The Soil Fertility Clock (SFC) concept is based on the assumption that the critical content (range) of essential nutrients in the soil is adapted to the requirements of the most sensitive plant in the cropping sequence (CS). This provides a key way to effectively control the productivity of fertilizer nitrogen (N_f). The production goals of a farm are set for the maximum crop yield, which is defined by the environmental conditions of the production process. This target can be achieved, provided that the efficiency of N_f approaches 1.0. Nitrogen (in fact, nitrate) is the determining yield-forming factor, but only when it is balanced with the supply of other nutrients (nitrogen-supporting nutrients; N-SNs). The condition for achieving this level of N_f efficiency is the effectiveness of other production factors, including N-SNs, which should be set at ≤1.0. A key source of N-SNs for a plant is the soil zone occupied by the roots. N-SNs should be applied in order to restore their content in the topsoil to the level required by the most sensitive crop in a given CS. Other plants in the CS provide the timeframe for active controlling the distance of the N-SNs from their critical range.

Reliable prediction of winter bread wheat grain yield (GY) and its qualitative parameters (crude protein (CP) and wet gluten (GL) content, wet gluten yield (GLY)) requires evaluation of the plant nutritional status in the Critical Cereal Window (CCW). The reliability of the forecast depends on the dedicated plant characteristics and the correct selection of the diagnostic plant parts. This hypothesis was verified in a one-factor field experiment carried out in the 2013/2014, 2014/2015, and 2015/2016 growing seasons. The field experiment included applying 0, 40, 80, 120, 160, 200, and 240 kg N ha⁻¹. The N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu content in wheat was determined in two growth stages: (i) beginning of booting (BBCH 40) and (ii) full flowering (BBCH 65). The evaluated plant components included the leaves and stem for BBCH 40 and the flag leaf, leaves, stem, and ear of BBCH 65. Grain yields were very high, significantly responding to the increased rates of fertilizer nitrogen (N_f), with a maximum yield of 11.3 t ha⁻¹ achieved in 2014 (N rate of 209 kg N ha⁻¹), 13.7 t ha⁻¹ in 2015, and 8.6 t ha⁻¹ in 2016 (N rate of 240 kg N ha⁻¹). The CP and GL content also increased linearly in accordance with the N_f rates. At the beginning of the booting stage, the GY forecast based on the content of nutrients in the leaves or the stem was 94%. Meanwhile, a slightly higher yield prediction was obtained for leaves during the full flowering stage (95%). The key nutrients comprised K, Ca, and Mn, accounting for 93% of the GY variability. The accuracy of the GL prognosis at BBCH 40, regardless of the plant part, exceeded 99%. Three nutrients, namely, P, Mg, and Zn, explained 98% of the GL variability, and the GLY forecast was high (97%). Both wheat traits depended on Zn, which buffered the action of N and Mg. At the full flowering stage, the highest, yet slightly weaker, predictions of GL and GLY were obtained for leaves (95% and 92%, respectively). At this stage of winter wheat growth, the significant role of Zn and K and the buffering effect of Cu on the action of both nutrients was apparent. The obtained results unequivocally confirm that the game for winter wheat grain yield occurs within the Critical Cereal Window. In addition, the end result depends on the plant’s N supply during this period and the nutritional status of other nutrients. Application of 40–80 kg N ha⁻¹ fertilizer critically impacted the GY and technological quality. Moreover, micronutrients, including Zn and Cu, influence the GY, GL, and GLY considerably. At the beginning of the booting phase (BBCH 40), winter wheat leaves serve as a highly reliable plant component indicator for evaluating nutrient content and quantitative (GY, GLY) and qualitative (GL) characteristics of grain. Moreover, analysis conducted during BBCH 40 allows the farmer to correct the nutritional status of the wheat, taking into account N and other nutrients as necessary.

The process of winter bread wheat (WW) nutrient management in the Critical Cereal Window (CCW) has a decisive impact on yield component formation and, consequently, the grain yield (GY) and grain protein content (GPC). This hypothesis was verified in a single-factor field experiment carried out in the 2013/2014, 2014/2015, and 2015/2016 seasons. It consisted of seven nitrogen-fertilized variants: 0, 40, 80, 120, 160, 200, and 240 kg N ha⁻¹. The mass of nutrients in ears was determined in the full flowering stage. The mass balance of nutrients (N, P, K, Mg, Ca, Fe, Mn, Zn, and Cu) was determined in leaves and stems. These sets of data were first used to calculate the soil nutrient uptake and then to predict the GY and GPC. Three nutrients, i.e., N, Ca, and Mg, were the main predictors of ear biomass. The set of ear nutrients significantly predicting GY and GE consisted of Ca, P, and Zn. Overall, this indirectly indicates a balanced N status for the ear. A positive nutrient balance in leaves, indicating their remobilization, was found for N, P, Fe, Zn, and Cu. Negative values, indicating a net nutrient accumulation in the non-ear organs of WW, were found for the remaining nutrients. The greatest impact on the GY and its components was observed for the balance of Mg and P but not N. The predictive worth of the nutrient balance for stems was much lower. The GPC, regardless of the type of indicator, depended solely on the N balance. Meanwhile, the main nutrient sources of N and Fe in ears were leaves and stems due to their uptake from the soil. For Cu, the primary source was soil, completed by its remobilization from leaves. For the remaining nutrients examined, the key source for the ear was soil, which was completed by remobilization from leaves and stems. Mg and Ca differed from other nutrients because their source for ears was exclusively soil. They were invested by WW in the ears and non-ear organs, mainly in the stems. The effective use of the yield potential of WW and other cereals requires insight into the nutritional status of the canopy at the beginning of the booting stage. This knowledge is necessary to develop an effective N management strategy and to correct and possibly apply fertilizers to improve both the yield and the GPC.

The mass of nutrients accumulated in the vegetative parts of winter wheat (WW) in the period from the beginning of booting to the full flowering stage (Critical Cereal Window, CCW) allows for the reliable prediction of the grain yield (GY) and its components, and the grain protein content (GPC) and its yield. This hypothesis was verified in a one-factor field experiment carried out in the 2013/2014, 2014/2015, and 2015/2016 growing seasons. The field experiment included seven nitrogen-fertilized variants: 0, 40, 80, 120, 160, 200, and 240 kg N ha⁻¹. The N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu content in wheat vegetative parts (leaves, stems) was determined in two growth stages: (i) beginning of booting (BBCH 40) and (ii) full flowering (BBCH 65). We examined the response of eight WW traits (ear biomass at BBCH 65, EAB; grain yield, GY; grain protein content, GPC; grain protein yield, GPY; canopy ear density, CED; number of grains per ear, GE; number of grains per m⁻²—canopy grain density, CGD; and thousand grain weight, TGW) to the amount of a given nutrient accumulated in the given vegetative part of WW before flowering. The average GY was very high and ranged from 7.2 t ha⁻¹ in 2016 to 11.3 t ha⁻¹ in 2015. The mass of ears in the full flowering stage was highest in 2016, a year with the lowest GY. The highest N mass in leaves was also recorded in 2016. Only the biomass of the stems at the BBCH 65 stage was the highest in 2015, the year with the highest yield. Despite this variability, 99% of GY variability was explained by the interaction of CGD and TGW. Based on the analyses performed, it can be concluded that in the case of large yields of winter wheat, GE is a critical yield component that determines the CGD, and in consequence the GY. The leaf nutrient mass at the BBCH 40 stage was a reliable predictor of the GPC (R² = 0.93), GPY (0.92), GE (0.84), and CED (0.76). The prediction of the GY (0.89), CGD (0.90), and TGW (0.89) was most reliable based on the leaf nutrient mass at the BBCH 65 stage. The best EAB prediction was obtained based on the mass of nutrients in WW stems at the BBCH 65 stage. The magnesium accumulated in WW parts turned out to be, with the exception of TGW, a key predictor of the examined traits. In the case of the TGW, the main predictor was Ca. The effect of Mg on the tested WW traits most often occurred in cooperation with other nutrients. Its presence in the developed stepwise regression models varied depending on the plant part and the WW trait. The most common nutrients accompanying Mg were micronutrients, while Zn, Fe, Mn, and Ca were the most common macronutrients accompanying Mg. Despite the apparently small impact of N, its yield-forming role was indirect. Excessive N accumulation in leaves in relation to its mass in stems, which appeared in the full flowering phase, positively impacted the EAB and GPC, but negatively affected the GE. Increasing the LE/ST ratio for both Mg and Ca resulted in a better formation of the yield components, which, consequently, led to a higher yield. This study clearly showed that nutritional control of WW during the CCW should focus on nutrients controlling N action.

It has been assumed that the long-term impact of a diversified soil use system (SUS) and the continuous application of manure and/or mineral fertilizers (NPK) affects the sustainability of soil fertility components. This influence is manifested through the content and distribution of nutrients, as well as some bioavailable heavy metals in the soil. This hypothesis was verified in 2022 in a long-term field experiment that started in 1957. It consisted of a seven-course crop rotation: potato–spring barley–winter triticale–alfalfa–alfalfa–winter wheat–winter rye and monocultures of these crops plus black fallow. The studies were carried out on three separate fields: black fallow (BF), winter wheat grown in monoculture (WW-MO), and crop rotation (WW-CR). Each of these experimental objects consists of five fertilizer variants (FVs) fertilized in the same way every year: absolute control (AC)—variant without fertilizers for 75 years; farmyard manure—FM; mineral fertilizers—NPK; mixed variant—NPK + FM; mineral fertilizers plus annually applied lime—NPK + L. The second factor was the soil layer: 0.0–0.3 m, 0.3–0.6 m, or 0.6–0.9 m. The obtained results clearly indicate that long-term fertilization with NPK + FM, especially in rotation with legumes, strengthens the eluviation/illuviation processes, decreasing the sustainability of soil fertility. Liming is a factor stabilizing the content and distribution of silt and clay particles in the soil. The key factor determining the content and distribution of micronutrients and heavy metals in the soil was the content of organic carbon (C_org). Its content decreased in the following order: WW-CR (13.2 ± 5.8) ≥ WW-MO (12.3 ± 6.9) > BF (6.6 ± 2.8 g·kg⁻¹). The large variability resulted from a distribution trend with soil depth, which increased as follows: MO ≥ CR > BF. FVs with FM had the highest C_org content. NPK, regardless of the long-term soil use system (SUS), had the lowest content. Among the elements studied, the key one impacting the content of both micronutrients and heavy metals was iron (Fe). The Fe content decreased in the order BL (100%) > WW-MO (90.5%) > WW-CR (85%). The opposite tendency was found for the remaining elements, the content of which was consistent with the content of C_org, which was the highest in CR. The strongest impact of Fe, modified by the SUS, was found for Zn, Pb, and Cd. Despite the differences observed between SUSs, fertilization variants, and soil layers, the content of Fe and Mn was in the medium class, while Zn and Cu were in the high class of availability. The content of Ni was the highest for NPK + FM in WW-CR. The content of Pb was weakly affected by the long-term SUS but showed a strong tendency for accumulation in the topsoil layer. The content of Cd was the highest in BF, where it exceeded the threshold of 0.27 mg·kg⁻¹. The long-term diversified SUS, as the main factor determining the sustainability of soil fertility, makes it possible to indicate the directions of humus accumulation and its distribution in the soil. It turned out to be a key factor, but in cooperation with Fe, it determined the content of micronutrients and bioavailable heavy metals in the soil.

It was assumed that the production of alfalfa in soils naturally poor in available nutrients, such as potassium (K) and calcium (Ca), depends on the use of fertilizers. This hypothesis was validated in an experiment with an alfalfa–grass mixture carried out in 2012, 2013 and 2014 on soil formed from loamy sand that had a low content of available Ca and K. The two-factor experiment consisted of two levels of applied gypsum as a source of Ca (0, 500 kg ha⁻¹) and five levels of PK fertilizers (absolute control, P60K0, P60K30, P60K60 and P60K120). The total yield of the sward was determined by the main seasons of alfalfa–grass sward use. Gypsum application increased the yield by 1.0 t ha⁻¹. The highest yield of 14.9 t ha⁻¹ was obtained on the plot fertilized with P60K120. Based on the nutrient content in the sward, it was shown that the main yield predictor was the content of K in the first cut of sward use. The reliable yield predictors, based on the total accumulation of nutrients in the sward, turned out to be K, Mg and Fe. The nutritional quality of the alfalfa–grass fodder, based on the K/Ca + Mg ratio, depended mainly on the season of the sward use, which was substantially deteriorated by the K fertilizer. Gypsum did not control this process. The productivity of the nutrients taken up by the sward depended on the accumulated K. Its yield-forming effect was significantly limited by manganese deficiency. The use of gypsum positively affected the uptake of micronutrients, consequently increasing their unit productivity, especially of manganese. Optimization of the production of alfalfa–grass mixtures in soils poor in basic nutrients requires micronutrients to be taken into account. Their uptake by plants can be limited by high doses of basic fertilizers.