Winter rye root growth and plasticity in response to nitrogen and phosphorus omission under field conditions

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Seidel, John Kormla Nyameasem, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6328255/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Dec, 2025 Read the published version in Plant and Soil → Version 1 posted 6 You are reading this latest preprint version Abstract Aims. We investigated the effects of N and P deficiencies on winter rye growth and root architecture under field conditions. Methods. Sampling was conducted during the 2022 season at the long-term fertilizer experiment Dikopshof, Germany. Four fertilizer treatments were chosen: (1) fully fertilized including manure (m) and supplemental mineral fertilizer (s) (NPKCa + m + s), (2) fully fertilized without manure (NPKCa), (3) N omitted (_PKCa), and (4) P omitted (N_KCa). Shoot biomass and topsoil root biomass, number of tillers, nodal root number, root angle, root length density (RLD), specific root length (SRL), and root diameter were assessed at five growth stages. Results. We found that that grain yield, shoot, and root biomass were highest in the NPKCa + m + s treatment and lowest under N omission. Around flowering, a trend for an enhanced root number in the N and P omission treatments was observed. At the same sampling date, the NPKCa + m + s treatment showed significantly higher SRL than the P omission treatment. The RLD increased for all treatments from date 1 to 4, with NPKCa + m + s and N omission treatments showing the highest and lowest RLD, respectively. At the onset of stem elongation, N and P omission led to a significant reduction in average root diameter, P omission promoted higher tiller number and N omission caused steeper root angles. Conclusions. These findings demonstrate the strong impact of management, environment and developmental stage on root phenotypic plasticity. shoot growth root growth root:shoot dry mass ratio crop yield nutrient stress Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Nitrogen (N) and phosphorus (P) are critical nutrients that are central to crop productivity, with N being key for amino acid and protein synthesis, while P is essential for energy transfer, photosynthesis, and structural development (Uga et al., 2015 ). However, the availability of these nutrients is often limited in agricultural soils, which can result in reduced crop yields and grain quality (Hammer et al., 2009 ). Addressing these constrains requires improved crop nutrient use efficiency to tackle the challenges of global food security and environmental sustainability. Enhancing the functional plasticity of root systems emerges as a key approach to improve nutrient acquisition and crop performance under resource-limited conditions. Many studies reported the belowground interactions occurring in the rhizosphere. The root system architecture—comprising traits such as root biomass, length, diameter and angle—is key to exploring soil and acquiring nutrients (Lynch, 1995 ; Lynch, 2019 ). Environmental factors, including microbiome activity, soil water availability, soil compaction, salinity, nutrient distribution but also the crop management further influence root growth dynamics, modulating root system depth, root angle, and nutrient and water uptake efficiency (Correa et al., 2019 ; Hecht et al., 2016 ; Manschadi et al., 2008 ; Oyanagi et al., 1993 ; Yu et al., 2021 ). Recent studies highlight strategic adjustments in root growth patterns that enable plants to optimize resource use efficiency in sub-optimal environments (Lynch, 2019 ). For instance, the root angle is a main determinant of root placement within the soil profile. Steeper root angles promote deeper soil penetration, enhancing access to mobile resources like nitrate and water under drought or low N conditions (Schneider et al., 2022 ; Trachsel et al., 2013 ). Conversely, shallower root angles facilitate topsoil exploration, improving the acquisition of immobile nutrients such as phosphorus (Bonser et al., 1996 ; Liao et al., 2001 ; Lynch & Brown, 2001 ). Moreover, root mass is an important trait for carbon storage and its sequestration (Kätterer et al., 2011 ; Poeplau & Don, 2015 ). A recent study showed that under N deficiency, root length and root biomass decreased by 9% and 7%, respectively, but root length per shoot biomass increased by 33%, alongside a 44% enhancement in the root:shoot (RS) ratio, reflecting carbon allocation strategies for nutrient foraging (Lopez et al., 2023 ). Root length density is linked to aggregate stability (Hudek et al., 2022 ) as well as water and nutrient acquisition (Tajima, 2021 ). Root diameter is also considered an important trait affecting nutrient acquisition (Perkons et al., 2014 ), for instance, in dicotyledonous plants, taproots with thicker diameters can penetrate compacted soil more easily than smaller root diameters (Materechera et al., 1992 ), enhancing the nutrient acquisition efficiency under sub-optimal conditions. Another important root morphological trait is the specific root length (SRL), defined as root length per root mass, which is an indicator of the root soil exploration capacity (Freschet et al., 2021 ). The SRL can also be linked with nutrient uptake efficiency (Eissenstat, 1992 ; Isaac & Borden, 2019 ; Kemper et al., 2023 ). Research shows that crops with increased SRL have long and thin roots and are less expensive to produce (Ostonen et al., 2007 ). Root phenotyping is often conducted under controlled environments, as it provides a greater likelihood of reproducible root phenotypes compared to field phenotyping. However, transferability of plant responses from controlled environments to field conditions remains a challenge (Langstroff et al., 2022 ). Therefore, field phenotyping remains a critical component in particular for root traits that are expressed at later stages of plant growth or in deeper soil layers (Tracy et al., 2020 ). Long-term fertilizer experiments (LTFE) serve as an important platform for research (Seidel et al., 2021 ); however, studies mostly focus on the above-ground traits as affected by fertilizer omission, often neglecting the specific impacts of nutrient omissions on root system architecture under field conditions (Lopez et al., 2023 ; Siddiqui et al., 2021 ). Renowned for its adaptability to nutrient-poor soils and challenging growing environments, winter rye ( Secale cereale ) serves as an excellent model for investigating root-shoot interactions under nutrient stress (Arsova et al., 2020 ). Compared to wheat, rye has demonstrated more vigorous early vegetative growth (Paponov et al., 1999 ), higher radiation use efficiency (RUE) (Sieling et al., 2016 ), and greater frost tolerance (Griffith et al., 1992 ; Limin & Fowler, 1991 ), all of which contribute to its resilience under sub-optimal conditions. A key factor behind the superior performance of rye is its highly developed root system, which facilitates efficient nutrient and water uptake, allowing it to thrive in marginal soils (Dittmer, 1937 ; Kaye et al., 2019 ). Despite this potential, the role of rye roots in nutrient acquisition and stress adaptation remains largely unexplored. Given that rye is a widely produced crop in Europe (European-Commission, 2024 ), the lack of studies on root phenotyping highlights a significant research gap (Comas et al., 2013 ; Takahashi & Pradal, 2021 ). Investigating rye’s root system architecture is a unique opportunity to understand how root traits respond to varying nutrient availability during the growth period. This study aims to fill this knowledge gap on rye responses to nutrient deficiency by investigating the effects of N and P deficiency on root and shoot traits of winter rye cultivated at a LTFE. By examining morphological root and shoot trait adaptations on various dates from tillering to anthesis, the study seeks to provide valuable insights for developing crop management and breeding strategies to improve productivity and resilience in nutrient-limited environments. Materials and Methods Experimental design A sampling campaign was conducted in 2022 at the long-term fertilizer experiment (LTFE) Dikopshof near Cologne, Germany (50.8079 N, 6.9529 E, 62 m a.s.l.). The experiment was established in 1904, with a 5-year crop rotation currently including sugar beet ( Beta vulgaris ), winter wheat ( Triticum aestivum L.), winter rye, persian clover ( Trifolium resupinatum L.), and potato ( Solanum tuberosum L.). The general soil type is classified as a Haplic Luvisol derived from loess above sand with a silty loam (topsoil) and (silty) clay loam (below 30 cm soil depth). The experiment is a non-randomized block design without replicates and comprises seven treatments: NPKCa + m + s ("+m" stands for farmyard manure fertilization and "+s" stands for supplemental mineral fertilization), NPKCa, _PKCa, N_KCa, NP_Ca, NPK_, and no fertilizer (the "_" stands for the omission of the corresponding nutrient, "Ca" stands for lime). After harvesting the preceding crop, cattle farmyard manure is supplied on sugar beet, potato, and winter rye plots at a total rate of 60 t ha − 1 per five-year rotation (fresh matter, treatments "+m"). The fertilizer management has not changed since 1953, except for a slight increase of the N fertilizer treatment (+ 30 kg N ha − 1 ) on winter wheat in some treatments, which occurred in the 1980s. For further details about the field experiment refer to Seidel et al. ( 2021 ). Crop management After farmyard manure application on 31/10/2021 and ploughing on 07/11/2021, winter rye cultivar Tribiano KWS was sown on 09/11/2021. Mineral P and N were applied on 28/03/2022 and the second N-fertilization (only NPKCa + m + s) was applied on 10/05/2022 (around BBCH 55). Harvest was on 27/07/2022. Shoot and root measurements Four treatments were considered in this study: Fully fertilized plus manure (NPKCa + m + s), fully fertilized with mineral fertilizer only (NPKCa), N omission (_PKCa), and P omission (N_KCa). Winter rye shoot biomass was estimated destructively on five dates (16/03, 04/04, 29/04, 27/05, and 21/06) from early tillering to end of flowering (BBCH stages 22–24, 30, 41–43, 56–58 and 69, respectively) by cutting four times 50 cm of a row. Simultaneously, manual soil coring using a 1 m auger with a 9 cm inner diameter, was conducted in each of the cut rows to sample the roots in the ploughed soil top layer (0–30 cm). Roots per auger were then carefully cleaned with tap water. For the current study, measured shoot and root traits included number of tillers, number of nodal roots, root angle, the specific root length (SRL), root length density (RLD), average diameter and root length per diameter class. The nodal root angles, number of tillers, and the number of nodal roots emerging from shoot tissue (root number) were estimated manually for all plants. The angular spread of the roots was defined as the deviation angle of the two most horizontally distant shoot roots (180° would be roots at soil surface, Figure S1 ). The samples were then sieved (2 mm and 0.63 mm) and sorted to remove the debris. The roots were then scanned with a flat-bed scanner (Expression 12000XL, Epson, Suwa, Japan). To avoid overlapping during the scanning, samples with abundant roots were divided into sub-samples. Images were then analyzed with WinRhizo 2016a software (Régent Instruments Inc., Quebec, QC; Canada) to estimate the SRL (cm), the RLD, (cm cm − 3 soil), average diameter (mm) and root length (cm) for each diameter class. Table 1 presents the equation for the SRL and RLD calculations. The RLD was calculated for the top 30 cm soil as the ploughed layer (Table 1 ). The dry matter root biomass (g m − 2 ) was calculated using the equation in Table 1 by considering the surface area of the auger cylinder. While specific root length (SRL) was also calculated based on the top 30 cm soil sample (Table 1 ). Table 1 Equations and units for the calculated root morphology parameters for winter rye fertilizer omission experiment at Dikopshof. Root parameter Unit Equation Root biomass 1 g m − 2 \(\:\text{R}\text{o}\text{o}\text{t}\:\text{b}\text{i}\text{o}\text{m}\text{a}\text{s}\text{s}=\frac{\text{R}\text{o}\text{o}\text{t}\:\text{m}\text{a}\text{s}\text{s}\:\text{f}\text{o}\text{r}\:\text{t}\text{h}\text{e}\:\text{p}\text{l}\text{o}\text{u}\text{g}\text{h}\text{e}\text{d}\:\text{l}\text{a}\text{y}\text{e}\text{r}}{\text{S}\text{u}\text{r}\text{f}\text{a}\text{c}\text{e}\:\text{a}\text{r}\text{e}\text{a}\:\text{o}\text{f}\:\text{c}\text{y}\text{l}\text{i}\text{n}\text{d}\text{e}\text{r}\:}\) Specific root length m g − 1 \(\:\text{S}\text{R}\text{L}=\:\:\:\frac{\text{R}\text{o}\text{o}\text{t}\:\text{l}\text{e}\text{n}\text{g}\text{t}\text{h}\:\text{i}\text{n}\:\text{t}\text{h}\text{e}\:\text{p}\text{l}\text{o}\text{u}\text{g}\text{h}\text{e}\text{d}\:\:\text{l}\text{a}\text{y}\text{e}\text{r}}{\text{R}\text{o}\text{o}\text{t}\:\text{m}\text{a}\text{s}\text{s}\:\text{f}\text{o}\text{r}\:\text{t}\text{h}\text{e}\:\text{c}\text{o}\text{r}\text{r}\text{e}\text{s}\text{p}\text{o}\text{n}\text{d}\text{i}\text{n}\text{g}\:\text{l}\text{a}\text{y}\text{e}\text{r}}\) Root length density cm cm − 3 \(\:\text{R}\text{L}\text{D}=\:\:\:\frac{\text{R}\text{o}\text{o}\text{t}\:\text{l}\text{e}\text{n}\text{g}\text{t}\text{h}\:\text{i}\text{n}\:\text{t}\text{h}\text{e}\:\text{p}\text{l}\text{o}\text{u}\text{g}\text{h}\text{e}\text{d}\:\:\text{l}\text{a}\text{y}\text{e}\text{r}}{\text{S}\text{o}\text{i}\text{l}\:\text{v}\text{o}\text{l}\text{u}\text{m}\text{e}\:\text{o}\text{f}\:\text{t}\text{h}\text{e}\:\text{l}\text{a}\text{y}\text{e}\text{r}}\) 1 Depth of ploughed layer = 30 cm. After scanning and image analysis the roots were then dried in the oven at 50°C and weighted using Sartorius ENTRIS 4231 fine scale with 0.001 g level of precision (Sartorius Lab Instrument GmbH & Co, Goettingen, Germany) to derive dry matter root biomass and determine C and N tissue content. To facilitate analysis, the root length was additionally categorized into six classes ranging from 0.75 mm diameter, with equal intervals of 0.15 mm, where L1 was the lowest and L6 was the highest root diameter, respectively (Table 2 ). Table 2 Root diameter classification ranges. Diameter class Description L1 0.75 mm Soil nutrient and water sampling and monitoring Four soil samples per treatment at each sampling date were collected from the ploughed topsoil (0–30 cm) with a Pürkhauer auger with an 18 mm-diameter. The samples per treatment were then pooled together and frozen. After thawing, the soil was analyzed for mineral N content (N min ) by extraction with potassium sulfate solution (VDLUFA, 1991 ). The N min concentrations in the extracts were measured by a Skalar Continuous Flow Analyser (Skalar Analytical B.V., Breda, Netherlands). The plant-available P (P cal ) and K (K cal ) were determined using a calcium acetate calcium lactate extract as described by Schüller ( 1969 ). The P concentration in the extracts was determined colorimetrically following molybdenum blue reaction (Murphy & Riley, 1962) on a spectrophotometer (Specord 205, Analytik Jena, Germany). Around flowering, when root systems of cereals commonly achieve their maximum root growth, volumetric soil water content at 3, 30 and 60 cm soil depth was measured using the FDR moisture sensor HH2 within ML3 Theta Probe (ecoTech Umwelt-Meßsysteme GmbH, Bonn, Germany) at winter rye flowering on 27/05/2022. Statistical analysis The collected data were analyzed using the R software (version 4.1.1), although the replicates are pseudo replicates (i.e. sub samples) due to the old experimental set up. A mean comparison test was carried out for all measurements, using the sub samples collected at each plot. Data normality was tested by sampling date by using the Shapiro wilk test. The log10 or negative square root data transformation was used when data was non-normally distributed. For the normally distributed data, a one-way analysis of variance (ANOVA) was conducted. Multiple comparisons between treatments were performed using the Tukey's test (Tukey test, P > 0.05). When data was not normally distributed, and data transformation was unsuccessful, an Aligned rank transform factorial ANOVA for non-parametric data was used by implementing the ARTool package (version 0.11.1). Finally, the ggcorr function in R was used to visualize the correlation coefficients between the shoot and root variables in a correlation matrix. To assess the relationships between key aboveground and belowground traits, we performed a Pearson correlation analysis. This analysis was conducted using the cor.test function in the stats package in R. To visualize the correlation matrix and identify significant relationships, we used the corrplot package for graphical representation of the correlation coefficients. Results Overall, N and P omission treatments significantly affected root and shoot biomass as well as root traits during the season. For the shoot biomass, treatment differences became more apparent during the last sampling dates, similarly as for root biomass. Fertilizer treatments significantly affected root morphological traits, with greater variation observed among the different treatments. Soil conditions The NPKCa + m + s resulted in the highest soil N min , K cal , and P cal contents during all sampling dates (Fig. 1 ). While soil P cal and K cal content were the lowest in the N_KCa treatment. As expected, the soil N min was the highest in the NPKCa + m + s treatment with the highest values observed in the first (29.14 mg kg − 1 ) and last (27.61 mg kg − 1 ) sampling dates, but declined in the second and third sampling dates (Fig. 1 ). The rest of treatments showed considerably lower N min values as well as a tendency to decrease as the season progressed. The soil N min values were lowest for _PKCa in all dates. For soil water content, the volumetric water content data collected around flowering on 27/05/2022, showed non-significant differences at the top 3 cm (Figure S2). However, at 30 cm, the N omission treatment resulted in the highest soil moisture at ~ 20%, followed by the P omission and NPKCa treatment. At 60 cm, most treatments resulted in non-significant differences, except for NPKCa + m + s, which showed the strongest decrease in soil moisture, suggesting more water uptake in the top layers, which reduced the supply to the deeper layer (Figure S2). Shoot biomass Fertilizer treatments significantly affected shoot biomass over the season (Fig. 2 ). The shoot biomass was significantly higher in the NPKCa + m + s treatment during all the sampling dates, with values ranging from 32.94 g m − 2 at sampling date 1 to 2,123 g m − 2 at sampling date 5 (Fig. 2 ). In contrast, the N omission led to the lowest shoot biomass among all treatments during the last two dates. In the last sampling date, differences became less apparent with even the NPKCa treatment showing similar shoot biomass to the NPKCa + m + s, while N_KCa and _PKCa treatments showed the lowest shoot biomass with non-significant differences between them. Root biomass Fertilizer treatments also affected root biomass in different magnitudes, over all the sampling dates (Fig. 2 , Table S1 ). Root biomass at the first and the third sampling dates showed non-significant differences. In sampling date 2, the NPKCa + m + s treatment led to the highest root biomass, but differences became less apparent in the later sampling dates. The N omission treatment often led to the lowest root biomass among treatments across sampling dates, while the P omission treatment resulted in the same root biomass as the NPKCa treatment in sampling dates 4 and 5 (Fig. 2 ). The NPKCa + m + s treatment showed a decline in root biomass, most probably due to a beginning of root decay. Shoot and root traits R/S ratio. At the beginning of the growing period R/S were higher than 1 indicating the belowground root growth occurring in the winter season despite the reduced growth of shoots (Fig. 2 ). In the first sampling date, the lowest value was observed in the treatment NPKCa + m + s and the highest (1.50) in the treatment N_KCa. In date 2, the values ranged from 0.72 to 1.24 with the highest value observed in the treatment P omission and lowest under the fully fertilized treatment NPKCa (Fig. 2 ). In date 3, we observed lower RS than in the previous sampling date, indicating an allocation of biomass into the shoot part. As the season progressed, in dates 4 and 5, the RS decreased for all treatments compared to the previous sampling date (Fig. 2 ). Tiller number. Non-significant differences were observed during the first two sampling dates, at sampling date 3, the NPKCa + m + s treatment resulted in significantly higher tiller number, though in the last sampling dates, this trend was reversed, as the P omission treatments showed significantly higher number of tillers than the NPKCa + m + s treatment (Fig. 3 a). Number of nodal roots. The NPKCa + m + s treatment showed the highest number of nodal roots in dates 2 and 3 and lowest in dates 4 and 5, although the treatment differences were not significant (Fig. 3 b). The number of nodal roots did not differ significantly among the treatments in any of the dates. However, there was a trend for higher number of nodal roots in the P omission treatment compared to the fully fertilized ones in the sampling dates 4 and 5 (Fig. 3 b). Root angle. Root angles increased from values lower than 90° at the beginning of the growth period (date 1) to the largest value of 122°(mean over all treatments), observed at date 3 (Fig. 3 c). The largest increase of 43% was observed in the NPKCa and N_KCa treatment, and the lowest increase in the _PKCa treatment. A decrease in root angles in all treatments was observed in dates 4 and 5. The comparison of mean root angles over all treatments revealed steeper root angles in the _PKCa treatment with significant differences compared to the other treatments in dates 3 and 5. This was not the case for the N_KCa where the values were similar to the fully fertilized treatments (Fig. 3 c). Root length density . In general, the RLD increased for all treatments from date 1 to date 4, but decreased date 4 to date 5, except for the treatment NPKCa. In date 1 and date 5, no significant differences among treatments were observed. However, the treatment with NPKCa + m + s resulted in the highest RLD in date 2 to 4 and the treatment compared to the N omission (_PKCa), which resulted in the lowest RLD values, in dates 2 to 4 (Fig. 3 d). Specific root length . The SRL was not significantly different among treatments across sampling dates 1 to 4, but there was a trend where the treatments with N omission (_PKCA) and P omission (N_KCa) resulted in higher SRL than the two fully fertilized treatments (Fig. 3 e). However, around flowering (sampling date 5), The NPKCa + m + s treatment resulted in significantly higher SRL than the P omission treatment (N_KCa). Average diameter and length per diameter classes . Average diameter of winter rye in our experiments ranged from 0.21 to 0.30 with lowest value observed for the treatment _PKCa in date 2 and the highest value observed (Fig. 3 f). The results showed that over the sampling dates there were no significant differences among the treatments. But for sampling date 2, we found significant differences between the treatments where both fully fertilized treatments showed higher average diameter compared to the N and P omission treatments (Fig. 3 f). As for the proportion of the different diameter classes to the total root length, all treatments showed considerable higher proportion of L1 and L2 classes (Fig. 4 ). The share of very fine roots (L1, less than 0.15 mm) of the N omission treatment was the highest among treatments at date 2 and 4. At the late stage, the share of medium to coarse roots tended to increase in all treatments and was highest for the fully fertilized treatments NPKCa + m + s and NPKCa. Also, in the P deficient treatment the share of very fine and fine roots was enhanced (Fig. 4 ). C and N tissue content. Fertilizer treatments affected root and shoot C and N contents and C:N ratio. Treatment effects on shoot C content were similar among treatments and across sampling dates (Figure S3 and S4). The average shoot C content was slightly higher (44.0%) as compared to the root C content (39.0%) and slightly increased as the season progressed (Figure S3). By contrast, N content in shoots decreased from 2.8% in date 1 to 0.8% at the end of the season, similarly for roots, decreasing from 2.8% at sampling date 1, to a decrease of 76% towards the end of the season (Figure S4). Mean root N content was highest for treatment _PKCa (0.83%) but as the total root biomass was reduced, the root N uptake (root biomass times root N content) was lowest compared to the other treatments in all dates. The C:N ratio was the lowest in shoots during sampling dates 1 to 3 (Figure S5), but significantly increased during the last two sampling dates caused by a reduction of shoot N content (Figure S4 and S5). The NPKCa + m + s showed the lowest shoot C:N ratio in date 4, this trend was maintained during the last sampling date, though not significant due to high variation in treatment responses (Figure S5). Root C:N ratio also increased as the season progressed, though no significant differences were observed among treatments, except for the last date, where the _PKCa treatment showed a lower C:N ratio compared to the N_KCa, but the N_KCa was not significantly different to the NPKCa treatments (Figure S5). Grain yield. Significant differences were observed among all treatments, with the NPKCa + m + s treatment showing the highest yield with 6.8 t ha -1 , even the NPKCa resulted in considerably lower yield of 3.8 t ha -1 . The P and N omission treatments resulted in the lowest yields, with 53% and 80% yield reduction, respectively, compared to the fully fertilized treatment with manure (Fig. 5 ). Correlation of measured variables Figure S6 shows the correlation coefficients for the collected root and shoot variables for all sampling dates. When correlating the root and shoot variables (all dates), a positive correlation (0.7) was observed between these two variables (Figure S6a). The RLD and root biomass showed the highest correlation coefficient with yield (0.4), among all the variables, including shoot biomass (0.3). As for the temporal differences, the root biomass in dates 1 to 4 was strongly associated with yield (0.6–0.8), but not on date 5 (0.3) (Figure S6b-S6e). The tiller number was positively associated with yield in most dates (0.1–0.7), except in date 5. The correlation of root angle with yield was generally positive, except in date 4. The number of nodal roots relationship with yield varied widely in direction and magnitude by dates. The SRL was negatively associated with yield during most dates, except at date, where a weak positive relationship was observed (0.2). Root biomass showed a strong correlation with RLD (06-0.9) in all sampling dates. In the later sampling dates 3 to 5, RLD showed a strong positive correlation with root angle (0.6–0.7). Discussion Our study presented the effects of N and P fertilizer omission on winter rye shoot and root growth from tillering to flowering. Our results demonstrated that N and P omission led to a decrease in shoot biomass over time, with stronger reduction in the N omission treatment particularly in the last two sampling dates. These findings align with well-established research showing that N and P availability strongly influence biomass accumulation in rye (Mirsky et al., 2017 )). In cereals, N application typically leads to substantial shoot biomass increases, whereas P fertilization effects are often less pronounced (Bélanger et al., 2015 ; Kostic et al., 2021 )). The reduction in shoot biomass observed in our N and P omission treatments indicates that winter rye, like other cereals, relies heavily on adequate N and P supply for optimal aboveground growth. With regard to root traits, our results showed that in this long-term fertilizer trial, N omission was more detrimental than the P omission treatment. This was possibly due to the fact that our root sampling focused on the ploughed topsoil (0–30 cm), where N-limited plants may not have fully expressed deeper root allocation strategies. Another possible reason is that P amounts in this soil tend to be in sufficient quantities (> 50 mg kg − 1 ) to be extracted from the plants, possibly reducing the P omission treatment effect. Plants often allocate more root biomass to deeper soil layers under N deficiency, while under P deficiency, root proliferation tends to be concentrated in the upper soil layers where P is more available (Kumar et al., 2020 ). Reduced root biomass has been reported in field studies where N and P omission led to a decrease in root biomass by 7% and 25%, respectively (Lopez et al., 2023 ). These findings suggest that while both nutrients impact root development, P deficiency typically results in more pronounced shoot reductions, whereas N limitation tends to affect both shoot and root biomass. Also, a decrease of root biomass in the fully fertilized treatment in date 5 was not reflected in shoot biomass, which indicates an alteration in above and below ground allocation of biomass. Consistent with previous studies, we observed an increase in the R/S ratio under N and P omission. This response is a well-documented adaptive mechanism in plants facing nutrient scarcity (Amanullah, 2015 ). Under N deficiency, plants allocate a greater proportion of biomass to roots at the expense of shoot growth (Lopez et al., 2023 ). This shift is driven by the plant's need to enhance N uptake by expanding its root system. Similarly, P limitation may lead to increased R/S ratio, although the effect varies depending on root plasticity and soil nutrient distribution (Kumar et al., 2020 ; Lopez et al., 2023 ). P omission tends to decrease the tiller number (Graham et al., 1983 ; Rodríguez et al., 1999 ). In our results, a trend to decreased tiller number in N and P omission treatments compared to the NPKCa + m + s treatment was observed, though not significant for dates 1 and 2, but significant for date 3. However, in date 5, the opposite trend was observed where the P omission treatment resulted in higher tiller numbers compared to the NPKca + m + s treatment. In general, under P omission, roots tend to have a wider root angle, due to shallower and broader roots (Bonser et al., 1996 ; Niu et al., 2013 ). This trend was not observed in our results as P omission treatment showed non-significant differences when compared to the fully fertilized treatment. Robinson et al. ( 2018 ) reported that root angle was more strongly associated with yield than root number. This was the case in our study for sampling dates 3 and 5 but not in the rest of sampling dates. N omission also showed more steep root angles around flowering (sampling date 5), this shift suggests a strategy to explore more soil volume and thus, allow more resource acquisition (Trachsel et al., 2013 ). The effect of N fertilizer on spring barley root phenotypes was assessed by Siddiqui et al. ( 2021 ) showing a tendency for longer and narrower root angles under manure application in an organic system, compared to the lines grown with mineral fertilizer N supply, which showed shorter and wider root system. In line with that we found that N omission treatment showed more steep root angles around flowering. Our findings on RLD reduction under N omission align with previous studies, which report that N deficiency leads to a decrease in total root length and RLD across multiple crops, including winter wheat, maize, cotton and sugar beet​ (Anderson, 1987 ; Barraclough et al., 1989 ; Chen et al., 2020 ; Fang et al., 2022 ; Hadir et al., 2021 ; Mehrabi et al., 2021 ; Xue et al., 2014 ). This reduction is particularly evident in the topsoil (0–30 cm), which may explain our results, as our sampling was limited to the ploughed layer​. Additionally, root morphology responses to P deficiency can be genotype-dependent, meaning that cultivars may exhibit different root system adjustments in response to nutrient limitations (Lopez et al., 2023 )​. Although our study did not find a consistent decrease in RLD under P deficiency, numerous studies have reported a reduction in root length or RLD under P-limited conditions across various crops. This has been observed in maize (Deng et al., 2014 ; Sheng et al., 2012 ; Zhang et al., 2012 ), oilseed rape (Duan et al., 2020 ), sugar beet (Hadir et al., 2021 ), soybean (Ao et al., 2010 ; Otani & Ae, 1996 ), common beans (Ho et al., 2005 ; Miguel et al., 2013 ; Ochoa et al., 2006 ), and wheat (Teng et al., 2013 ), as well as in buckwheat, castor, peanut, and sorghum (Otani & Ae, 1996 ). The lack of effect of P omission on RLD could be attributed to the fact that we explored only the ploughed soil layer (0–30 cm), where Kemper et al., ( 2023 ) reported that under organic farming conditions winter rye RLD exhibits its highest value. The response of average diameter to nutrient omission was more pronounced in the beginning of the growing period where we observed negative impact of both N and P omission on the root diameter of winter rye. However, around flowering and in later growth stages, we did not find significant differences in average root diameter under either N or P omission, suggesting that these nutrient deficiencies may not strongly influence this trait in winter rye. Similar findings have been reported in other crops, such as potato under N deficiency (Sharifi et al., 2005 ) and maize under P omission (Li et al., 2017 ). However, the literature presents conflicting results, with some studies showing an increase in root diameter under N deficiency (Anderson, 1987 ), while others report a decrease (Eghball et al., 1993 ; Hadir et al., 2021 ). Likewise, P deficiency has been linked to reduced root diameter in maize at specific growth stages (Sheng et al., 2012 ; Zhang et al., 2012 ). These inconsistencies suggest that root diameter responses to nutrient availability may be species-specific, influenced by environmental conditions, plant developmental stage, or genotype. Our study did not find significant differences in SRL under either N or P omission, around flowering SRL was significantly lowered under P omission. In contrast, previous studies reported higher SRL under low-nutrient conditions (Ostonen et al., 2007 ). Poorter and Ryser ( 2015 ) explored SRL as an adaptive trait in response to nutrient constraints, drawing parallels with specific leaf area (SLA) adjustments under light limitations. While SLA showed more pronounced changes, SRL responses were less consistent. However, when root types were analyzed separately, they found that lateral roots (often the most active in nutrient acquisition) tended to exhibit higher SRL under nutrient-limited conditions. This could explain why some studies report increased SRL in deficient treatments, whereas our results did not show significant changes, potentially due to differences in root sampling or the specific root types measured. With regards to the relationships between traits and grain yield, a positive but only moderate correlation between the number of nodal roots and grain yield was observed. Also, during the last two sampling dates, the number of nodal roots had a tendency to be higher in the P omission treatment, compared to the fully fertilized treatment with manure. A meta-analysis from (Niu et al., 2013 ), reported similar findings, where P omission promoted lateral root growth in cereal crops. Grando and Ceccarelli ( 1995 ), also compared modern barley cultivars, landraces and wild barley and showed that there was a significant increase in the number of seminal roots during domestication, suggesting that there may be a relationship between seminal root number and crop productivity. In plant breeding programs, root traits are generally less prioritized for selection because root traits carry large phenotypic variation, particularly under nutrient deficiency conditions, and require labor-intensive field measurements (Maqbool et al., 2022 ; Purushothaman et al., 2017 ; Wissuwa et al., 2016 ). However, some studies state that architectural traits like root preference for shallow or deep soil layers, root angle, and lateral branching are under strong genetic control (El Hassouni et al., 2018 ; Lynch, 2007 ). El Hassouni et al. ( 2018 ) tested 25 durum genotypes at five locations with different water regimes. All traits connected to root angle showed a very high heritability and were not affected by the water scarcity after anthesis. In contrast, Robinson et al. ( 2018 ) tested 216 spring barley breeding lines in pots and found a genetic relationship between seminal root traits and yield ( including field data from 20 sites), but the direction and magnitude of the correlations varied across the environments. In our study, we found a high variability of the root traits across dates and often within treatments. A rather strong positive correlation was observed between shoot and root biomass in most sampling dates, as well as root biomass with final yield, except around flowering. In declining order, the root biomass, RLD, average diameter, no. of tillers, and root angle were associated with final yield across sampling dates. Uga ( 2021 ) defined so-called root system architecture ideotypes for defined conditions. Promising cereal ideotypes under N deficiency may have steeper, longer, fewer, and thicker roots for an efficient N uptake and accumulation. Especially in the later sampling dates, we observed significantly steeper roots and a trend for lower nodal root numbers in case of N deficiency. The authors also proposed a root cereal ideotype with a greater number of axial roots and shallower axial roots for a more effective capture of topsoil P under low P soil conditions (Uga, 2021 ). However, trade-offs can occur depending on soil nutrient conditions. For instance, while investing in thicker roots may be advantageous when nutrients are abundant, in nutrient-limiting conditions, root hairs and lateral roots may be more effective in capturing available nutrients (Gonzalez et al., 2021 ). In the low P conditions, we observed no significant differences of the root angle compared to the fully fertilized treatment but a clear trend for higher numbers of nodal roots in late sampling dates. Conclusion We conclude that the environment and development stage at sampling have a strong impact on winter rye root phenotypic plasticity. Effects of fertilizer omission on the shoot are not only easier to determine but also clearer in terms of direction and treatment ranking. However, roots play a critical role in plant adaptation to abiotic stresses, with root characteristics being central to soil exploration and nutrient acquisition. Strategic adjustments in root growth patterns e.g. via breeding or improved site-specific cultivar selection are needed to enable plants to optimize resource use efficiency in sub-optimal environments. Declarations Funding The presented study has been funded by the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food (BLE) (grant number 2822ABS010), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy-EXC 2070-390732324 (PhenoRob), by DFG – SFB 1502/1–2022 project number: 450058266, the Federal Ministry of Education and Research (BMBF) (project “Sustainable Subsoil Management-Soil3, Grant 031B0151A), as well as by the European Union (EU horizon project IntercropVALUES, grant agreement No 101081973). References Amanullah. (2015). Specific leaf area and specific leaf weight in small grain crops wheat, rye, barley, and oats differ at various growth stages and NPK Source. Journal of Plant Nutrition , 38 (11), 1694-1708. https://doi.org/10.1080/01904167.2015.1017051 Anderson, E. L. (1987). 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Supplementary Files SupplementarymaterialWinterRyeNPomissionV04.docx Cite Share Download PDF Status: Published Journal Publication published 02 Dec, 2025 Read the published version in Plant and Soil → Version 1 posted Editorial decision: Major revisions 09 Jun, 2025 Reviewers agreed at journal 17 Apr, 2025 Reviewers invited by journal 14 Apr, 2025 Editor invited by journal 01 Apr, 2025 Editor assigned by journal 01 Apr, 2025 First submitted to journal 31 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6328255","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442500131,"identity":"66612f72-2ebd-4342-9e5e-c2ab593386bb","order_by":0,"name":"Sofia Hadir","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Sofia","middleName":"","lastName":"Hadir","suffix":""},{"id":442500132,"identity":"de56b0ce-5e2e-4e35-84a8-0beb914c23af","order_by":1,"name":"Gina Marcela Lopez","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Gina","middleName":"Marcela","lastName":"Lopez","suffix":""},{"id":442500133,"identity":"ef88b976-3d0d-475b-81ae-8a28654fba31","order_by":2,"name":"Sabine J. Seidel","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Sabine","middleName":"J.","lastName":"Seidel","suffix":""},{"id":442500134,"identity":"39a0510c-5abe-407b-9dfe-8885b8d7c8ea","order_by":3,"name":"John Kormla Nyameasem","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"Kormla","lastName":"Nyameasem","suffix":""},{"id":442500135,"identity":"a4563870-b571-4f1b-93c5-5656992a3067","order_by":4,"name":"Sara L. Bauke","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"L.","lastName":"Bauke","suffix":""},{"id":442500136,"identity":"2970378e-5714-4301-b273-0ecb6b994810","order_by":5,"name":"Ixchel Manuela Hernandez-Ochoa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACNgkIzdjAwHyAgcGAIQHM5SFOC1sCcVoYEFp4DEAMwlr4pJuPfS6ouSPbz3/mm3RBAUMev3TvAYY3FXgcJnMsefaMY8+MZzac3SY9w4ChWHLOuQTGOWfw+SXHmJmH7XDihoO926R5DP4nbriRY8DM24ZPS/5nZp5/hxP3H+Z5BtTCANXyD68tzEAzgbaw8bAhaWnApyXNmJm377DxjDNsxtY8IL/MyDE4OOcYbi3yM5IfM/N8Oyzb33/44W2eP8AQk8gxfPCmBrcW7OAAqRpGwSgYBaNgFKACAPRGShJfi535AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2531-823X","institution":"University of Bonn: Rheinische Friedrich-Wilhelms-Universitat Bonn","correspondingAuthor":true,"prefix":"","firstName":"Ixchel","middleName":"Manuela","lastName":"Hernandez-Ochoa","suffix":""}],"badges":[],"createdAt":"2025-03-28 12:40:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6328255/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6328255/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11104-025-08088-w","type":"published","date":"2025-12-02T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81367046,"identity":"f2cc4bac-bebb-4d40-a88e-da4dfbe8d4c6","added_by":"auto","created_at":"2025-04-25 09:39:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":97307,"visible":true,"origin":"","legend":"\u003cp\u003eSoil P\u003csub\u003ecal\u003c/sub\u003e, K\u003csub\u003ecal\u003c/sub\u003e and N\u003csub\u003emin\u003c/sub\u003e content for four sampling dates during the 2022 winter rye growing season as affected by N and P omission treatments. Treatments: Fully fertilized plus manure (NPKCa+m+s), fully fertilized with mineral fertilizer only (NPKCa), N omission (_PKCa) and P omission (N_KCa); \u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e Soil P and K content measured using the calcium acetate-lactate extract method; \u003csup\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eSoil mineral nitrogen content (N\u003csub\u003emin\u003c/sub\u003e) measured by extraction with potassium sulfate solution. One pooled sample collected by treatment and sampling date.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6328255/v1/55f6dcbf357f48591182a483.png"},{"id":81367368,"identity":"488d29f5-0ef2-4c49-8d2a-f876ca73dc1a","added_by":"auto","created_at":"2025-04-25 09:47:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96526,"visible":true,"origin":"","legend":"\u003cp\u003eAverage dry matter shoot biomass and average root biomass in the topsoil 30 cm layer in g m\u003csup\u003e-2\u003c/sup\u003e and root:shoot ratio (R/S) as affected by N and P omission treatments over five sampling dates (1: 16/03/2022 (2-4 tillers detectable), 2: 04/04/2022 (beginning of stem elongation), 3: 29/04/2022 (early to mid-boot stage), 4: 27/05/2022 (60-80% of inflorescence emerged) and 5: 06/21/2022 (end of flowering)). Treatments: Fully fertilized plus manure (NPKCa+m+s), fully fertilized with mineral fertilizer only (NPKCa), N omission fertilized (_PKCa) and P omission fertilized (N_KCa). Treatments followed by the same letter\u0026nbsp; do not differ according to Tukey high significant difference at 5% confidence level. NS= not significant at 5% confidence level. Error bars refer to the standard deviation.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6328255/v1/a77f5d4ed7d9ce6c250bd05e.png"},{"id":81367050,"identity":"987e632c-ac75-4933-94a7-313d57497951","added_by":"auto","created_at":"2025-04-25 09:39:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103614,"visible":true,"origin":"","legend":"\u003cp\u003eAverage number (no.) of tillers (a), nodal roots (b), root angle (c), root length density (RLD, d)), specific root length (SRL, e), and root diameter (f) as affected by N and P omission treatments over five sampling dates (1: 16/03/2022 (2-4 tillers detectable ), 2: 04/04/2022 (beginning of stem elongation), 3: 29/04/2022 (early to mid-boot stage), 4: 27/05/2022 (60-80% of inflorescence emerged) and 5: 06/21/2022 (end of flowering)) in the top 30 cm soil layer. Treatments: Fully fertilized plus manure (NPKCa+m+s), fully fertilized with mineral fertilizer only (NPKCa), N omission (_PKCa) and P omission (N_KCa). Treatments followed by the same letter do not differ according to Tukey high significant difference at 5% confidence level. NS= not significant at 5% confidence level for the ANOVA or the Aligned rank transform for non-parametric factorial ANOVA (implemented for tillers per shoot on sampling dates 3, 4 and 5). Error bars refer to the standard deviation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6328255/v1/d84162f02f89dbd7fd10cacc.png"},{"id":81367367,"identity":"09eba418-acb7-4aac-a97a-a31536f7da9e","added_by":"auto","created_at":"2025-04-25 09:47:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":98029,"visible":true,"origin":"","legend":"\u003cp\u003eProportion (%) for each diameter class to total root length as affected by N and P omission treatments over five sampling dates \u0026nbsp;( a) 16/03/2022 (2-4 tillers detectable ), b): 04/04/2022 (beginning of stem elongation), c) 29/04/2022 (early to mid-boot stage), d) 27/05/2022 (60-80% of inflorescence emerged) and e) 06/21/2022 (end of flowering). Treatments: Fully fertilized plus manure (NPKCa+m+s), fully fertilized with mineral fertilizer only (NPKCa), N omission (_PKCa) and P omission (N_KCa). Average values of root length per root diameter class were used to represent the proportion.L1: \u0026lt; 0.15 mm, L2: 0.15 to 0.30 mm, L3: 0.30 to 0.45 mm, L4: 0.45 to 0.60 mm, L5: 0.60 to 0.75 mm, L6: \u0026gt; 0.75 mm\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6328255/v1/a89e66790958753ca3da4af6.png"},{"id":81367049,"identity":"341d9ce7-4b0a-4863-91ae-9a1287624de3","added_by":"auto","created_at":"2025-04-25 09:39:49","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":29082,"visible":true,"origin":"","legend":"\u003cp\u003eWinter rye grain yield as affected by N and P omission treatments during the 2022 season. Treatments: Fully fertilized plus manure (NPKCa+m+s), fully fertilized with mineral fertilizer only (NPKCa), N omission (_PKCa) and P omission (N_KCa). Treatments followed by the same letter do not differ according to Tukey high significant difference at 5% confidence level. Error bars refer to the standard deviation.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6328255/v1/79c09b9ab249d45b4afdf323.png"},{"id":97723788,"identity":"c6e318ea-b82b-4164-92f0-6b52f1d7b884","added_by":"auto","created_at":"2025-12-08 16:06:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1219826,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6328255/v1/73cfa23a-d30e-4329-9136-85e9a957c916.pdf"},{"id":81367054,"identity":"05a2f32c-2834-4eae-999a-bed0c25b5e61","added_by":"auto","created_at":"2025-04-25 09:39:49","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":2167813,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarymaterialWinterRyeNPomissionV04.docx","url":"https://assets-eu.researchsquare.com/files/rs-6328255/v1/f97931ad3f43f8b9fe55bb76.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eWinter rye root growth and plasticity in response to nitrogen and phosphorus omission under field conditions\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNitrogen (N) and phosphorus (P) are critical nutrients that are central to crop productivity, with N being key for amino acid and protein synthesis, while P is essential for energy transfer, photosynthesis, and structural development (Uga et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, the availability of these nutrients is often limited in agricultural soils, which can result in reduced crop yields and grain quality (Hammer et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Addressing these constrains requires improved crop nutrient use efficiency to tackle the challenges of global food security and environmental sustainability. Enhancing the functional plasticity of root systems emerges as a key approach to improve nutrient acquisition and crop performance under resource-limited conditions. Many studies reported the belowground interactions occurring in the rhizosphere. The root system architecture\u0026mdash;comprising traits such as root biomass, length, diameter and angle\u0026mdash;is key to exploring soil and acquiring nutrients (Lynch, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Lynch, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Environmental factors, including microbiome activity, soil water availability, soil compaction, salinity, nutrient distribution but also the crop management further influence root growth dynamics, modulating root system depth, root angle, and nutrient and water uptake efficiency (Correa et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hecht et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Manschadi et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Oyanagi et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent studies highlight strategic adjustments in root growth patterns that enable plants to optimize resource use efficiency in sub-optimal environments (Lynch, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For instance, the root angle is a main determinant of root placement within the soil profile. Steeper root angles promote deeper soil penetration, enhancing access to mobile resources like nitrate and water under drought or low N conditions (Schneider et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Trachsel et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Conversely, shallower root angles facilitate topsoil exploration, improving the acquisition of immobile nutrients such as phosphorus (Bonser et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Liao et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Lynch \u0026amp; Brown, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Moreover, root mass is an important trait for carbon storage and its sequestration (K\u0026auml;tterer et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Poeplau \u0026amp; Don, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). A recent study showed that under N deficiency, root length and root biomass decreased by 9% and 7%, respectively, but root length per shoot biomass increased by 33%, alongside a 44% enhancement in the root:shoot (RS) ratio, reflecting carbon allocation strategies for nutrient foraging (Lopez et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Root length density is linked to aggregate stability (Hudek et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) as well as water and nutrient acquisition (Tajima, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Root diameter is also considered an important trait affecting nutrient acquisition (Perkons et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), for instance, in dicotyledonous plants, taproots with thicker diameters can penetrate compacted soil more easily than smaller root diameters (Materechera et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1992\u003c/span\u003e), enhancing the nutrient acquisition efficiency under sub-optimal conditions. Another important root morphological trait is the specific root length (SRL), defined as root length per root mass, which is an indicator of the root soil exploration capacity (Freschet et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The SRL can also be linked with nutrient uptake efficiency (Eissenstat, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Isaac \u0026amp; Borden, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kemper et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Research shows that crops with increased SRL have long and thin roots and are less expensive to produce (Ostonen et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Root phenotyping is often conducted under controlled environments, as it provides a greater likelihood of reproducible root phenotypes compared to field phenotyping. However, transferability of plant responses from controlled environments to field conditions remains a challenge (Langstroff et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, field phenotyping remains a critical component in particular for root traits that are expressed at later stages of plant growth or in deeper soil layers (Tracy et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLong-term fertilizer experiments (LTFE) serve as an important platform for research (Seidel et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); however, studies mostly focus on the above-ground traits as affected by fertilizer omission, often neglecting the specific impacts of nutrient omissions on root system architecture under field conditions (Lopez et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Siddiqui et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Renowned for its adaptability to nutrient-poor soils and challenging growing environments, winter rye (\u003cem\u003eSecale cereale\u003c/em\u003e) serves as an excellent model for investigating root-shoot interactions under nutrient stress (Arsova et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Compared to wheat, rye has demonstrated more vigorous early vegetative growth (Paponov et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), higher radiation use efficiency (RUE) (Sieling et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and greater frost tolerance (Griffith et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Limin \u0026amp; Fowler, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), all of which contribute to its resilience under sub-optimal conditions. A key factor behind the superior performance of rye is its highly developed root system, which facilitates efficient nutrient and water uptake, allowing it to thrive in marginal soils (Dittmer, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1937\u003c/span\u003e; Kaye et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Despite this potential, the role of rye roots in nutrient acquisition and stress adaptation remains largely unexplored. Given that rye is a widely produced crop in Europe (European-Commission, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), the lack of studies on root phenotyping highlights a significant research gap (Comas et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Takahashi \u0026amp; Pradal, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Investigating rye\u0026rsquo;s root system architecture is a unique opportunity to understand how root traits respond to varying nutrient availability during the growth period. This study aims to fill this knowledge gap on rye responses to nutrient deficiency by investigating the effects of N and P deficiency on root and shoot traits of winter rye cultivated at a LTFE. By examining morphological root and shoot trait adaptations on various dates from tillering to anthesis, the study seeks to provide valuable insights for developing crop management and breeding strategies to improve productivity and resilience in nutrient-limited environments.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental design\u003c/h2\u003e \u003cp\u003eA sampling campaign was conducted in 2022 at the long-term fertilizer experiment (LTFE) Dikopshof near Cologne, Germany (50.8079 N, 6.9529 E, 62 m a.s.l.). The experiment was established in 1904, with a 5-year crop rotation currently including sugar beet (\u003cem\u003eBeta vulgaris\u003c/em\u003e), winter wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L.), winter rye, persian clover (\u003cem\u003eTrifolium resupinatum\u003c/em\u003e L.), and potato (\u003cem\u003eSolanum tuberosum\u003c/em\u003e L.). The general soil type is classified as a Haplic Luvisol derived from loess above sand with a silty loam (topsoil) and (silty) clay loam (below 30 cm soil depth). The experiment is a non-randomized block design without replicates and comprises seven treatments: NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s (\"+m\" stands for farmyard manure fertilization and \"+s\" stands for supplemental mineral fertilization), NPKCa, _PKCa, N_KCa, NP_Ca, NPK_, and no fertilizer (the \"_\" stands for the omission of the corresponding nutrient, \"Ca\" stands for lime). After harvesting the preceding crop, cattle farmyard manure is supplied on sugar beet, potato, and winter rye plots at a total rate of 60 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e per five-year rotation (fresh matter, treatments \"+m\"). The fertilizer management has not changed since 1953, except for a slight increase of the N fertilizer treatment (+\u0026thinsp;30 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) on winter wheat in some treatments, which occurred in the 1980s. For further details about the field experiment refer to Seidel et al. (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCrop management\u003c/h3\u003e\n\u003cp\u003eAfter farmyard manure application on 31/10/2021 and ploughing on 07/11/2021, winter rye cultivar Tribiano KWS was sown on 09/11/2021. Mineral P and N were applied on 28/03/2022 and the second N-fertilization (only NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s) was applied on 10/05/2022 (around BBCH 55). Harvest was on 27/07/2022.\u003c/p\u003e\n\u003ch3\u003eShoot and root measurements\u003c/h3\u003e\n\u003cp\u003eFour treatments were considered in this study: Fully fertilized plus manure (NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s), fully fertilized with mineral fertilizer only (NPKCa), N omission (_PKCa), and P omission (N_KCa). Winter rye shoot biomass was estimated destructively on five dates (16/03, 04/04, 29/04, 27/05, and 21/06) from early tillering to end of flowering (BBCH stages 22\u0026ndash;24, 30, 41\u0026ndash;43, 56\u0026ndash;58 and 69, respectively) by cutting four times 50 cm of a row. Simultaneously, manual soil coring using a 1 m auger with a 9 cm inner diameter, was conducted in each of the cut rows to sample the roots in the ploughed soil top layer (0\u0026ndash;30 cm). Roots per auger were then carefully cleaned with tap water. For the current study, measured shoot and root traits included number of tillers, number of nodal roots, root angle, the specific root length (SRL), root length density (RLD), average diameter and root length per diameter class. The nodal root angles, number of tillers, and the number of nodal roots emerging from shoot tissue (root number) were estimated manually for all plants. The angular spread of the roots was defined as the deviation angle of the two most horizontally distant shoot roots (180\u0026deg; would be roots at soil surface, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The samples were then sieved (2 mm and 0.63 mm) and sorted to remove the debris. The roots were then scanned with a flat-bed scanner (Expression 12000XL, Epson, Suwa, Japan). To avoid overlapping during the scanning, samples with abundant roots were divided into sub-samples. Images were then analyzed with WinRhizo 2016a software (R\u0026eacute;gent Instruments Inc., Quebec, QC; Canada) to estimate the SRL (cm), the RLD, (cm cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e soil), average diameter (mm) and root length (cm) for each diameter class. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the equation for the SRL and RLD calculations. The RLD was calculated for the top 30 cm soil as the ploughed layer (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The dry matter root biomass (g m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) was calculated using the equation in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e by considering the surface area of the auger cylinder. While specific root length (SRL) was also calculated based on the top 30 cm soil sample (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\u003eEquations and units for the calculated root morphology parameters for winter rye fertilizer omission experiment at Dikopshof.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEquation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot biomass\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{R}\\text{o}\\text{o}\\text{t}\\:\\text{b}\\text{i}\\text{o}\\text{m}\\text{a}\\text{s}\\text{s}=\\frac{\\text{R}\\text{o}\\text{o}\\text{t}\\:\\text{m}\\text{a}\\text{s}\\text{s}\\:\\text{f}\\text{o}\\text{r}\\:\\text{t}\\text{h}\\text{e}\\:\\text{p}\\text{l}\\text{o}\\text{u}\\text{g}\\text{h}\\text{e}\\text{d}\\:\\text{l}\\text{a}\\text{y}\\text{e}\\text{r}}{\\text{S}\\text{u}\\text{r}\\text{f}\\text{a}\\text{c}\\text{e}\\:\\text{a}\\text{r}\\text{e}\\text{a}\\:\\text{o}\\text{f}\\:\\text{c}\\text{y}\\text{l}\\text{i}\\text{n}\\text{d}\\text{e}\\text{r}\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecific root length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003em g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{S}\\text{R}\\text{L}=\\:\\:\\:\\frac{\\text{R}\\text{o}\\text{o}\\text{t}\\:\\text{l}\\text{e}\\text{n}\\text{g}\\text{t}\\text{h}\\:\\text{i}\\text{n}\\:\\text{t}\\text{h}\\text{e}\\:\\text{p}\\text{l}\\text{o}\\text{u}\\text{g}\\text{h}\\text{e}\\text{d}\\:\\:\\text{l}\\text{a}\\text{y}\\text{e}\\text{r}}{\\text{R}\\text{o}\\text{o}\\text{t}\\:\\text{m}\\text{a}\\text{s}\\text{s}\\:\\text{f}\\text{o}\\text{r}\\:\\text{t}\\text{h}\\text{e}\\:\\text{c}\\text{o}\\text{r}\\text{r}\\text{e}\\text{s}\\text{p}\\text{o}\\text{n}\\text{d}\\text{i}\\text{n}\\text{g}\\:\\text{l}\\text{a}\\text{y}\\text{e}\\text{r}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot length density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecm cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{R}\\text{L}\\text{D}=\\:\\:\\:\\frac{\\text{R}\\text{o}\\text{o}\\text{t}\\:\\text{l}\\text{e}\\text{n}\\text{g}\\text{t}\\text{h}\\:\\text{i}\\text{n}\\:\\text{t}\\text{h}\\text{e}\\:\\text{p}\\text{l}\\text{o}\\text{u}\\text{g}\\text{h}\\text{e}\\text{d}\\:\\:\\text{l}\\text{a}\\text{y}\\text{e}\\text{r}}{\\text{S}\\text{o}\\text{i}\\text{l}\\:\\text{v}\\text{o}\\text{l}\\text{u}\\text{m}\\text{e}\\:\\text{o}\\text{f}\\:\\text{t}\\text{h}\\text{e}\\:\\text{l}\\text{a}\\text{y}\\text{e}\\text{r}}\\)\u003c/span\u003e\u003c/span\u003e\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 Depth of ploughed layer\u0026thinsp;=\u0026thinsp;30 cm.\u003c/p\u003e \u003cp\u003eAfter scanning and image analysis the roots were then dried in the oven at 50\u0026deg;C and weighted using Sartorius ENTRIS 4231 fine scale with 0.001 g level of precision (Sartorius Lab Instrument GmbH \u0026amp; Co, Goettingen, Germany) to derive dry matter root biomass and determine C and N tissue content. To facilitate analysis, the root length was additionally categorized into six classes ranging from \u0026lt;\u0026thinsp;0.15 mm up to \u0026gt;\u0026thinsp;0.75 mm diameter, with equal intervals of 0.15 mm, where L1 was the lowest and L6 was the highest root diameter, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRoot diameter classification ranges.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiameter class\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.15 mm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15 to 0.30 mm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30 to 0.45 mm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.45 to 0.60 mm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60 to 0.75 mm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.75 mm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eSoil nutrient and water sampling and monitoring\u003c/h3\u003e\n\u003cp\u003eFour soil samples per treatment at each sampling date were collected from the ploughed topsoil (0\u0026ndash;30 cm) with a P\u0026uuml;rkhauer auger with an 18 mm-diameter. The samples per treatment were then pooled together and frozen. After thawing, the soil was analyzed for mineral N content (N\u003csub\u003emin\u003c/sub\u003e) by extraction with potassium sulfate solution (VDLUFA, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). The N\u003csub\u003emin\u003c/sub\u003e concentrations in the extracts were measured by a Skalar Continuous Flow Analyser (Skalar Analytical B.V., Breda, Netherlands). The plant-available P (P\u003csub\u003ecal\u003c/sub\u003e) and K (K\u003csub\u003ecal\u003c/sub\u003e) were determined using a calcium acetate calcium lactate extract as described by Sch\u0026uuml;ller (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1969\u003c/span\u003e). The P concentration in the extracts was determined colorimetrically following molybdenum blue reaction (Murphy \u0026amp; Riley, 1962) on a spectrophotometer (Specord 205, Analytik Jena, Germany). Around flowering, when root systems of cereals commonly achieve their maximum root growth, volumetric soil water content at 3, 30 and 60 cm soil depth was measured using the FDR moisture sensor HH2 within ML3 Theta Probe (ecoTech Umwelt-Me\u0026szlig;systeme GmbH, Bonn, Germany) at winter rye flowering on 27/05/2022.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe collected data were analyzed using the R software (version 4.1.1), although the replicates are pseudo replicates (i.e. sub samples) due to the old experimental set up. A mean comparison test was carried out for all measurements, using the sub samples collected at each plot. Data normality was tested by sampling date by using the Shapiro wilk test. The log10 or negative square root data transformation was used when data was non-normally distributed. For the normally distributed data, a one-way analysis of variance (ANOVA) was conducted. Multiple comparisons between treatments were performed using the Tukey's test (Tukey test, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). When data was not normally distributed, and data transformation was unsuccessful, an Aligned rank transform factorial ANOVA for non-parametric data was used by implementing the ARTool package (version 0.11.1). Finally, the ggcorr function in R was used to visualize the correlation coefficients between the shoot and root variables in a correlation matrix. To assess the relationships between key aboveground and belowground traits, we performed a Pearson correlation analysis. This analysis was conducted using the \u003cem\u003ecor.test\u003c/em\u003e function in the stats package in R. To visualize the correlation matrix and identify significant relationships, we used the \u003cem\u003ecorrplot\u003c/em\u003e package for graphical representation of the correlation coefficients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, N and P omission treatments significantly affected root and shoot biomass as well as root traits during the season. For the shoot biomass, treatment differences became more apparent during the last sampling dates, similarly as for root biomass. Fertilizer treatments significantly affected root morphological traits, with greater variation observed among the different treatments.\u003c/p\u003e\n\u003ch3\u003eSoil conditions\u003c/h3\u003e\n\u003cp\u003eThe NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s resulted in the highest soil N\u003csub\u003emin\u003c/sub\u003e, K\u003csub\u003ecal\u003c/sub\u003e, and P\u003csub\u003ecal\u003c/sub\u003e contents during all sampling dates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). While soil P\u003csub\u003ecal\u003c/sub\u003e and K\u003csub\u003ecal\u003c/sub\u003e content were the lowest in the N_KCa treatment. As expected, the soil N\u003csub\u003emin\u003c/sub\u003e was the highest in the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment with the highest values observed in the first (29.14 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and last (27.61 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) sampling dates, but declined in the second and third sampling dates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The rest of treatments showed considerably lower N\u003csub\u003emin\u003c/sub\u003e values as well as a tendency to decrease as the season progressed. The soil N\u003csub\u003emin\u003c/sub\u003e values were lowest for _PKCa in all dates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor soil water content, the volumetric water content data collected around flowering on 27/05/2022, showed non-significant differences at the top 3 cm (Figure S2). However, at 30 cm, the N omission treatment resulted in the highest soil moisture at ~\u0026thinsp;20%, followed by the P omission and NPKCa treatment. At 60 cm, most treatments resulted in non-significant differences, except for NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s, which showed the strongest decrease in soil moisture, suggesting more water uptake in the top layers, which reduced the supply to the deeper layer (Figure S2).\u003c/p\u003e\n\u003ch3\u003eShoot biomass\u003c/h3\u003e\n\u003cp\u003eFertilizer treatments significantly affected shoot biomass over the season (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The shoot biomass was significantly higher in the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment during all the sampling dates, with values ranging from 32.94 g m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at sampling date 1 to 2,123 g m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at sampling date 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, the N omission led to the lowest shoot biomass among all treatments during the last two dates. In the last sampling date, differences became less apparent with even the NPKCa treatment showing similar shoot biomass to the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s, while N_KCa and _PKCa treatments showed the lowest shoot biomass with non-significant differences between them.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRoot biomass\u003c/h2\u003e \u003cp\u003eFertilizer treatments also affected root biomass in different magnitudes, over all the sampling dates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Root biomass at the first and the third sampling dates showed non-significant differences. In sampling date 2, the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment led to the highest root biomass, but differences became less apparent in the later sampling dates. The N omission treatment often led to the lowest root biomass among treatments across sampling dates, while the P omission treatment resulted in the same root biomass as the NPKCa treatment in sampling dates 4 and 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment showed a decline in root biomass, most probably due to a beginning of root decay.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003eShoot and root traits\u003c/b\u003e \u003c/p\u003e\u003cp\u003e \u003cb\u003eR/S ratio.\u003c/b\u003e At the beginning of the growing period R/S were higher than 1 indicating the belowground root growth occurring in the winter season despite the reduced growth of shoots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the first sampling date, the lowest value was observed in the treatment NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s and the highest (1.50) in the treatment N_KCa. In date 2, the values ranged from 0.72 to 1.24 with the highest value observed in the treatment P omission and lowest under the fully fertilized treatment NPKCa (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In date 3, we observed lower RS than in the previous sampling date, indicating an allocation of biomass into the shoot part. As the season progressed, in dates 4 and 5, the RS decreased for all treatments compared to the previous sampling date (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTiller number.\u003c/b\u003e Non-significant differences were observed during the first two sampling dates, at sampling date 3, the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment resulted in significantly higher tiller number, though in the last sampling dates, this trend was reversed, as the P omission treatments showed significantly higher number of tillers than the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003cb\u003eNumber of nodal roots.\u003c/b\u003e The NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment showed the highest number of nodal roots in dates 2 and 3 and lowest in dates 4 and 5, although the treatment differences were not significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The number of nodal roots did not differ significantly among the treatments in any of the dates. However, there was a trend for higher number of nodal roots in the P omission treatment compared to the fully fertilized ones in the sampling dates 4 and 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003cb\u003eRoot angle.\u003c/b\u003e Root angles increased from values lower than 90\u0026deg; at the beginning of the growth period (date 1) to the largest value of 122\u0026deg;(mean over all treatments), observed at date 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). The largest increase of 43% was observed in the NPKCa and N_KCa treatment, and the lowest increase in the _PKCa treatment. A decrease in root angles in all treatments was observed in dates 4 and 5. The comparison of mean root angles over all treatments revealed steeper root angles in the _PKCa treatment with significant differences compared to the other treatments in dates 3 and 5. This was not the case for the N_KCa where the values were similar to the fully fertilized treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003cb\u003eRoot length density\u003c/b\u003e. In general, the RLD increased for all treatments from date 1 to date 4, but decreased date 4 to date 5, except for the treatment NPKCa. In date 1 and date 5, no significant differences among treatments were observed. However, the treatment with NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s resulted in the highest RLD in date 2 to 4 and the treatment compared to the N omission (_PKCa), which resulted in the lowest RLD values, in dates 2 to 4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSpecific root length\u003c/b\u003e. The SRL was not significantly different among treatments across sampling dates 1 to 4, but there was a trend where the treatments with N omission (_PKCA) and P omission (N_KCa) resulted in higher SRL than the two fully fertilized treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). However, around flowering (sampling date 5), The NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment resulted in significantly higher SRL than the P omission treatment (N_KCa).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAverage diameter and length per diameter classes\u003c/b\u003e. Average diameter of winter rye in our experiments ranged from 0.21 to 0.30 with lowest value observed for the treatment _PKCa in date 2 and the highest value observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). The results showed that over the sampling dates there were no significant differences among the treatments. But for sampling date 2, we found significant differences between the treatments where both fully fertilized treatments showed higher average diameter compared to the N and P omission treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs for the proportion of the different diameter classes to the total root length, all treatments showed considerable higher proportion of L1 and L2 classes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The share of very fine roots (L1, less than 0.15 mm) of the N omission treatment was the highest among treatments at date 2 and 4. At the late stage, the share of medium to coarse roots tended to increase in all treatments and was highest for the fully fertilized treatments NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s and NPKCa. Also, in the P deficient treatment the share of very fine and fine roots was enhanced (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eC and N tissue content.\u003c/b\u003e Fertilizer treatments affected root and shoot C and N contents and C:N ratio. Treatment effects on shoot C content were similar among treatments and across sampling dates (Figure S3 and S4). The average shoot C content was slightly higher (44.0%) as compared to the root C content (39.0%) and slightly increased as the season progressed (Figure S3). By contrast, N content in shoots decreased from 2.8% in date 1 to 0.8% at the end of the season, similarly for roots, decreasing from 2.8% at sampling date 1, to a decrease of 76% towards the end of the season (Figure S4). Mean root N content was highest for treatment _PKCa (0.83%) but as the total root biomass was reduced, the root N uptake (root biomass times root N content) was lowest compared to the other treatments in all dates. The C:N ratio was the lowest in shoots during sampling dates 1 to 3 (Figure S5), but significantly increased during the last two sampling dates caused by a reduction of shoot N content (Figure S4 and S5). The NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s showed the lowest shoot C:N ratio in date 4, this trend was maintained during the last sampling date, though not significant due to high variation in treatment responses (Figure S5). Root C:N ratio also increased as the season progressed, though no significant differences were observed among treatments, except for the last date, where the _PKCa treatment showed a lower C:N ratio compared to the N_KCa, but the N_KCa was not significantly different to the NPKCa treatments (Figure S5).\u003c/p\u003e \u003cp\u003e \u003cb\u003eGrain yield.\u003c/b\u003e Significant differences were observed among all treatments, with the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment showing the highest yield with 6.8 t ha\u003csup\u003e-1\u003c/sup\u003e, even the NPKCa resulted in considerably lower yield of 3.8 t ha\u003csup\u003e-1\u003c/sup\u003e. The P and N omission treatments resulted in the lowest yields, with 53% and 80% yield reduction, respectively, compared to the fully fertilized treatment with manure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation of measured variables\u003c/h2\u003e \u003cp\u003eFigure S6 shows the correlation coefficients for the collected root and shoot variables for all sampling dates. When correlating the root and shoot variables (all dates), a positive correlation (0.7) was observed between these two variables (Figure S6a). The RLD and root biomass showed the highest correlation coefficient with yield (0.4), among all the variables, including shoot biomass (0.3). As for the temporal differences, the root biomass in dates 1 to 4 was strongly associated with yield (0.6\u0026ndash;0.8), but not on date 5 (0.3) (Figure S6b-S6e). The tiller number was positively associated with yield in most dates (0.1\u0026ndash;0.7), except in date 5. The correlation of root angle with yield was generally positive, except in date 4. The number of nodal roots relationship with yield varied widely in direction and magnitude by dates. The SRL was negatively associated with yield during most dates, except at date, where a weak positive relationship was observed (0.2). Root biomass showed a strong correlation with RLD (06-0.9) in all sampling dates. In the later sampling dates 3 to 5, RLD showed a strong positive correlation with root angle (0.6\u0026ndash;0.7).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study presented the effects of N and P fertilizer omission on winter rye shoot and root growth from tillering to flowering. Our results demonstrated that N and P omission led to a decrease in shoot biomass over time, with stronger reduction in the N omission treatment particularly in the last two sampling dates. These findings align with well-established research showing that N and P availability strongly influence biomass accumulation in rye (Mirsky et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)). In cereals, N application typically leads to substantial shoot biomass increases, whereas P fertilization effects are often less pronounced (B\u0026eacute;langer et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kostic et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)). The reduction in shoot biomass observed in our N and P omission treatments indicates that winter rye, like other cereals, relies heavily on adequate N and P supply for optimal aboveground growth.\u003c/p\u003e \u003cp\u003eWith regard to root traits, our results showed that in this long-term fertilizer trial, N omission was more detrimental than the P omission treatment. This was possibly due to the fact that our root sampling focused on the ploughed topsoil (0\u0026ndash;30 cm), where N-limited plants may not have fully expressed deeper root allocation strategies. Another possible reason is that P amounts in this soil tend to be in sufficient quantities (\u0026gt;\u0026thinsp;50 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to be extracted from the plants, possibly reducing the P omission treatment effect. Plants often allocate more root biomass to deeper soil layers under N deficiency, while under P deficiency, root proliferation tends to be concentrated in the upper soil layers where P is more available (Kumar et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Reduced root biomass has been reported in field studies where N and P omission led to a decrease in root biomass by 7% and 25%, respectively (Lopez et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These findings suggest that while both nutrients impact root development, P deficiency typically results in more pronounced shoot reductions, whereas N limitation tends to affect both shoot and root biomass. Also, a decrease of root biomass in the fully fertilized treatment in date 5 was not reflected in shoot biomass, which indicates an alteration in above and below ground allocation of biomass. Consistent with previous studies, we observed an increase in the R/S ratio under N and P omission. This response is a well-documented adaptive mechanism in plants facing nutrient scarcity (Amanullah, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Under N deficiency, plants allocate a greater proportion of biomass to roots at the expense of shoot growth (Lopez et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This shift is driven by the plant's need to enhance N uptake by expanding its root system. Similarly, P limitation may lead to increased R/S ratio, although the effect varies depending on root plasticity and soil nutrient distribution (Kumar et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lopez et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eP omission tends to decrease the tiller number (Graham et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Rodr\u0026iacute;guez et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). In our results, a trend to decreased tiller number in N and P omission treatments compared to the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment was observed, though not significant for dates 1 and 2, but significant for date 3. However, in date 5, the opposite trend was observed where the P omission treatment resulted in higher tiller numbers compared to the NPKca\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment. In general, under P omission, roots tend to have a wider root angle, due to shallower and broader roots (Bonser et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Niu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This trend was not observed in our results as P omission treatment showed non-significant differences when compared to the fully fertilized treatment. Robinson et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported that root angle was more strongly associated with yield than root number. This was the case in our study for sampling dates 3 and 5 but not in the rest of sampling dates. N omission also showed more steep root angles around flowering (sampling date 5), this shift suggests a strategy to explore more soil volume and thus, allow more resource acquisition (Trachsel et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The effect of N fertilizer on spring barley root phenotypes was assessed by Siddiqui et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) showing a tendency for longer and narrower root angles under manure application in an organic system, compared to the lines grown with mineral fertilizer N supply, which showed shorter and wider root system. In line with that we found that N omission treatment showed more steep root angles around flowering.\u003c/p\u003e \u003cp\u003eOur findings on RLD reduction under N omission align with previous studies, which report that N deficiency leads to a decrease in total root length and RLD across multiple crops, including winter wheat, maize, cotton and sugar beet​ (Anderson, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Barraclough et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hadir et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mehrabi et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xue et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This reduction is particularly evident in the topsoil (0\u0026ndash;30 cm), which may explain our results, as our sampling was limited to the ploughed layer​. Additionally, root morphology responses to P deficiency can be genotype-dependent, meaning that cultivars may exhibit different root system adjustments in response to nutrient limitations (Lopez et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)​. Although our study did not find a consistent decrease in RLD under P deficiency, numerous studies have reported a reduction in root length or RLD under P-limited conditions across various crops. This has been observed in maize (Deng et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sheng et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), oilseed rape (Duan et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), sugar beet (Hadir et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), soybean (Ao et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Otani \u0026amp; Ae, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), common beans (Ho et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Miguel et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ochoa et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), and wheat (Teng et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), as well as in buckwheat, castor, peanut, and sorghum (Otani \u0026amp; Ae, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). The lack of effect of P omission on RLD could be attributed to the fact that we explored only the ploughed soil layer (0\u0026ndash;30 cm), where Kemper et al., (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported that under organic farming conditions winter rye RLD exhibits its highest value. The response of average diameter to nutrient omission was more pronounced in the beginning of the growing period where we observed negative impact of both N and P omission on the root diameter of winter rye. However, around flowering and in later growth stages, we did not find significant differences in average root diameter under either N or P omission, suggesting that these nutrient deficiencies may not strongly influence this trait in winter rye. Similar findings have been reported in other crops, such as potato under N deficiency (Sharifi et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and maize under P omission (Li et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, the literature presents conflicting results, with some studies showing an increase in root diameter under N deficiency (Anderson, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1987\u003c/span\u003e), while others report a decrease (Eghball et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Hadir et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Likewise, P deficiency has been linked to reduced root diameter in maize at specific growth stages (Sheng et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These inconsistencies suggest that root diameter responses to nutrient availability may be species-specific, influenced by environmental conditions, plant developmental stage, or genotype.\u003c/p\u003e \u003cp\u003eOur study did not find significant differences in SRL under either N or P omission, around flowering SRL was significantly lowered under P omission. In contrast, previous studies reported higher SRL under low-nutrient conditions (Ostonen et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Poorter and Ryser (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) explored SRL as an adaptive trait in response to nutrient constraints, drawing parallels with specific leaf area (SLA) adjustments under light limitations. While SLA showed more pronounced changes, SRL responses were less consistent. However, when root types were analyzed separately, they found that lateral roots (often the most active in nutrient acquisition) tended to exhibit higher SRL under nutrient-limited conditions. This could explain why some studies report increased SRL in deficient treatments, whereas our results did not show significant changes, potentially due to differences in root sampling or the specific root types measured.\u003c/p\u003e \u003cp\u003eWith regards to the relationships between traits and grain yield, a positive but only moderate correlation between the number of nodal roots and grain yield was observed. Also, during the last two sampling dates, the number of nodal roots had a tendency to be higher in the P omission treatment, compared to the fully fertilized treatment with manure. A meta-analysis from (Niu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), reported similar findings, where P omission promoted lateral root growth in cereal crops. Grando and Ceccarelli (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), also compared modern barley cultivars, landraces and wild barley and showed that there was a significant increase in the number of seminal roots during domestication, suggesting that there may be a relationship between seminal root number and crop productivity.\u003c/p\u003e \u003cp\u003eIn plant breeding programs, root traits are generally less prioritized for selection because root traits carry large phenotypic variation, particularly under nutrient deficiency conditions, and require labor-intensive field measurements (Maqbool et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Purushothaman et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wissuwa et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, some studies state that architectural traits like root preference for shallow or deep soil layers, root angle, and lateral branching are under strong genetic control (El Hassouni et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lynch, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). El Hassouni et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) tested 25 durum genotypes at five locations with different water regimes. All traits connected to root angle showed a very high heritability and were not affected by the water scarcity after anthesis. In contrast, Robinson et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) tested 216 spring barley breeding lines in pots and found a genetic relationship between seminal root traits and yield ( including field data from 20 sites), but the direction and magnitude of the correlations varied across the environments. In our study, we found a high variability of the root traits across dates and often within treatments. A rather strong positive correlation was observed between shoot and root biomass in most sampling dates, as well as root biomass with final yield, except around flowering. In declining order, the root biomass, RLD, average diameter, no. of tillers, and root angle were associated with final yield across sampling dates.\u003c/p\u003e \u003cp\u003eUga (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) defined so-called root system architecture ideotypes for defined conditions. Promising cereal ideotypes under N deficiency may have steeper, longer, fewer, and thicker roots for an efficient N uptake and accumulation. Especially in the later sampling dates, we observed significantly steeper roots and a trend for lower nodal root numbers in case of N deficiency. The authors also proposed a root cereal ideotype with a greater number of axial roots and shallower axial roots for a more effective capture of topsoil P under low P soil conditions (Uga, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, trade-offs can occur depending on soil nutrient conditions. For instance, while investing in thicker roots may be advantageous when nutrients are abundant, in nutrient-limiting conditions, root hairs and lateral roots may be more effective in capturing available nutrients (Gonzalez et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In the low P conditions, we observed no significant differences of the root angle compared to the fully fertilized treatment but a clear trend for higher numbers of nodal roots in late sampling dates.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe conclude that the environment and development stage at sampling have a strong impact on winter rye root phenotypic plasticity. Effects of fertilizer omission on the shoot are not only easier to determine but also clearer in terms of direction and treatment ranking. However, roots play a critical role in plant adaptation to abiotic stresses, with root characteristics being central to soil exploration and nutrient acquisition. Strategic adjustments in root growth patterns e.g. via breeding or improved site-specific cultivar selection are needed to enable plants to optimize resource use efficiency in sub-optimal environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe presented study has been funded by the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food (BLE) (grant number 2822ABS010), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany\u0026rsquo;s Excellence Strategy-EXC 2070-390732324 (PhenoRob), by DFG \u0026ndash; SFB 1502/1\u0026ndash;2022 project number: 450058266, the Federal Ministry of Education and Research (BMBF) (project \u0026ldquo;Sustainable Subsoil Management-Soil3, Grant 031B0151A), as well as by the European Union (EU horizon project IntercropVALUES, grant agreement No 101081973).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmanullah. (2015). Specific leaf area and specific leaf weight in small grain crops wheat, rye, barley, and oats differ at various growth stages and NPK Source. \u003cem\u003eJournal of Plant Nutrition\u003c/em\u003e,\u003cem\u003e 38\u003c/em\u003e(11), 1694-1708. https://doi.org/10.1080/01904167.2015.1017051 \u003c/li\u003e\n\u003cli\u003eAnderson, E. L. (1987). Corn root-growth and distribution as influenced by tillage and nitrogen-fertilization. \u003cem\u003eAgronomy Journal\u003c/em\u003e,\u003cem\u003e 79\u003c/em\u003e(3), 544-549. \u003c/li\u003e\n\u003cli\u003eAo, J., Fu, J., Tian, J., Yan, X., \u0026amp; Liao, H. (2010). Genetic variability for root morph-architecture traits and root growth dynamics as related to phosphorus efficiency in soybean. \u003cem\u003eFunctional Plant Biology\u003c/em\u003e,\u003cem\u003e 37\u003c/em\u003e(4), 304-312. https://doi.org/10.1071/FP09215 \u003c/li\u003e\n\u003cli\u003eArsova, B., Foster, K., Shelden, M., Bramley, H., \u0026amp; Watt, M. (2020). 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Fine root patterning and balanced inorganic phosphorus distribution in the soil indicate distinctive adaptation of maize plants to phosphorus deficiency. \u003cem\u003ePedosphere\u003c/em\u003e,\u003cem\u003e 22\u003c/em\u003e(6), 870-877. \u003c/li\u003e\n\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"shoot growth, root growth, root:shoot dry mass ratio, crop yield, nutrient stress","lastPublishedDoi":"10.21203/rs.3.rs-6328255/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6328255/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims.\u003c/h2\u003e \u003cp\u003eWe investigated the effects of N and P deficiencies on winter rye growth and root architecture under field conditions.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e \u003cp\u003eSampling was conducted during the 2022 season at the long-term fertilizer experiment Dikopshof, Germany. Four fertilizer treatments were chosen: (1) fully fertilized including manure (m) and supplemental mineral fertilizer (s) (NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s), (2) fully fertilized without manure (NPKCa), (3) N omitted (_PKCa), and (4) P omitted (N_KCa). Shoot biomass and topsoil root biomass, number of tillers, nodal root number, root angle, root length density (RLD), specific root length (SRL), and root diameter were assessed at five growth stages.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e \u003cp\u003eWe found that that grain yield, shoot, and root biomass were highest in the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment and lowest under N omission. Around flowering, a trend for an enhanced root number in the N and P omission treatments was observed. At the same sampling date, the NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s treatment showed significantly higher SRL than the P omission treatment. The RLD increased for all treatments from date 1 to 4, with NPKCa\u0026thinsp;+\u0026thinsp;m\u0026thinsp;+\u0026thinsp;s and N omission treatments showing the highest and lowest RLD, respectively. At the onset of stem elongation, N and P omission led to a significant reduction in average root diameter, P omission promoted higher tiller number and N omission caused steeper root angles.\u003c/p\u003e\u003ch2\u003eConclusions.\u003c/h2\u003e \u003cp\u003eThese findings demonstrate the strong impact of management, environment and developmental stage on root phenotypic plasticity.\u003c/p\u003e","manuscriptTitle":"Winter rye root growth and plasticity in response to nitrogen and phosphorus omission under field conditions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-25 09:39:45","doi":"10.21203/rs.3.rs-6328255/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2025-06-09T04:58:06+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-17T04:52:38+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-14T06:15:42+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2025-04-01T04:47:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-01T04:44:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2025-03-31T04:49:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2c265fc3-7412-440c-b77c-aa6ff56e1714","owner":[],"postedDate":"April 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T15:59:51+00:00","versionOfRecord":{"articleIdentity":"rs-6328255","link":"https://doi.org/10.1007/s11104-025-08088-w","journal":{"identity":"plant-and-soil","isVorOnly":false,"title":"Plant and Soil"},"publishedOn":"2025-12-02 15:57:11","publishedOnDateReadable":"December 2nd, 2025"},"versionCreatedAt":"2025-04-25 09:39:45","video":"","vorDoi":"10.1007/s11104-025-08088-w","vorDoiUrl":"https://doi.org/10.1007/s11104-025-08088-w","workflowStages":[]},"version":"v1","identity":"rs-6328255","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6328255","identity":"rs-6328255","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}