Optimizing Nursery Production of Apple Trees: Assessing the Dose Response to Water and Fertilizer in Two Cultivars

Abstract

This study examined the effects of two apple cultivars (Gala and Jonagold), four irrigation levels (0, 10, 20, and 30 mm), and four fertilization treatments (N₀P₀K₀, N₈P₈K₈, N₁₆P₁₆K₁₆, N₂₄P₂₄K₂₄) on nursery tree density. Jonagold exhibited a slightly higher mean density (95.63 ± 4.790%) compared to Gala (93.50 ± 6.195%). Tree density peaked at 99.38 ± 1.295% under the 30 mm irrigation level and declined with reduced irrigation, while fertilization levels showed no significant independent effect. Both cultivars achieved their highest densities under the 30 mm irrigation level (Gala: 99.25 ± 1.650%; Jonagold: 99.50 ± 0.827%), and several cultivar–fertilizer–irrigation combinations reached 100% density. The lowest density (89.00 ± 6.944%) occurred in Gala under the N₂₄P₂₄K₂₄ treatment without irrigation. Overall, results indicate that irrigation, particularly the 30 mm norm, is the key determinant of maximizing nursery tree density, with select combinations enabling complete survival.

1. Introduction

1.1. Importance of the Nursery Phase

The nursery phase is an important stage in the lives of grafted fruit trees, influencing their productivity and profitability in the orchard. Traditional nursery management usually employs a one-size-fits-all approach, providing uniform amounts of water and fertilizer to an entire block of trees. This approach, while simple, may fail to meet the specialized needs of individual trees or developmental stages, resulting in suboptimal growth and poor productivity.

1.2. Determinants of Nursery Success

1.2.1. Irrigation

Irrigation is crucial for nutrient distribution, root growth, and overall plant health. Even in soils rich in nutrients, a lack of water hinders absorption and limits growth potential [1,2,3]. Well-planned irrigation schedules can greatly enhance yields; however, Romanian nurseries face a significant technological gap. Numerous producers depend on outdated or basic systems, leading to water wastage and inefficiency. These issues are intensified by extreme weather events, including extended droughts and heat waves, which increase water needs beyond what conventional methods can provide. Young fruit trees, with their less developed root systems, are especially susceptible, making accurate irrigation management vital for robust growth and successful orchard establishment [4,5,6,7].

Like all cultivated plants, the growth of fruit trees in nurseries is heavily influenced by climatic and soil conditions. Among the critical factors—heat, light, air, and nutrients—water is especially important, constituting 75–85% (or more) of tree biomass [8,9,10,11]. Thus, water is essential for sustained horticultural productivity, yet high demand and decreasing availability due to climate change pose challenges to economic viability, environmental sustainability, and social equity [12,13,14].

1.2.2. Fertilization

Soil fertility plays a crucial role in the success of nurseries. Proper fertilization guarantees a steady supply of readily available nutrients that meet the needs of each species, rootstock, or scion–rootstock pairing at various growth stages [15]. Contemporary fertilization methods integrate long-term strategies for soil enhancement—like increasing organic matter, implementing crop rotation, and using green manures—with specific applications of mineral fertilizers (nitrogen to promote growth, phosphorus for root establishment, and potassium for resilience against stress) [16,17]. The efficacy of these methods relies on tailoring application rates, timing, and techniques based on the soil’s agrochemical characteristics and the plants’ requirements. During the growing season, fertilizers continue to be the primary nutrient source for horticultural crops [18]. Insufficient levels of nitrogen, phosphorus, or potassium can lead to reduced seedling density and overall growth. The amount of nutrients taken up each year is influenced by factors such as climate, soil type, tillage practices, and the strength of the grafted rootstock–scion combination [19]. Additionally, the genetic factor of the fruit tree planting material plays a vital role in how trees absorb and utilize nutrients. Firstly, the type of species and variety determine the nutritional needs.

In this research, fertilization treatments were restricted to nitrogen, phosphorus, and potassium, as these macronutrients are the main limiting factors for vegetative growth, root development, and initial establishment in nursery apple cultivation. Nitrogen promotes shoot growth and canopy development; phosphorus aids in root formation and energy transfer; and potassium manages osmotic balance, stomatal conductance, and resilience to stress. These roles render NPK the most critical nutrients during the initial year of grafted tree growth. Micronutrients like magnesium, calcium, iron, and zinc were not treated as separate variables because initial soil evaluations at the site revealed that these elements were adequately present to support the growth of young trees, and no deficiency symptoms were observed in the nursery. Therefore, introducing micronutrient variables would have complicated the study without contributing additional explanatory insights regarding the experiment. By concentrating on NPK, the research highlights the macronutrients most likely to limit early growth and survival under the local pedoclimatic conditions. NPK are widely acknowledged as the key macronutrients that limit the growth of young apple trees, affecting root development, canopy growth, and physiological processes [20]. Since initial soil evaluations indicated that micronutrient levels (e.g., Mg, Ca, Fe, Zn) fell within acceptable ranges—and there were no signs of deficiency—micronutrients were not considered as separate treatments, which aligns with established nutrient management practices in apple nurseries.

1.2.3. Cultivar Selection

Selecting the right cultivar establishes the genetic basis for nursery production, affecting how well plants adapt to local soil conditions and climate as well as their resistance to various pests and diseases [21]. While it may have a smaller statistical impact on production variability compared to irrigation or fertilization, cultivar choice is crucial for the inherent growth potential and overall quality of the plants. Utilizing robust and well-suited cultivars lessens the need for corrective measures, ensuring both immediate success in the nursery and lasting stability in the orchard.

1.3. Challenges in Integrated Management

Although irrigation, fertilization, and cultivar selection are crucial, their effective integration in practice is often hindered by systemic challenges. Many nursery operators do not have a thorough grasp of how these elements work together, as this understanding typically originates from years of practical experience [22,23,24]. Financial constraints also limit their access to advanced technologies such as drip irrigation systems, high-quality fertilizers, and certified planting materials [25,26]. Additionally, climate change introduces more uncertainties, with possible droughts or new diseases threatening to disrupt well-structured management strategies [27,28]. The challenges of integrating irrigation, fertilizer, and cultivar in grafted tree production stem not from a lack of desire but from structural obstacles: gaps in knowledge, financial limitations, and the complexity of natural ecosystems. A successful approach necessitates technical knowledge, financial resources, and the ability to adapt to changing circumstances [29].

1.4. Current Limitations in Nursery Water and Nutrient Management

While water and nutrient management are acknowledged as crucial factors for nursery success, there are still several significant knowledge gaps regarding grafted fruit trees. Most of the existing studies on irrigation and fertilization have focused on mature orchards or container-grown systems, leaving the nursery stage less explored, even though it plays a vital role in developing root systems, vigour, and future orchard performance. Specifically, irrigation thresholds that are appropriate for shallow and developing root systems are not clearly defined, forcing managers to rely on findings from orchard studies that may not be suitable for young trees. Additionally, the relationship between water availability and nutrient supply is not well understood: although irrigation significantly affects nutrient uptake, only a limited number of studies have rigorously examined the interactions of various irrigation and fertilization strategies in grafted trees grown in open-field nursery settings. Recent studies emphasize both the potential and the constraints of our current understanding. Duan et al. [30] illustrated in extremely dry areas that the combination of irrigation with high levels of fertilization maximized both crop yield and water-use efficiency in apple orchards, highlighting the crucial role of interactions between water and nutrients. Likewise, Mankotia et al. [31] found that different fertigation schedules in high-density apple orchards not only affected fruit size and yield but also impacted biochemical quality traits, indicating that fertilization interacts with water to influence physiological results. In trials conducted in Europe, subsurface drip irrigation systems notably enhanced the yields and quality of Gala apples when compared to surface irrigation methods [32], while a worldwide meta-analysis of irrigation strategies validated that deficit irrigation techniques can improve water-use efficiency, yet their success is highly dependent on factors like cultivar, climate, and growth phase [33,34,35]. These results underline the significance of integrated management of water and nutrients, but they also point out that most of the evidence is derived from mature orchards rather than nurseries.

1.5. Research Rationale and Objectives

While apple (Malus domestica) cultivars are extensively grown and appreciated for their adaptability to climatic conditions in Romania, their substantial water needs and ineffective soil moisture utilization raise issues amid increasing climate variability [36]. Earlier research has explored the physiology of apple growth and orchard management, but there has been limited focus on quantifying the specific water and nutrient requirements of different rootstocks in nursery settings or on applying these insights toward practical management solutions. This research aims to fill that void by evaluating the following hypotheses: (H1) increasing irrigation within the tested operational range will increase nursery tree density and seedling quality more strongly than proportional increases in NPK alone, because water limits nutrient uptake and root growth in early stages; (H2) cultivar responses will differ, with Jonagold and Gala showing distinct sensitivity to water and nutrient levels; and (H3) water × fertilizer interactions will reveal threshold effects (i.e., a water level above which additional NPK provides diminishing returns), indicating an efficient management frontier that nurseries can adopt. These hypotheses are grounded in recent experimental findings on water-fertilizer coupling in juvenile apples and in broader syntheses calling for integrated water–nutrient management in horticulture [37,38,39]. Our methodological framework merges physiological evaluations with hands-on nursery management to ensure both scientific accuracy and practical usability. The objective of this research is to (i) quantify the effects of incrementally increased irrigation and NPK levels—delivered through a practical drip-fertigation setup—on grafted apple tree density (proxy for production quality), (ii) test cultivar-specific responses (Gala vs. Jonagold) to the same management regimes, and (iii) explore interaction effects (water × fertilization × cultivar) that inform trade-offs between water inputs and fertilizer dosing under local pedoclimatic conditions.

2. Materials and Methods

2.1. Climate and Soil Conditions of the Research Location

The research was conducted in a private nursery in north-western Romania, located at geographical coordinates 47.0722° N, 21.9211° E, Bihor County, Oradea. Climatic conditions were characterised using data sourced from the Meteorological Station of Oradea, situated approximately 5 km southeast of the research site. In 2024, the average annual temperature was 10.7 °C. The coldest month in 2024 was January, with an average temperature of −2.5 °C, and the warmest month was July, with an average temperature of 24 °C. The highest amount of precipitation was recorded in May, totalling 103.8 mm, whereas the lowest precipitation was observed in January 2024, with 12.5 mm, as shown in

Table 1. Average monthly temperatures and average monthly precipitation in 2024 (°C).

Month	Jan.	Feb.	Mar.	Apr.	May	Jun.	Jul.	Aug.	Sep.	Oct.	Nov.	Dec.	Average
Average monthly temperatures (°C)	−2.5	−1.9	4	12.5	16	19.5	24	20	18.3	13.5	7.5	−2.4	10.7
Average monthly precipitations (mm)	12.5	15.7	18	2	103.8	55.6	86.4	30.8	57	63	20.4	54.3	43.29

. Late spring frosts are common in March, given Romania’s climate. Early autumn frosts rarely occur in September, but are common in October and November. Late spring frosts occasionally occur as unexpected climatic events, posing a threat to the normal growth and development of grafted trees. In contrast, early autumn frosts have a minimal adverse impact, as they typically coincide with the end of the grafted trees’ vegetative cycle.

Geomorphologically, the experimental field features a predominantly flat terrain, subtly disrupted by depressions and gravel banks—elements characteristic of floodplain landscapes. A distinctive characteristic of the area is the presence of rolled gravel banks scattered throughout, appearing across all types of micro-relief—whether on gravel ridges, within depressions, or on flat terrain. The experiment involves soils of various textures, formed by fluvial deposits, particularly coarse, and fluvial gravel in various stages of evolution: from young, unevolved soils (alluvial soils—Aluviosols) to cambisols (Eutricambosols) and Preluvosols (former brown clayey alluvial soils). The experiment was carried out on a Preluvosol soil, distinguished by its layered composition, featuring an ochric horizon (Ao), an argic horizon (Bt), which exhibits clay accumulation resulting from migration from the upper layers, and a C horizon, representing the parent rock. The Ao horizon, 20–25 cm thick, is lighter in colour—typically brown or light brown; the Bt horizon, measuring approximately 75 cm in thickness, is characterized by significant clay accumulation and exhibits a more yellowish hue in its upper section. Beneath it, the C horizon consists of unconsolidated rock material. The soil reaction is acidic to slightly acidic, with a pH between 5.75 and 6.35 in the Ao and Bt horizons.

The initial soil analysis in

Table 2. Baseline soil micronutrient composition prior to establishing the experiment.

Micronutrient	Measured Value (mg/kg)	Sufficiency Range (mg/kg)	Interpretation
Magnesium (Mg)	82	50–120	Sufficient
Calcium (Ca)	1120	500–1500	Sufficient
Iron (Fe)	12.4	4–20	Sufficient
Zinc (Zn)	2.8	1–5	Sufficient
pH	6.7	6.0–7.5	Suitable
Organic matter (%)	2.4%	1.5–3.5	Suitable

reveals that the micronutrient levels at the experimental site are generally conducive to the growth of young apple trees. Concentrations of magnesium and calcium are within acceptable limits, indicating sufficient cation exchange capacity and balanced nutrient availability for the early development of roots. Levels of iron and zinc also fall within optimal ranges, suggesting that there should be no micronutrient-related constraints on chlorophyll production, enzymatic functions, or early vegetative growth. With a soil pH of 6.7, the conditions are ideal for apple cultivation, supporting optimal nutrient availability and reducing the likelihood of micronutrient fixation or toxicity issues. Additionally, the organic matter content, measured at 2.4%, is within a favourable range, enhancing soil structure, moisture retention, and the capacity to buffer micronutrients. The vertical distribution of humus indicates moderate fertility across the soil profile, with concentrations decreasing from 1.85% in the upper layer to approximately 1.4–1.7% in the lower layer. This pattern is characteristic of cultivated agricultural soils and suggests that the rooting zone retains adequate humus levels to facilitate nutrient exchange and water retention during the initial stages of tree growth. Notably, humus levels remained above 1% throughout the rooting depth, which helps ensure stable availability of micronutrients.

Nevertheless, despite the assessment of micronutrients, pH, and humus content, there was no pre-experimental evaluation of macronutrients (available N, P, and K). This lack of initial analysis limits the capacity to fully interpret the impact of fertilization treatments, as the baseline status of macronutrients may have influenced the observed minimal response to NPK applications. If macronutrient levels were already adequate, any additional fertilizer may not necessarily result in significant improvements in tree density. On the other hand, if macronutrients were deficient, the consistently high survival rates could suggest that early growth was influenced more by irrigation than by nutrient availability. Therefore, while the data on micronutrients and soil organic matter support a generally fertile environment for initial growth, the absence of macronutrient data should be acknowledged as a limitation when assessing fertilizer impacts.

2.2. Research Methods and Biological Material Used

To achieve the research objectives, a comprehensive experimental framework was employed, structured as a 4 × 2 × 4 factorial design. The study was conducted in five replications, arranged in a Randomized Complete Block Design, with each plot containing four trees arranged at a density of 0.7 × 0.25 m.

Tree density (%) was measured as the proportion of trees that survived and remained viable at the end of the growing season compared to the total number of trees initially planted. The calculation for tree density was performed using the formula below:

$$\mathrm{Tree} \mathrm{Density} (\%)={\displaystyle \frac{\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{u}\mathrm{r}\mathrm{v}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{t}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{s}}{\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{s} \mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{a}\mathrm{l}\mathrm{l}\mathrm{y} \mathrm{p}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{d}}}\times 100$$

A tree was deemed “surviving” if it demonstrated ongoing shoot growth, preserved cambial tissue, and displayed no indications of significant desiccation or necrosis during the final assessment in September 2024.

Irrigation served as the primary factor in the study, encompassing four treatments: no irrigation, and irrigation levels of 10 mm, 20 mm, and 30 mm. The apple cultivars Gala and Jonagold were treated as the secondary factor, while fertilisation was evaluated as the tertiary factor. To obtain the NPK doses corresponding to the fertilisation treatments, complex fertiliser 16:16:16 was used in the following quantities (kg/ha): 50 kg for N₈P₈K₈; 100 kg for N₁₆P₁₆K₁₆; 150 kg for N₂₄P₂₄K₂₄. The fertilizer is water-soluble and is produced by Azomureș, a Romanian manufacturer. Prior analyses of micronutrients performed before the experiment indicated adequate levels of Mg (82 mg kg⁻¹), Ca (1120 mg kg⁻¹), Fe (12.4 mg kg⁻¹), and Zn (2.8 mg kg⁻¹), with all measurements falling within the recommended sufficiency thresholds for nursery apple cultivation. As a result, these nutrients were not treated as separate variables in the experimental setup. Restricting the treatments to nitrogen, phosphorus, and potassium enabled us to focus on the main macronutrients that usually limit the initial growth of apple trees, while avoiding the inclusion of treatment factors for micronutrients, which baseline soil tests indicated were not limiting. The study took place on soils that reflect nursery conditions in northwestern Romania; however, the initial concentrations of available nitrogen, phosphorus, and potassium were not measured prior to the application of treatments. Therefore, the results of the fertilization should be viewed as a reflection of the treatments applied rather than in relation to established nutrient levels. Future research will include a comprehensive chemical analysis of the soil to provide a clearer understanding of the responses to fertilization. By focusing on NPK, our study isolates the macronutrients most relevant to root development and early seedling vigor, without confounding effects of nutrients that were not limiting in our experimental soil.

The irrigation and fertilization levels in our study (0, 10, 20, and 30 mm; N₀P₀K₀, N₈P₈K₈, N₁₆P₁₆K₁₆, and N₂₄P₂₄K₂₄) were chosen based on two practical considerations: (i) their alignment with common nursery management practices in northwestern Romania, and (ii) the technical limitations of the drip irrigation and fertigation system used, which allowed precise water delivery increments of 10 mm and fertilizer dosing corresponding to multiples of 8% of NPK 16:16:16. This factorial structure ensured both feasibility for nursery operators and statistical robustness in evaluating treatment effects.

The statistical software identified the cultivar as ‘JonaGold’ in the exported results. In this paper, we adopt the standardized spelling ‘Jonagold’. Similarly, for easier interpretation, the fertilizer treatments N₀P₀K₀, N₈P₈K₈, N₁₆P₁₆K₁₆, N₂₄P₂₄K₂₄ are shortened to NPKv0, NPKv8, NPKv16, and NPKv24.

For the establishment of field I, the land was prepared by deep plowing to a depth of 35 cm, performed in August 2023. This was followed by the levelling operation (through discing and harrowing) in October.

In field II, in the spring of 2024, a heading-back cut (or pruning to the base/bud) was executed. This was followed by two mechanical cultivations between the rows and four manual cultivations on the row. Furthermore, four manual weeding operations (to remove wild growth) and two tipping/pinching operations of the lateral shoots were also carried out.

For the control of diseases and pests, three treatments were applied using the fungicide Dithane 75 WG (active component: mancozeb; Corteva Agriscience, Indianapolis, IN, USA) at a concentration of 0.2%, along with the insecticide Fastac 10 EC (active component: alpha-cypermethrin; BASF SE, Ludwigshafen, Germany) at a concentration of 0.02%. Both products were sourced through an authorized agricultural supplier in Romania.

The initial biological material for the study consisted of MM 106 apple layer classified under the ‘Certified’ category. Dormant buds from the Gala and Jonagold cultivars were used for grafting. The propagation technique used in this study was chip budding. Early August 2024 was the carefully chosen time for the grafting because late summer is frequently thought to be ideal for bud establishment. Since the cambium of the scion and rootstock is still active at this time of year the graft will unite quickly and heal successfully.

Fertigation was conducted using a drip irrigation system that featured 16-mm hoses (with a wall thickness of 0.4 mm) fitted with pressure-compensated drippers placed at 25 cm intervals, each providing 2 L h⁻¹ at a pressure of 1 bar. The irrigation standards (0, 10, 20, and 30 mm) were maintained by adjusting the duration of the system’s operation: 3.5 h for 10 mm, 7 h for 20 mm, and 10.5 h for 30 mm. Fertigation intervals were determined based on the dynamics of soil moisture. Irrigation was initiated when the soil moisture at a depth of 15 cm reached the minimum threshold (19.85%) for the 10-mm treatment, as measured by the HD2 moisture meter (IMKO GmbH, Ettlingen, Germany). The equipment was sourced through an authorized agricultural supplier in Romania. Consequently, fertigation—and consequently all irrigation—was carried out on four specific dates in 2024: July 20, August 17, August 20, and August 23. The applications were performed in the early morning (from 04:00 to 08:00) to reduce evaporation losses. A fertilizer solution was prepared in a reservoir prior to each application and injected through the drip system to ensure even distribution.

The density of grafted trees per hectare was determined by the number of seedlings in the plot that had suitable vigour to be used as planting material (higher than 1 m and healthy). To ascertain the significance of the differences between the gradations and combinations of the three factors, the experimental data was processed using three-way ANOVA (p = 0.05) and L^p-norm (N = 5). The analysed factors were: Cultivar, with two levels Gala and JonaGold; Water_Norm, with four levels: 0 mm (i.e., without any irrigation), 10 mm, 20 mm and 30 mm and Fertilisation with four levels: NPKv0 (i.e., without any fertilizers), NPKv8, NPKv16 and NPKv24.

The decision to use p = 2.5 was guided by insights from existing literature and preliminary validation before the main experiment. Prior research has shown that p values ranging from 2 to 3 provide a balanced influence of both large and small deviations, thereby increasing the analysis’s sensitivity to changes in growth metrics. For example, Harb et al. [40] illustrated how effective L^p-norms can be in approximating tree structures, underscoring the importance of intermediate p-values in identifying subtle differences in tree morphology. Furthermore, our preliminary tests conducted on a sample of our data indicated that p = 2.5 yielded the most reliable and distinctive outcomes for assessing tree density and growth uniformity. This choice reinforces the reliability of the L^p-norm analysis utilized in our research. Statistical analysis of grafted tree density was conducted through XLSTAT v27.1.3.0 (Lumivero LLC, 1331 17th Street, Suite 404, Denver, CO, USA). The Supplementary Materials (Tables S1–S14) provide all extended statistical data, including ANOVA summaries and Duncan post-hoc comparisons for all factors and interactions.

2.3. Calculations

To assess the direct water usage (or agricultural water demand), a soil water balance was created based on the moisture levels in the soil at both the start and end of each month from April to September.

The soil water reserve (R) was determined using the formula [41]:

R = 100 × DA × H × W

where DA is the bulk density (t/m³); H is the depth of the active soil layer (m); W is the soil moisture content (%).

For the irrigation norm during the vegetation period in the case of a closed-circuit water balance (irrigation hydrological regime without groundwater contribution), the relation is [41]:

∑m = ∑ (E + T) + R_f + R_i − P_v (m³/ha);

where ∑(E + T) is the overall water usage from the soil throughout the growing season; R_f is the amount of available soil water at the conclusion of the growing season, calculated using a formula that factors in the soil bulk density for the specified depth, the depth of the saturated soil layer, and the wilting point for that depth (m³/ha); R_i is the initial amount of soil water available in the wetted layer at the start of the growing season, calculated using a formula similar to the one for the final reserve, but utilizing the field capacity of the soil rather than the wilting point (m³/ha); P_v is the total summer rainfall that is equal to or exceeds 5 mm.

To establish the moment when soil water supplementation through irrigation is necessary, the minimum threshold (Pmin) was determined, which represents the lower limit of soil moisture readily accessible to plants. For medium-textured soils, which include the soil of the experimental plot, the minimum threshold (Pmin) (as a percentage) was calculated using the formula [41]:

Pmin = CO + ½(CC-CO);

where CO is the wilting coefficient (%); CC is the Field Capacity (FC) (%).

The volumetric minimum threshold (m³/ha) was calculated using the formula [41]:

Pmin.vol.=100 × DA × H × Pmin.

For the indirect determination of water consumption, potential evapotranspiration (PET) was estimated using the Thornthwaite method. This method estimates PET as a function of air temperature using the formula [41]:

$$\mathrm{E}\mathrm{T}\mathrm{P}=160{\left({\displaystyle \frac{10\cdot t}{I}}\right)}^a\cdot K;$$

where ETP is potential monthly evapotranspiration (m³ per month); t_n is the mean monthly temperature for which ETP is calculated (°C); I is annual thermal index.

$$I={\displaystyle \sum _{n=1}^{n=12}i}={{\displaystyle \sum _{n=1}^{n=12}\left(\frac{t_n}{5}\right)}}^{1.514}$$

a—empirical coefficient determined by the relation: a = 0.000000675 I²—0.000077 I + 0.01279211 I + 0.49239; K—light coefficient (or correction factor) based on the field’s latitude (for the April–September period: 1.135, 1.3, 1.32, 1.133, 1.225, 1.045).

2.4. Water Consumption for Different Irrigation Conditions

Considering water consumption across various irrigation methods, the analysis identified how precipitation, soil moisture reserves, and irrigation standards contribute to meeting the water requirements of apple seedlings (

Table 3. Sources of water consumption coverage for different irrigation conditions in 2024 (m³/ha).

Year	Irrigation Rate	Total Water Consumption (m3/ha)	Source of Water Consumption Coverage (m3 /ha)
			Soil	Rainfall	Irrigation
2024	0 mm	3.872	0.071	3.162	-
	10 mm	4.020	0.0558	3.162	0.3
	20 mm	4.217	0.0455	3.162	0.6
	30 mm	4.251	0.0189	3.162	0.9

).

In 2024, for the non-irrigated variant, seedlings relied on useful precipitation in a proportion of 81.67% and on the internal soil reserve in an amount of 18.33% to meet their water requirements, as shown in Figure 1. Under the 10 mm irrigation regime, water consumption was covered by precipitation (76.66%), soil reserves (12.88%) and irrigation (7.46%). In terms of water consumption coverage for the variant irrigated with a watering rate of 20 mm, there was a slight reduction in the contribution of precipitation (74.98%) and soil reserves (10.70%) against a significant increase in the contribution of irrigation (14.23%), compared to the 10 mm irrigation rate. Changing the irrigation rate from 20 to 30 mm led to a reduction in the contribution of soil water (4.44%) associated with a constant contribution of precipitation and an increase in the contribution of irrigation (21.17%) to meet the water requirements of the seedlings.

3. Results

3.1. Effect of Fertilisation, Irrigation Level and Cultivar on Apple Tree Density

As indicated in

Table 4. Tree density percentage in relation to cultivar, irrigation level, and fertilisation.

Cultivar	Frequency	Tree_Density (%)
Gala	80	93.50 b ± 6.195
Jonagold	80	95.63 a ± 4.790
Water_Norm	Frequency	Tree_Density (%)
0 mm	40	91.00 c ± 5.987
10 mm	40	92.50 c ± 4.701
20 mm	40	95.38 b ± 5.236
30 mm	40	99.38 a ± 1.295
Fertilisation	Frequency	Tree_Density (%)
NPKv0	40	95.75 a ± 4.882
NPKv8	40	93.75 a ± 6.484
NPKv16	40	94.00 a ± 5.330
NPKv24	40	94.75 a ± 5.665

Lowercase letters (a–c) indicate significant differences in treatment means using post-hoc tests at p < 0.05. Treatments with the same letter are not significantly different.

, the cultivar factor revealed a significant difference in tree density, with Jonagold showing a higher average tree density percentage (95.63 a ± 4.790) in comparison to Gala (93.50 b ± 6.195). The percentage of tree density consistently increased with the amount of water applied, ranging from a low of 91.00 c ± 5.987 at the 0 mm level to a peak of 99.38 a ± 1.295 at the 30 mm level. The highest tree density recorded was 99.38 a ± 1.295 under the 30 mm irrigation level, which significantly exceeded all other water application rates. This table represents the upper limit typically employed in regional nursery practices, as irrigation levels beyond 30 mm were not considered due to their unrealistic management conditions. The notable increase seen at the 20 mm level (95.38 b ± 5.236), when compared to the lower irrigation levels (0 mm and 10 mm, with 91.00 c ± 5.987 and 92.50 c ± 4.701, respectively), underscores the critical importance of sufficient water supply for successful tree establishment. Conversely, varying NPK fertilization levels (N₀P₀K₀ to N₂₄P₂₄K₂₄) did not have a statistically significant impact on tree density. All four fertilization treatments produced similar density results, which ranged narrowly from 93.75 a ± 6.484 (N₈P₈K₈) to 95.75 a ± 4.882 (N₀P₀K₀). The absence of significant differences among the fertilization treatments suggests that, given the soil conditions at the experimental site, the NPK rates applied did not notably affect early tree survival or density. While the baseline levels of micronutrients were adequate, the study did not assess the initial soil levels of N, P, or K; consequently, no deductions can be made regarding the availability of macronutrients prior to the application of treatments.

According to Figure 2, as the irrigation level rises, the tree density for the Gala cultivar generally shows an upward trend. The tree density value is lowest at an irrigation level of 0 mm, with a range of roughly 86 to 96%. The tree density values are consistently higher at the highest irrigation level of 30 mm, typically ranging from 97 to 100%. The tree density is also influenced by the fertilisation treatments (N₀P₀K_0, N₈P₈K_8, N₁₆P₁₆K₁₆, N₂₄P₂₄K₂₄), with N₂₄P₂₄K₂₄ frequently displaying the highest values within each irrigation level. Additionally, as the irrigation level rises, the Jonagold cultivar shows an increase in tree density. Like the Gala cultivar, the lowest tree density values, which range from roughly 91 to 94%, are found at the 0 mm irrigation level. The tree density values are highest at the 30 mm irrigation level, regularly hitting 100% or very nearly. The effects of the various fertilisation methods are also apparent, as N₂₄P₂₄K₂₄ continuously displays high tree density values.

Jonagold shows higher tree density values than Gala under the same conditions when comparing the two cultivars. At higher irrigation levels, this difference becomes more noticeable. At the given irrigation levels, Jonagold often reaches 100% tree density, whereas Gala reaches a maximum of roughly 100% but has a wider range of values. Overall, the findings indicate that a higher percentage of tree density is positively correlated with both using the Jonagold cultivar and raising the irrigation level.

3.2. Effect of Water Norm and Cultivar on Apple Tree Density

At the lowest irrigation level (0 mm), both cultivars showed statistically similar and minimal tree density, with Gala at 90.50 d ± 7.090 and Jonagold at 91.50 cd ± 4.774, indicating that severe water stress negates any cultivar-specific advantage, as shown in

Table 5. Interaction effect of cultivar and irrigation level on tree density percentage.

Cultivar*Water_Norm	Frequency	Tree_Density (%)
Gala_0 mm	20	90.50 d ± 7.090
Gala_10 mm	20	90.25 d ± 4.494
Gala_20 mm	20	94.00 bc ± 5.544
Gala_30 mm	20	99.25 a ± 1.650
Jonagold_0 mm	20	91.50 cd ± 4.774
Jonagold_10 mm	20	94.75 b ± 3.810
Jonagold_20 mm	20	96.75 ab ± 4.644
Jonagold_30 mm	20	99.50 a ± 0.827

“*” is stating that Water_Norm refers to the water-norm applied to each cultivar. Lowercase letters (a–d) indicate significant differences in treatment means using post-hoc tests at p < 0.05. Treatments with the same letter are not significantly different.

. As the water norm increased, Jonagold consistently maintained a numerically higher or equal tree density percentage compared to Gala, and, crucially, demonstrated a significant response at a lower irrigation level. Specifically, Jonagold at the 10 mm norm reached 94.75 b ± 3.810, which was statistically superior to Gala at the same norm (90.25 d ± 4.494) and statistically comparable to the density achieved by Gala only at the 20 mm norm (94.00 bc ± 5.544). At the highest irrigation level (30 mm), both cultivars attained their maximum tree density percentage, with Gala reaching 99.25 a ± 1.650 and Jonagold reaching 99.50 a ± 0.827. These results were statistically indistinguishable, suggesting that under non-limiting water conditions, both cultivars achieve near-perfect tree establishment. The statistically similar high densities across both cultivars at 30 mm confirm that adequate irrigation is the most critical factor for maximizing tree density, although the better performance of Jonagold at intermediate water levels suggests it may be marginally more resilient or efficient under moderate water limitations.

According to Figure 3, at higher irrigation levels, this difference becomes more noticeable between the two apple cultivars. At the given irrigation levels, Jonagold often reaches 100% density, whereas Gala reaches a maximum of roughly 100% but has a wider range of values. Overall, the findings indicate that a higher percentage of tree density is positively correlated with both using the Jonagold cultivar and raising the irrigation level.

3.3. Effect of Fertilisation and Cultivar on Apple Tree Density

For the Gala cultivar, tree density remained remarkably consistent across all NPK fertilisation levels, ranging from a low of 93.00 bc ± 5.912 at N₁₆P₁₆K₁₆ to a high of 94.00 c ± 6.751 at N₈P₈K₈. All four Gala treatments fell into statistically similar groupings (‘bc’ or ‘c’), reinforcing the earlier observation from the main effects analysis that NPK application had minimal, if any, influence on Gala’s establishment success (

Table 6. Interaction effect of cultivar and fertilisation on tree density percentage.

Cultivar*Fertilisation	Frequency	Tree_Density (%)
Gala_NPKv0	20	93.75 bc ± 5.486
Gala_NPKv8	20	94.00 c ± 6.751
Gala_NPKv16	20	93.00 bc ± 5.912
Gala_NPKv24	20	93.25 bc ± 6.950
Jonagold_NPKv0	20	97.75 a ± 3.226
Jonagold_NPKv8	20	93.50 abc ± 6.370
Jonagold_NPKv16	20	95.00 ab ± 4.611
Jonagold_NPKv24	20	96.25 bc ± 3.582

“*” is stating that Fertilisation refers to the treatment applied to each cultivar. Lowercase letters (a–c) indicate significant differences in treatment means using post-hoc tests at p < 0.05. Treatments with the same letter are not significantly different.

). In contrast, the Jonagold cultivar showed a wider, though mostly overlapping, range of responses. The most prominent result is the significantly higher tree density percentage achieved by Jonagold under the N₀P₀K₀ regime (97.75 a ± 3.226). This N₀P₀K₀ result was statistically superior to all four Gala treatments and to the Jonagold NPKv8 treatment (93.50 abc ± 6.370), suggesting that, for Jonagold, the addition of NPK at the 8%/ha rate might have slightly depressed tree density relative to the unfertilised control, or that the baseline nutrient supply was already optimal. The other Jonagold treatments (N₁₆P₁₆K₁₆ at 95.00 ab ± 4.611 and N₂₄P₂₄K₂₄ at 96.25 bc ± 3.582) generally resulted in higher density than Gala treatments but were statistically less dense than the Jonagold N₀P₀K₀ condition.

Across the various fertilisation treatments, the density values for the Gala cultivar remain comparatively constant (Figure 4). At roughly 94%, N₀ P₀ K₀ and N₈ P₈ K₈ and exhibit higher values. The values of tree density for the N₁₆P₁₆K₁₆ and N₂₄P₂₄K₂₄ treatments range from 93% to 93.5%. Conversely, the Jonagold apple cultivar shows a more noticeable fertilisation-based variation in tree density. At roughly 97.5%, the N₀ P₀ K₀ treatment produces the highest density for this cultivar. The values then drop for N₈P₈K₈ and N₁₆P₁₆K₁₆, reaching roughly 93 and 95%.

The most significant difference is noticed with the N₀ P₀ K₀ treatment, where Jonagold reaches approximately 97.5% compared to Gala, approximately 94%. The difference is less pronounced for the other fertilisation treatments.

Despite Jonagold exhibiting somewhat higher density values under the unfertilized condition in comparison to Gala, these variations should be regarded as general trends rather than conclusive evidence of enhanced performance in the absence of nutrients, since they were not consistently significant across all interactions. This experiment did not assess physiological characteristics that could elucidate cultivar-specific responses—such as rooting depth, dynamics of early root growth, efficiency of nutrient uptake, or carbohydrate reserves. As a result, the underlying mechanisms that might contribute to Jonagold’s perceived stability under low-input conditions remain unclear. For future research, it would be essential to include measurements of root architecture, nutrient-uptake efficiency, or physiological interactions between scion and rootstock to ascertain whether Jonagold possesses traits that facilitate improved performance with reduced fertilization.

3.4. Effect of Irrigation Level and Fertilisation on Apple Tree Density

The data overwhelmingly confirm that irrigation level is the dominant factor determining tree density, irrespective of the fertilisation regime. Across all four NPK levels (N₀P₀K₀, N₈P₈K₈, N₁₆P₁₆K₁₆, and N₂₄P₂₄K₂₄), the highest tree density percentages were consistently achieved at the 30 mm water norm, ranging from 99.00 cd ± 0.943 (N₈P₈K₈) to the perfect 100.00 abc ± 0.000 (achieved with N₁₆P₁₆K₁₆). This trend highlights that sufficient water is the prerequisite for maximizing tree establishment success. Conversely, the lowest tree densities for all NPK treatments were recorded at the 0 mm water norm. the interaction analyses revealed more nuanced effects. In the Cultivar × Fertilisation interaction, NPK application had virtually no effect on the Gala cultivar. For Jonagold, the unfertilised control (N₀P₀K₀) resulted in the highest tree density percentage (97.75 a ± 3.226), which was statistically superior to the N₈P₈K₈ treatment, suggesting that the lowest application rate may have been marginally detrimental or that the baseline nutrient supply was already optimal for this cultivar. The most distinct role for fertilisation was observed in the Fertilisation × Water Norm interaction. Under conditions of 30 mm irrigation (low water stress), NPK levels were irrelevant, as all treatments achieved statistically high densities. Conversely, under 0 mm irrigation (high water stress), the N₀P₀K₀ treatment resulted in the highest density (95.00 bcd ± 2.867) within that group, statistically outperforming the highest rate (N₂₄P₂₄K₂₄_0 mm at 89.00 ab ± 6.944). This suggests that NPK application under severe drought conditions may exacerbate stress. Finally, at intermediate irrigation levels, particularly 20 mm, the highest NPK rate (N₂₄P₂₄K₂₄_20 mm) yielded the highest tree density (96.50 a ± 3.689) within that water norm, suggesting that higher NPK rates may be most beneficial when water is moderately limiting (

Table 7. Interaction effect of cultivar and fertilisation on tree density percentage.

Fertilisation*Water_Norm	Frequency	Tree_Density (%)
NPKv0_0 mm	10	95.00 bcd ± 2.867
NPKv0_10 mm	10	93.00 de ± 6.325
NPKv0_20 mm	10	96.00 e ± 5.416
NPKv0_30 mm	10	99.00 e ± 2.211
NPKv8_0 mm	10	90.50 cde ± 7.807
NPKv8_10 mm	10	91.00 de ± 3.801
NPKv8_20 mm	10	94.50 cde ± 7.382
NPKv8_30 mm	10	99.00 cd ± 0.943
NPKv16_0 mm	10	89.50 abc ± 3.598
NPKv16_10 mm	10	92.00 cd ± 5.011
NPKv16_20 mm	10	94.50 cd ± 4.223
NPKv16_30 mm	10	100.00 abc ± 0.000
NPKv24_0 mm	10	89.00 ab ± 6.944
NPKv24_10 mm	10	94.00 ab ± 3.266
NPKv24_20 mm	10	96.50 a ± 3.689
NPKv24_30 mm	10	99.50 a ± 0.850

“*” is stating that Water_Norm refers to the irrigation applied together with each fertilization treatment. Lowercase letters (a–e) indicate significant differences in treatment means using post-hoc tests at p < 0.05. Treatments with the same letter are not significantly different.

).

There is a consistent pattern across all fertilisation treatments: the tree density rises in tandem with the irrigation level (Figure 5). The 0 mm irrigation level yields the lowest density values, which range from roughly 89% to 95%. The 30 mm irrigation level consistently yields the highest density values, with values approaching or surpassing 100% for all fertilisation treatments.

There are some differences when the fertilisation treatments are compared. With tree density beginning higher at 0 mm and then sharply increasing with higher irrigation levels, the N₀ P₀ K₀ and N₂₄P₂₄K₂₄ treatments exhibit a similar pattern. In comparison to N₀ P₀ K₀ and N₂₄P₂₄K₂₄, the N₈ P₈ K₈ and N₁₆P₁₆K₁₆ treatments exhibit lower tree density values at the 0 mm and 10 mm irrigation levels. All fertilisation treatments produce high tree density at the 30 mm irrigation level, with N₁₆P₁₆K₁₆ and N₂₄P₂₄K₂₄ displaying values at or close to 100%.

3.5. Classification of Apple Cultivars Based on Water and Fertilisation Treatments

The grafted apple tree density for different levels of factor interactions can be classified using the L^p-norm. The L^p-norm was calculated using the general p-space normalization formula: $L^p= \sqrt[p]{{\displaystyle \frac{1}{N}}\ast {\sum }_{i=1}^N\left({TreeDens}_i^p\right)}, x\in [0;1]$. The values of the grafted apple tree density for each factor level were scaled (i.e., normalized) in the range [0, 1] with the formula $\left[{TreeDens}_i+{\displaystyle \frac{\mathrm{m}\mathrm{i}\mathrm{n}\left(TreeDens\right)}{\max \left(TreeDens\right)-\mathrm{m}\mathrm{i}\mathrm{n}\left(TreeDens\right)}}\right]$. In our case, p = 2.5 was considered and we derive the values for the interaction factor Cultivar * Water_Norm * Fertilisation in Table 3 and Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10.

Quartiles of L^p-norm for the interaction factor Cultivar * Water_Norm * Fertilisation perform values, in decreasing order of tree density, from: 4, with L^p-norm values range [0.9901; 1.0000]; 3, with L^p-norm values range [0.9510, 0.9901]; 2, with L^p-norm values range [0.9206; 0.9810] and 1, with L^p-norm values range [0.8652; 0.9206].

The interactions between factors: fertilisation (N₀ P₀ K_0, N₈ P₈ K_8, N₁₆P₁₆K₁₆, N₂₄P₂₄K₂₄) and cultivar (Gala and Jonagold) at various irrigation levels (0 mm, 10 mm, 20 mm, and 30 mm) are shown in Figure 6 and Figure 7. Particularly with N₁₆P₁₆K₁₆ and N₂₄P₂₄K₂₄ fertilisation, the ‘L^p-norm’ values for the Gala cultivar are low at 0 mm and 10 mm irrigation levels but greatly increase at 20 mm and 30 mm. Conversely, the Jonagold cultivar exhibits greater ‘L^p-norm’ values at the 0 mm and 10 mm irrigation levels, especially when fertilized with N₀ P₀ K₀ and N₈ P₈ K₈. With lower values for Gala at low irrigation levels and higher values at high irrigation levels, the patterns for “Quartiles” are comparable to those for “L^p-norm”. Jonagold displays a range of values, with high “Quartiles” at irrigation levels of 20 and 30 mm.

Two complementary heatmaps were created to gain a better understanding of treatment impacts across cultivars, water-norm levels, and fertilization regimes. Figure 6 depicts L^p-norm -based median distances, which indicate relative deviations in the total distribution of responses. This statistic is effective for discovering small but persistent differences in variability between treatments. Figure 7 depicts the median of the quartile range, allowing for a more direct evaluation of distributional dispersion and heterogeneity within each treatment combination. Although both figures are based on the same experimental parameters, the different statistical metrics highlight different elements of the data structure. They work together to provide a more robust interpretation of treatment-dependent patterns, highlighting differences that would be difficult to discover with a single summary statistic. This dual-metric visualization improves the reproducibility of the results and allows for a more detailed understanding of cultivar- and treatment-specific responses.

Larger irrigation volumes (30 mm) consistently led to greater tree density among the different cultivars. Figure 6 demonstrates the significant relationship between early establishment and soil moisture, indicating that inadequate irrigation leads to reduced survival and consistency, while sufficient watering facilitates quick root activation and effective graft development. Variations among the cultivars highlight their natural sensitivity to the availability of moisture.

The density of trees primarily increased with the addition of irrigation, whereas variations among NPK treatments were minimal when there was adequate water. Figure 7 illustrates that the impact of fertilizers is limited in conditions of low soil moisture and becomes apparent only after the necessary hydraulic needs are fulfilled. This observation highlights the biological principle that the absorption of nutrients is restricted by water availability in young grafted trees that have shallow root systems developing.

The Lp-norm values and quartiles for various water levels among the apple cultivars are illustrated in Figure 8 and Figure 9. These figures emphasize the different reactions of Gala and Jonagold to increased irrigation, with Gala displaying consistently low values at 0 and 10 mm and significantly high values at 30 mm, whereas Jonagold shows more variability but generally higher values.

Figure 8 illustrates a distinct upward trend in tree density as irrigation levels increased. The most significant enhancement was observed between the non-irrigated control and the 20 mm irrigation treatment, while the increase from 20 to 30 mm was smaller yet still positive. Jonagold typically displayed slightly greater density across various irrigation and fertilization combinations, even in zero-fertilizer conditions. This indicates potential cultivar-specific variations in early nutrient absorption efficiency, root development, or tolerance to possible salt buildup associated with higher NPK levels in sandy soils. Overall, these trends demonstrate that genetic traits significantly influence early establishment responses, interacting with but not entirely reliant on fertilization, while water availability remains the primary factor.

Figure 10 depicts the interaction among irrigation, fertilization, and cultivar in a three-way analysis. The treatments were primarily grouped based on water availability, showing that the greatest tree densities were consistently found under the 30 mm irrigation level. Conversely, non-irrigated treatments created a distinctly low-density cluster independent of fertilization, highlighting the significant effect of soil moisture during the initial establishment phase. Differences between cultivars were also apparent: Jonagold typically fell into the higher density range across most treatment combinations, while Gala demonstrated considerable sensitivity to water scarcity, with very low-density values at 0 and 10 mm and significantly higher values at 30 mm according to both the L^p-norm and quartile assessments. Jonagold exhibited a wider range of values across varying irrigation levels, indicating greater physiological adaptability. While irrigation emerged as the primary factor influencing density, some minor, cultivar-specific responses to NPK were noted at higher moisture levels. Overall, the figure indicates that essential biological processes—such as shoot elongation, expansion of leaf area, and initiation of the root system—are collectively influenced by the availability of water and nutrients, yet become significantly restricted when soil moisture drops below critical levels.

Figure 11 illustrates the combined impact of irrigation and fertilization using a heatmap that encapsulates the overall trends identified in the experiment. The N₀P₀K₀ treatment exhibits marginally higher values at the 10 mm irrigation level, but tree densities remain consistently low across both cultivars under both 0 mm and 10 mm irrigation, irrespective of the fertilization method used. In contrast, significantly greater values are observed at 20 mm and 30 mm, with the most intense red hues consistently seen at the 30 mm irrigation level for all NPK treatments. This trend signifies a strong positive correlation between tree density and increased irrigation, emphasizing that soil moisture is the key factor driving early establishment success. Consequently, the heatmap reflects a biological hierarchy of influencing elements: (1) irrigation as the primary factor governing survival and density, (2) cultivar effects associated with genetic strength and root system traits, and (3) relatively minor contributions from NPK fertilization that depend on moisture levels. The visualization emphasizes the crucial function of sufficient irrigation in promoting nutrient absorption, root activity, and canopy growth during the initial year of graft development. Quartile analysis further confirms these associations. The fourth quartile—representing the highest tree densities—predominantly comprises samples receiving 30 mm irrigation and high fertilization levels across both cultivars, along with the Jonagold treatments at 20 mmNPKv0 and 30 mmNPKv0 that achieved notable densities even without fertilization. The third quartile includes treatments with 10 mm and 20 mm irrigation coupled with elevated fertilizer levels, as well as isolated examples such as Jonagold 10 mmNPKv0 and Gala 0 mmNPKv0, where density remained moderate despite lacking fertilization. The second quartile encompasses a diverse array of treatments from 0 mm, 10 mm, and 20 mm irrigation across all NPK levels for both cultivars, illustrating the transitional phase of density responses. Altogether, these patterns indicate that the L^p-norm classification method effectively differentiates density levels within the Cultivar × Irrigation × Fertilization interplay. Furthermore, the consistent arrangement of treatments across quartiles reinforces the notion that irrigation plays a pivotal role in early nursery tree density, with fertilization providing an additional benefit only when adequate moisture is present.

The horizontal lines represent critical reference levels for both the L^p-norm values (left y-axis) and the L^p-norm quartiles (right y-axis), allowing for direct comparison of distributional shifts between treatments. The major experimental factors are separated by vertical dashed lines, with blue lines marking the boundaries between fertilisation treatments within the GALA cultivar, green lines indicating the transition from GALA to Jonagold, and red lines distinguishing the different water-norm levels (0 mm, 10 mm, 20 mm, and 30 mm). These lines work together to create a visual framework that clarifies how the ordered treatment combinations connect to cultivar, water-norm, and fertilisation categories, making the observed trends easier to interpret.

4. Discussion

This study investigated the impact of consistent irrigation and fertilization methods on the initial growth of grafted apple trees, aiming to offer insights for nursery management techniques specific to different growth stages. The results consistently demonstrate that irrigation is the main factor affecting tree density, while the influences of fertilization and cultivar are secondary and largely dependent on water availability. A significant finding is the strong positive relationship between watering levels and tree density. The irrigation standard of 30 mm resulted in the highest average density for all cultivars and fertilization combinations, confirming the importance of adequate soil moisture during the early establishment phase. These findings align with previous research indicating that increased irrigation enhances dry matter accumulation, water use efficiency, and early survival rates in young apple trees [41]. Additional studies on the early development of roots in fruit trees reveal that a sufficient water supply promotes root initiation and initial shoot growth, further emphasizing the vital role of moisture during the establishment phase [42]. Comparable conclusions have been made regarding high-density plantings, where irrigation or fertigation significantly boosted early growth and yield, even in humid environments [43]. The selection of cultivar also affected the outcomes, with Jonagold exhibiting a slightly greater overall density compared to Gala. Notably, Jonagold maintained high density even without fertilization, which could indicate sufficient initial soil fertility, possible salt stress from over-fertilization in sandy soils, or specific vigour and nutrient-uptake efficiency related to the cultivar. These results are consistent with studies highlighting the significance of genetic traits, rootstock compatibility, and planting density in influencing nursery performance. Differences in root system architecture, nutrient uptake effectiveness, and hydraulic behaviour based on genotype have also been observed in apples, reinforcing the notion that physiological characteristics unique to cultivars can significantly impact early establishment results [44].

Although fertilization interacted with both irrigation and cultivar, its direct impact on tree density was negligible. All NPK treatments produced comparable results when irrigation was sufficient, indicating that the nutrient levels provided were sufficient for initial establishment and that water availability was the main limiting factor [45,46]. This is consistent with previous research suggesting that fertilization promotes vegetative growth and physiological efficiency primarily when water availability is not limited. Investigations into the relationship between water and fertilizer in young apple trees also indicate that irrigation plays a pivotal role in dry matter accumulation, photosynthesis, and water-use efficiency, while the influence of fertilizer is secondary and reliant on the water supply. Low moisture levels in the soil have been found to hinder nutrient absorption due to diminished root function and slower nutrient diffusion, which clarifies why extra fertilizer has minimal impact under inadequate water conditions. Studies that integrate irrigation with fertigation in orchards further highlight that ensuring an adequate water supply enhances nutrient status, vegetative growth, and overall tree performance.

Wider research at the orchard level supports these trends: effective irrigation boosts vegetative growth, canopy development, and overall yield, whereas a lack of water significantly hinders performance. Further studies reveal that water-related factors are strong predictors of apple yield under deficit irrigation, highlighting the crucial role of water management in orchard productivity. Water stress experienced during the establishment stage has also been connected to a decrease in long-term vigour and yield potential in high-density orchards. Our research broadens these insights to the nursery stage, indicating that irrigation has the most significant impact on early tree density. Even though fertilization had little impact on survival rates, research into integrated nutrient management reveals the advantages of combining mineral fertilizers with organic materials, biofertilizers, or precision-applied inputs that are customized based on soil and cultivar properties [47,48]. Insufficient soil moisture has been found to hinder nutrient absorption because of diminished root function and slower movement of nutrients, which clarifies why extra fertilizer has minimal impact in less-than-ideal water conditions [49]. Research that integrates irrigation with fertigation in orchards illustrates that ensuring an adequate water supply enhances nutrient levels, plant growth, and overall tree health [50]. Research conducted at the orchard level supports these trends: effective irrigation promotes vegetative growth, enhances canopy structure, and increases yield, while insufficient water availability significantly hampers performance [51]. Further studies indicate that water-related factors are strong predictors of apple yield in conditions of deficit irrigation, highlighting the critical role of water management in orchard productivity [52]. Water stress during the initial establishment period has also been associated with diminished long-term vigour and yield potential in high-density orchards [53]. Our results build upon these findings by showing that irrigation has the most significant impact on early tree density during the nursery stage. In apple-based systems, integrated nutrient management strategies have been proven to boost yields, improve soil health, and enhance nutrient-use efficiency when compared to traditional fertilization methods alone [54]. The application of organic composites and precision nutrient techniques has also shown potential in optimizing nutrient use while minimizing environmental repercussions [55]. The high densities achieved in some treatments without fertilizer in our research highlight the potential for adaptable, stage-specific nutrient management instead of depending solely on uniform high-dose applications. A key insight from these findings is that nurseries can enhance management efficiency by focusing on irrigation scheduling before modifying fertilization approaches. Given that tree density is significantly influenced by water availability and only slightly affected by NPK inputs, nurseries can either decrease fertilizer usage or apply it more accurately without jeopardizing establishment, thus providing both economic and environmental advantages.

From a physiological perspective, these findings indicate that early growth is more heavily influenced by hydraulic factors than by nutritional ones, highlighting the significance of root activation, vascular development, and preventing moisture stress. Variations in fertilization and cultivar seem to have a more pronounced impact only after these essential hydraulic needs are satisfied.

More generally, this research highlights that the initial performance of orchards results from the interplay between water availability, soil characteristics, and cultivar attributes. By demonstrating that irrigation consistently plays a more critical role than fertilization during the establishment phase, this study lays the groundwork for adaptable nursery practices that promote productivity while optimizing resource use and maintaining resilience amid growing environmental fluctuations.

5. Conclusions

The findings of this research indicate that irrigation is the primary factor affecting early apple tree density in nursery settings. The noticeable increase in density seen with the 20 mm and 30 mm watering treatments highlights the importance of maintaining adequate soil moisture for successful initial establishment. These results are in line with prior studies that suggest a consistent but moderate water supply enhances root growth and minimizes early survival rates in young fruit trees. The variety of the apple tree also significantly influenced survival, with Jonagold exhibiting slightly better survival rates than Gala. Although these differences were statistically significant, the extent was minor, indicating that cultivar impacts tend to diminish when water supply is adequately managed. Conversely, NPK fertilization did not influence tree density within the evaluated range. All fertilizer treatments yielded comparable results, indicating that the rates applied were sufficient for initial survival. Notably, since baseline soil levels of N, P, and K were not assessed, no conclusions can be drawn regarding macronutrient availability before treatment application. Nevertheless, the micronutrient analyses conducted demonstrate that essential trace elements were within adequate ranges, implying that the absence of a fertilizer effect is unlikely related to hidden deficiencies in micronutrients. Overall, these findings underscore that water availability, rather than NPK fertilization, is the key factor influencing early tree establishment under the conditions of this study. When sufficient irrigation is provided, both cultivars attain similarly high establishment rates, and the impact of fertilizers seems minimal during the seedling phase. In summary, the results highlight that irrigation management is the primary factor influencing nursery tree density, while the effects of cultivar and fertilization are secondary, becoming apparent primarily under conditions of limited water availability.

Future research should broaden these findings to include a wider range of cultivars, soil types, and climatic conditions to enhance the overall applicability of nursery management guidelines.