*4.1. Seed Density and Yield*

The basis of a soil productivity evaluation in a field experiment is the yield obtained on a plot without application of fertilizer nitrogen (Nf), i.e., N control plot. A crop response to the applied Nf indicates its potential productivity, assuming an optimization of N supply [15,30]. The study clearly showed that the natural, indigenous productivity of the studied sites, with respect to its content in spring (Nmins), differed significantly. The order of sites, assuming a 10% difference between sites [(Sn-Sn-1)/Sn < 0.1], as the discrimination criterion was as follows:

$$\text{Do (2.93)} \ge \text{Ko (2.65)} > \text{Go (2.28)} \ge \text{Wi (2.10)} \ge \text{Ve (2.01)} > \text{Bu (1.41 t ha}^{-1}).$$

The order obtained clearly indicates that the fields located at Do and Ko were, irrespective of year, the most productive. On both these sites, the indigenous N content in spring was low compared to the other sites, but the content of available K and Mg was high, consequently creating favorable conditions for enhancing N productivity, as corroborated by high values of the PFPN index (Tables 2 and 5). It has been recently documented that a shortage of these nutrients disturbs the development of yield components during both the onset of flowering and SFP [11,25,31,32]. The second group of studied sites, showing a relatively high Ni productivity, comprised three sites, i.e., Go (2009), Wi (2010), and Ve (2011). The main reason for the high yield was the high content of Nmins at Go and Ve, which exceeded 100 kg ha−<sup>1</sup> (Table 1). The fertility level of soil at Wi, including Nmins content, was only moderate. The third group, with the lowest yield, comprised only one site, i.e., Bu (2010).

A different order of sites was obtained based on the Nf optimum (Nfop) or Nfmax, taking into account the mode of yield response to the applied Nf, i.e., quadratic and linear, respectively:

1. Ve (4.46) > Do (4.01) ≥ Wi (3.79) ≥ Ko (3.63) = Bu (3.59) > Go (3.14 t ha−1);

2. Yield increase: Ve (+2.45) > Bu (+2.18) > Wi (+1.69) > Go (+1.38) > Do (+1.08) ≥ Ko (+0.98).

The highest yield was harvested at Ve, where it increased linearly in relation to the applied Nf. The same type of response was found for Wi, but at a much lower level. This type of WOSR response to Nf indicates that the Nf rate of 160 kg ha−<sup>1</sup> was too low to maximize crop productivity in these two sites. A limited supply of N to WOSR plants during pre-flowering growth results in a significant decrease in PD and SD, i.e., yield components determining the sink strength [11,33]. A slightly lower yield response to Nf, as compared to Ve, was recorded for Bu. In this site, a Nf of 104.3 kg ha−<sup>1</sup> was sufficient to reach the maximum yield. The same type of response was the attribute of the other three sites, located at Go, Do, and Ko. The quadratic response model of Nf impact on WOSR yield indicates

the occurrence of factors constraining Nf productivity. In this case, the most probable reason for the limited Nf productivity was the shortage of nutrients other than N during SFP, which are responsible for the supply of assimilates to the growing pods and seeds [34,35].

Yield of WOSR was significantly driven by SD. The course of weather in a particular growing season was revealed as a decisive factor, impacting the course of the obtained trends. As shown in Figure 2, WOSR yield in 2009 fitted the quadratic regression model the best, indicating a saturation status of SD. In this exact year, an SD of 90.2 m<sup>−</sup><sup>2</sup> resulted in the Ymax of 3.661 t ha−1. In the other two years, irrespective of the site, yield increased linearly with the increased SD. The impact of the N pools on SD was analyzed based on the effect of:

(1) Indigenous N (Nmins, control N plot):

> Ko (57707) > Do (49646) ≥ Go (49562) > Ve (39935) > Wi (34135) > Bu (27745 seeds m<sup>−</sup>2).

(2) N input (Nin) for Nfop or Nfmax for respective treatments:

> Ko (83612) ≥ Ve (76463) >Do (67810) ≥ Go (66312) ≥ Bu (59755) ≥ Wi (56359 seeds m<sup>−</sup>2).

The net SD increase in response to Nfop or Nfmax was as follows:

Ve (36528) > Bu (32010) > Ko (25905) > Wi (22224) > Do (18164) ≥ Go (16750 seeds m<sup>−</sup>2).

**Figure 2.** Regression models of seed yield response to seed density in particular years.

The obtained order of sites clearly stresses the impact of Nf on SD, which was the highest in the most productive sites with respect to the agronomy class, i.e., at Ve, and Bu. However, SD depends not only on the supply of N but also on the supply of other nutrients such as K and Mg during SFP [25,31,36]. The final yield of WOSR does not depend only on SD but is significantly corrected by the supply of assimilate to the growing seeds during the SFP [34]. The lower yield, as recorded in 2009,

irrespective of the site, was due to lower TSW, in spite of a reasonably high SD (Table 3). The observed phenomenon, known as the yield compensation mechanism, can be explained by a natural decrease in radiation use e fficiency in WOSR during SFP [37]. In fact, the lower TSW was due to a significantly higher SD, resulting in a dilution of dry matter in the growing seeds.

#### *4.2. Seed Nitrogen as Yield Driver*

As shown in Figure 1a,b, the amount of N accumulated in seeds at WOSR harvest, i.e., seed nitrogen (Nse), showed the strongest impact on yield. A close relationship was observed between Nse, treated as a single predictor, and yield. The relationship obtained followed the linear regression model:

$$\text{Y} = 0.023 \text{N}\_{\text{sc}} + 0.685 \text{ for } \text{n} = 24, \text{R}^2 = 0.92, \text{ and } p \le 0.001. \tag{16}$$

The regression model developed clearly shows that any increase in the Nse at harvest resulted in the higher yield of seeds. The relationship obtained is corroborated by the simultaneous increase in both Nse and yield in response to the progressive Nf rate (Tables 3 and 4, and Table A3). An Nse increase is also recorded after application of other nutrients, resulting in an increase of N content in WOSR seeds [35,38]. As reported by Fordo ´nski et al. [19], the significant relationship between Nc in seeds and yield was only found when wheat was a preceding crop for WOSR, but not when this crop followed peas or faba beans. This type of dependency indicates a lower supply of N to WOSR when cereals preceded WOSR. The finding obtained as shown by Equation (16), is indirectly supported by the study by Ho ffmann et al. [13], who presented data on Nse, but without an analysis of its relationship with yield. The regression model developed based on Ho ffmann's data gave an even better estimation of WOSR yield dependence on Nse than our own:

$$\text{Y = 0.038N}\_{\text{se}} + 0.948 \text{ for } \mathbf{n} = 16, \mathbf{R}^2 = 0.95, \text{and } p \le 0.001. \tag{17}$$

The high reliability of these two presented regression models indicates the significant response of Nse to the applied Nf rates. There remains, however, a question concerning the yield forming importance of Nse, which summarizes the e ffect of two components, i.e., SD and the Nc in seeds at harvest. As shown in Tables 3 and A1, SD responded significantly to the applied Nf rate, but the type of response was site-specific. In four of six sites, the e ffect of Nf followed the quadratic regression model, indicating a saturation SD status with respect to the rate of applied Nf. In the other two cases, the Nf rate was too low to maximize SD, subsequently indicating a shortage of N supply to the growing pods and seeds during the SFP. This model also indicates a lack of synchronization between the rate of seed growth and the rate of N remobilization from vegetative WOSR organs during SFP [11]. The Nc in seeds, with the exception of 2009, increased progressively with the applied Nf rate. As a result, WOSR seeds in these two years, in spite of the same SD, accumulated significantly more N (Figure 3). The direction coe fficient for the 2010/2011 regression model was by 50% higher as compared to that developed for 2009. The di fference obtained indicates, irrespective of weather, a better supply of N to the growing seeds during SFP, consequently resulting in higher yield (Equation (16). These two models clearly support the hypothesis of the sink strength dominance over the source strength with respect to seed yield [39]. The result obtained clearly demonstrates that WOSR plants well-supplied with N during the SFP have a potential to minimize the competition for assimilates between growing seeds and their weight (TSW), consequently leading to a higher seed yield [11]. In this study, yield showed, in spite of the important impact of weather in consecutive years, a positive and significant response to all yield components:

$$\text{Y} = -4.26 \, ^{\*\*\*} + 0.0002 \text{PD} \, ^{\*\*\*} + 0.11 \text{Se/PD} \, ^{\*\*\*} + 0.0003 \text{SD} \, ^{\*\*\*} + 0.61 \text{TSW} \, ^{\*\*\*} \text{ for n} = 24, \text{R}^2 = 0.99. \tag{18}$$

**Figure 3.** Regression models of seed density impact on the seed nitrogen.

#### *4.3. Impact of the In-Season N Supply on Nse and Yield*

In this study, it has been assumed that Nse is significantly affected by the N supply to WOSR plants during the growing season. The total pool of N, termed as total N input (Nint) is composed of three sub-pools. The first N source, defined in this study as the N input (Nin), comprised two sub-pools of N. The first one, the indigenous N (Ni), is equal to the Nmins content in the rooted soil zone in spring [17,21,23]. The Ni affects Nse on the N-non fertilized plot. The second N source for WOSR plants during the growing season is equal to the N dose applied in fertilizer. The third N pool is the amount of N released from N soil resources during WOSR spring vegetation. The maximum Nse depends, however, on the optimum N supply to WOSR from all N pools (Nintop) or to its maximum (Nintmax) supply. These three N pools were used as criteria for a site evaluation with respect to Nse:

(1) Nse response to Ni:

> Do (102.5) ≥ Ko (93.1) > Wi (71.0) ≥ Go (66.7) ≥ Ve (66.1) > Bu (46.1 kg ha−1);

(2) Nse response to Nin, i.e., Nseinop or Nseinmax:

> Do (153.2) ≥ Ve (145.8) > Ko (131.2) ≥ Wi (125.2) ≥ Bu (124.2 kg ha−1) > Go (95.1, kg ha−1);

(2) Nse net increase with respect to the N control:

> Ve (+79.7) ≥ Bu (+78.1) > Wi (+54.2) ≥ Do (+50.7) > Ko (+38.1) > Go (+28.4 kg ha−1);

(1) Nse response to Nint, i.e., Nseintop or Nseintmax:

Do (162.7) ≥ Ve (152.9) > Ko (135.1) ≥ Bu (123.0) ≥ Wi (116.4) > Go (91.9, kg ha−1);

(3) Nse net increase with respect to Nin:

> Do (+9.5) > Ve (+7.8) > Ko (+3.9) > Bu (−1.2) > Go (−3.2) > Wi (−8.8 kg ha−1).

The first row clearly shows that fields at Ko and Do were naturally the most productive, as results from the highest Nse at harvest. On the opposite site are fields at Bu and Ve, which increased Nse the highest in response to Nf application during the growing season. The third group of sites is

represented by the field at Go, which showed only a moderate productivity of Ni and low response to Nf. The highest productivity of N as recorded in 2011 was due to a high response of Nse to the amount of N released from the soil N resources during the spring growing season. The shortage of N supply to WOSR plants from the indigenous N pools during the spring growing season, as recorded for three sites, i.e., Bu, Go, and Wi, resulted in yield stagnation. The results obtained explain the observation presented by Grzebisz et al. [11]. According to these authors, the shortage of N during SFP, leads to an SD decrease, consequently resulting, as shown this study, in a decline of both, i.e., Nse and yield. This study corroborates the observation by Barłóg and Grzebisz [15], who documented that the Nc in leaves at the onset of pod growth (BBCH 71) is probably due to a net supply of N to the growing seeds, which explains 81% of yield variability.

The Nsemax, irrespective of the N pool, was revealed as a significant discriminator of the studied sites with respect to yield (Table A5). The linear regression model obtained showed the same level of accuracy for Nin and Nint in yield prediction (Figure 4). The lowest WOSR yield as a result of low Nsemax was characterized by the field located at Go. The main reason for low Nsemax was the low efficiency of N in the soil/WOSR system (46% vs. 37% for Nin and Nint, respectively). The second group, with a significantly higher Nsemax, concomitant with a moderate yield level, comprised three sites, i.e., Ko, Bu, and Wi. This group was characterized by a high efficiency of Nin (60–70%), but a low efficiency of Nint (32–38%). The gap obtained indicates a low efficiency of N released from soil N resources during the growing season. The third group comprised two sites, i.e., Do and Ve, which yielded the highest due to both a much higher Nsemax, and Nint efficiency. The key difference between these two sites resulted from differences in N efficiency. The field located at Ve was characterized by a moderate use efficiency of Nin (58%), and the field located at Do by the high efficiency of Nint (44%).

**Figure 4.** WOSR yield prognosis based on Nsemax calculated for the N input to the soil/plant system at the beginning of WOSR spring regrowth and its total input.

The next question formulated during the study referred to the applicability of Nf, Nin, and Nint as yield prognostic tools. Excluding Nf, because its rates were the same in all experiments, the yield prognosis, based on Nin and Nint, was slightly better for the total N input:

$$\text{(1)}\ \text{N}\_{\text{in}} \colon \text{Y} = -0.000034 \text{N}\_{\text{in}}\text{ }^2 + 0.0178 \text{N}\_{\text{in}} + 1.324 \text{ for } \text{n} = 24, \text{R}^2 = 0.48, p \le 0.05,\tag{19}$$

$$\text{(2) N}\_{\text{int}} \colon \text{ Y = 0.009N}\_{\text{int}} + 0.592 \text{ for } \mathbf{n} = 24, \mathbf{R}^2 = 0.61, p \le 0.001. \tag{20}$$

The maximum yield, calculated based on equ. 19, for the Ninop of 261.8 kg ha−<sup>1</sup> was 3.654 t ha−1. The linear model for Nint corroborates the importance of N released during the SFP for exploitation of the WOSR yielding potential due the better supply of N to the growing seeds.

Nitrogen use efficiency (NUE) can also be used as a criterion for site discrimination with respect to the key yield driving factor, i.e., Nse. The NUE indices as shown in Table 5, in a major part corroborate the opinion expressed by Bouchet et al. [40] about the limited possibility of NUE improvement with respect to the increase of the seed yield of WOSR. The results obtained are in line with this opinion because the developed NUE indices, such as PFPN, AEN, PEN, R decreased in accordance with the increasing Nf rate (Table 5). In spite of this, the best criterion for the study site discrimination was the PFPN, but only for an Nf rate of 160 kg ha−1. The order of sites obtained based on the PFPN160 was as follows:

Ve (27.9) > Do (24.5) ≥ Wi (23.6) ≥ Ko (23.0) > Go (18.4) ≥ Bu (18.3; kg seeds kg−1N).

The order obtained was significantly correlated with Nsemax, as calculated, based on Ninop/max or Nintop/max:

$$(1)\ \text{N}\_{\text{in}} \colon \text{N}\_{\text{semax}} = 4.279 \text{PFP}\_{\text{N16O}} + 32.36 \text{ for } \text{n} = 6, \text{R}^2 = 0.61, p \le 0.05,\tag{21}$$

$$\text{(2) N}\_{\text{int}} \text{: N}\_{\text{semmax}} = 5.248 \text{PFP}\_{\text{N160}} + 11.65 \text{ for } \mathbf{n} = 6, \mathbf{R}^2 = 0.57, p \le 0.05. \tag{22}$$

These two equations are contradictory to the opinion expressed by Bouchet et al. [40]. The relationships obtained clearly showed that Nse responded positively to the increasing PFPN, including the site factor. This seemingly contradictory effect of N fertilizer on WOSR yield and NUE indices indirectly corroborates the hypothesis on Nse as the driving yield factor. This hypothesis is in accordance with the sink hypothesis presented by Körner [39]. This author clearly stated that sink strength in seed crops is a factor determining the source activity, and the consequent yield. On the other hand, too high Nc in seeds leads to decline in the crude oil concentration [41].
