Conventional vs. Photoselective Nets: Impacts on Tree Physiology, Yield, Fruit Quality and Sunburn in “Gala” Apples Grown in Mediterranean Climate

Abstract

The impact of five different nets—conventional black, grey, white, and photoselective red and yellow—on the performance of “Gala Redlum” apples was evaluated over a five-year period (2020–2024) and compared to an uncovered control. The cumulative production over this period, ranked from highest to lowest, was as follows: white net (182.4 t/ha), grey net (178.5 t/ha), yellow net (175.8 t/ha), black net (175.5 t/ha), red net (169.5 t/ha), and uncovered control (138.8 t/ha). Vegetative growth results were inconsistent among the studied years. The cumulative photosynthetic rate (An) was slightly higher under the white net (57.9 µmol m⁻² s⁻¹). Fv/Fm values remained closest to optimal levels under the black and grey nets. Netting effectively protected fruits from elevated temperatures, particularly under the grey net, and reduced sunburn damage, with the grey, black, and yellow nets performing best in this regard. Overall profitability was increased by netting: the black net provided the highest cumulative income per hectare over a five-year period (EUR 72,315) alongside the second-lowest sunburn loss (0.69%), while the yellow net also showed strong economic performance (€64,742) with a moderate sunburn loss (1.26%) compared to the red net. Fruit dry matter and soluble solids content (SSC) were generally higher in the uncovered control, whereas °Hue values tended to be higher under the red and yellow nets. In summary, the black and yellow nets provided more balanced microclimatic conditions that enhanced tree performance, particularly under heat stress, leading to improved yield and profitability. However, the economic feasibility of each net type should be evaluated in relation to its installation and maintenance costs.

1. Introduction

Global climate change has created an urgent need for agronomic, eco-friendly, and sustainable practices that protect crops from biotic and abiotic stresses, enhance fruit quality and yield, and minimize environmental impact. In this context, the use of various types of nets in fruit production has been increasingly explored as a means of protecting trees from climate stressors such as high temperatures, excessive radiation, hail, wind, and threats from insects and other pests, as well as birds [1,2].

In apple orchards, nets known as anti-hail or shading nets were initially introduced to protect crops from hailstorms and wind damage [1,3]. Black and translucent crystal-white nets have been commonly used for this purpose [4,5]. However, the effectiveness of these nets largely depends on their shading factor, which reduces the amount of solar radiation reaching plants and potentially affecting their growth, particularly in the case of opaque black nets [2,5]. Later, exclusion nets made from transparent threads were introduced to protect crops from pest damage [1].

To mitigate the negative shading effect of nets, a novel technology—photoselective nets—was developed. These nets incorporate chromatic elements that alter the spectral composition of sunlight and scatter it, enhancing both light penetration and the proportion of diffuse light [2,3,6]. Photoselective nets modify light quality in the ultraviolet (UV) (100–400 nm), photosynthetically active radiation (PAR) (400–700 nm), and near infra-red (NIR) (760–1500 nm) wavelength ranges [3]. While conventional black nets primarily reduce light quantity, transparent or shading nets diffuse light without altering its spectral characteristics, and photoselective nets both scatter and modify light, altering its spectral composition [1,2,3].

The texture, mesh size, and color of nets are the key factors that determine their shading factor and, consequently, their capacity to alter light quantity and quality [2]. Photoselective nets can be classified as “colored nets” (red, yellow, green, and blue) and “neutral-colored” (grey, pearl, and white) [2]. Moreover, the changes in solar radiation are particularly significant for plants within the spectrum ranging from 280 to 800 nm, which encompasses UV-B (280–320 nm), UV-A/B (300–400 nm), PAR (400–700 nm), and far-red (700–800 nm) [2,6]. Plants detect light signals through specific photoreceptors: phytochromes (sensitive to red (R) and far-red (FR) wavelengths) and cryptochromes and phototropins (responsive to blue and UV-A light) [1,2]. Some of these receptors are shade avoidance mechanisms and respond to reductions in R, FR, and blue (B) and UV-A radiation, or to changes in R:FR and blue/green ratios [2].

In apple orchards, net-induced reduction in solar radiation alters the orchard microclimate, influencing light intensity, spectral composition, canopy temperature, relative humidity, and air and soil temperatures [1,5,6,7]. These alterations in light stimulate photomorphogenic and physiological responses in trees, which, in turn, affect growth and development [3]. Netting can affect vegetative growth and leaf morphology, either by promoting optimal growth conditions or triggering shade avoidance responses [3,6]. The effects of different net types on flowering and fruit setting in apple trees are variable [7,8], with differing impacts on fruit yield and weight depending on the net type, apple cultivar, and environmental conditions [5,7,8]. Photoselective nets have also been shown to enhance photosynthetic efficiency under conditions of light and thermal stress [2,9,10]. Additionally, netting reduces water loss from both soil and plant transpiration, thereby improving water use efficiency [1].

By reducing stress from extreme light and temperature, netting can positively affect fruit quality traits such as color, soluble solids content (SSC), and carbohydrate levels [1,3,11]. Additionally, the shading effect of nets has been shown to significantly reduce sunburn in apples, with higher shading factors appearing to be more effective [5,8,12,13]. However, the excessive shading effect of nets can also reduce photosynthetic efficiency, impacting fruit quality by lowering carbohydrate reserves, firmness, sugar content, and pigment accumulation [1,5,8]. Photoselective nets, by altering the UV, blue, and red regions of the light spectrum, influence phytochrome and cryptochrome responses that regulate physiological processes, including those related to color development [1,11]. Fruit coloration is dependent on the accumulation of pigments such as chlorophyll, anthocyanins, and carotenoids, each of which responds differently to variations in light and temperature. For instance, in apples, red coloration is largely driven by anthocyanin accumulation, which occurs under high light intensity and temperature stress [3].

Growing evidence suggests that photoselective netting has a positive impact on fruit quality, although reported effects remain variable [14]. However, most research has focused on specific physiological or agronomic traits, with responses often dependent on environmental conditions [3]. This variability highlights the need for further investigation to better understand the mechanisms through which netting influences fruit trees and to optimize the use and development of this technology [2]. This study provides a comprehensive evaluation of the impact of five different net types (three conventional and two photoselective) on “Gala Redlum” apple trees (Malus domestica Borkh.) over five consecutive years (2020–2024), under Mediterranean conditions. The conventional nets tested were black, grey, and white, which primarily modify light quantity but not its spectral composition, while the photoselective nets were red and yellow, with an uncovered control used for comparison. Several parameters were assessed, including productivity, vegetative growth, photosynthetic activity and overall physiological performance, fruit quality, and sunburn reduction. The primary goal of this study is to provide scientific data that improves understanding of the effects and mechanisms of different net types in improving apple production under Mediterranean conditions. Furthermore, the data will contribute to helping apple growers in making informed decisions about net cover investments, improving both crop management and sustainability.

2. Materials and Methods

2.1. Experimental Site

The experiment was carried out over five growing seasons (2020–2024) in an apple orchard located in Alcobaça, Portugal (39°32′59.5″ N, 8°57′37.3″ W), to evaluate the effects of shading nets on the “Gala Redlum” apple cultivar (Figure 1). The orchard was established in 2018 at a planting density of 3.50 × 0.90 m (3175 trees/ha) and covered with nets in June 2020. Six modalities were evaluated, consisting of five net types and one uncovered control, with six trees selected per modality: (i) Black net—average shading factor: 22.4%; (ii) red net—average shading factor: 20.6%; (iii) grey net—average shading factor: 15.7%; (iv) yellow net—average shading factor: 14.7%; (v) white (crystal) net—average shading factor: 9.6%; (vi) uncovered control. The nets were made of high-density polyethylene (HDPE). The black, grey, and white nets had nominal shading factors of approximately 18%, 14%, and 8%, respectively (mesh size 2.80 × 8.50 mm; Type Austria, Artes Politecnica, Italy). The photoselective red and yellow nets (mesh size 2.40 × 4.80 mm; Iridium^®, Agrintech, Italy) had nominal average shading factors of 15% and 19%, respectively. Each modality consisted of at least three consecutive rows, with data collected from the central row.

Uniform irrigation, fertilization, and pest control practices were applied across all trees in the orchard, according to Portuguese integrated production practices [15,16]. Figure S1 presents the average monthly temperature and solar radiation recorded between 2021 and 2024, following the first year of net installation, as well as the number of days with maximum temperatures above 35 °C during the same period. These data were obtained from the meteorological station installed in the experimental field, located approximately 30 m from the orchard where the trials were conducted, within the interior of the agricultural estate. They were used to provide an overview of the post-installation environmental conditions and their influence on the evaluated parameters.

2.2. Agronomic Determinations

At each harvest, all selected trees (6 trees × 6 modalities) were harvested individually. Fruits from each tree were counted and weighed to calculate total yield (t/ha) and average fruit weight (g) and then stored at ~1 °C for further measurements. Fruit size was determined by measuring diameter (mm) and classifying according to standard commercial size classes: <50, 50–55, 55–60, 60–65, 65–70, 70–75, 75–80, and >80 mm.

To assess the economic impact of the net cover modalities on the Gala “Redlum” cultivar, the average price per size class and the total revenue per modality were calculated based on national wholesale market prices (<50 mm, EUR 0.00; 50–55 mm, EUR 0.05; 55–60 mm, EUR 0.10; 60–65 mm, EUR 0.28; 65–70 mm, EUR 0.40; 70–75 mm, EUR 0.60; 75–80 mm, EUR 0.63; >80 mm, EUR 0.70). From the gross value paid to the producer, the average costs associated with the packing house—mainly labor and handling expenses—were deducted to estimate the net economic return per modality.

The alternation index (I), which quantifies yield variation between consecutive years, was calculated using yield data from the 2020 to 2024 harvests. This index represents the absolute difference between the average yields of two successive harvests and ranges from 0 to 1, where 0 indicates no alternation and 1 indicates maximum alternation. Lower values indicate greater yield stability [17,18]. The index was calculated using the following equation [18].

(1)$I={\displaystyle \frac{1}{n-1}}\times {\sum }_{i=2}^n\left({\displaystyle \frac{\left|y_{i+1}-y_i\right|}{\left|y_{i+1}+y_i\right|}}\right)$

where $y$y is the yield observed in year i, and n is the total number of years evaluated.

To assess the variation in annual tree growth among net treatments, changes in branch length (∆ Branch), trunk cross-sectional area (∆ TCSA), tree height (∆ Height), and crown volume (∆ Volume) were measured. Measurements were taken annually from 2021 to 2024 on six selected trees per modality. Trunk diameter measurements for TCSA calculations were taken using a digital caliper (Sylvac S_Cal EVO BT, Yverdon-les-Bains, Switzerland) at the beginning and end of each annual cycle. Tree height was measured using a Bosch field measuring rod, while the lengths of all main axes and lateral branches (primary and secondary), as well as canopy dimensions, were recorded using a flexible measuring tape. Primary branches were defined as those over 3 cm emerging directly from the main axis, while secondary branches were considered as growths exceeding 3 cm arising from primary branches. Branch growth measurements were taken at the beginning of each annual cycle on the following dates: 20 April 2022, 27 March 2023, and 3 April 2024. Final measurements were made on 11 January 2023, 29 January 2024, and 4 February 2025.

To evaluate the variation in TCSA (cm²), the stem diameter of each tree was measured at three equidistant points around the stem circumference, all located 20 cm above the graft union. This approach was used because most trunks are not perfectly circular, so measuring at multiple points provides a more accurate estimation of stem cross-sectional area. The crown volume (m³) was determined by measuring the average width at three positions: at the base (D1—first branch), at the middle of the crown (D2—half the height between D1 and D3), and 50 cm below the highest point of the crown (D3), then multiplied by the difference between the height of the highest point of the crown minus the height of the first branch. The trees were trained using a central leader system, and the rootstock used in the trial was M9. TCSA, tree height, and crown volume were measured at the beginning of each growing season: 22 April 2021, 12 April 2022, 6 April 2023, and 26 March 2024. Final measurements were taken on 16 September 2021, 28 November 2022, 14 November 2023, and 5 December 2024.

To compare results and assess the relationship between annual growth and yield, average branch growth, TCSA variation, and yield per tree (kg/tree) were normalized. Data normalization was achieved by dividing the average values of each variable by the maximum value found for each corresponding parameter, scaling all variables between 0 and 1 [19]. The relative growth rate (RGR) of TCSA, which expresses the increase in trunk biomass per unit time relative to its initial size, was calculated using the following equation, as adapted by [20]:

(2)$RGR={\displaystyle \frac{({TCSA}_{ final} - {TCSA}_{ initial})}{{TCSA}_{ initial}}} \times {\displaystyle \frac{1}{t_2 - t_1}}$

where TCSA_final and TCSA_initial represent the final and initial cross-sectional areas of individual trees at times $t_2$ (end of the annual cycle) and $t_1$ (beginning), respectively. The term ($t_2$ − $t_1$) denotes the number of days in each annual cycle which growth was measured.

The annual fruit set rate (%) was calculated as the ratio of fruits set to the number of flowers per corymb, from 2021 to 2024. Flower and fruit counts were conducted on four corymbs per tree—one from each quadrant—on each marked tree, totaling 24 replicates per modality. Flower counts were performed at full bloom (BBCH 65) on 29 April 2021, 26 April 2022, 18 April 2023, and 29 April 2024, while fruit counts were carried out on 31 May 2021, 28 June 2022, 13 June 2023, and 26 June 2024.

To monitor fruit growth over time, the equatorial diameter of 10 fruits per modality was measured weekly (~11 to 15 times per season) throughout the growing period following full bloom each year from 2020 to 2024. The full bloom dates were 24 April 2020, 5 April 2021, 22 April 2022, 17 April 2023, and 29 April 2024.

2.3. Physiological Determinations

The physiological parameters—net photosynthetic rate (A_n), stomatal conductance (g_s), intracellular carbon dioxide concentration (Ci), and transpiration rate (E)—were measured on six fully expanded leaves per treatment between 10:00 a.m. and 12:30 p.m. (morning) and 2:30 p.m. and 5:00 p.m. (afternoon) on various dates from 2020 to 2024. Measurements were conducted on clear-sky days using a portable gas exchange analyzer (Infra-Red Gas Analyzer—IRGA; ADC Bioscientific Ltd., LCproT, Hoddensdon, UK), equipped with a broadleaf chamber (6.35 cm²) that measures CO₂ and water via infrared radiation. No artificial light was used in the chamber. The temperature was set at 25 °C, and the CO₂ concentration at 400 ppm. Morning readings were taken on the east-facing side of the canopy, and afternoon readings on the west-facing side, using sun-exposed, fully expanded external leaves. In 2020, measurements were taken only during the morning period on 14 July, 21 July, and 19 August. In 2021, they were taken in the morning (10:30 a.m.–12:30 p.m.) on 9 June and 7 July and in the afternoon (3:00–5:00 p.m.) on 7 July. From 2022 to 2024, measurements were taken in both morning and afternoon periods on the following dates: 25 May, 20 July, and 19 August 2022; 5 July and 17 August 2023; and 2 July and 19 August 2024.

Additional measurements of stomatal conductance (g_s) and stomatal resistance (r_L) were obtained using a portable dynamic porometer (Delta-T Devices, AP-4, England). These were taken on the same dates and during the same time periods as the IRGA measurements, except on 27 June 2023, when measurements were taken only in the morning.

Chlorophyll a fluorescence parameters were recorded on the same dates as gas exchange measurements. These included initial fluorescence (Fo), variable fluorescence (Fv), maximum fluorescence (Fm), and PSII quantum efficiency with and without dark adaptation (Fv/Fm and Fv’/Fm’). Two portable fluorometers were used: FluorPen FP 110 (PSI, Drasov, Czech Republic) from 2020 to 2021 and Handy PEA (Hansatech Instruments, Pentney, UK) from 2022 to 2024. Measurements were taken on the upper surface of fully expanded, healthy leaves (6 replicates per treatment). A minimum dark adaptation period of 20 min was applied, using leaf clips to ensure full oxidation of PSII reaction centers. Particular attention was given to the maximum quantum efficiency of PSII (Fv/Fm and Fv’/Fm), as these parameters are widely recognized as global indicators of plant stress.

Leaf chlorophyll content index (CCI) was determined using a chlorophyll meter (MC-100, Apogee Instruments, USA). Spectral reflectance was also measured on fully expanded leaves from the middle third of the current year’s branches, using a reflectance meter (PSI, PolyPen RP410, Brno, South Moravian Region, Czech Republic). Two reflectance indices were calculated: the Photochemical Reflectance Index (PRI) and the Normalized Difference Vegetation Index (NDVI), following [21,22]. Measurements of CCI, PRI, and NDVI were carried out on the same dates as the aforementioned parameters, between 2022 and 2024.

(3)$PRI={\displaystyle \frac{(R_{531}-R_{570})}{{(R}_{531 }+R_{570} )}}$

(4)$NDVI={\displaystyle \frac{{(R}_{NIR }-R_{RED })}{(R_{NIR }+R_{RED })}}$

where R₅₃₁ and R₅₇₀ indicates reflectance at the 531 and 570 nm wavebands, respectively; R_NIR and R_RED refer to near-infrared and red wavelength reflectance, respectively.

The specific leaf area (SLA) was determined using 50 leaves per treatment each year, between 2020 and 2024. Leaves were sampled on the following dates: 24 June 2020, 13 July 2021, 24 May 2022, 26 June 2023, and 2 July 2024. From the selected leaves, 20 discs with a diameter of 14 mm were collected per replicate (5 replicates × 6 treatments). The fresh weight of the 20 discs from each replicate was recorded immediately after sampling. Samples were then oven-dried at 70 °C for 48 h until constant weight. The dry weight of each replicate was measured, and the SLA was calculated using the following equation [23]:

(5)$SLA\left({\displaystyle \frac{{cm}^2}{g}}\right) =\pi \times {\left({\displaystyle \frac{disc diameter}{2}}\right)}^2\times number of discs \times {\displaystyle \frac{1}{Dry weight discs}}$

2.4. Fruit Quality Determinations

Each year from 2020 to 2024, 40 fruits from the predominant size category were collected per treatment to evaluate quality parameters: fruit diameter, height, weight, firmness, SSC, and dry matter. Diameter and height were measured with a digital caliper (Calibit, Horticultural Knowledge, Italy). SSC, expressed in °Brix, was determined using a digital refractometer (HANNA HI96801, France). Color parameters (L*, C*, and hue angle [°Hue]) were measured on the same samples with a Minolta colorimeter (CR-300 Chroma Meter, Konica Minolta, Tokyo, Japan).

Between 2020 and 2024, starch content was assessed annually on 20 fruits per treatment using the CTIFL scale (Centre Technique Interprofessionnel des Fruits et Légumes, Paris, France). The scale ranges from 0 (no starch) to 10 (high starch content), based on the intensity of coloration after iodine staining. Dry matter was measured in six replicates per treatment, each consisting of five fruit slices (one slice taken from each fruit). The fresh weight of these slices was recorded using an analytical balance (Kern ALJ 160-4AM, max 180 g, precision 0.1 mg; Kern & Sohn GmbH, Ballingen, Germany). Samples were then placed in Petri dishes and oven-dried at 70 °C until two consecutive weight measurements indicated constant dry weight.

Fruit and leaf surface temperatures were measured on both the exterior and interior sides of the canopy from 2021 to 2024, at 2:00 p.m., using a thermal camera (FLIR E6-XT, Flir Systems AB, Täby, Sweden). The thermal camera was regularly maintained and operated following the manufacturer’s guidelines to ensure accuracy (ε = 0.96). In 2024, additional measurements of leaf temperature were taken at 11:30 a.m. and 4:30 p.m., and of fruit temperature at 4:30 p.m., on the exterior of the canopy.

Between 2022 and 2024, sunburn damage was assessed during fruit grading by counting fruits showing sunburn symptoms and classifying them into four severity levels based on the degree of surface discoloration and tissue damage, adapted from [13]. The levels were (A) slight, characterized by slight alteration in the color of the epidermis with no internal tissue damage or commercial depreciation; (B) moderate, involving slight internal tissue damage and significant discoloration of the epidermis; (C) severe, presenting necrotic sunburn with significant burns on both the epidermis and internal tissues; and (D) very severe, with major necrotic lesions on the epidermis and internal tissues resulting in total fruit destruction (Figure 2).

2.5. Statistical Analyses

Data were subjected to one-way analysis of variance (ANOVA). Prior to analysis, data normality and variance homogeneity were tested using the Shapiro–Wilk and Levene’s tests, respectively. Levene’s test was also used to determine whether equal variances were present (no correction) or if Welch’s correction was required (unequal variances). When significant differences among treatments were detected, means were compared using Tukey’s test (for equal variances) or the Games–Howell test (for unequal variances) [24]. If the assumptions of ANOVA were not met, the Kruskal–Wallis test was applied, followed by Dunn’s post hoc test when significant differences were found. A significant threshold of p ≤ 0.05 was adopted.

Principal component analysis (PCA) was conducted to explore relationships among variables and to assess the effects of net cover modalities. Data from 2022 to 2024 were used. For parameters measured in both morning and afternoon, only morning values were included, following standard protocols. Variables were selected for PCA based on their Measure of Sampling Adequacy (MSA) and standardized as Z-scores. Sampling adequacy was confirmed using the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity. Components with eigenvalues greater than 1 were retained, and varimax rotation was applied [24]. The scores of the retained components were analyzed using ANOVA to assess treatment effects in each year. Post hoc comparisons followed the same criteria described above. All statistical analyses were performed using JASP v0.19.1 (University of Amsterdam, Amsterdam, The Netherlands).

3. Results and Discussion

3.1. Productivity and Vegetative Growth

The cumulative average yields of the “Gala Redlum” cultivar over the five-year period evaluated (2020–2024) showed no statistically significant differences between net-covered and uncovered modalities (Figure 3A). Yield cumulative values over the five-year period for the different modalities, in decreasing order, were white net (182.4 t/ha), grey net (178.5 t/ha), yellow net (175.8 t/ha), black net (175.5 t/ha), red net (169.5 t/ha), and the uncovered control (138.8 t/ha). This finding is in line with previous studies reporting positive effects of netting on apple yield [7,25]. Furthermore, Amarante et al. [8] observed higher yields for “Gala” apples under white netting compared to the uncovered control, which aligns with the highest cumulative yield recorded under the white net in the present study.

Across the different years, significant differences between modalities were found in 2020, 2021, and 2022. The highest average yields were recorded under the grey net in 2020, 2021, and 2024, and under the black net in 2023. Conversely, the lowest average yields were recorded under the uncovered control, except in 2020, when the grey net had the lowest yield and the control had the second lowest. The yield difference between the highest and lowest values was smallest for the black (25.6 t/ha) and control (25.8 t/ha) modalities and largest for the grey net (42.5 t/ha). Notably, the grey net yielded the second-highest cumulative average but also showed the greatest year-to-year variability. McCaskill et al. [12] reported that the total yield of “Royal Gala” apples (including both damaged and undamaged fruit) under a grey net with a 10% shading factor was lower than in non-netted orchards. Compared to other colored nets, grey nets are known to absorb infrared radiation more efficiently [2]. This unique spectral property may have contributed to greater variability in plant responses to light. These findings clarify that although cumulative yield differences between net-covered and uncovered treatments were not statistically significant across the full five-year period, year-to-year yield variability was strongly influenced by interannual climatic conditions, resulting in significant differences in total annual yield when averaged across treatments.

Analysis of average yields across years revealed statistically significant differences (Figure 3B). The highest total average yield was recorded in 2024 (52.2 t/ha), while the lowest occurred in 2020 and 2022, at 21.25 and 24.7 t/ha, respectively. All modalities reached their peak productivity in 2024 and their lowest in 2020—except for the grey net, which had its lowest yield in 2022. In July 2022, high solar radiation values were recorded (Figure S1). It was also the only year between 2021 and 2024 in which temperatures exceeded 35 °C during the first two weeks of July, coinciding with early fruit development. Exposure to high light stress is known to impair the photosynthetic apparatus, particularly Photosystems I and II, reducing photosynthetic rate and efficiency [10]. This supports the hypothesis that the grey net contributed to increased variability due to light sensitivity. On the other hand, the higher yields across all treatments in 2024 may be attributed to favorable weather, with lower solar radiation and no temperatures exceeding 35 °C during the summer.

The alternate bearing index (I), calculated for 2020–2024, was as follows (in ascending order): white net (0.13), control (0.17), red (0.19), yellow (0.20), black (0.21), and grey (0.34) (Figure S2). Lower index values indicate more stable crop cycles, relevant for consistent quality and economic return [18]. In contrast, higher indices may indicate yield fluctuations due to stressors such as high temperatures or late frost [18,26]. Thus, the higher alternation index for the grey net may reflect a complex plant response to fluctuating shade and light intensity. It is plausible that grey-netted trees experienced stress from inconsistent light and temperature regimes. Conversely, the low alternation index under the white net may suggest that it provided a more stable microclimate, enhancing plant adaptation and productivity. The moderate index observed in the control treatment may reflect the trees’ adaptive response to natural environmental variation.

The vegetative growth of trees under the net-covered modalities and the uncovered control was assessed using three main indicators: TCSA, RGR, and branch growth. TCSA evolution between modalities was observed only in 2021 (Table S1; Figure 4). However, these differences cannot be directly attributed to the netting system, as it was installed in mid-2020 and likely reflect initial variability in tree size prior to treatment effects. When comparing TCSA at the start of 2021 and the end of 2024, the black net appears to have been more effective in promoting trunk growth (Figure 4). In terms of cumulative TCSA variation over the period, no statistically significant differences were detected between modalities (Figure S3). However, trees under the black and white nets recorded the highest cumulative increases, with means of 8.63 cm² and 7.73 cm², respectively, followed by the uncovered control (6.63 cm²), yellow (6.51 cm²), grey net (6.42 cm²), and red (6.14 cm²) nets. Annual TCSA variation showed no significant differences either, though the highest values were observed under the white net (3.04 cm² in 2021, and 2.30 cm² in 2023); and the black net (2.62 cm² in 2022, and 1.89 cm² in 2024). The lowest values were found under the red (1.83 cm² in 2021, and 1.18 cm² in 2023), white (1.33 cm² in 2022), and yellow (0.93 cm² in 2024) nets. The notably higher relative growth rate (RGR) of TCSA observed in 2021 is attributed to the earlier timing of the second measurement that year. This timing was adjusted in subsequent years to ensure more consistent and comparable data. Overall, RGR, tree height, and crown volume data (Table S1) showed high variability without clear trends across years. Branch growth (Table S2, 2022–2024) consistently exhibited higher average values under the black net, followed by the grey net, whereas the uncovered control showed the lowest growth, followed by the white net. These results suggest that trees grown under the black, white, and grey nets invested more in vegetative growth. In the case of the black net (highest shading factor), this may be due to shade avoidance responses driven by stronger reductions in PAR [3,11], along with lower heat stress, promoting growth [5]. Light scattering of the colored nets may also influence canopy microclimate and promote different growth patterns [3,11]. Conversely, the red net (with similar shading to black) and the uncovered control showed lower investment in trunk growth. Regarding other vegetative parameters, trees under the red net showed intermediate values, while the uncovered control consistently had the lowest branch growths. These patterns may reflect a response to high radiation stress under natural conditions [5,27]. Although red nets are known to increase the red/blue light ratio (potentially enhancing vegetative growth [6,11], in this study, trees under the red net had lower TCSA growth while showing moderate values in other vegetative traits.

The parameters of annual variation in branch growth, TCSA variation, and per-tree yield (kg) were normalized based on the highest value observed for each parameter in order to compare the overall performance of each net cover modality (Figure S4). The results revealed that, when combining TCSA and branch growth with per-tree production, the black net modality showed the best overall performance from 2022 to 2024 (values between 0.60 and 1). Conversely, the lowest performance occurred either under the uncovered control or the red net. The cumulative yield to final TCSA ratio (2021–2024) was also calculated and showed no statistically significant differences between net cover modalities (Figure 5). However, the results indicated that cumulative yield production relative to final trunk growth was highest under the red net (5.23 kg/cm²) and lowest under the grey net (3.72 kg/cm²), with significant differences observed between the two modalities. This outcome suggests that trees under the red net may have prioritized assimilate allocation to reproductive organs over vegetative structural development.

This is consistent with findings by Solomakhin and Blanke [28], who reported that red anti-hail nets reduced trunk thickening but favored shoot elongation and increased fruit mass in “Pinova” and “Fuji Kiku 8” apple trees. Nevertheless, under Mediterranean conditions, apple trees grafted onto M9 rootstock often exhibit suboptimal vigor, motivating the selection of more vigorous cultivars instead of compensating through higher planting densities.

The results for the average setting rate of “Gala Redlum” apple trees between 2021 and 2024 revealed statistically significant differences between modalities in 2021 and 2022 (Figure 6). In 2021, all modalities exhibited relatively high average setting rates, with the white net showing the highest value (56.4%) and the black net the lowest (28.8%). In contrast, 2022 showed the lowest average setting rates for all modalities, ranging from 6.5% under the grey net to 22.8% under the yellow net. The data also indicated an alternating pattern in setting rates between annual cycles across all modalities. No clear correlation was observed between shading factor and setting rate; however, the white, red, and yellow nets generally promoted higher average setting rates. Black and grey nets, along with the control, tended to negatively affect setting rates, although this effect appeared to lessen over time. Given their shading levels (15–23%), black and grey nets may reduce fruit setting by limiting light availability, a factor known to interact negatively with high temperatures [2]. Additionally, the increased vegetative growth observed under these net modalities may have further contributed to lower setting rates, possibly due to reduced assimilate availability [2,29]. Despite a similar shading factor, the red net appeared to positively influence fruit setting, possibly due to alterations in the R/FR and B/R light ratios, which are known to affect plant development [1,3]. Moreover, the quality of light filtered through the colored nets, particularly its light-scattering properties, can influence the efficiency of radiation use and promote more favorable metabolic processes for fruit setting [1].

Fruit growth monitored after full bloom from 2020 to 2024 showed significant differences in several weeks of each season (except 2021), particularly during the early stages of development (Figure 7). In the first year, 2020, the highest average fruit sizes were observed for trees under black, yellow, or white netting modalities (32.9 to 70.6 mm), while the lowest values were recorded for the uncovered control (28.9 to 66.6 mm). In 2024, the uncovered control produced the largest fruits up to 92 days after full bloom, after which the black net modality recorded the highest values. In contrast, at certain points during fruit development, the black, red, and white nets showed the smallest fruit sizes (10.5 to 55.0 mm). Black net trees tended to produce larger fruits in 2020–2022, whereas in 2023 and 2024, larger fruits were observed in the uncovered control. Notably, the black net and control showed intermediate fruit setting rates compared to the other modalities. These results suggest that reduced fruit load—due to less assimilate competition and/or enhanced early cell division—may have contributed to increased fruit size [30]. Previous studies also indicate that the influence of netting on apple fruit size is modulated by cultivar, net type, and environmental conditions [7,8,11]. Overall, the findings of this study suggest that netting did not negatively impact fruit growth, as no significant differences were observed between the net-covered and uncovered control in the later stages of fruit development.

3.2. Physiological Parameters

The cumulative average of photosynthetic rate (A_n) measured in the morning between 2021 and 2024 showed no statistically significant differences between the net-covered and uncovered modalities (Figure 8). However, the average values under net-covered modalities were higher than those in the uncovered control. The highest cumulative average was observed under the white net (57.9 µmol m⁻² s⁻¹), followed by the grey net (55.9 µmol m⁻² s⁻¹), while the lowest value was recorded in the uncovered control (48.5 µmol m⁻² s⁻¹). Among the photoselective nets, the cumulative value under the red net (55.4 µmol m⁻² s⁻¹) was slightly higher than that under the yellow net (54.7 µmol m⁻² s⁻¹). Regarding annual averages, significant differences were found between the modalities for each year of the study, except for 2023. The highest annual average values of A_n were observed under the white net in 2020 and 2024 (14.27 and 15.87 µmol m⁻² s⁻¹, respectively), under the grey net in 2021 (12.99 µmol m⁻² s⁻¹), and under the yellow net in 2022 and 2023 (9.79 and 9.13 µmol m⁻² s⁻¹, respectively). Conversely, the lowest average A_n values were recorded in the control modality in 2021, 2022, and 2023 (9.27, 7.32, and 7.98 µmol m⁻² s⁻¹, respectively), and under the yellow net in 2024 (13.4 µmol m⁻² s⁻¹). Other studies have associated higher photosynthetic rates with netting that provides a moderate shading factor [1]. These findings are consistent with the current study, as the best photosynthetic performance was observed under the white, grey, and yellow nets.

It was also observed that average A_n values were highest in 2024 for all modalities (ranging from 13.56 to 15.87 µmol m⁻² s⁻¹). In contrast, the lowest values were recorded in 2022 (7.32 to 9.79 µmol m⁻² s⁻¹) and 2023 (7.98 to 9.13 µmol m⁻² s⁻¹). Photosynthetic efficiency is directly influenced by light quantity and quality. However, increases in light availability only enhance photosynthetic activity up to the plant’s optimal threshold [2]. Thus, the higher A_n values in 2024 and the lower values in 2022 and 2023 may be attributed to the prevailing radiation levels and air temperatures on the measurement days. In 2024, the average maximum solar radiation was 177.4 W m⁻², significantly lower than the higher levels recorded in 2022 (233.2 W m⁻²) and 2023 (238.9 W m⁻²). Furthermore, air temperatures above 35 °C were recorded during several summer months in both 2022 and 2023, which likely contributed to reduced photosynthetic activity. These results highlight the benefits of netting, which can alleviate high light stress, as reported in other studies [1,3]. The average A_n values measured at different times of day (morning and afternoon) on the same date and on different dates throughout each year showed that the differences between the highest and lowest values were more pronounced in the morning (Figure S5; Tables S3 and S4). This trend is likely due to earlier stomatal closure in trees under higher radiation exposure, leading to a greater reduction in photosynthetic rate during the morning.

The average values of leaf stomatal conductance (g_S), leaf internal CO₂ concentration (Ci), and transpiration (E) measured between 2020 and 2024 at different times of the day (morning and afternoon) and on various dates each year are presented in Tables S3 and S4. Significant differences between modalities were observed on specific dates for each of these parameters; however, no consistent trends were identified. Additional values of g_S and r_L showed significant differences between modalities only in 2024 (Figure 9). In general, r_L was higher in the morning than in the afternoon, whereas the opposite was observed for g_S. This behavior may be attributed to temperature, vapor pressure deficit, and plant water status, which are known to influence stomatal activity throughout the day [3,31]. Compared to 2022 and 2023, g_S values in 2024 were markedly higher (0.06 to 0.16 mm s⁻¹ in the morning; 0.07 to 0.21 mm s⁻¹ in the afternoon), while r_L values were lower (0.83 to 1.93 s cm⁻¹ in the morning; 0.57 to 1.45 s cm⁻¹ in the afternoon). Conversely, in 2022 and 2023, significantly higher r_L values were recorded (4.47 to 11.9 s cm⁻¹ in 2022; 7.42 to 10.8 s cm⁻¹ in 2023), accompanied by lower g_S values. These outcomes, obtained during the peak of the summer season, suggest a heat stress response in trees during 2022 and 2023 compared to 2024 (Figure 9). This is indicated by the lower g_S values (suggesting stomatal closure) and higher r_L values (indicating reduced water loss from leaves) [10,32]. Additionally, the values of E recorded on the same dates (Tables S3 and S4) were lower in 2022 (1.21 to 2.17 µmol m² s⁻¹) and 2023 (1.04 to 1.32 µmol m² s⁻¹), compared to 2024 (1.83 to 2.71 µmol m² s⁻¹), reinforcing the evidence of reduced transpiration likely caused by stomatal closure [10].

Among modalities, the significant differences observed in 2024 were more pronounced for average g_S values than for r_L. The lowest g_S values were recorded under the yellow net (0.06 and 0.07 mm s⁻¹ for morning and afternoon, respectively), which were significantly lower than those recorded under the black net, white net, and control in the morning (0.16, 0.15, and 0.12 mm s⁻¹, respectively), as well as under the white net in the afternoon (0.21 mm s⁻¹). The lower g_S values under the yellow net may be related to its higher transmission of green light, which can counteract the effect of blue light—a wavelength known to promote stomatal opening—thereby reducing stomatal conductance [3,33]. Conversely, the highest g_S values observed under the white net and uncovered control in the afternoon might be linked to a reduced vapor pressure deficit due to higher relative humidity and air temperature [3]. In contrast, the high g_S values recorded under the black net—the one with the highest shading level—may reflect lower heat stress due to increased protection from solar radiation.

The average values of SLA, measured between 2020 and 2024, showed significant differences between modalities in each year, except in 2023 (Figure 10). The highest average SLA values were observed in trees under the black net (93.7, 104.0, 145.6, 120.8 cm² g⁻¹ in 2020, 2021, 2022, and 2023, respectively) and under the grey net (137.4 cm² g⁻¹ in 2024). The lowest values were observed under the white net (86.4, 91.5, and 108.1 cm² g⁻¹ in 2020, 2021, and 2023, respectively) and the uncovered control (118.9 and 120.5 cm² g⁻¹ in 2022 and 2024, respectively). Overall, the results suggest a trend of thinner leaves (i.e., higher SLA), under the black net, followed by the grey and yellow nets. In contrast, thicker leaves (lower SLA) were observed under the white net, followed by the control and red nets. Similarly, Salazar-Canales et al. [34] reported a reduction in leaf thickness in hazelnut trees under nets with higher shading effects (black and blue-grey) compared to those under a pearl-grey net. This reduction may be a plant response to lower light availability, allowing for increased light interception and enhanced photosynthesis [6]. In the case of the red net, the thicker leaves may be attributed to the reduced transmission of blue light [11]. Chlorophyll content (CCI) and reflectance indices (PRI and NDVI) were estimated on various dates between 2022 and 2024 (Table S6). No significant differences in average CCI values between modalities were found, and no consistent trends emerged. However, significant differences between modalities were observed for NDVI on 17 August 2023 and 19 August 2024, and for PRI on 27 June 2023 and 17 August 2023. Both indices are related to photosynthetic activity. While NDVI is widely used to estimate vegetation parameters and photosynthetic potential, PRI is more directly linked to radiation-use efficiency and key stress adaptation mechanisms such as the xanthophyll cycle and non-photochemical quenching (NPQ) [35]. Despite these findings, no consistent patterns were observed across treatments. Notably, the lowest NDVI and PRI values were recorded on 19 August 2022 and 27 June 2023 across all treatments.

The average maximum quantum efficiency of PSII, measured with (Fv/Fm) and without (Fv’/Fm’) dark adaptation, was recorded annually from 2020 to 2024 on various dates (Table S7; Figure 11). Significant differences between modalities were found only for Fv/Fm on two dates: 22 July 2020 and 19 August 2022. On these dates, the highest Fv/Fm values were recorded under the red net (0.81 in 2020 and 0.80 in 2022), significantly higher than the lowest values under the yellow net (0.78 in 2020) and the control (0.75 in 2022). Similarly, Aoun and Manja [25] reported significantly higher Fv/Fm values in apple leaves under red nets compared to uncovered controls, suggesting higher stress in the latter. Fv/Fm is a widely used indicator of plant stress, with values below ~0.80 potentially indicating photoinhibition or environmental stress [32,36]. In this study, Fv/Fm values below the optimal threshold were recorded across all modalities between 2020 and 2022, particularly when measurements were taken from mid-May to mid-July (Table S7). More frequently, values closer to the optimal level were observed under the black and grey nets, suggesting that the higher shading they provide may help mitigate heat stress. Conversely, the lowest values were often recorded under the uncovered control, indicating greater susceptibility to stress conditions [13,37].

Comparing Fv/Fm and Fv’/Fm’ values from 2022 to 2024, Fv’/Fm’ values were consistently lower, as expected [38]. Moreover, Fv’/Fm’ values recorded in 2023 and 2024 were consistently above 0.5 and showed less variability than Fv/Fm (Figure 11). Changes in Fv’/Fm’ reflect inverse changes in NPQ activity, particularly in response to rapid light increases [38,39]. NPQ is a key protective mechanism in photosynthesis that dissipates excess energy as heat [32,35]. As NPQ increases, Fv’/Fm’ typically drops below 0.6 [38]. The higher Fv’/Fm’ values (>0.5) observed across all modalities in 2023 and 2024 suggest more favorable light conditions. In contrast, on 19 August 2022, Fv’/Fm’ values fell below 0.5 in all modalities except the red net. The lowest value was recorded under the uncovered control (0.24), followed by the black (0.35) and yellow (0.36) nets. Interestingly, from 2022 to 2024, Fv’/Fm’ values under the red net consistently remained above 0.5, suggesting lower sensitivity to rapid light changes. Similarly, Özkaya et al. [40] reported higher Fv’/Fm’ values in apple leaves under black and red nets compared to blue and pearl nets during the growing season.

3.3. Fruit Quality and Economic Evaluation

3.3.1. Fruit Temperatures and Sunburn Damage

The surface temperatures of leaves and fruit, measured on both the exterior and interior of the canopy, were recorded between 2021 and 2024 (Table 1). Significant differences were found between modalities for average values at each canopy position, except for leaf temperatures (both exterior and interior) in 2021 and 2023. Differences between exterior and interior positions were also significant in most cases, with the exception of leaf temperatures under the red net in 2021. Overall, temperatures were higher on the exterior of the canopy, ranging from 31.2 °C to 43.9 °C for leaves and from 37.2 °C to 49.2 °C for fruit. Interior canopy temperatures ranged from 28.1 °C to 38.3 °C for leaves and from 30.3 °C to 39.8 °C for fruit. The highest annual interior fruit temperatures were observed under the red net (33.5 °C in 2021, 33.0 °C in 2023, and 36.1 °C in 2024) and under the white net (39.8 °C in 2022). On the exterior of the canopy, the highest fruit temperatures were most frequently recorded under the uncovered control (49.2 °C in 2022 and 47.9 °C in 2024), followed by the red net (44.5 °C in 2021) and the white net (40.7 °C in 2023). Notably, the lowest temperatures—both on leaves and fruit, regardless of canopy position—were most often observed under the grey net.

Overall, the results suggest that the grey, yellow, and black nets were the most effective in reducing the surface temperatures of exposed fruit. These findings align with those of McCaskill et al. [12], who reported that grey netting effectively reduced surface temperatures in “Royal Gala” apples. Kalcsits et al. [41] similarly observed lower fruit surface temperature in “Honeycrisp” apples under pearl, red, and blue nets compared to the uncovered control. However, results across studies vary, likely due to complex interactions between shading, microclimate, and the greenhouse effect [1]. Crucially, although interior fruit temperatures under red and white nets were relatively high, the average values remained well below the minimum threshold of 46 °C typically associated with sunburn damage [13,42]. In contrast, average temperatures exceeding 46 °C were observed in 2022 for exterior fruit under all modalities except grey and black nets.

In 2024, temperatures of leaves and fruit were also measured at three different times of day (11:30 a.m., 2:00 p.m., and 4:30 p.m.) to assess daily temperature variations (Figure S6; Table S8). Significant differences between modalities were observed at all times. Temperatures generally peaked in the late afternoon (4:30 p.m.). For exterior fruit, average temperatures ranged from 38.8 °C (grey net) to 47.9 °C (control) at 2:00 p.m. and from 45.6 °C (yellow net) to 51.2 °C (control) at 4:30 p.m. These findings are consistent with McCaskill et al. [12], supporting the notion that surface temperatures tend to peak later in the day and that netting can effectively reduce heat exposure by mitigating solar intensity during afternoon hours.

Sunburn damage on Gala “Redlum” apples was evaluated from 2022 to 2024 based on symptom severity, corresponding to discoloration levels on the exposed fruit surface. Four damage categories were defined: (i) sunburn necrosis—the most severe form, characterized by dark brown or black lesions affecting both epidermal and subepidermal tissue; and (ii) sunburn browning—the most common type, identified by yellow, brown, or tan discoloration in the epidermis [13]. The four damage categories were labeled as slight, moderate, severe (indicating browning), and very severe (indicating necrosis).

From 2022 to 2024, the incidence of sunburn damage (all categories combined) remained below 12% on average (Figure 12). The highest average incidence occurred in fruit from uncovered trees: 11.4% in 2022, 9.89% in 2023, and 2.91% in 2024. These trees also exhibited the highest proportion of very severe damage (sunburn necrosis): 3.45% in 2022, 1.94% in 2023, and 1.13% in 2024. In contrast, the lowest damage rates were observed in fruit from trees under grey and black nets. Grey netting recorded sunburn levels between 0.43% (2024) and 3.24% (2023), with very severe damage occurring only in 2023 (0.31%). Black netting ranged from 0.34% (2024) to 3.93% (2023).

Sunburn damage was generally higher in 2022 and 2023 than in 2024, likely due to greater heat exposure during the May-August period. The number of hours above 30 °C and 35 °C were as follows: 85 and 31 h in 2022; 54 and 9 h in 2023; and 52 and 0 h in 2024. These results are consistent with previous studies showing a strong relationship between fruit surface temperatures and sunburn risk in the “Gala” cultivar [12,13,43]. The threshold for sunburn browning typically ranges from 46 °C to 49 °C, while necrosis is induced at temperatures exceeding 50 °C [13,42]. These thresholds are reflected in our results, particularly for fruit on uncovered trees, which surpassed at the 46 °C mark (see Table 1; Figure 12). In the years with greater sunburn damage (2022 and 2023), the highest rates of very severe damage were consistently observed under uncovered trees, followed by those under white and red nets. Overall, our findings indicate that black and grey nets were the most effective in protecting fruit from sunburn, in agreement with previous research [5,7,40].

3.3.2. Fruit Weight and Economic Evaluation

The results for the cumulative average fruit weight of the “Gala Redlum” cultivar over the five-year period (2020–2024) showed no statistically significant differences between modalities (Figure 13). The highest cumulative fruit weight was observed under the uncovered control (685.4 g), followed by the net-cover modalities (in decreasing order): black (664.7 g), white (646.7 g), grey (622.6 g), yellow (618.4 g), and red (611.9 g). The slightly higher cumulative average value recorded for the uncovered control appears to be due to a lower fruit load per tree, as revealed by the tendency observed in 2021, a year of low productivity (Figure 3B), in which most modalities (except for the grey net) recorded the highest average fruit weights (Figure 13). Conversely, in 2024, the year of highest productivity for all modalities, the uncovered control recorded the lowest average yield but the highest average fruit weight, while the grey net recorded the highest average yield but the lowest average fruit weight (Figure 3B and Figure 11). This trend was also observed in some of the previous years, although not as markedly.

Significant differences in annual average fruit weight were found among modalities, except in 2022 (Figure 13). The average fruit weight recorded under grey and yellow nets showed the greatest variation, alternating between the highest and lowest average values. Among the modalities with the lowest average values per year were the net modalities: yellow (112.0 g in 2020 and 122.0 g in 2022), grey (126.9 g in 2021 and 91.9 g in 2024), and red (106.9 g in 2023). Conversely, the modalities that exhibited the highest annual average values of fruit weight were the net-covered grey (141.0 g in 2020 and 149.2 g in 2022), white (154.9 g in 2021), yellow (139.8 g in 2023), and the uncovered control (132.3 g in 2024). Mixed effects (positive, negative, or none) of different colored nets on apple fruit size have been reported in other studies, indicating that environmental factors might play a relevant role in influencing the specific response among net types [2,7].

The economic analysis of netting effects on “Gala Redlum” apple trees over the five-year period (2020 to 2024), based on average prices calculated per fruit caliber, revealed that the highest cumulative income (EUR/ha) was achieved under the black net (EUR 72,315), followed by white (EUR 71,095), yellow (EUR 64,742), red (EUR 62,449), and grey (EUR 61,145) nets, all of them higher than the uncovered control (EUR 60,947) (Figure 14B; Tables S9 and S10). Among the net treatments, the grey net resulted in the lowest cumulative income, despite recording the second highest cumulative yield (178.5 t/ha), due to a lower proportion of large-caliber fruits, which are more commercially valuable, and greater annual yield fluctuations. In addition, higher percentages of fruit with a caliber ≥ 60 were recorded more often between years under the uncovered control and black modality (Figure 14A). When analyzing annual yield (Table S10), the highest incomes (EUR/ha) were recorded under the white net (€16,393 in 2022 and €19,615 in 2024), black net (EUR 17,434 in 2021), yellow net (EUR 15,120 in 2023), and grey net (EUR 12,557 in 2020). Conversely, the lowest incomes (EUR/ha) for each year were recorded under the uncovered control (EUR 6616 in 2020 and EUR 12,651 in 2021), grey net (EUR 7632 in 2022 and EUR 13,025 in 2024), and red net (EUR 11,361 in 2023). Iglesias and Alegre [5] also evaluated the economic impact of netting on “Mondial Gala” apples, considering depreciation due to sunburn and cracking. Their study found that total income (€/ha) was higher for fruit of trees under crystal net compared to the uncovered control, while black net resulted in lower income. In another study, McCaskill et al. [12] observed a higher income in the non-netted apple orchard, though this was compensated by a significantly higher percentage of sunburn damage in comparison to the orchard with grey netting. In the present study, considering the average sunburn damage between 2022 and 2024 (excluding slight damage, as such fruit may still be marketable), the highest sunburn loss was observed in the uncovered control (5.64%), followed by white net (2.42%), red net (1.76%), yellow net (1.26%), black net (0.69%), and grey net (0.51%). Consequently, the cumulative income (€/ha), accounting for sunburn depreciation, was lower in the uncovered control compared to all the other netting. It is important to highlight that during the evaluated period, no hail damage occurred. Therefore, the economic benefit of nets for hail protection could not be demonstrated in our trial. In some regions where hail is frequent, the reduction in yield losses can offset or even exceed the investment cost in net structures [44]. Nonetheless, and even without the occurrence of hail, the economic benefit obtained during this period already surpassed the additional investment cost needed to cover the orchard (net, cables, and horizontal structure).

These findings align with the previously mentioned studies [5,12] in the comparison of economic return between netted and uncovered orchards. When comparing black and white nets, which provided the highest cumulative incomes, sunburn losses were significantly lower for black netting. Among the red, grey, and yellow nets, yellow netting resulted in a higher cumulative fruit yield and lower sunburn losses than red netting. These results provide new and valuable insights into the economic returns between conventional and photoselective nets.

3.3.3. Fruit Quality Parameters

Fruit quality parameters such as firmness (kg/cm²), diameter (mm), height (mm), weight (g), dry matter (%), starch index (1–10) and SSC (expressed in °Brix) were assessed between 2020 and 2024 (Table S11). Significant differences between net cover modalities were observed for dry matter, starch index, and SSC across evaluated years. For the remaining parameters, significant differences occurred only in specific years. Overall, the results indicate a trend of higher average values of dry matter and SSC in fruits from trees under the uncovered control. This is consistent with the greater fruit weight observed under this modality, as previously discussed. Regarding SSC, other studies have also reported lower values in apples grown under netting [8,11,45]. SSC reflects the soluble sugar content in fruit. Higher values in uncovered fruit may result from increased light intensity and temperature, which favor sugar accumulation and ripening [46] and are commonly used as indicators of fruit flavor [1]. Serra et al. [11] also found higher SSC values in uncovered apples compared to those from trees under netting, but the differences (below 1 °Brix) were not sufficient to affect consumer-perceived fruit quality. Similarly, the differences observed in our study (~1 to 3 °Brix) are unlikely to significantly affect fruit quality.

Fruit color parameters, specifically L*, C*, and °Hue, were also measured between 2020 and 2024 (Table 2; Figure 15). Significant differences in average L* and °Hue values were found across all years, while differences in C* were observed in 2020 and 2024. Average L* and °Hue values were highest under the red net, followed by the yellow net. A decrease in °Hue and an increase in L* are associated with a lighter red color in the fruit [47]. Thus, red and yellow nets may have delayed ripening, as evidenced by higher °Hue values [48]. On the other hand, average L* values were generally lower in fruit from trees under the grey net. This aligns with our observation that fruits under the grey net, which provides lower light transmission, showed lower L* values [2]. This finding is consistent with the results observed for the grey net relative to L* values, although we did not observe the same marked tendency for the black net. C* values were lowest across all modalities in 2024, the year with the lowest summer heat stress. This likely reflects reduced light intensity, which resulted in less intense fruit coloration.

3.4. Principal Component Analysis

A PCA was performed on the data collected between 2022 and 2024 to elucidate the influence of net cover modalities on the performance of “Gala Redlum” apple trees (Table 3). The adequacy of the sampling performance was evaluated through the KMO test and Bartlett’s test of sphericity. The inclusion of variables in the PCA was contingent upon attaining MSA values above 0.5. The MSA is a specific particularization of the KMO test for each variable, where values below 0.5 were excluded, as they do not adequately align with the structure defined by the remaining variables [24]. The overall KMO value obtained was 0.808, indicating a good level of factor analysis suitability, which confirmed the dataset’s adequacy for PCA. Bartlett’s test of sphericity yielded statistically significant results (p < 0.001), indicating sufficient inter-variable correlations. The variables included mainly comprised productivity and growth parameters (e.g., yield, fruit weight, RGR), physiological traits (A_n, E, r_L, g_s, Fv/Fm, PRI, NDVI, CCI), and fruit quality parameters, specifically temperatures measured on leaves and fruits located at the exterior of the canopy (TLE and TFE). A total of three principal components (PC1, PC2, and PC3) were retained, explaining together 69.0% of the total variance. PC1 explained the largest portion (32.4%), followed by PC2 (24.3%) and PC3 (12.3%).

Regarding PC1 (32.4% of the total variance), the highest loadings were negative for PRI (−0.921) and NDVI (−0.913), while TLE (0.893), TFE (0.822), and Ci (0.725) presented high positive loadings. Yield showed a moderate negative loading (−0.575), and fruit weight a moderate positive loading (0.534). Changes in PRI are strongly associated with photosynthetic dynamics, especially under high light conditions, via mechanisms like NPQ and the xanthophyll cycle [35]. Like PRI, NDVI is a robust indicator of vegetation status, and its decline typically reflects plant stress [49,50]. Therefore, the combination of decreasing reflectance indices (PRI, NDVI) and increasing leaf/fruit temperatures (TLE, TFE) suggests a stress response to elevated light intensity. The high positive loading of Ci may indicate enhanced CO₂ uptake due to increased light, even in the absence of a clear stress response. Since CO₂ assimilation is linked to heat tolerance [10], these results may reflect adaptive responses in trees under net cover. In sum, variability in PC1 appears to reflect responses to light intensity and associated stress conditions, which in some cases resulted in reduced yield but increased fruit weight.

For PC2 (24.3% of the variance), high positive loadings were observed for A_n (0.899), E (0.899), and g_s (0.770), and a moderate one for yield (0.487), whereas r_L showed a high negative loading (−0.814). These patterns indicate an enhanced photosynthetic response—high photosynthetic rate, greater transpiration, improved gas exchange, and reduced stomatal resistance—which are traits associated with improved productivity [6,10]. This set of traits is linked to increased yield, although the relationship is moderate.

In PC3 (12.3% of the variance), the strongest loadings were positive for CCI (0.760) and negative for RGR (−0.707), with a moderate positive loading for Fv/Fm (0.465). Since canopy architecture and leaf structure are key for light interception and photosynthetic performance [31], these results suggest a trade-off—higher investment in foliage (CCI) at the expense of structural growth (RGR), potentially explaining the observed increase in photosynthetic efficiency (Fv/Fm).

The distribution of principal component scores by year and net cover modality (Figure 16; Table S12) reveals distinct trends: between years, 2022 stands out as particularly stressful, with high positive PC1 scores across all modalities—indicative of elevated temperature and light stress. In contrast, 2024 had more favorable conditions, reflected in negative PC1 scores and higher values for PC2 and PC3—indicating better physiological and photosynthetic performance. Between modalities, the control showed the highest PC1 scores consistently, reinforcing its role in light moderation and stress mitigation—in line with other studies [5,12]. Regarding PC2, the black net showed the most inter-annual variation: lowest values in 2022–2023 and highest in 2024—indicating high year-to-year dependence on light conditions. PC3 showed more internal variation between and within modalities. The black net consistently presented low PC3 values, pointing to increased structural growth investment under this net, a trend supported by other studies linking high-shading nets to increased vegetative development and altered assimilate distribution [1,51]. The PCA results suggest that netting effects are highly influenced by yearly climatic conditions, particularly light intensity. The ability of net covers to modulate plant responses—enhancing performance in favorable years and reducing stress in challenging ones—appears to be a key factor in explaining the variability observed.

4. Conclusions

This study provided a comprehensive five-year evaluation of the effects of conventional and photoselective netting on the physiological performance, yield, fruit quality, and economic outcomes of “Gala Redlum” apple trees under Mediterranean conditions. While the use of netting did not consistently lead to statistically significant differences in cumulative yield, despite being 24% higher under the white net than the uncovered control, it had clear benefits in mitigating heat and light stress, as demonstrated by improved physiological responses (e.g., higher photosynthetic rate, Fv/Fm values, and stomatal conductance) and lower fruit surface temperatures.

Among the tested nets, the black and yellow nets showed the most balanced performance across physiological, agronomic, and economic parameters. The grey net was most effective at reducing canopy temperatures and sunburn incidence but showed greater variability in yield. The uncovered control produced fruit with higher dry matter and SSC, yet was more susceptible to sunburn and heat-related physiological stress. Principal Component Analysis further confirmed that stress responses under high light conditions were more pronounced in the uncovered control, whereas the black and grey nets moderated plant responses and improved physiological performance consistency.

From an economic perspective, all netting treatments outperformed the uncovered control. Notably, the black net yielded the highest cumulative income, with low sunburn-related losses and stable fruit calibers. These results underscore the potential of netting technologies, particularly conventional black and photoselective yellow nets, as effective tools for climate adaptation in apple orchards. Future studies will explore cost–benefit analyses that include installation and maintenance expenses, combinations of different net colors in order to increase photoselective effects, and assessments of long-term impacts on soil–plant–microclimate interactions to refine netting strategies under warming scenarios.

Author Contributions

Conceptualization, M.L.d.S.; methodology, M.G., M.R., F.M. and M.L.d.S.; software and validation, M.G., M.R., F.M., S.A. and M.L.d.S.; formal analysis, S.A., M.G., M.R. and M.L.d.S.; investigation, M.G., M.R., F.M., V.A., S.R. and M.L.d.S.; resources, M.L.d.S.; data curation, M.G., M.R., F.M., V.A., S.R., S.A. and M.L.d.S.; writing—original draft preparation, S.A.; writing—review and editing, S.A., M.G., M.R., F.M., V.A., S.R., and M.L.d.S.; supervision, M.G., M.R., F.M., and M.L.d.S.; project administration, M.L.d.S.; funding acquisition, M.L.d.S. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data will be made available upon request.

Acknowledgments

This work was supported by Fundação para a Ciência e a Tecnologia (Portugal) through the R&D Unit “GREEN-IT—Bioresources for Sustainability” (UIDB/04551/2020, DOI: 10.54499/UIDB/04551/2020 and UIDP/04551/2020, DOI: 10.54499/UIDP/04551/2020) and LS4FUTURE Associated Laboratory (LA/P/0087/2020, DOI: 10.54499/LA/P/0087/2020). Authors also want to thanks to Élia Pimenta, Griba and Quality Plant. Special thanks to Susana Ferreira for their invaluable assistance with the revision process and for significantly improving English quality.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:

An	cumulative photosynthetic rate
B	blue (light range)
CCI	chlorophyll content index
Ci	intracellular CO2 concentration
CO2	carbon dioxide
CTIFL	Centre Technique Interprofessionnel des Fruits et Légumes
E	transpiration rate
FR	far-red (light range)
Fv/Fm	maximum quantum efficiency of photosystem II with dark adaptation
Fv’/Fm’	maximum quantum efficiency of photosystem II without dark adaptation
gs	stomatal conductance
HDPE	high-density polyethylene
IRGA	infra-red gas analyzer
KMO	Kaiser–Meyer–Olkim
MSA	measure sampling adequacy
NDVI	normalized difference vegetation index
NIR	near infrared
NPQ	non-photochemical quenching
PAR	photosynthetic active radiation
PCA	principal component analysis
PC	principal components
PRI	photochemical reflectance index
R	red (light range)
RGR	relative growth rate
SLA	specific leaf area
SSC	soluble solids content
TCSA	trunk cross-sectional area
TFE	temperature of fruit at the exterior of canopy
TLE	temperature of leaf at the exterior of canopy
UV	ultraviolet

Footnotes

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Figures and Tables

Figure 1 Photoselective nets installed in the apple orchard located at the INIAV Innovation Center (INIAV, IP), Alcobaça, Portugal.

Figure 2 “Gala Redlum” apple fruit with different sunburn severity levels: (A) slight, (B) moderate, (C) severe, and (D) very severe.

Figure 3 (A) Cumulative yield (mean ± standard error) of “Gala Redlum” apple trees between 2020 and 2024, according to the net cover modality and associated shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and the uncovered control. Means followed by different lowercase letters (within each year and between net cover modalities) and uppercase letters (within each modality for cumulative yield) are significantly different (Tukey’s test, p ≤ 0.05). (B) Annual yield (mean ± standard error) of “Gala Redlum” apple trees from 2020 and 2024, averaged across all net modalities in the experimental field, as a function of year. Means followed by different letters are significantly different (Games–Howell test, p ≤ 0.05).

Figure 4 Evolution of average trunk cross-sectional area (TCSA) of apple trees of the “Gala Redlum” cultivar, with initial (i) and final (f) measurements (mean ± standard error) taken in each year (2021–2024) as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and uncovered control.

Figure 5 Ratio of cumulative yield to final trunk cross-sectional area (TCSA) of “Gala Redlum” apple trees (mean ± standard error), measured annually from 2021–2024, under different net cover modalities with distinct shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and the uncovered control. Means followed by the same lowercase letters (between modalities in each year) and uppercase letters (within each modality for cumulative values are not significantly different (Tukey’s test, p ≤ 0.05).

Figure 6 Setting rate of apple trees of the “Gala Redlum” cultivar (mean ± standard error) taken in each year (2021–2024) as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modalities are significantly different (Dunn’s test, p ≤ 0.05).

Figure 7 Average fruit growth (mm) of Gala “Redlum” along the days after full bloom, in each year, from 2020 to 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control). Means followed by different letters within each date and between net cover modalities are significantly different (in 2024, 24 d, by Games–Howell test; 2020, 44 d, 76 d and in 2024, 30 d, by Tukey’s test; remaining significant cases in 2022 and 2023 by Dunn’s test; p ≤ 0.05).

Figure 8 Cumulative photosynthetic rate (A_n) of “Gala Redlum” apple trees (mean ± standard error), measured in the morning between 2020 and 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and uncovered control. Means followed by different letters within each year and between net cover modality (lowercase letters), and within each modality for the cumulative A_n rate (uppercase letters) are significantly different (A_n in 2020, and 2021–2023 by Dunn’s test; p ≤ 0.05).

Figure 9 Stomatal resistance (r_L) (A) and stomatal conductance (g_S) (B) of “Gala Redlum” apple leaves (mean ± standard error), measured in the morning and afternoon on each date between 2022 and 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and uncovered control. Means followed by different letters within each date—for the morning period (uppercase) and afternoon period (lowercase)—and between net cover modalities are significantly different [r_L in 2024 (19 August; afternoon) by Games–Howell test; other significant cases by Dunn’s test; p ≤ 0.05].

Figure 10 Specific leaf area (SLA) of “Gala Redlum” apple leaves (mean ± standard error), measured between 2020 and 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and uncovered control. Means followed by different letters within each date and between net cover modalities are significantly different (SLA in 2024 by Tukey’s test; all other significant differences by Dunn’s test; p ≤ 0.05).

Figure 11 Maximum quantum efficiency of photosystem II measured with dark adaptation (Fv/Fm) (A) and without (Fv’/Fm’) (B) in “Gala Redlum” cultivar for each date from 2022 to 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and a control without net cover.

Figure 12 Incidence of sunburn on fruits of the Gala “Redlum” cultivar, categorized by damage severity (slight, moderate, severe, and very severe), from 2022 and 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control).

Figure 13 Cumulative apple fruit weight of the “Gala Redlum” cultivar (mean ± standard error), between 2020 and 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modality (lowercase) and within each modality for cumulative weight (uppercase) are significantly different (in 2020 by Dunn’s test; 2021, 2022, and 2024 by Tukey’s test; p ≤ 0.05).

Figure 14 (A) Cumulative average percent of fruit with a caliber ≥60 mm in diameter; and (B) cumulative average yield price per caliber (calculated based on the national supply market prices for all the years evaluated) of apple fruit of the “Gala Redlum” cultivar, between 2020 and 2024, as a function of the net cover modalities with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control).

Figure 15 Evolution of the average Hue angle (°Hue) of the “Gala Redlum” cultivar from 2020 to 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control).

Figure 16 Principal component (PC) scores (mean ± standard error), as a function of year (2022 to 2024) and net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control).

Table 1

Temperatures measured on leaves (T. Leaf) and fruits (T. Fruit) of the “Gala Redlum” cultivar (mean ± standard error), located on the exterior and interior of the canopy, recorded at 2:00 p.m. each year (2021–2024), as a function of the net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modalities are significantly different (T. Fruit on exterior in 2024 by Games–Howell test; T. Fruit on interior, in 2021 and 2024, by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05).

			Modality
Year	Parameter	Position	Black	Red	Grey	Yellow	White	Control
2021	T. Leaf	Exterior	32.5 ± 0.77 a	31.2 ± 1.98 a	32.5 ± 0.87 a	32.8 ± 1.12 a	31.3 ± 0.77 a	32.4 ± 0.67 a
		Interior	29.7 ± 0.58 a	28.8 ± 0.22 a	28.1 ± 0.55 a	29.7 ± 0.23 a	29.2 ± 0.46 a	28.9 ± 0.24 a
		p-value (position)	0.0213 *	0.2739	0.0029 **	0.0267 *	0.0465	<0.001 ***
	T. Fruit	Exterior	38.8 ± 1.46 b	44.5 ± 1.07 a	39.8 ± 1.25 ab	42.7 ± 1.03 ab	41.7 ± 0.73 ab	42.9 ± 0.97 ab
		Interior	32.5 ± 0.33 ab	33.5 ± 0.24 a	30.3 ± 0.59 c	32.7 ± 0.26 ab	32.6 ± 0.54 ab	31.5 ± 0.39 bc
		p-value (position)	0.0031 **	0.0088 **	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
2022	T. Leaf	Exterior	43.2 ± 0.87 a	42.8 ± 0.72 ab	39.2 ± 0.82 b	42.8 ± 1.26 ab	43.9 ± 0.74 a	43.3 ± 0.58 a
		Interior	37.4 ± 0.47 ab	38.3 ± 0.53 a	34.8 ± 0.22 c	37.7 ± 0.66 ab	38.0 ± 0.28 ab	36.2 ± 0.32 bc
		p-value (position)	<0.001 ***	<0.001 ***	<0.001 ***	0.0048 **	<0.001 ***	<0.001 ***
	T. Fruit	Exterior	46.0 ± 0.88 ab	47.4 ± 0.48 ab	43.7 ± 1.09 b	46.3 ± 0.63 ab	47.7 ± 1.34 a	49.2 ± 0.42 a
		Interior	39.1 ± 0.19 b	39.7 ± 0.28 ab	36.8 ± 0.16 c	39.0 ± 0.25 b	39.8 ± 0.14 a	39.3 ± 0.15 ab
		p-value (position)	<0.001 ***	<0.001 ***	0.0012 **	<0.001 ***	0.0020 **	0.0038 **
2023	T. Leaf	Exterior	34.7 ± 0.59 a	33.8 ± 0.49 a	33.7 ± 0.55 a	34.7 ± 0.39 a	35.3 ± 0.67 a	35.2 ± 0.42 a
		Interior	29.9 ± 0.33 a	29.7 ± 0.22 a	30.9 ± 0.48 a	29.7 ± 0.39 a	30.6 ± 1.37 a	29.6 ± 0.21 a
		p-value (position)	<0.001 ***	<0.001 ***	0.0020 **	<0.001 ***	0.0082 **	<0.001 ***
	T. Fruit	Exterior	39.6 ± 0.79 ab	39.4 ± 0.81 ab	37.2 ± 0.64 b	38.1 ± 0.60 ab	40.7 ± 0.76 a	40.5 ± 0.70 a
		Interior	31.3 ± 0.13 c	33.0 ± 0.17 a	31.6 ± 0.29 bc	31.7 ± 0.13 bc	32.2 ± 0.09 ab	31.6 ± 0.28 bc
		p-value (position)	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
2024	T. Leaf	Exterior	34.5 ± 0.65 abc	36.8 ± 0.66 a	32.3 ± 0.46 c	33.5 ± 0.61 bc	35.6 ± 0.38 ab	36.6 ± 0.60 a
		Interior	32.4 ± 0.20 c	34.1 ± 0.37 a	30.3 ± 0.30 d	31.2 ± 0.42 cd	32.4 ± 0.37 bc	33.7 ± 0.18 ab
		p-value (position)	0.0016 **	0.0042 **	0.0031 **	0.0065 **	<0.001 ***	0.0015 **
	T. Fruit	Exterior	43.1 ± 0.83 bc	44.7 ± 0.83 ab	38.8 ± 1.30 c	39.9 ± 0.74 c	46.0 ± 0.52 ab	47.9 ± 0.87 a
		Interior	34.8 ± 0.23 ab	36.1 ± 0.23 a	32.5 ± 0.43 c	33.8 ± 0.33 bc	35.8 ± 0.39 a	35.6 ± 0.75 ab
		p-value (position)	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***

*, **, *** Significant at 0.05, 0.01 and 0.001 levels, respectively.

Table 2

Fruit color parameters of the “Gala Redlum” cultivar (mean ± standard error) measured annually from 2020 to 2024, as a function of net cover modality with different shading levels: Black (≈22.4%), red (≈20.6%), grey (≈15.7%), yellow (≈14.7%), white (≈9.6%), and for apple trees without net cover (control). Different letters within each year and among net cover modalities indicate statistically significant differences (L* in 2024 and °Hue in 2022 by Games–Howell test; all other significant differences by Dunn’s test; p ≤ 0.05).

Year	Color	Black		Red		Grey		Yellow		White		Control
2020	L*	41.9 ± 0.79	ab	43.0 ± 0.78	a	38.6 ± 0.73	c	42.3 ± 1.00	ab	39.3 ± 0.77	bc	39.3 ± 0.51	bc
	C*	52.1 ± 0.49	ab	53.1 ± 0.40	a	50.0 ± 0.63	bc	51.9 ± 0.52	ab	49.6 ± 0.60	c	49.5 ± 0.51	c
	°Hue	30.3 ± 0.75	a	31.0 ± 0.65	a	27.9 ± 0.66	b	32.4 ± 1.19	a	28.2 ± 0.79	b	26.2 ± 0.42	b
2021	L*	39.4 ± 0.80	c	46.7 ± 1.38	a	39.8 ± 0.84	c	45.4 ± 1.68	ab	42.3 ± 1.28	bc	43.3 ± 1.02	ab
	C*	49.3 ± 0.59	a	48.3 ± 0.79	a	47.7 ± 0.71	a	48.6 ± 0.72	a	49.1 ± 0.93	a	48.6 ± 0.63	a
	°Hue	27.3 ± 0.57	b	33.6 ± 1.57	a	29.8 ± 0.92	ab	33.5 ± 1.72	ab	31.1 ± 1.56	ab	31.5 ± 1.26	ab
2022	L*	44.4 ± 0.80	bcd	55.5 ± 1.35	a	42.9 ± 0.97	bcd	47.2 ± 1.32	bc	40.6 ± 0.83	d	47.7 ± 1.53	bc
	C*	50.8 ± 0.76	a	46.6 ± 0.83	b	48.9 ± 0.97	a	50.1 ± 0.68	a	51.1 ± 0.72	a	49.6 ± 0.89	a
	°Hue	31.9 ± 0.72	bcd	44.9 ± 2.12	a	30.5 ± 1.15	cd	35.6 ± 1.43	bc	28.8 ± 0.84	d	37.5 ± 1.82	ab
2023	L*	48.9 ± 0.97	bc	52.6 ± 1.15	a	46.1 ± 1.12	c	49.3 ± 1.20	b	47.3 ± 1.00	bc	47.6 ± 1.28	bc
	C*	49.3 ± 0.69	a	50.3 ± 0.72	a	50.5 ± 0.74	a	50.4 ± 0.50	a	51.1 ± 0.40	a	52.0 ± 0.30	a
	°Hue	36.5 ± 1.11	ab	42.0 ± 1.62	a	35.2 ± 1.63	b	36.7 ± 1.41	ab	35.2 ± 1.04	b	37.2 ± 1.48	ab
2024	L*	48.3 ± 0.69	ab	51.3 ± 1.27	a	43.4 ± 0.86	c	50.2 ± 1.22	a	45.7 ± 0.88	bc	44.3 ± 1.22	bc
	C*	44.2 ± 0.69	bc	43.2 ± 0.91	c	46.4 ± 0.75	a	44.8 ± 0.95	abc	44.8 ± 0.61	abc	46.0 ± 0.63	ab
	°Hue	39.5 ± 1.03	ab	44.2 ± 1.94	a	34.7 ± 0.97	c	44.7 ± 2.08	a	35.6 ± 1.06	bc	36.0 ± 1.57	bc

L*—lightness; C*—chroma.

Table 3

Principal components (PC) extracted with principal component analysis using data from 2002 to 2024, and the corresponding eigenvalues, variance (explained and accumulated), and loadings for each variable included in the analysis, as well as the percentage of each variable’s variance not explained by the components (uniqueness).

	PC1	PC2	PC3	Uniqueness
Eigenvalues	5.166	3.470	1.025
Explained variance (%)	32.40	24.30	12.30
Cumulative variance (%)	32.40	56.70	69.00
Component Loadings:
PRI	−0.921			0.1426
NDVI	−0.913			0.1431
TLE	0.893			0.1948
TFE	0.822			0.2586
Ci	0.725			0.3607
Yield	−0.575	0.487		0.3229
Fruit weight	0.534			0.5995
An		0.899		0.1311
E		0.899		0.1002
rL		−0.814		0.3333
gS		0.770		0.3668
CCI			0.760	0.3679
RGR			−0.707	0.3350
Fv/Fm			0.465	0.6827

PRI—photochemical reflectance index; NDVI—normalized difference vegetation index; TLE—temperature of leaf at the exterior of canopy; TFE—temperature of fruit at the exterior of canopy; Ci—leaf internal concentration of CO₂; A_n—photosynthetic rate; E—transpiration; r_L—stomatal resistance; g_s—stomatal conductance; CCI—chlorophyll content index; RGR—relative growth rate of the trunk cross-sectional area; Fv/Fm—maximum quantum efficiency of photosystem II with dark adaptation; negative and positive correlations are highlighted in different color.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15081812/s1, Figure S1: (A) Temperature (average, minimum and maximum) and accumulated solar radiation recorded monthly between January 2021 and December 2024; (B) Temperatures above 35 °C registered between January 2021 and December 2024; Figure S2: Alternate bearing index (I) of apple trees of the “Gala Redlum” cultivar for the harvest of 2020 to 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control); Figure S3: Cumulative variation on trunk cross-sectional area (TCSA) of apple trees of the “Gala Redlum” cultivar (mean ± standard error) taken in each year (2021–2024) as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by same letters within each year and between net cover modality (lowercase) and within each modality for cumulative variation (uppercase), are not significantly different; Figure S4: Normalization of average annual branch growth (∆ Branch), annual variation in trunk cross-sectional area (∆ TCSA) and yield per tree (kg/tree) of apple trees of the “Gala Redlum” cultivar, relative to the net cover modality that exhibited the highest values for each parameter. The net cover modalities included different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control); Figure S5: Average photosynthetic rate (A_n) of apple trees of the “Gala Redlum” cultivar, between periods (morning—M; and afternoon—A) and years (2021 to 2024), as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control); Figure S6: Temperatures registered on leaves and fruits of the “Gala Redlum” cultivar (mean ± standard error), located on the exterior of the canopy (TLE and TFE), between different times (2:00 and 4:30 pm) in 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover(control). Means followed by different letters within each year and between net cover modality are significantly different (TFE at 2:00 pm by Games–Howell test; TLE at 11:30 p.m. and TFE at 4:30 pm by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05); Table S1: Biometric data of apple trees of the “Gala Redlum” cultivar (mean ± standard error) taken in each year (2021–2024) as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modality are significantly different (TCSA_initial in 2021 and variation of height in 2024 by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05); Table S2: Biometric data on annual branch growth (cm) of apple trees of the “Gala Redlum” cultivar (mean ± standard error) taken in each year (2022–2024) as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modality are significantly different (Branch_initial in 2022, by Games–Howell test; remaining significant cases by Tukey’s test; p ≤ 0.05); Table S3: Physiological parameters of apple leaves of the “Gala Redlum” cultivar (mean ± standard error) taken in the morning period for each date and between years (2020–2024), as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each date and year and between net cover modality are significantly different [A_n in 2020, g_S in 2021, Ci in 2020 (21 Sep) and 2023, E in 2020 (19 Aug), by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05]; Table S4: Physiological parameters of apple leaves of the “Gala Redlum” cultivar (mean ± standard error) taken in the afternoon period for each date and between years (2021–2024), as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each date and year and between net cover modality are significantly different [Ci in 2022 (19 Aug), E in 2022 (20 Jul), by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05]; Table S5: Stomatal resistance (r_L) and conductance (g_S) of apple leaves of the “Gala Redlum” cultivar (mean ± standard error), taken in the morning and afternoon for each date and between years (2022–2024), as a function of the net cover modality with different shading levels Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each date and year and between net cover modality are significantly different [r_L in 2024 (19 Aug; afternoon) by Games–Howell test; g_S in 2022 (20 July; morning), by Tukey’s test; remaining significant cases by Dunn’s test; p ≤ 0.05]; Table S6: Chlorophyll and reflectance indices of apple leaves of the “Gala Redlum” cultivar (mean ± standard error) for each date and between years (2022–2024), as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each date and year and between net cover modality are significantly different (NDVI index in 2024 by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05); Table S7: Maximum quantum efficiency of photosystem II with dark adaptation (Fv/Fm) and without (Fv’/Fm’) of apple leaves of the “Gala Redlum” cultivar (mean ± standard error) for each date and between years (2020–2024), as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each date and year and between net cover modality are significantly different by Tukey’s test (p ≤ 0.05); Table S8: Temperatures registered on leaves and fruits of the “Gala Redlum” cultivar (mean ± standard error), located on the exterior (TLE and TFE) and the interior (TLI and TFI) of the canopy, between different times (11:30 a.m., 2:00 and 4:30 p.m.) in 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modality are significantly different (TFE at 2:00 p.m. by Games–Howell test; TLE and TLI at 11:30 a.m. and TFE at 4:30 p.m. by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05); Table S9: Average yield percent of apple fruit of the “Gala Redlum” cultivar per caliber (between < 50 and > 80), between 2020 and 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control); Table S10: Average yield value of apple fruit of the “Gala Redlum” cultivar, per caliber and total per modality, between 2021 and 2024, as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control); Table S11: Fruit quality parameters of the “Gala Redlum” cultivar (mean ± standard error) taken in each year (2020–2024) as a function of the net cover modality with different shading levels: Black (≈22.4%), Red (≈20.6%), Grey (≈15.7%), Yellow (≈14.7%), White (≈9.6%) and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modality are significantly different (dry matter in 2020 by Games–Howell test; firmness in 2020, diameter in 2020, 2021 and 2024, weigh in 2020 and 2024, dry matter in 2021, and starch in 2022 and 2024, by Dunn’s test; remaining significant cases by Tukey’s test; p ≤ 0.05); Table S12: Principal component (PC) scores (mean ± standard error) as a function of year (2022 to 2024) and net cover modality with different shading levels: Black (FE ≈ 22.4%), Red (FE ≈ 20.6%), Grey (FE ≈ 15.7%), Yellow (FE ≈ 14.7%), White (FE ≈ 9.6%) and for apple trees without net cover (control). Means followed by different letters within each year and between net cover modality are significantly different by Tukey’s test (p ≤ 0.05).

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