41134ef146081191structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/915102e98995d4cbd6e2b1e8.xml"},{"id":97765131,"identity":"11b1ff37-d7af-476e-9276-f457aa16b7f5","added_by":"auto","created_at":"2025-12-09 06:59:42","extension":"html","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":116465,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/181b6ee68a8827869c63c98d.html"},{"id":97765102,"identity":"72d35e8b-63dc-4e6b-93bd-b1b485ec3f4a","added_by":"auto","created_at":"2025-12-09 06:59:41","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":159222,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWinter wheat yield nitrogen response plateau at 140 kg N ha\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e-1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e (A) \u003c/strong\u003eOpti-plot field trials were conducted where each variety was grown under 6 N levels (0, 70, 140, 210, 280 and 350 kg N ha\u003csup\u003e-1\u003c/sup\u003e) each within a plot and in 4 blocks. All varieties were replicated in each block. Untreated plots were positioned in the middle and at the end of each block. A total of 52 winter wheat genotypes were tested and we present here the data from the 15 commercial varieties included. \u003cstrong\u003e(B)\u003c/strong\u003e wheat yield (t ha\u003csup\u003e-1\u003c/sup\u003e) data shown as the mean ± se combined both 2017 and 2018 harvest, individual plot datapoints are also shown. \u003cstrong\u003e(C) \u003c/strong\u003eBLUEs for yield under 140 kg N ha\u003csup\u003e-1\u003c/sup\u003e were plotted against BLUEs for yield under 70 kg N ha\u003csup\u003e-1\u003c/sup\u003e.\u003cstrong\u003e \u003c/strong\u003eBlack line indicates the linear regression for the data while the dashed red line corresponds to y=x regression line. Two outlier varieties can be noted: Siskin and Claire.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/6a0c3cb0bc3301f0e4baba14.jpg"},{"id":97765103,"identity":"85b6d6cf-3295-46db-b4dc-1d2c111018d2","added_by":"auto","created_at":"2025-12-09 06:59:41","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":164015,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNUE decreases with increasing N application. (A \u0026amp; B) \u003c/strong\u003eNUE calculated as the yield per unit of N available (sum of soil available N and fertiliser applied) for each variety measured at each of the six N application rates. Data shown as individual datapoint and the mean ± se separately for 2017 and 2018. \u003cstrong\u003e(C) \u003c/strong\u003eData shown as\u003cstrong\u003e \u003c/strong\u003eBLUEs (Best Linear Unbiased Estimators) from combined data for 2017 and 2018. Letters indicate significant differences amongst varieties.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/53467995bf5a644fbf0c8183.jpg"},{"id":97765104,"identity":"8933f334-8788-4a25-95be-522dad22bcbb","added_by":"auto","created_at":"2025-12-09 06:59:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":158365,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNDVI measurements at GS31 are correlated to yield (A)\u003c/strong\u003eNDVI measurements were conducted on each plot at five different timepoints during the season- (November- GS13, January- GS23, March- GS25, April- GS31, and June- GS61). Data shown as individual plot datapoints and mean ± se per variety. \u003cstrong\u003e(B) \u003c/strong\u003eNDVI\u003cstrong\u003e \u003c/strong\u003emeasurements at GS31 are positively correlated with yield. Data shown as individual plot datapoints and mean ± se per variety.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/1f1fe043e0906714ee8a31dd.jpg"},{"id":97896464,"identity":"cdb8a3e4-05da-423c-828c-b87214c46ef7","added_by":"auto","created_at":"2025-12-10 15:36:35","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":179075,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between shoot number yield. (A: 2017 \u0026amp; B: 2018) \u003c/strong\u003eShoot number per plant at GS31. Data shown as individual plant datapoints and mean ± se. \u003cstrong\u003e(C: 2017\u0026amp; D: 2018)\u003c/strong\u003e Shoot number at GS31 was positively correlated with yield only in 2017, not in the year of the late drought (2018). Data shown as individual datapoints.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/25c67b971dd8ca2c5203960e.jpg"},{"id":97896389,"identity":"ded36d31-27fc-4b54-8367-394f23623ba3","added_by":"auto","created_at":"2025-12-10 15:36:29","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":127567,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWheat spike weight does not respond to increased nitrogen availability. (A: 2017 \u0026amp; B: 2018) \u003c/strong\u003eSpike weight measured before harvest. Data shown as individual plant datapoints and mean ± se. \u003cstrong\u003e(C: 2017\u0026amp; D: 2018)\u003c/strong\u003e There is overall no correlation between spike weight and yield. Data shown as individual datapoints.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/667064741bcb417c7dd4e226.jpg"},{"id":97896179,"identity":"171a32d1-d24d-42af-89ab-89762c6364ae","added_by":"auto","created_at":"2025-12-10 15:36:01","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":145967,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWheat grain protein contents plateau at higher N rate than yield (A)\u003c/strong\u003e Wheat grain protein content (%) data shown as the mean ± se combined both 2017 and 2018 harvest, individual plot datapoint are also shown. \u003cstrong\u003e(B) \u003c/strong\u003eGrain protein content is negatively correlated with yield. Data are shown as BLUEs at 140 kg N. ha\u003csup\u003e-1\u003c/sup\u003e. \u003cstrong\u003e(C)\u003c/strong\u003e Kernel \u003csup\u003e15\u003c/sup\u003eN excess, as indicator of post-anthesis nitrogen uptake (PANU) measured for four wheat varieties under two N application levels in 2018. Data shown as mean ± se for one plant per plot and for each of the four replicates plots. \u003cstrong\u003e(D) \u003c/strong\u003eThe kernel \u003csup\u003e15\u003c/sup\u003eN excess is negatively correlated with the kernel N content at the time of measurements. Data shown as individual data point and linear model for the regression.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/7bb42ee0715a45c0e7d294d1.jpg"},{"id":97765111,"identity":"7817ad2a-7753-4e45-86a5-8d6622b55d66","added_by":"auto","created_at":"2025-12-09 06:59:41","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":110319,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePot based post-anthesis N uptake measurements. (A) \u003c/strong\u003e\u003csup\u003e15\u003c/sup\u003eN excess was measured in the kernel, flag leaves and roots of wheat plants grown under controlled conditions and exposed to \u003csup\u003e15\u003c/sup\u003eN labelled ammonium nitrate. \u003cstrong\u003e(B) \u003c/strong\u003eKernel N content. \u003cstrong\u003e(C) \u003c/strong\u003eThe kernel \u003csup\u003e15\u003c/sup\u003eN excess is negatively correlated with the kernel N content at the time of measurements. Data shown as individual data point for 5 biological replicates and linear model for the regression.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/a35669b7043c3de04bfba817.jpg"},{"id":97902800,"identity":"a3f54631-88b6-4cef-8c42-bb4308522057","added_by":"auto","created_at":"2025-12-10 15:53:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2085855,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/48e3c0d9-385c-43c7-ba9d-31a0e4b9b5f1.pdf"},{"id":97765115,"identity":"542d19e4-61a1-4ff9-aa0a-62f016f77e33","added_by":"auto","created_at":"2025-12-09 06:59:41","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1234724,"visible":true,"origin":"","legend":"","description":"","filename":"EliteNResponsivenesssupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8261533/v1/44feffc57b126a1c4943d19a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Novel field-based approaches reveal wheat genotypic differences in nitrogen use efficiency and grain protein dynamics","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNitrogen (N) is an essential macronutrient for plant growth and tends to be limiting plant primary productivity in all ecosystems except deserts (LeBauer and Treseder \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The widespread availability of synthetic N fertiliser, made possible through the development of the Haber-Bosch process, has sustained crop yields in many production regions across the globe over the last century (Erisman et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This industrial and chemical innovation and accompanying innovative agronomic practises, have been particularly important for cereal crops such as wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L.), which has a high N requirement. Concurrent advances in plant breeding led to the selection of short-strawed cultivars which were tolerant to lodging (physical displacement of stems) and more likely to allocate biomass towards the grain. Since then, wheat varieties have tended to be selected under high N inputs, which has driven increases in yield. In the UK, these have plateaued since the 1990s (Hawkesford \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) FAOSTAT, 2025). Agronomic N use efficiency (NUE), the ratio of yield produced per unit of available N, is often used to describe the impact of additional N fertilization on yield. However, the usefulness of the NUE term has been questioned (Swarbreck et al \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), since under recommended N application levels, NUE continues to remain quite low (Voss-Fels et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and is high under lower N availabilities (which also limit yield). Also, NUE does not account for the economic cost of increasing N applications, relative to yield, and it has recently been suggested that research should focus on N responsiveness: maximising yield relative to reduced N inputs (Swarbreck et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSoil available N is mostly taken up in the form of nitrate by wheat grown in temperate climates since it is the most available N source under those conditions (Kindred et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Assessing soil N availability to ensure optimal supply to the crop is difficult because of seasonal fluctuations due to soil microbial activity, leaching and denitrification. However, it is essential that growers adjust their fertiliser application rate while taking into account available N. The UK RB209 Nutrient Management Guide issued by the Agricultural and Horticultural Developmental Board (AHDB) in the UK provides information on how to estimate soil available N based on soil type and previous cropping regimes. Applications of higher levels of N fertiliser are often used to maximise yield, and in some cases to increase grain protein content. In the UK, wheat grown for bread making (belonging to the UK Flour Millers Group 1) tends to require higher N applications to achieve the requisite 13% grain protein content (GPC) which is accompanied by a price premium (N. S. Fradgley et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; N. Fradgley et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In order to reduce N inputs and losses due to run-off and volatilisation, studies are required to determine whether commercially available varieties could maintain yield quantity and quality at lower applied N levels (Swarbreck et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Tools are available to growers to adjust N application during the season such as measurements using NDVI (normalised difference vegetation index), or low-cost chlorophyll meters. In addition, the leaf colour chart which was developed initially at the International Rice Research Institute (IRRI) has been applied to in-season N recommendations for rice cultivation in India (Irri \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) and adapted for wheat (Varinderpal-Singh et al. 2012, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn North West Europe (especially France and the UK), many studies have evaluated the performance of winter wheat varieties under contrasting N levels over the past 5 decades. Some studies report differences amongst commercial varieties (Barraclough et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Barraclough, Lopez-Bellido, and Hawkesford \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) though varieties tend to respond more similarly (Morris N., Clarke S., Swarbreck S.M., Peters C. and Hague B. 2024; Morris, N., Hoad, S., Roberston, D. and Charlton, M. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recently released elite genotypes tend to be less efficient in acquiring soil N in the absence of supplementation from N fertiliser, (Foulkes, Sylvester-Bradley, and Scott \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), and may be better adapted to acquire N dispensed at specific stages in large doses and perhaps less dependent on microbial activities. For UKFM group 1 varieties, the requirement for high GPC adds to the N requirement although post-anthesis N uptake can lead to higher GPC (Bogard et al. 2010), providing a specific timepoint for intervention.\u003c/p\u003e\u003cp\u003eIn Europe, a total of 225 winter wheat varieties released between 1969 and 2010 (mostly released between 1985 and 2010) were tested under two N rates in four experiments (Cormier et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This uncovered significant Genotype (G) x N rate interactions for grain yield, GPC and NUE. The year of registration had a significant effect on G x N rate interaction for yield and NUE. Modern varieties had a G x N rate interaction that increased yield under high N, with a corresponding decrease under low N. These G x N rate interactions could be explained by variations in quality classes (more recent varieties tended to be higher yielding but had lower GPC and earlier flowering times). In a follow up study, tolerance indices were defined and used to identify specific QTL regions underpinning tolerance to low N (Mini et al. 2023). Overall, reports of varietal differences in yield under varied N levels have been noted. Farmers cannot simply assume that the performance of a wheat variety will be maintained at lower N and understanding the biological basis for these differences can inform selection of cultivars better suited to low input agriculture, and reduce N losses and emissions from more intensive systems or late fertiliser applications (Swarbreck et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, accounting for changing climatic conditions (winter flooding or low water recharge, summer drought) requires additional research to inform farmers on timing for optimal N fertilisation schedules.\u003c/p\u003e\u003cp\u003eThe aim of this study was to investigate the responses of modern elite wheat varieties, released between 1989 and 2014, selected across the 4 UKFM milling groups under contrasting N inputs. The set include varieties issued from Danish breeding programmes, which have been conducted under lower N availability compared to the UK. The use of a novel Opti-plot design allowed 6 contrasting N concentrations to be delivered to a specific variety within a single plot, across a replicated field experiment, with a modified combined harvester quantifying yields for each variety at each N level. The field trial was repeated over two contrasting growing seasons, 2016\u0026ndash;2018 with measurements of canopy development, chlorophyll content and soil N content, as well as \u003csup\u003e15\u003c/sup\u003eN uptake and utilisation post-anthesis.\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eOpti-plot field trials\u003c/h2\u003e\u003cp\u003eA total of 15 winter wheat commercial varieties were selected for field testing, representing UK commercially available lines from each of the four UK Flour Millers groups as well as varieties selected for the Danish market, where restrictions on N applications are in place (Petersen et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eList of winter wheat varieties included\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVarieties\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK/Denmark\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUKFM\u0026nbsp;Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYear of registration\u003csup\u003e1,2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClaire\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCordiale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrusoe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEvolution\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGrafton\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHereward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1989\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJB Diego\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRobigus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSiskin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkyfall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBelgrade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDenmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBenchmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDenmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMariboss\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDenmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTorp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDenmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Year of registration indicates year of completion of the statutory National Listing.\u003c/p\u003e\u003cp\u003eTwo field experiments were conducted in Stetchworth (Suffolk, UK) on different fields on the same farm in 2016/2017 (52\u0026deg;2180\u0026rsquo; N, 0\u0026deg;3707\u0026rsquo; E) and 2017/2018 (52\u0026deg;2125\u0026rsquo; N, 0\u0026deg;3721\u0026rsquo; E). The trial was drilled on 28th September 2016 and on 5th October 2017. Soil types were sandy loams. Climatic conditions throughout the growth period, including rainfall and temperature patterns, are presented in Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The total rainfall from 1st January until the 31st August was lower in 2017 (215.8 mm) compared to 2018 (387.4 mm). However, during the grain filling period post-anthesis (1st June- 15th August), the total amount of rainfall was much higher in 2017 (126.2 mm) compared to 2018 (54.8 mm). Trials in both years used the experimental field design (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), that held four blocks, each containing variety mainplots of 2m x 32m each, plus 2m x 32m \u0026lsquo;uniformity plots\u0026rsquo; at each end and in the centre of each block, flanked by 2m x 32m discard plots. Varieties were grouped and the groups were randomised in each block. N treatments ran across blocks in 4m strips, so that each 32m plot is split into eight 4m subplots. The central six N subplots included six N treatment (0, 70, 140, 210, 280 and 350 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) achieved through the application of ammonium nitrate granules (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), the subplot at each end of the plot were treated at 210 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e rate and discarded because it contained a tractor wheeling. The order of N treatments in each block was randomised, with the randomisation restricted such that adjacent N treatments did not differ by more than 2 N levels. All plots were planted at a seed rate of 350 seeds m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e and replicated in each block. A total of 52 winter wheat genotypes including 15 commercial varieties were tested and we present here the data from the commercial varieties only (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the first trial year, soil mineral N was measured on 26th January 2017 to be 75 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (soil analysis was completed at a commercial lab following BS EN 13652:200). Polysulphate was applied at a rate of 101.5 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e across the trial on the 10/03/17 to avoid S limitation (48.7 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e SO\u003csub\u003e3\u003c/sub\u003e, no N). In the second year, soil mineral content was measured on 30th January 2018 to be 25 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. A rate of 100 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e ammonium sulphate was applied across the trial 20/03/18 to avoid S limitation (21 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e N, 60 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e SO\u003csub\u003e3\u003c/sub\u003e). In each season, N was applied in three splits (details of the dates and N applied at each split is shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Field trials were managed following typical practices including application of fungicides, herbicides and pesticides. Grain yield for each individual N application level was measured by plot harvester (Sampo 2010) and expressed at 85% dry matter. Grain protein and moisture contents were measured using Near-Infrared Spectroscopy at a commercial lab.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eNDVI measurements\u003c/h3\u003e\n\u003cp\u003eNDVI measurements were conducted using a RapidScan CS-45 (Holland Scientific) on 2nd November 2016, 27th January 2017, 1st March 2017, 25th April 2017 and 1st of June 2017.\u003c/p\u003e\n\u003ch3\u003eShoot number at GS31\u003c/h3\u003e\n\u003cp\u003eThe number of shoots per plant was counted on ten uprooted plants from each sub-plot at GS31.\u003c/p\u003e\n\u003ch3\u003eGrab samples\u003c/h3\u003e\n\u003cp\u003ePre-harvest samples of 30 whole shoots were cut at ground level from each subplot at two N rates (0 and 210 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Samples were split into ears and straw and oven-dried at 80\u003csup\u003eo\u003c/sup\u003eC for 24 hours before weighing. The ears threshed to separate grain and chaff, and the grain re-dried and weighed. Samples of straw\u0026thinsp;+\u0026thinsp;chaff were analysed by Dumas for %N content. Plot yields were used to calculate grain, chaff and straw biomass (t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and N content (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e\n\u003ch3\u003eChlorophyll content and leaf measurements\u003c/h3\u003e\n\u003cp\u003eChlorophyll contents were estimated using a portable chlorophyll content meter (CCM-200 plus, Opti-Sciences, Hudson, USA) on 12 flag leaves from individual plants per sub-plot between 1st June 2017 and 21st June 2017 and on 8 plants per sub-plot between 5th June 2018 and 21st June 2018, around flowering time (after GS61). Assessments using the leaf color chart (LCC) were conducted over the same period in 2018 (Varinderpal-Singh et al. 2012, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePost anthesis nitrogen measurements\u003c/h2\u003e\u003cp\u003eFor a subset of varieties (Claire, Crusoe, Evolution and Siskin), post-anthesis nitrogen uptake was estimated using a \u003csup\u003e15\u003c/sup\u003eN isotopic method. In the field, a volume of 10mL of a 1mM \u003csup\u003e15\u003c/sup\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e15\u003c/sup\u003eNO\u003csub\u003e3\u003c/sub\u003e (\u003csup\u003e15\u003c/sup\u003eN\u003csub\u003e2\u003c/sub\u003e 98%, Cambridge Isotope Lab Inc.) solution was added to the base of one plant at milk stage (GS75) and one tiller of the targeted plant was collected after 2 days. Additional tillers from untreated plants were collected from each plot as control. Tillers were then dried at 75\u0026deg;C for 48h or until no further loss of weight could be measured. All samples were weighed, ground to a fine powder and analysed for isotopic ratio of \u003csup\u003e14\u003c/sup\u003eN/\u003csup\u003e15\u003c/sup\u003eN. Post-anthesis N uptake was estimated as the capacity of plants to take up \u003csup\u003e15\u003c/sup\u003eN over the 2-day labelling period.\u003c/p\u003e\u003cp\u003eIn a separate pot experiment, plants (varieties Claire, Crusoe and Siskin) were grown under controlled conditions with 16h photoperiod, 20\u0026deg;C day/18\u0026deg;C night, light intensity (200 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), in 1L pots on a 1:1 (v/v) mixture of sand and terragreen, supplemented with a modified Hoagland solution (Taulemesse et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Nutrient solution including 1mM KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, 1.5mM KNO\u003csub\u003e3\u003c/sub\u003e, 0.25mM Ca(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e, 4H\u003csub\u003e2\u003c/sub\u003eO, 2mM MgSO\u003csub\u003e4\u003c/sub\u003e, 7H\u003csub\u003e2\u003c/sub\u003eO, 3.25mM CaCl\u003csub\u003e2\u003c/sub\u003e, 3,5 mM 2H\u003csub\u003e2\u003c/sub\u003eO, 3.5mM KCl, 1mM NH\u003csub\u003e4\u003c/sub\u003eNO\u003csub\u003e3\u003c/sub\u003e, 10\u0026micro;M H\u003csub\u003e3\u003c/sub\u003eBO\u003csub\u003e3\u003c/sub\u003e, 0.7\u0026micro;M ZnCl\u003csub\u003e2\u003c/sub\u003e, 0.4\u0026micro;M CuCl\u003csub\u003e2\u003c/sub\u003e, 2H\u003csub\u003e2\u003c/sub\u003eO, 4.5\u0026micro;M MnCl\u003csub\u003e2\u003c/sub\u003e, 4H\u003csub\u003e2\u003c/sub\u003eO, 0.2\u0026micro;M MoO\u003csub\u003e3\u003c/sub\u003e and 50\u0026micro;M EDFS-Fe, was supplied every 2\u0026ndash;3 days. At GS75, a volume of 10mL of a 1mM \u003csup\u003e15\u003c/sup\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e15\u003c/sup\u003eNO\u003csub\u003e3\u003c/sub\u003e was provided to each pot. Samples were then collected. Roots were washed from the sand and terragreen. Grains were collected from the middle of the spike from the main tiller. Flag leaves were also collected from the main tiller.\u003c/p\u003e\u003cp\u003ePlant material was dried at 75\u0026deg;C for 48h, before grinding to a fine powder using a Tissue Lyser (Qiagen). Samples sealed in tin capsules were analyzed for percentage carbon, percentage nitrogen, \u003csup\u003e12\u003c/sup\u003eC/\u003csup\u003e13\u003c/sup\u003eC (δ\u003csup\u003e13\u003c/sup\u003eC) and \u003csup\u003e14\u003c/sup\u003eN/\u003csup\u003e15\u003c/sup\u003eN (δ\u003csup\u003e15\u003c/sup\u003eN) using a Costech Elemental Analyzer attached to a Thermo DELTA V mass spectrometer in continuous flow mode. The dried sample was carefully weighed (0.5mg) into a tin capsule, sealed and loaded into the auto-sampler (analyses conducted at the Godwin Laboratory, Department of Earth Sciences, University of Cambridge). Precision of analyses is better than 0.1\u0026permil; for \u003csup\u003e12\u003c/sup\u003eC/\u003csup\u003e13\u003c/sup\u003eC. Data are presented as \u003csup\u003e15\u003c/sup\u003eN excess, which was calculated based on measurements of δ\u003csup\u003e15\u003c/sup\u003eN and tissue N% as described in (Bandyopadhyay et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analysis of the field trial data was conducted in R and using the lme4 package. A linear mixed model was used to analyse the data: lmer(variable\u0026thinsp;~\u0026thinsp;Year * Variety * N Treatment + (1| Year:Block) + (1| Year:Block:Plot) + (1| Year:Block:Subplot). The term \u0026ldquo;(1| Year:Block)\u0026rdquo; was included to account for the block as a random effect, while \u0026ldquo;(1| Year:Block:Plot)\u0026rdquo; was included to account for plot within blocks as random effect (as each varieties is one plot) while \u0026ldquo;(1| Year:Block:Subplot)\u0026rdquo; was included to account for the fact that all N levels are on the same strip. Best Linear Unbiased Estimates and confidence intervals were calculated using the emmeans function from the emmeans package in R.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAll tested winter wheat varieties respond to increased N availability\u003c/h2\u003e\u003cp\u003eData are presented for the 15 wheat commercial varieties included in the trial grown, at six N levels (0, 70, 140, 210, 280 and 350 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) in an opti-plot field trial system (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) over two seasons (2016\u0026ndash;2017, 2017\u0026ndash;2018), with contrasting weather conditions (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All varieties showed a typical response to the provision of N fertiliser, with an initial clear increase in yield from 0 to 70 or 140 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Table S2). (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). For most varieties, the yield tended to plateau above 140 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, except for Cordiale which plateaued at 70 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The yield achieved in harvest year 2018 tended to be lower (reaching a maximum of 8.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) than that achieved in harvest year 2017 (reaching, a maximum of 11.7 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, Fig S2). While all varieties responded to the provision of N fertiliser, there were significant difference in yield amongst varieties at different N levels (Fig. S3A). Under no additional N supply, Siskin and Santiago showed significantly higher yield compared to Cordiale, Robigus, Crusoe and Hereward. Siskin remained a high yielding variety maintained at high N availability. Danish derived varieties, Belgrade, Torp and Mariboss were the top performers at low (70 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) N level. While there was overall good correlation between performance at 70 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 140 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, the varieties Claire and Siskin produced significantly higher yields under 140 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e than predicted for their performance at 70 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e yields (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). These appear as clear outliers relative to the regression line, which reflects a higher N responsiveness than observed for the remaining varieties.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eNUE decreases with increasing N application rate\u003c/h2\u003e\u003cp\u003eNUE was calculated as the ratio of yield per unit of available N (i.e. estimated as the sum of residual soil N and applied N). Overall, there was no significant difference between 2017 and 2018 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, lmer n.s.). The differences amongst varieties were significant at the lowest N rate (lmer, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and there was a significant interaction between variety and N treatment (lmer, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Santiago and Siskin showed the highest NUE, while Crusoe showed the lowest (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). NUE decreased with increased N availability (lmer, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). NUpE (defined as the ratio of total N uptake per unit of N available) also declined with the addition of N fertiliser (lmer, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and no significant differences amongst varieties could be measured (Fig. S4A) while the Nitrogen Harvest Index (proportion of N in the grain to the total N) remained similar between 0 and 210 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e treatments (Fig. S4B, lmer, \u003cem\u003en.s.\u003c/em\u003e).\u003c/p\u003e\u003cp\u003eGrain yield increased with the date of variety registration with more recent varieties showing higher yield overall (Fig. S5). However, in the absence of N fertiliser, the slope was lower (0.04 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e per year, compared to 0.06 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e per year under 70kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and the correlation was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07), compared to the other N application rates. With applied N rates above 210 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, the correlation tended to be greater than 0.6.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eNDVI is an indicator of N dependent yield increase\u003c/h2\u003e\u003cp\u003eNDVI measurements were conducted at five timepoints throughout the first trial season (November- GS13, January- GS23, March- GS25, April- GS31, and June- GS61) and identified significant differences between varieties at all time points except late in the season (June). NDVI values increased throughout the season indicating increased ground coverage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In April, a significant response to an increase in N availability was detected from 70 to 140 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). At this timepoint, there was a significant correlation between NDVI measurements and yield (Fig.\u0026nbsp;3B, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.48, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Overall, there was no significant interaction between varieties and N treatment. While most varieties showed a positive correlation between yield and NDVI measured in April, this was not the case for Cordiale (Fig. S6). It is worth noting that the correlation between yield and NDVI was strongest under lower N levels (Fig. S7).\u003c/p\u003e\u003cp\u003eLeaf greenness was measured using SPAD at flowering in both 2017 and 2018, and clearly increased with additional N availability (Fig. S8). The LCC was also used in 2018 to capture visible changes in leaf greenness (Fig. S8). Overall, there was good correlation between SPAD and LCC measurements (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eNitrogen dependent yield increase is linked to increased shoot number when rainfall is sufficient\u003c/h2\u003e\u003cp\u003eWheat yield is the product of grain number (grain number per spike and spike number) and grain weight. The number of shoots was higher in 2018 (ranging from a mean of 2.98 shoots per plant for Claire to a mean of 5 shoots per plant for Mariboss), compared to 2017 (mean of 2.21 shoots per plant for Hereward to a mean of 3.88 shoots per plant for Cordiale, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). There were significant differences in shoot number amongst varieties in both years (lmer, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and differences amongst varieties. These were generally higher in the wetter winter of 2018 (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), with Hereward and Claire showing a lower shoot number compared to other varieties (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). There was a positive, though weak, correlation between shoot number at GS31 and yield but only in the harvest year 2017 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.08, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and not in harvest year 2018 (\u003cem\u003en.s.\u003c/em\u003e), when there was a late drought following anthesis (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eSpike weight does not respond to increased nitrogen availability\u003c/h2\u003e\u003cp\u003eEar weight was not significantly affected by N level (lmer, n.s.) in both 2017 and 2018 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). There were significant differences amongst varieties in both years (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). While Mariboss generally showed lower spike weight compared to all other varieties (lmer, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Torp showed significantly higher spike weight (Fig. S9). The spike weight for Crusoe was also significantly higher compared to other varieties (lmer, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWheat grain protein content plateaus at higher N availability than yield.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAll varieties showed a clear response to the provision of N fertiliser, with an increase in GPC (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). For most varieties, GPC tended to plateau at 210 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which is a higher N level than the yield plateau. The overall GPC achieved in 2017 tended to be higher (range of 7.19\u0026ndash;14.39%) than that achieved in 2018 (range of 4.54\u0026ndash;12.15, Fig S2), again showing the impact of the late drought. While the N dependent yield and GPC increase showed a positive correlation (2017: R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.26, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; 2018 R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) overall, at each N level we observe the expected negative correlation between yield and GPC (Fig. S11).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003ePositive grain protein deviation is linked to post-anthesis N uptake\u003c/h2\u003e\u003cp\u003eThere was significant differences grain protein content amongst varieties (Fig. S10) as expected given their UKFM group. Some varieties showed positive grain protein deviation (GPD, representing an increase in grain protein content relative to yield, and hence positioned above the regression line in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB) including Siskin (also higher yielding) and Crusoe (lower yielding), while others showed a negative GPD (Claire and Evolution, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Positive GPD has been linked to increased post-anthesis N uptake (Bogard et al. 2010), and this was measured in the field using \u003csup\u003e15\u003c/sup\u003eN labelling (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). While there were no significant differences amongst varieties, there was increased post-anthesis N uptake under lower N supply (70 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) compared to higher N supply (280 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, lmer \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). A negative correlation between kernel N content and kernel \u003csup\u003e15\u003c/sup\u003eN excess was measured in the field, suggesting higher PANU potential in lower N-containing grains.\u003c/p\u003e\u003cp\u003eIn a separate experiment, PANU was measured in plants grown in pots under controlled conditions following a similar method of application of \u003csup\u003e15\u003c/sup\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e15\u003c/sup\u003eNO\u003csub\u003e3\u003c/sub\u003e to the growth substrate. Under these conditions, roots could be washed and analysed as well as the flag leaves and grains. Grains represented the largest store of \u003csup\u003e15\u003c/sup\u003eN post-anthesis while very little \u003csup\u003e15\u003c/sup\u003eN remained in the flag leaf (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Under these conditions, a significant difference was recorded, with positive GPD varieties (Crusoe and Siskin) showing higher PANU compared to Claire which has negative GPD (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Overall, there was also a negative correlation between grain N content at the time of analysis and PANU as measured through \u003csup\u003e15\u003c/sup\u003eN excess (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC), consistent with the field data.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBalancing the need for wheat production for food and feed with environmental impact associated with modern fertiliser inputs is a challenge that requires continued investigation, especially in the context of seasonal variations in water supply and drought associated with climate change. Here we report the response of elite winter wheat cultivars from Northern European breeding programmes (all released in the last 25 years) to N rates ranging from 0 to 350 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. There was a clear positive effect of N application on the yield of all cultivars tested, while some varietal differences could be measured. NUE showed a strong decline under even modest N application for all varieties. We show that the N-dependent yield increase is linked to an increased spike number, rather than spike weight, thus identifying a possible mechanism for N responsive yield increase and a target for crop breeders.\u003c/p\u003e\u003cp\u003eField trials across the broad range of N application rates used here are unusual because of the technical complexity. Unless wheat is grown under organic farming practices (Przystalski et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), some level of N is added which makes the level 0 in our study unique. At the other end of the spectrum, applying 350 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is not economically viable for farmers (except where fertiliser is heavily subsidised) and results in environmental losses. However, assessing diverse wheat cultivars under this range of N applications rate is valuable as it allows precise quantification of their N responses. The opti-plot testing approach used here allows for testing of 6 N levels with sufficient plot sizes to allow for reliable agronomic assessment of crop growth and grain yield. The plots and treatment are arranged to ensure some level of randomisation and reduces the likelihood of impact from high N sub-plots onto low N sub-plots. Yield of all varieties tested tended to plateau at 140 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, in both 2017 and 2018 even though climatic conditions (late drought) which probably limited yield in 2018.\u003c/p\u003e\u003cp\u003eAll varieties tested here showed a clear increase in yield under higher N availability. Since the varieties had all been selected for and commercialised in the last 25 year, this is expected. Modern wheat cultivars tend to show higher yield responses under high N availability compared to older (and taller) varieties (Ortiz-MonasterioR et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). We also noted increases in yield at all N levels related to the year of registration which, and this is in-line with similar analyses conducted on German wheat germplasm (Voss-Fels et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We also found that the positive correlation was more apparent under higher N level (Fig.S5), suggesting that perhaps selecting under lower N levels would lead to greater genetic gains for performance under lower N. While all varieties tended to respond to the same level, selected varieties (Siskin and Claire, Fig. S3) showed a greater than expected N responsiveness suggesting that this is a trait that has not yet been maximised for all commercially released varieties. N responsiveness is the capacity of plants to respond to increased N availability. We argued that varieties showing higher N responsiveness should be a selection marker, as this trait is linked to the molecular signalling associated with plant N uptake and mobilisation (Swarbreck et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The response for Cordiale to higher N was lower, and we propose this to be linked to its early flowering phenology (Fig. S12), which may have resulted in mis-timed N fertiliser application. It is worth noting that Danish varieties performed well under 70 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, though their overall NUE was not particularly improved compared to varieties selected through breeding programmes in the UK (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). However, they are able to achieve high yields using different strategies as Mariboss showed a very low spike weight that was compensated by greater spike numbers.\u003c/p\u003e\u003cp\u003eAlthough NUE does not effectively capture the economic costs associated with N application (which makes N responsiveness such a useful metric), we confirmed that it was much greater under lower N availability, in line with other studies (Voss-Fels et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The higher NUE under no fertiliser application can be associated with either increased NUpE (the ratio of total N uptake per unit of N available) or NUtE (yield per unit of N taken up by the plant). Higher NUpE can be achieved under no additional N application when microbial dependent N sources become more important (King et al., 2001). Under no additional N application, soil processes can be improved or increase recruitment of beneficial microbes, which tend to be inhibited at elevated N availability (Oldroyd and Leyser 2020). In our study, we could see a similar pattern of increase NUpE under low N but no change in NHI (grain N content relative to above-ground plant N) suggesting that increased uptake efficiency underpins the higher NUE without any fertiliser application. This supports the finding that in a study of French wheat varieties (historical, pre-Green Revolution and more recent varieties) grown under two levels of N (no addition, and 170 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e addition), NUpE accounted for more of the variation of NUE for grain yield at N0 than under N fertilisation (Le Gouis et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Under low N, wheat plants can develop more extensive root systems to explore and exploit a larger soil volume and access a higher proportion of soil available N (Smith and De Smet 2012; Aziz et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Finch et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIt is interesting that differences in grain yield, hence NUE, amongst varieties are very strong at N0. It is often thought that plants need to be grown under optimal/high N rate to see differences amongst varieties and enable efficient breeding. However here, the strongest differences were seen at lower N level. Perhaps it is because these varieties were selected under generally higher N levels that no differences amongst variety specific NUE can be observed at high N levels. This raises the potential of including reduced N level screening in selection of germplasm in breeding and assessment of commercial varieties in the UK (Morris N., Clarke S., Swarbreck S.M., Peters C. and Hague B. 2024) as is done in other countries such as France.\u003c/p\u003e\u003cp\u003eYield is a complex trait that includes grain size and grain number (which itself is dependent on spike number and number of grains per spike). Here we show that spike number varies amongst varieties and is correlated with grain yield, although only under sufficient moisture (2017). Our data show a similar pattern to data from foxtail millet (Bandyopadhyay et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) where N-dependent yield increased is underpinned by increases in grain number rather than grain size. This lack of increase in grain weight under increasing N level is also noted as spike weight remained stable at all six N levels in both trial years of the experiments. It remains to be seen whether improving individual grain size response to increased N may lead to further yield increase under higher N availability. Danish varieties Torp and Mariboss adopted contrasting strategies to achieve high yield. Torp showing higher spike weight compared to Mariboss under all N levels, and lower spike numbers.\u003c/p\u003e\u003cp\u003eIn our study, N dependent GPC tended to plateau at higher N application rates than yield. GPC of varieties was also negatively correlated with their yield. However, when yield increase is driven by increasing N, there is an overall positive correlation between yield and GPC. It is only at each N level, that a negative varietal correlation was noted. From this analysis, we could identify varieties with higher yield such as Evolution and Siskin, and varieties with lower yield such as Claire and Crusoe. In terms of grain protein content relative to yield (GPD), both Crusoe and Siskin showed positive GPD while Claire and Evolution showed negative GPD. Such data provides a basis for crop breeders to select varieties with enhanced yields in association with more sustainable N inputs.\u003c/p\u003e\u003cp\u003ePost-anthesis N applications are often used to enhance GPC and nudge grain quality towards UKFM bread-making requirements. Using an \u003csup\u003e15\u003c/sup\u003eN based method we were able to measure post anthesis N uptake (PANU) at a specific time point and showed overall a lower PANU (expressed as \u003csup\u003e15\u003c/sup\u003eN kernel excess) at higher N rates. This is a novel method for measuring PANU, as previous reports included estimating the total N content in the grain and straw at maturity in comparisons with the total plant N at anthesis (Nehe et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Our \u003csup\u003e15\u003c/sup\u003eN based measurement is useful as it allows temporal resolution of PANU. This trait remains quite poorly understood and somewhat goes again the general concept that N in the grain is derived from the remobilisation from vegetative tissues. However, it was shown to be particularly relevant to the improvement of GPC (Bogard et al. 2010). While no varietal differences could be noted in the field, under controlled conditions (well watered) there was significant differences, with varieties showing positive GPD also showing higher PANU. Our findings that under higher N availability PANU declines are in agreement with a previous report (Taulemesse et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), which also suggested a key role for the high affinity nitrate transporter \u003cem\u003eTaNRT2.1\u003c/em\u003e. There is a need for further exploration of the genetic basis for PANU, especially in terms of regulation by plant-N status and contribution from remobilisation of existing N assimilates. Our data suggest that grain N content itself is correlated with PANU but the nature of the signalling mechanism from grain N status to root uptake is not known currently.\u003c/p\u003e\u003cp\u003eFrom an agronomic and crop breeding perspective, the novel opti-plot approach, combining a wide range of N availabilities across two contrasting years in the field has provided insights for the traits that underpin higher performance in these conditions. Given the low level of genetic diversity amongst commercial wheat varieties in the UK, evaluating these under an extensive range of N level enables resolution of their N response differences, with a view to the selection of varieties which sustain yield and grain quality at lower N inputs. Our work also demonstrated that measurements of NDVI (and other low technology solutions, such as the LCC) throughout the season, and especially at GS31, provided a good indication of overall yield. However, climatic conditions in both years contributed to overall yield and grain quality, whether in terms of lower tillering in a dry winter (2017) or a reduction in spike productivity in a late season drought. These findings are a step towards providing farmers with a clearer understanding of how changing climatic conditions can alter the effectiveness of late N applications, whether in terms of enhancing GPD or recovering the financial cost of the additional inputs. In future, such an economic N optimum will need to be associated with individual crop varieties, and more sustainable farming practices, which minimise N losses and maximise grain yield and quality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eWe thank BBSRC (BB/N013441/1: Cambridge-India Network in Translational Nitrogen CINTRIN), the Newton-Bhabha Trust Fund and Department of Biotechnology (India) for funding (Grant No.: BT/IN/UK-VNC/42/RG/2014-15).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDK, RSB, HG and AB acquired the funding and designed the experiments. AL, SR and SMS acquired and analysed the data. SMS conducted further data analysis and interpreted the data together with AB and HG. SMS, AB and HG wrote the manuscript with contributions from RSB.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eRainfall and temperature data were provided by KisanHub. The authors would like to thank members of the CINTRIN project for interesting discussions. The authors would also like to acknowledge Dr Tally Wright and Dr Greg Deakin for support in statistical analyses, and the trial team at ADAS.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAziz, Moyassar M., Jairo A. Palta, Kadambot H. M. Siddique, and Victor O. Sadras. 2017. \u0026ldquo;Five Decades of Selection for Yield Reduced Root Length Density and Increased Nitrogen Uptake per Unit Root Length in Australian Wheat Varieties.\u0026rdquo; \u003cem\u003ePlant and Soil\u003c/em\u003e 413 (1): 181\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBandyopadhyay, Tirthankar, Jyoti Maurya, Alison R. 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Using Leaf Colour Chart.\u0026rdquo; \u003cem\u003eField Crops Research\u003c/em\u003e 130 (March): 109\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVoss-Fels, Kai P., Andreas Stahl, Benjamin Wittkop, Carolin Lichthardt, Sabrina Nagler, Till Rose, Tsu-Wei Chen, et al. 2019. \u0026ldquo;Breeding Improves Wheat Productivity under Contrasting Agrochemical Input Levels.\u0026rdquo; \u003cem\u003eNature Plants\u003c/em\u003e 5 (7): 706\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-sustainable-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Sustainable Agriculture](https://www.nature.com/npjsustainagric/)","snPcode":"44264","submissionUrl":"https://submission.springernature.com/new-submission/44264/3","title":"npj Sustainable Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8261533/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8261533/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAchieving high yield and grain quality in wheat typically requires the application of substantial amounts of nitrogen (N) fertiliser. However, given economic and environmental constraints, it is critical to understand whether growers can reduce N inputs without compromising performance, and whether existing varieties differ in their ability to cope with lower N availability. Using a novel field-based experimental platform, we assessed the performance of fifteen registered wheat varieties under six N regimes and over two seasons with contrasting weather patterns. As expected, yields and grain protein contents both increased with N application, although protein content plateaued at a higher N threshold than yield. We noted higher genotypic differences in N use efficiency (NUE; defined as yield per unit of available N) under zero- N fertiliser applications, revealing intrinsic variation in low-N resilience. N-driven yield increase was more strongly associated with spike number rather than spike weight. Two varieties selected in Denmark where tight regulations on N applications are applied were included for comparison and could achieve high yield with contrasting strategies; one with low and the other with high spike weight. In addition, using a novel stable isotope field-based method, we could show that under higher N levels, the post-anthesis N uptake was decreased and this trait is critical to achieving positive grain protein deviation (higher increase in grain protein content than expected given its yield). Our findings highlight the necessity of evaluating commercial and pre-breeding wheat germplasm under reduced N conditions to identify genotypes suited to sustainable, lower-input agricultural systems in a changing climate.\u003c/p\u003e","manuscriptTitle":"Novel field-based approaches reveal wheat genotypic differences in nitrogen use efficiency and grain protein dynamics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-09 06:59:36","doi":"10.21203/rs.3.rs-8261533/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-23T00:01:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-21T17:12:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-10T13:19:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82657810110872554506279266662134996623","date":"2026-01-29T15:39:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77507967881646567956954658443579609490","date":"2026-01-28T10:16:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137537906958526650290738346015925726251","date":"2026-01-27T08:01:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-23T12:10:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"206756474858175604056055597733386418444","date":"2025-12-05T09:06:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195486628508060137488158422177045256842","date":"2025-12-05T08:41:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-05T08:32:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-05T05:39:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-05T02:59:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Sustainable Agriculture","date":"2025-12-02T14:01:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-sustainable-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Sustainable Agriculture](https://www.nature.com/npjsustainagric/)","snPcode":"44264","submissionUrl":"https://submission.springernature.com/new-submission/44264/3","title":"npj Sustainable Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"72836c7f-6e02-42a8-adbc-a8432ddd51b8","owner":[],"postedDate":"December 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":59260111,"name":"Biological sciences/Genetics"},{"id":59260112,"name":"Biological sciences/Plant sciences"}],"tags":[],"updatedAt":"2026-05-19T22:53:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-09 06:59:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8261533","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8261533","identity":"rs-8261533","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}