Cytokinin- and Auxin-Based Plant Growth Regulators Enhance Cell Expansion, Yield Performance, and Fruit Quality in ‘Maxi Gala’ Apple Fruits in Southern Brazil

Abstract

Cytokinin- and Auxin-Based Plant Growth Regulators (PGRs) are commonly employed to increase fruit size due to their ability to modulate cellular structure. This study aimed to evaluate the effects of different PGR application protocols on histological parameters, yield components, and fruit quality in ‘Maxi Gala’ apple. The experiments were carried out under humid subtropical conditions of southern Brazil across two growing seasons (2021/22 and 2022/23), allowing comparison of treatment performance under distinct climatic patterns. Data from common treatments were combined across years for integrated analysis. The PGRs used included 6-benzyladenine (BA) as a cytokinin source; naphthalene acetic acid (NAA) as an auxin source; and tryptophan, a precursor of auxin biosynthesis. PGRs were applied in various combinations and concentrations between 10 days after dormancy break (BBCH 01) and fruit diameters of 25–27 mm (BBCH 74), following a randomized block design with four replicates of twelve trees each. The multivariate analysis of treatments was performed using Principal Component Analysis (PCA). Additionally, an analysis of variance was performed for flesh firmness loss, with means compared using Tukey’s test (p < 0.05). PGRs significantly influenced only the histological parameters of the fruit flesh tissues. BA and tryptophan had the greatest effects on cell size and cell number in the fruit flesh, respectively, both reducing intercellular spaces. Tryptophan was associated with a higher number of smaller cells, whereas NAA promoted larger cell sizes. The combination of BA and NAA, as well as a single application of BA at petal fall, resulted in the highest yield performances and increased the proportion of large fruits. Furthermore, BA enhanced the percentage of red skin coloration and improved flesh firmness during storage.

1. Introduction

The association of high yield with fruit quality is essential to meet consumer market expectations and enhance the profitability of apple orchards. Fruit size is one of the most relevant yield parameters, as it significantly influences both market acceptance and overall yield performance [1]. The increase in fruit size depends on multiple factors, including edaphoclimatic conditions, integrated crop management, and, above all, the genetic characteristics of the cultivar [2].

In Brazil, approximately 60% of apple production corresponds to the ‘Gala’ group, which typically yields small to medium-sized fruits [3]. Increasing fruit size involves complex physiological processes, particularly the formation and expansion of cells in the fruit flesh. In Japanese plum, cell division occurs mainly during the first weeks after flowering, extending up to approximately 20–30 days after full bloom (DAFB), followed by a prolonged cell expansion phase lasting until around 80–100 DAFB, depending on temperature and cultivar [2,4,5,6]. These developmental phases are strongly influenced by environmental conditions such as temperature and light, which regulate hormonal activity and assimilate allocation. Increases in both the number and size of these cells are often associated with a reduction in intercellular space, which can positively influence flesh firmness during storage [4,6].

Management techniques that promote cell division in the fruit flesh are of great interest, and one of the most effective strategies is the use of plant growth regulators (PGRs), particularly those belonging to the cytokinin and auxin groups [5,6,7]. Hormonal regulation of fruit development involves a dynamic interplay among auxins, cytokinins, gibberellins, abscisic acid, and ethylene, rather than isolated effects of a single compound. Cytokinins and auxins, in particular, act synergistically to modulate cell division and differentiation, but their effects depend on tissue sensitivity, developmental stage, and hormonal balance [8,9]. This intricate cross-talk regulates flower abscission, fruit retention, and final fruit size, highlighting the need to evaluate PGR combinations that act through different hormonal pathways [10,11]. Recent studies in apple have reported PGR-dependent improvements in fruit set, size, and quality using CPPU (forchlorfenuron), BA, and NAA under temperate conditions [11,12]. At the mechanistic level, work on apple fruit development links PGR responses to cell-cycle regulators (e.g., CYCD-type cyclins) and cell-expansion factors (e.g., expansions), supporting a coordinated control of cell number and enlargement [13,14]. However, for ‘Maxi Gala’ under Brazilian high-altitude, humid subtropical conditions, evidence remains lacking regarding the optimal compound, dose, and timing (DAFB), and whether single or combined applications translate into histological gains, yield performance, and fruit quality.

Important aspects remain poorly understood, particularly regarding the optimal plant growth regulator, dose, and timing of application under Brazilian high-altitude conditions. In ‘Maxi Gala’ apple trees, little information exists on how single versus combined applications of cytokinin- and auxin-based PGRs influence fruit development stages, such as cell division and expansion, or how these treatments affect the histological determinants of fruit size, including cell number and cell enlargement. This study advances the field by jointly evaluating BA, NAA, and tryptophan in ‘Maxi Gala’ apple trees under subtropical highland conditions across two growing seasons, integrating histological, yield performance and fruit quality parameters, and multivariate (PCA) analyses. A combined mechanistic evaluation encompassing an auxin precursor (tryptophan) alongside cytokinin- and auxin-based regulators under documented seasonal contrasts has not been previously reported. This approach provides new insight into hormonal interactions affecting fruit cell expansion and overall fruit quality in highland regions of southern Brazil.

2. Materials and Methods

2.1. Experimental Area

The experiments were conducted in a ‘Maxi Gala’ apple orchard located in the municipality of Vacaria, State of Rio Grande do Sul, Southern Brazil (28°26′ S, 50°51′ W), at an average altitude of 920 m above sea level. The climate of the region is classified as humid mesothermic (Cfb) according to the Köppen classification [15]. Daily data on average, maximum and minimum temperature (°C), rainfall (mm), chilling period and hours (hs) were recorded by the A880 automatic station of the National Institute of Meteorology [16]. The soil is a typical dystrophic bruno oxisol [17], with high clay content (430 g kg⁻¹) and organic matter (95 g kg⁻¹). The orchard, established in 2009, consists of ‘Maxi Gala’ apple trees grafted onto ‘M.9’ rootstock, trained as Tall Spindle trees with a spacing of 4.0 m × 0.7 m, equivalent to 3571 trees per hectare.

2.2. Experimental Protocol

The treatments included nine protocols consisting of different combinations of benzyladenine (BA), naphthalene acetic acid (NAA), and tryptophan (TRY) (

Table 1. Plant growth regulators (PGR) protocols of naphthalene acetic acid (NAA), 6-benzyladenine (BA), and tryptophan (TRY) applied at different spray timings and phenological growth stages in ‘Maxi Gala’ apple trees in the highland region of Southern Brazil, during the 2021/22 and 2022/23 growing seasons.

Treatments	Spray Timing at Different Phenological Stages
	S1	S2	S3	S4	S5
	10 Days After Bud Break BBCH * 01	Full Bloom BBCH 65	Petal Fall BBCH 67	Fruits 8–10 mm BBCH 71	Fruits 25–27 mm BBCH 74
Control	-	-	-	-	-
BA-S1	BA-60 mg L−1	-	-	-	-
BA-S2	-	BA-10 mg L−1	-	-	-
BA-S3	-	-	BA-10 mg L−1	-	-
BA-S1 + S3	BA-60 mg L−1	-	BA-10 mg L−1	-	-
BA-S1 + S2	BA-60 mg L−1	BA-10 mg L−1	-	-	-
BA-S1 + S2 + S3	BA-60 mg L−1	BA-10 mg L−1	BA-10 mg L−1	-	-
BA + TRYP	BA 60 mg L−1	BA-10 mg L−1 + 2 g ha−1 tryptophan	BA-10 mg L−1 + 2 g ha−1 tryptophan	-	-
BA + NAA-6	BA 60 mg L−1	BA-10 mg L−1 + 6 mg L−1 NAA	BA-10 mg L−1 + 6 mg L−1 NAA	-	-
** BA + NAA-10	BA 60 mg L−1	BA-10 mg L−1 + 10 mg L−1 NAA	BA-10 mg L−1 + 10 mg L−1 NAA	-	-
** BA-S2 + S4	-	BA-10 mg L−1	-	BA-10 mg L−1	-
** BA + NAA-S2 + S4 + S5	-	BA-10 mg L−1 + 6 mg L−1 NAA	-	BA-10 mg L−1 + 6 mg L−1 NAA	BA-10 mg L−1

NAA: naphthalene acetic acid; BA: 6-benzyladenine; TRYP: tryptophan. * BBCH (Biologische Bundesanstalt, Bundessortenamt and Chemical industry) phenological growth stages of all mono- and dicotyledonous plant species scale, according to [18]. ** Treatments added to the protocol and evaluated only in the 2022/23 season.

). Applications were carried out at different phenological stages of the plant, as follows:

S1 = 10 days after dormancy break (BBCH 01);

S2 = full bloom (BBCH 65);

S3 = petal fall (BBCH 67);

S4 = fruit at 8–10 mm diameter (BBCH 71);

S5 = fruit at 25–27 mm diameter (BBCH 74).

The experiments were conducted in a randomized block design with four replications, each plot containing twelve trees, with four trees serving as the experimental unit and eight as border plants. Based on the results from the first growing season, the experimental protocol was refined for the 2022/2023 growing season by adding three additional treatments to verify and extend the first-year findings, specifically targeting (i) timing refinement across key developmental stages and (ii) cytokinin–auxin co-application strategies. These adjustments were made while maintaining the same experimental design, replication structure, and measurement protocols to ensure comparability between growing seasons.

The PGRs were applied using the following active ingredient (a.i.) concentrations and commercial products:

(a)

BA (MaxCel^®, Valent BioSciences, Libertyville, IL, USA);

(b)

NAA, 95% concentration;

(c)

L-Tryptophan (C₁₁H₁₂N₂O₂).

No surfactant or adhesive was added to the spray solution in any of the protocols.

The selection of PGR concentrations was based on previous studies reporting effective ranges for cytokinin and auxin analogs in apple under comparable environmental conditions [19], as well as on preliminary field observations conducted in the same orchard during prior seasons (unpublished data).

2.3. Histological Parameters of Fruit Flesh Cells

Twenty spurs bearing a single fruit, located in the middle third of the trees, were collected 50 days after full bloom. Fresh weight, equatorial diameter, and fruit height were determined using a precision scale and a digital caliper. For anatomical analyses, samples were obtained from transverse sections along the equatorial axis of the fruits and in the cortex, between the epidermis and the outer boundary of the carpel. Samples were fixed in FAA70% solution (formaldehyde 37%, glacial acetic acid, and 70% ethanol; 5:5:90, v/v) under vacuum (−600 mmHg) for 48 h, dehydrated in an ascending ethanol series (50, 60, 70, 80, 90, and 95%), and embedded in historesin (Leica Microsystems, Wetzlar, Germany) according to the manufacturer’s instructions. After polymerization at 35 °C for 48 h, histological sections (8 µm thick) were obtained using a rotary microtome (Leica SM2010 R) and stained with basic fuchsin. Images were captured using an automated microscope (Leica Microsystems^®) with a 10× objective lens, using a calibrated scale of 0.64 µm per pixel. Each image covered an area of 1310.72 × 983.04 µm (1,288,487.53 µm²), and a standard area corresponding to one-quarter of this dimension (322,178.625 µm²) was defined for cellular analysis. The number and size of cells (µm²) were determined manually by counting and measuring, excluding edge cells. Intercellular spaces (µm²) were calculated by subtracting the total cellular area from the standard analyzed area.

2.4. Yield Performance and Fruit Quality Parameters

The parameters, including number of fruits per plant (nº plant⁻¹), yield per plant (kg plant⁻¹), and productivity (t ha⁻¹), were measured at commercial maturity. These were obtained through manual fruit counts, weighing of fruits from each treatment, and by multiplying the average fruit weight per plant by the number of plants per hectare. Additionally, 50 fruits from the middle third of the plants in each treatment were selected for physicochemical evaluations. Of these, 20 fruits were used to measure diameter (fruit width—FW), height (fruit height—FH), and the FW/FH ratio (mm), colorimetry, percentage of red coloration on the fruit epidermis, density, DA-meter index (IAD), flesh firmness, and soluble solids content.

Colorimetric analysis was performed using a Minolta colorimeter, model CR 400 (Tokyo, Japan), to determine lightness (L) and hue angle (H) in both the most colored (red region—RR) and least colored (green region—GR) parts of the fruit, generating the variables Hue angle in the red region (HRR), Lightness in the red region (LRR), Hue angle in the green region (HGR), and Lightness in the green region (LGR). The percentage of epidermis covered with red coloration (%) was visually estimated according to standards established in the Brazilian Technical Regulation for the Identity and Quality of Apples [19].

The absorption difference index (IAD) was measured using a DA-meter^®, model FRM01-F (generic fruit), where lower values indicate lower chlorophyll content and, therefore, greater fruit maturity. Fruit density was determined by the water displacement method, as described by [20], with values expressed in g/mL. Flesh firmness (N) was assessed on two opposite sides of each fruit, after removing a disk of epidermis, using a texture analyzer (TA.XTexpress, Stable Micro Systems, Surrey, UK) equipped with an 11 mm probe. Soluble solids content (°Brix) was measured using a digital refractometer (Woonsocket, RI, USA).

The remaining 30 fruits were individually weighed and classified into three size categories (g): (a) large fruits (158 g to 279 g); (b) medium (127 g to 157 g); and (c) small (50 g to 126 g). After classification, the fruits were placed in polyethylene mesh bags, stored in plastic crates, and kept in cold storage at 1 ± 0.5 °C and 90–92% relative humidity for 30 days. At the end of the storage period, 20 fruits were selected to measure flesh firmness (N) following the same methodology previously described.

2.5. Experimental Design and Data Analysis

The mean data from treatments common to both growing seasons (2021/22 and 2022/23) were subjected to statistical analysis. Due to adjustments in the experimental protocol, including the addition of three new treatments in the 2022/23 season, the data from this cycle were also analyzed separately, encompassing all twelve treatments.

Data normality was assessed through kurtosis and skewness parameters. The optimal number of clusters was determined using the silhouette coefficient, and group formation was performed using the non-hierarchical K-means clustering algorithm. A multivariate approach was applied through Principal Component Analysis (PCA). For univariate analysis, residual normality was initially tested using the Shapiro–Wilk test. Once statistical assumptions were met, data were submitted to analysis of variance (ANOVA), and when significant differences among treatments were detected (p < 0.05), Tukey’s multiple comparison test was applied using the agricolae package [21]. All analyses were performed in the RStudio statistical programming environment using R version 4.3.1 [22].

3. Results

3.1. Climatic Conditions During the Growing Seasons

The monthly fluctuations in average, maximum, and minimum temperatures (°C), precipitation (mm), chilling units (CU), and chilling hours (CH) are shown in Figure 1 and Figure 2. The two growing seasons (2021/2022 and 2022/2023) exhibited marked differences under climatic conditions. The average monthly precipitation for the period from January 2021 to September 2023 reached 147.8 mm (Figure 1).

During the 2021/2022 growing season, the average temperature from flowering to harvest remained relatively stable, ranging from 15.8 °C to 18.4 °C. This period was notably marked by a prolonged period with low rainfall, with total accumulated rainfall of only 305.6 mm. In contrast, the 2022/2023 growing season presented more favorable moisture conditions, with total rainfall of 517.1 mm from flowering to harvest. The average temperatures ranged from 16.2 °C to 19.3 °C, slightly higher than in the previous 2021/2022 growing season (Figure 1).

The accumulation of chilling hours (CH) from April to September, based on the Modified North Carolina Model [23], reached 1077 CH in 2021, 1640 CH in 2022, and 1068 CH in 2023 (Figure 2A). For the same period, the accumulated chilling hours below 7.2 °C reached 864 CH, 735 CH, and 488 CH in 2021, 2022, and 2023, respectively (Figure 2B).

3.2. Histological Parameters, Yield Performance, and Fruit Quality Parameters

Principal component analysis (PCA) of the histological parameters of fruit flesh cells (Figure 3A) enabled the formation of three distinct groups. Treatment BA-S2 showed the largest cell size (4834.713 µm²), which represents a 19.5% increase compared to the control, indicating that BA had a significant effect on cell expansion. The treatments BA-S1, BA-S3, and BA-S1 + S2 + S3, as well as the control, exhibited larger intercellular spaces and were clustered in Group 2 (Figure 3A). In contrast, Group 3, composed of combined protocols (BA + NAA and BA + TRYP), exhibited less intercellular space, suggesting a greater proportion of tissue area occupied by cells. The parameters of intercellular space and cell-occupied area were inversely proportional, as indicated by the opposite direction of their vectors in the PCA biplot (Figure 3A). The third cluster (Group 3) comprised the treatments most strongly associated with the reduction of intercellular space. Accordingly, the protocols involving the combination of BA with NAA and Tryptophan, as well as BA-S1 + S3 and BA-S1 + S2, exhibited effects opposite to those observed in Group 2. That is, by increasing the cell-occupied area, these treatments contributed to a decrease in intercellular space.

The PCA for yield performance and fruit size primarily separated treatments based on the proportion of small fruits (Figure 3B). Treatment BA + NAA-6 (Group 2) showed the best performance, with the highest yield and a greater proportion of large fruits (41.2%), classified as bigger size (158 g to 279 g). On the other hand, treatments BA-S1 + S2 and BA-S1 + S2 + S3 (Group 1) had the highest proportions of small fruits (23.4% and 22.8%, respectively), suggesting that excessive combinations of applications might not benefit final fruit size.

PCA for fruit epidermis coloration quality (Figure 3C) grouped treatments based on the intensity and hue of skin color. Group 1 (BA-S2 and BA-S3) included fruits with lighter (greater LRR) and less reddish coloration (greater HRR). Group 2, containing BA-S1 + S3, BA-S1 + S2, and control, showed higher red color coverage (≥60%) and darker hues, including in less sun-exposed areas. Treatments in Group 3 were characterized by lower coloration percentages and by higher Hue angle values in the less-exposed regions of the fruit surface (HGR).

The correlation between histological parameters and fruit physicochemical quality (Figure 3D) allowed treatments to be separated into four groups. Protocols BA-S2 and BA-S1 + S3 (Group 1) showed higher fruit density, cell size, and pulp firmness. The treatments BA-S3, BA-S1 + S2 + S3, and control (Group 2) were characterized by a higher number of cells and IAD values. Treatments BA-S1 + S2, BA + TRYP, and BA + NAA (Group 3) were positioned near the center of the PCA graph (Figure 3D), indicating responses close to the general average. Treatment BA-S1 alone formed Group 4, showing a significant association with larger intercellular space. Notably, this treatment appeared in the opposite quadrant from pulp firmness, suggesting that fruits with more intercellular space also had lower firmness. This trend is particularly evident when comparing protocols BA-S1 and BA-S2. Both had similar maturity levels (IAD = 0.22); however, fruits from BA-S2 were 25.98% firmer (73.46 N) compared to those from BA-S1 (58.31 N).

To evaluate the consistency of PGR responses under distinct climatic conditions, the same parameters assessed in 2021/2022 (Figure 3) were reanalyzed for the 2022/2023 growing season (Figure 4). Based on the 2022/2023 growing season data and following adjustments to the experimental protocol, the PCA of histological parameters resulted in the formation of four distinct clusters (Figure 4A). The largest group (Group 1) included five protocols (BA-S1, BA-S2, BA-S3, BA-S1 + S2, and BA + NAA-6) along with the control, all of which showed higher cell sizes compared to the other treatments. Protocols BA + TRYP and BA-S2 + S4 (Group 2) showed a higher number of smaller cells, classifying them as intermediate in terms of intercellular space. On the other hand, protocol BA + NAA-S2 + S4 + S5 (Group 3) showed the lowest intercellular space among all treatments.

PCA of yield performance for the 2022/2023 growing season separated treatments into two main groups (Figure 4B). The first group included the most yield protocols (BA-S3, BA-S1 + S3, BA + NAA-6, BA + NAA-10, BA-S2 + S4, and control). Among them, BA S2 + S4 had the highest yield (81.24 t ha⁻¹), followed by BA + NAA-10 (79.55 t ha⁻¹) and BA-S1 + S3 (79.35 t ha⁻¹). However, despite their similar yields, BA + NAA-10 had the highest percentage of small fruits (32.5%) among all protocols. In contrast, the remaining treatments (Group 2) were positioned in the opposite quadrant from the production variables (Figure 4B). Within this analysis, protocol BA-S3 (BA applied at petal fall) stood out by promoting both the highest productivity and the highest percentage of large fruits (52.5%).

The first and second principal components related to epidermis coloration parameters explained 82.5% of the total data variation (Figure 4C). The PCA graph showed the formation of three distinct groups, differentiating treatments based on higher or lower epidermal coloration. Group 1 was characterized by higher HRR and LRR values, indicating lighter and less reddish hues, with the exception of BA-S3, which correlated more strongly with vectors indicating redder fruits (Fruit color 60 and Fruit color 40). Group 2 showed the highest percentage of fruits in the 40% and 60% red coverage categories and had darker red skin tones. Finally, the treatments in Group 3 were associated with fruits showing low red color coverage. This is an important commercial attribute, as it allows for fruit classification into higher market categories.

In the joint analysis between the yield performance and fruit quality parameters and the histological parameters of fruit flesh cells, fruit density was once again positively correlated with cell size (Figure 4D). Among the three clusters formed, the BA + TRYP protocol (Group 3) showed the highest pulp firmness among treatments. Groups 2 and 1 were primarily characterized by the highest values of IAD and intercellular spaces, observed in the BA-S1 + S2 and BA + NAA-6 protocols, respectively.

3.3. Pulp Firmness and Firmness Loss

The data from the yield performance and fruit quality parameters, including equatorial diameter (mm), height (mm), and fruit weight collected 50 days after full bloom, showed no significant differences among the protocols, regardless of the evaluation season, as observed in the preliminary analysis. However, regarding the isolated analysis of flesh firmness and firmness loss obtained during the 2021/2022 and 2022/2023 seasons (

Table 2. Pulp and loss firmness of ‘Maxi Gala’ fruits evaluated at harvest (pre-storage) and after 30 Days of Storage (post-storage), submitted to different PGRs spraying in the municipality of Vacaria-RS, Southern Brazil, during the 2021/22 and 2022/23 growing seasons. NAA: naphthalene acetic acid; BA: 6-benzyladenine; TRYP: tryptophan; S1: stage 1 (10 days after bud break—BBCH 01); S2: stage 2 (full bloom—BBCH 65); S3: stage 3 (petal fall—BBCH 67), S4: stage 4 (fruits measuring 8 to 10 mm—BBCH 71), S5: stage 5 (fruits measuring 25 to 27 mm—BBCH 74), and Control—untreated. Means followed by different letters in the column differ from each other according to Tukey’s test (p < 0.05).

Treatment	Pre-Storage Firmness (N)	Post-Storage Firmness (N)	Loss of Fruit Firmness (N)
Control	65.96 ns	47.06 abcd	18.90 ab
BA-S1	64.25	48.21 abcd	16.04 ab
BA-S2	63.42	49.06 abc	14.36 ab
BA-S3	65.06	49.41 abc	12.65 ab
BA-S1 + S3	65.36	50.61 ab	14.74 ab
BA-S1 + S2	68.16	52.84 a	15.32 ab
BA-S1 + S2 + S3	63.61	52.83 a	10.78 b
BA + TRYP	69.95	44.24 cd	25.71 a
BA + NAA-6	68.41	43.76 cd	24.65 a
BA + NAA-10	65.01	44.75 bcd	20.26 ab
BA-S2 + S4	67.34	42.43 d	24.91 a
BA + NAA-S2 + S4 + S5	62.09	45.73 bcd	16.36 ab
Mean	65.47	47.58	17.89
CV (%)	7.09	5.02	30.64

ns = not significant (p < 0.05).

), no significant differences were observed in pre-storage firmness values, with an overall average of 65.47 N. Nevertheless, after 30 days of cold storage, fruits from the BA-S1 + S2 + S3 protocol maintained higher firmness compared to those from the BA + TRYP, BA + NAA-6, and BA-S2 + S4 treatments. Additionally, the BA-S3 protocol stood out with the second-lowest firmness loss during storage. This result correlates with the histological analysis of the BA-S1 + S2 + S3 protocol, which showed a higher number of smaller cells (Figure 3B).

4. Discussion

The marked differences in climatic conditions between the two growing seasons (2021/2022 and 2022/2023) may have influenced plant development and the efficacy of PGR applications (Figure 1 and Figure 2). The 2021/2022 growing season was characterized by a prolonged dry period, with cumulative rainfall of 305.6 mm and mean temperatures ranging from 15.8 °C to 18.4 °C during fruit development. This reduced water availability may have limited cell expansion and increased plant stress, potentially affecting PGR absorption and action. In contrast, the 2022/2023 season exhibited 517.1 mm of total rainfall and slightly higher mean temperatures (16.2–19.3 °C), especially during fruit set and early development, which likely favored more effective physiological responses to PGR treatments [24]. The comparison between seasons indicates that rainfall distribution and temperature stability played a crucial role in modulating fruit growth and PGR efficiency [25], reinforcing the importance of considering climatic variability when designing and interpreting hormonal field trials.

The results obtained in this study demonstrate the relevance of evaluating the interaction between PGRs and their application timings on histological parameters, yield performance, and fruit quality in ‘Maxi Gala’ apples. By combining univariate and multivariate analyses (including PCA and cluster analysis), it was possible to elucidate specific physiological effects associated with the use of 6-benzyladenine (BA), naphthaleneacetic acid (NAA), and tryptophan (TRYP), individually and in combination.

The environmental conditions observed during the 2021/2022 and 2022/2023 growing seasons influenced the physiological responses to PGRs. In 2021/2022, higher rainfall during flowering and the early fruit set phase (approximately 0–30 DAFB), followed by a prolonged dry period from mid-development onward, likely promoted uniform hormonal absorption early in the cycle but later limited fruit expansion due to reduced water availability. In contrast, the 2022/2023 growing season presented higher maximum temperatures (up to 30 °C) and lower relative humidity during flowering and early fruit development (0–50 DAFB), conditions that may have reduced the effectiveness of multiple PGR applications (e.g., BA-S1 + S2 + S3), as increased evapotranspiration can interfere with absorption efficiency [23]. These climatic variations also help explain the differences in fruit skin coloration between seasons, since anthocyanin accumulation is temperature-sensitive [9,26]. Warmer nights and elevated maturation temperatures in 2022/2023 tended to reduce red pigmentation [27], reinforcing the importance of aligning PGR applications with environmental forecasts.

Fruit growth and development represent the continuation of physiological processes initiated in the previous cycle, such as floral induction and differentiation. Two main stages are involved in apple fruit development: cell division, which predominates until approximately 40 to 50 days after full bloom, and cell expansion, which continues until harvest [27]. These stages are influenced by hormonal balance, environmental conditions, stress, and orchard management practices. Consequently, these factors, acting individually or in combination, determine the potential for fruit growth [28,29].

In terms of management, the use of PGRs offers potential to modulate fruit development, particularly those related to cytokinins, auxins, and gibberellins [1,30,31]. These substances have proven to be effective strategies for enhancing fruit growth and improving final size [6]. It is plausible that the cytokinin BA is perceived by histidine kinase receptors such as AHK2, AHK3, and CRE1/AHK4, which may activate a signaling cascade involving phosphotransfer proteins (AHPs) and response regulators (ARRs), leading to the expression of genes encoding cyclins A and B, associated with cell cycle progression through the S (DNA synthesis) and M (mitosis) phases [23]. Likewise, NAA, as a synthetic analog of natural auxin, is thought to interact with receptors of the TIR1/AFB family [24], promoting the degradation of Aux/IAA repressor proteins and the subsequent activation of ARF transcription factors that regulate genes involved in cell division (type D cyclins) and expansion [24,30]. The cyclin-dependent kinase CDKA, a key regulator of mitotic entry, appears to be modulated by both auxin and cytokinin signaling, which may coordinate the balance between division-promoting and inhibitory factors during fruit growth [27,28,29]. Although the present study focused on phenotypic and histological outcomes, future research should include molecular and hormonal assays to verify these regulatory mechanisms under field conditions.

The histological analysis clearly showed that the application of BA, especially at full bloom (BA-S2), led to an approximate 19.5% increase in mean cell area compared to the control (from 4 045.8 to 4 834.7 µm²; Figure 3A), suggesting a consistent enlargement effect of BA on cell expansion. These findings confirm the cytokinin-like action of BA in stimulating cell expansion, as previously reported by [31,32]. In contrast, treatments involving multiple applications (BA-S1 + S2 and BA-S1 + S2 + S3) promoted a greater number of smaller cells, consistent with a reduced intercellular space, which in turn influenced pulp firmness. Interestingly, the PCA revealed that protocols combining BA with TRYP or NAA were more efficient in reducing intercellular space while increasing the relative area occupied by cells. This synergistic behavior likely results from the complementary roles of auxins and cytokinins in fruit tissue development. NAA promotes cell wall loosening by enhancing the activity of enzymes such as expansins and pectin methylesterase, favoring cell enlargement. In contrast, BA stimulates cell division by upregulating cyclin-dependent processes. Their combined application may therefore synchronize cell expansion and division, producing denser parenchyma with reduced intercellular space. Tryptophan, as an auxin precursor, supports endogenous IAA synthesis and sustained cell proliferation, contributing to tissue compactness and higher fruit firmness [12,13,14]. This observation corroborates the hypothesis that the synergistic use of auxins and amino acid precursors may enhance tissue compactness, improving mechanical resistance and postharvest storage potential, as also noted by [25] and supported by earlier observations from [15,33].

In both growing seasons, treatments with BA applied during petal fall (BA-S3) and those combining BA with NAA (especially BA + NAA-6) resulted in the highest yields. This reinforces previous observations that early application of cytokinins can increase fruit set and reduce early drop [24,26]. Although BA + NAA-10 produced comparable yields, the associated high percentage of small fruits (32.5%) suggests that excessive hormonal load may compromise final fruit size. It is important to highlight that BA-S3 was the most efficient treatment in reconciling high yield and a high percentage of fruits in the ‘large’ category (52.5%). This performance can be attributed to the balanced action of BA at a critical stage of fruit cell division and expansion, aligning with results reported by [1,34,35].

Regarding skin fruit lightness, PCA showed clear separation among treatments according to the hue angle and red skin coverage. Treatments BA-S2 and BA-S3 produced fruits with lighter and less intensely red epidermis, possibly due to hormonal influence on anthocyanin biosynthesis [16,36]. On the other hand, treatments like BA-S1 + S3 and BA-S1 + S2 were associated with higher red color coverage, even in shaded areas, indicating that application timing strongly affects light-independent color development pathways [15,33].

This is a particularly relevant result, as consumer preference and market classification of apples heavily depend on uniformity and intensity of red skin coloration [28,35,36]. Thus, application strategies that enhance coloration under variable light exposure can provide commercial advantages. Fruit density and pulp firmness were positively correlated with cell size and inversely correlated with intercellular spaces, in agreement with the structural basis of firmness proposed by [10,28]. Protocols BA-S2 and BA-S1 + S3 stood out by promoting both greater firmness and compact tissue, which may explain their superior performance in postharvest evaluations. Although pre-storage firmness values were not significantly different among treatments, the storage phase revealed distinctions. BA-S1 + S2 + S3 maintained the highest firmness after 30 days of cold storage. This may be explained by the high number of small cells observed in its histological profile (Figure 4A), as compact tissue has been associated with reduced enzymatic degradation during storage [25,27]. In contrast, treatments with higher intercellular space (e.g., BA-S1 and BA + TRYP) showed greater firmness loss after storage. This reinforces the idea that tissue compactness, rather than initial firmness alone, is a better predictor of postharvest behavior [16,35,36]. Furthermore, the most important histological parameters for maintaining pulp firmness in apples were a higher number of cells and a smaller cell size. PGRs represent a viable strategy to increase both yield and quality in ‘Maxi Gala’ apples [31].

Overall, the results demonstrate that fine-tuning the application timing and combining PGRs can enhance not only yield and fruit size but also quality parameters such as firmness and skin coloration [36]. The analyses of histological parameters provided a robust physiological basis for these agronomic outcomes, supporting the integration of microscopic and yield data for decision-making in orchard management. This study advances previous knowledge by incorporating multivariate analysis to evaluate the joint effects of different PGRs and application timings, thus offering a more holistic understanding of their roles. Further research is encouraged to evaluate the long-term effects of these treatments across multiple growing seasons and cultivars.

5. Conclusions

The application rates and phenological stages of plant growth regulators (PGRs) directly influenced cell size, with 6-benzyladenine (BA) being the most effective in promoting this parameter, regardless of the timing of application. Tryptophan primarily stimulated cell division, resulting in a greater number of smaller cells, whereas NAA was associated with increased cell size. The simultaneous increase in both cell number and cell size contributed to reduced intercellular spaces. The combined use of NAA and BA enhanced fruit productivity and size, while the isolated application of BA at the petal fall stage represented the most effective and practical strategy to improve fruit size, epidermal coloration, and pulp firmness after cold storage under the highland conditions of southern Brazil.