The study was carried out at Quinta da Alufinha, municipality of Resende, Portugal (latitude 41°06′ N and longitude 7°54′ W), on a 7-year-old sweet cherry commercial orchard, located at a low altitude (140 m above sea level), in the years of 2019, 2020, and 2021. Trees were trained under a vertical axis system with a spacing of 3.0 m between rows and 2.5 m in the row. Between March and August, trees were drip-irrigated daily, ensuring a uniform water supply. In addition, trees were also periodically fertilized. Standard meteorological variables [air temperature (°CC), rainfall (mm), and solar radiation (W m⁻²)] for the 3 years were recorded by an automatic weather station set up near the experimental site ( Figure 1 ). In 2019, the average air temperature between March and May was approximately 1.42°C lower than that of 2020, and 1.09°C higher than that of 2021. Based on the annual precipitation data, the year 2019 recorded the highest annual rainfall (1,163 mm), followed by 2020 (1,091 mm), and 2021 (1,076 mm). Furthermore, the mean solar radiation until May was also higher in 2019 than in the other 2 years. Compared to climate normals available (1971–2000), all 3 years were drier (especially 2021, with 20% less rainfall), while, regarding temperature, all 3 years were all hotter than the 30-year average, namely, 2020 (average hotter by 1°C).

The early cultivar (cv.) Early Bigi and the late cv. Lapins, both grafted onto “Santa Lucia 64”, were selected for this trial, due to its economic importance of this region.

Eight trees from each cultivar, homogeneous, and in good phytosanitary conditions, were chosen for each treatment, resulting in a total of 48 trees per cultivar. Six treatments (expressed as % of volume/volume) were foliar sprayed, using a mechanical sprayer, and they included two concentrations of GB (97%) (GB 0.25% and GB 0.40%), two concentrations of E. maxima seaweed-based biostimulants (EM 0.30% and EM 0.15%), a combination of the lowest concentrations of both biostimulants (Mix —GB 0.25 and EM 0.15), and a control (C) group (water). Foliar treatments were repeated at three different dates during the phenological stages of the cherry tree, according to the BBCH scale [Biologische Bundesantalt, Bundessortenamt und Chemische Industrie (Fadon et al., 2015)]: stage 77 (70% of final fruit size), stage 81 (beginning of fruit coloring), and stage 86 (coloring advanced, 3 days before fruit harvesting). To achieve more accurate results, treatments ( Table 1 ) were applied for three consecutive years (2019, 2020, and 2021), in a windless morning ( Table 2 ).

Healthy, fully expanded, sun-exposed, and mature leaves in a similar position were carefully chosen for the assessment of gas exchange, electrolyte leakage (EL), and relative water content (RWC). These assessments were carried out at solar noon in both cultivars, 3 days after the application of the biostimulants, for the years 2019 and 2021. Additionally, about seven leaves per tree and treatment were collected for biochemical analyses and were immediately frozen in liquid nitrogen, ground to a fine powder, and then stored at −80°C for further analysis. In 2020, despite the foliar applications of the treatments being carried out, it was impossible to conduct these assessments due to the COVID-19 pandemic.

Leaf gas exchange measurements were accomplished using a portable infrared gas analyzer system (LC Pro+, ADC, Hoddesdon, UK). The IRGA was equipped with a 2. 5-cm² leaf chamber (ADC-PLC) and operated in open mode. Incident photosynthetic photon flux density (PPFD) on the leaves was always greater than 1,500 μmol m⁻² s⁻¹. The measurements were performed on cloudless days, under natural light conditions, and at solar noon. Through the formulas proposed by von Caemmerer and Farquhar (1981), the net photosynthetic rate (A, μmol m⁻² s⁻¹), transpiration rate (E, mmol m⁻² s⁻¹), stomatal conductance (g_s, mmol m⁻² s⁻¹), and intercellular CO₂ concentration (Ci, µmol mol⁻¹) were calculated. The intrinsic water use efficiency was calculated as the ratio of A/g_s (A/g_s, µmol mol⁻¹), to dismiss the potential effects of air humidity and temperature on transpiration (Iacono et al., 1998). Measurements were only performed in the year 2019 (for cv. Early Bigi on April 14, April 22, and May 3, and for cv. Lapins on April 14, May 19, and May 27), as the portable infrared gas analyzer system was unavailable in 2021. Results are expressed as the mean ± standard deviation (SD) of eight replicates.

For water status analysis, detached sweet cherry leaves were immediately placed into airtight containers with the petiole facing downwards. Fresh weight (FW, g) was measured, and after immersing leaf petioles in demineralized water for 48 h in the dark at 4°C, turgid weight (TW, g) was measured. Dry weight (DW, g) was determined after drying at 70°C until a constant weight was achieved. Leaf area (LA, cm²) was also measured using the WinDias image analysis system (Delta-T Devices Ltd., Cambridge, UK). Furthermore, the RWC was calculated as:

Leaf mass per unit area (LMA) (g m⁻²) was calculated by the ratio between leaf area and DW. Results are expressed as the mean ± standard error (SE) of eight replicates.

The statistical analysis was conducted using the SPSS V.27 software (SPSS-IBM, Corp., Armonk, New York, USA). After testing for analysis of variance (ANOVA) assumptions, namely, the homogeneity of variances with Levene’s mean test and normality with the Shapiro–Wilk’s test, statistical differences among treatments within each variety and year were evaluated by one-way ANOVA, followed by the post-hoc Tukey’s test. To assess the effects of treatment, year, phenological stage, and their interactions, a multivariate analysis of variance (MANOVA) was performed using Pillai’s trace statistic in SPSS V.27 software. Differences were considered statistically significant at a significance level of p ≤ 0.05.

Correlations between measured gas exchange parameters were assessed using Pearson correlation coefficients.

Data are presented as the mean ± SD of eight replicates, and the results are presented by dry weight, for photosynthetic pigments. For leaf water status, total soluble sugars, starch and protein, total phenolics, and cell membrane damage, data are presented as the mean ± SD of eight replicates.

The application of biostimulants affected the two tested cultivars differently regarding leaf gas exchange parameters ( Tables 3 , 4 ). For cv. Early Bigi, the general trend in leaf gas exchange parameters showed an increase as the season progressed ( Table 3 ). The effect of spraying biostimulants appears to have some influence, as C leaves always presented the lowest values, even though significant effects of treatments were not recorded on all sampling dates. Indeed, at the first sampling date, significant effects were not recorded for Ci and A/g_s, while for other parameters, higher values were observed in trees treated with GB 0.25%, even though these values were similar to other treatments (for A, similar to GB 0.25% and Mix treatments; for E and g_s, similar to EM 0.3% and Mix). In the second sampling moment, a different trend was found, with differences between treatments only recorded for Ci, and only when comparing EM 0.3% to C leaves. At fruit harvest, significant changes were only recorded for E and g_s. For the former parameter, lower values were recorded for the C treatment, while the transpiration rate increased in all other treatments, namely, in the lower dosages of EM and GB. The effects recorded on stomatal conductance follow a similar pattern, although significant differences were only observed between the C and GB 0.25% treatments.

Regarding cv. Lapins, and in contrast to cv. Early Bigi, there is no noticeable major trend in leaf gas exchange as the season progresses. For instance, A is lower at harvest than during the first sampling, whereas E is higher ( Table 4 ). Regarding the application of biostimulants, no significant effects were recorded on the first sampling date, as the data were similar among treatments for all analyzed parameters. On the second sampling date, significant differences were noted for all leaf gas exchange parameters, with lower values recorded for C in almost all of them, except for A/g_s. The influence of the applied treatments was also evident at harvest, as only Ci and A/g_s values were statistically similar across all samples ( Table 4 ). Indeed, values of A, E, and g_s were significantly different among treatments, with higher values recorded for EM 0.15% for A (significantly different from C and EM 0.30%), E (significantly different from C), and g_s (also significantly different from C).

Some correlations were found between the measured gas exchange parameters. Indeed, for cv. Early Bigi, the photosynthetic rate (A) presented correlations with Ci (r = −0.595, p ≤ 0.001), g_s (r = 0.220, p = 0.043), and E (r = 0.215, p = 0.048). Similarly, for cv. Lapins, correlations were also found, namely, for A and g_s (r = 0.697, p ≤ 0.001) and between A and E (r = 0.433, p ≤ 0.001). These relationships have been previously reported in sweet cherries (Gonçalves et al., 2005, 2007; Correia et al., 2020b; Houghton et al., 2023). Furthermore, the positive effects on leaf gas exchange parameters due to the application of biostimulants have been documented in various crops. For example, the application of E. maxima has sowed beneficial effects in melon, cucumber, and tomato (Lefi et al., 2023); Cucurbita pepo L (Rouphael et al., 2017); or Vigna unguiculata (Gyogluu Wardjomto et al., 2023). The use of GB as a biostimulant has improved leaf gas exchange parameters in olive (Denaxa et al., 2020), Lactuca sativa (Lin et al., 2020) or Solanum lycopersicum (Annunziata et al., 2019).

This improvement in leaf gas exchange parameters can be linked to several factors. Enhanced photosynthesis may lead to increased dry matter accumulation (Carvalho et al., 2019; Mateus-Cagua and Rodríguez-Yzquierdo, 2019), by enhancement of mineral nutrient availability and uptake (Caruso et al., 2019), plant hormone regulation, and an increase in metabolites that benefit the electron transport chain (Sorrentino et al., 2022). Furthermore, biostimulants can also potentially improve water-use efficiency in plants (Burghardt and Riederer, 2006; Jiménez-Arias et al., 2022), increasing turgor pressure in leaf guard cells and enhancing gaseous exchange attributes.

The leaf water status of both cultivars was affected by different factors (years, phenological stage, treatment, and their interaction), although in different ways ( Supplementary Table S1 ). Regarding cv. Early Bigi, significant influence of the RWC was recorded for all factors, apart from the year and the interaction of treatment, year, and phenological stage, while for cv. Lapins, influence was found for all factors and their interaction. For cv. Early Bigi, the RWC trend was similar in both 2019 and 2021, with an increase in values during fruit development ( Figure 2 ). However, in 2019, significant changes were more noticeable in the last sampling date (at fruit harvest), with differences in treatments C and Mix, both with lower values, while treatment GB 0.25% had higher values. In 2021, significant differences were observed in all sampling moments, with a clear difference recorded for the C treatment (always lower values), while higher values were observed when using the EM 0.15% treatment (even though it does not differ significantly from other treatments, except for the abovementioned C). For cv. Lapins, there is also a similar trend in both years, with an increase of RWC from the first to the second sampling date. However, the values recorded at harvest differed: in 2019, there was a reduction, while in 2021, the water content remained almost the same ( Figure 2 ). In 2019, and at the first sampling date, no differences were observed between treatments, but in the following analyses, C samples recorded the lowest RWC, with leaves from EM 0.15% sprayed trees recording the higher values (even though statistically similar to other treatments). In 2021, C leaves recorded the lowest values even at the first sampling date, with leaves from the EM 0.30% treatment presenting increased water content. Water stress can influence RWC values, which can result in growth limitations and changes in physiological and metabolic processes (Irigoyen et al., 1992), with the benefits of high RWC arising from greater resistance of cell walls and their ability to endure tissue destruction or mechanical damage caused by dehydration. However, in the present study, no water stress situation appears to be occurring, as RWC values are usually above 90%, suggesting sufficient drip irrigation, except for those recorded for the C treatment, in 2021. Even so, the application of both biostimulants on either cultivar results in increased RWC values, with a more pronounced effect for cv. Early Bigi, in 2021, a year that was hotter and dryer than 2019. The use of GB or algae-based biostimulants has demonstrated positive effects on sweet cherry, as reviewed by Afonso et al. (2022), including an increase in RWC (Correia et al., 2020b; Serapicos et al., 2022), corroborating our findings.

Data for leaf mass per unit area (LMA) show, again, different behavior for the two cultivars under study ( Figure 3 ). This variable was affected by all factors, with the exception of the interaction of the treatment, year, and phenological year for both cultivars, and the interaction of treatment and year was only recorded for cv. Lapins ( Supplementary Table S1 ). Values recorded for cv. Early Bigi shows an overall increase of LMA with fruit development, in both years of study. Interestingly, no differences in LMA were recorded at the first sampling date in either year. However, at subsequent stages, C leaves exhibited lower LMA compared to the other treatments, particularly EM 0.15% and GB 0.40%. Regarding cv. Lapins, a similar trend was observed, with an increase in LMA with fruit development. Nonetheless, C leaves consistently had lower values, except for the first sampling date of 2019 and at harvest, in 2021. In contrast, algae-based biostimulants, specifically the EM 0.15% treatment, resulted in increased LMA throughout all sampling dates. High values of LMA have been associated with a higher density of mesophyll or thickness of total lamina, reflecting an increased tolerance to adverse conditions (Centritto, 2002; de la Riva et al., 2016), with improved photosynthetic capacity often related to higher LMA (Reich et al., 2000).

Biotic or abiotic stresses can cause the accumulation of reactive oxygen species, causing damage to cell membranes through lipid peroxidation, thereby changing their permeability (Sachdev et al., 2021). These changes in permeability can be monitored by measuring the EL, an indicator of cell membrane integrity (Bajji et al., 2001), or by detecting the presence of TBARS.

In the current study, both indexes of membrane damage exhibit a very similar tendency ( Figure 7 ). In leaves of both cultivars, these indexes were affected by year (p ≤ 0.001), phenological stage (p ≤ 0.001), treatments (p ≤ 0.001), and the interaction of treatment and phenological stage (p ≤ 0.001). The EL was also influenced by the interaction between year and treatment (p ≤ 0.001) and the interaction between treatment, year, and phenological stage (p ≤ 0.01) only for cv. Early Bigi. The interaction between year and phenological stage affected the EL (p ≤ 0.001 for both cultivars) and TBARS (p ≤ 0.001 and p ≤ 0.01, for cv. Early Bigi and Lapins, respectively) ( Supplementary Table S1 ).

Results for cv. Early Bigi ( Figure 7 ) in both years show a similar trend, with an overall decrease in EL with the advance of fruit development, observed in both 2019 and 2021. The application of biostimulants appears to affect this specific parameter, as significantly higher values were recorded for C leaves in all sampling dates of both years (the only exception on the first sampling of 2019). This same pattern was recorded in leaves of cv. Lapins, with a decrease of EL with fruit development, and higher values were recorded for C treatment (with exceptions noted in the first sampling of both years).

The lower EL observed with the application of biostimulants might point out a positive effect with the use of these compounds in preserving cell membranes during dehydration (Savé et al., 1999), even in the absence of severe stress, as in the current work.

The evaluation of TBARS allows an overview regarding peroxidation of membrane lipids mediated by reactive oxygen species, which can lead to cellular damage (Sofo et al., 2004; Beis and Patakas, 2012), and typically, higher TBARS values indicate a higher exposure to stress. The results of the present work underscore the significant effect of the use of biostimulants in this specific parameter ( Figure 7 ). The overall trend of TBARS is a decrease of their content with fruit development, in all situations. However, the use of biostimulants presented two different effects: firstly, in all samples, the decrease in TBARS content was significantly higher than that recorded in the C samples; in addition, in the 2021 dataset, the initial TBARS content was already considerably lower in leaves from sprayed trees. This pronounced effect of biostimulants on TBARS data has previously been recorded in sweet cherry leaves (Correia et al., 2020b).

This study evaluated the impact of biostimulants on leaf water status, photosynthetic pigments, soluble sugars, starch, soluble proteins, and leaf gas exchange parameters in two cultivars of sweet cherries.

Results revealed significant differences between cultivars and years, with notable effects observed in 2021, a hotter and dryer year compared to 2019. Despite variations, the application of biostimulants generally led to an improved leaf water status, enhanced photosynthetic pigment content, and increased photosynthetic activity (Jolayemi et al., 2023). Furthermore, the application of biostimulants also contributed to the preservation of cell membrane integrity.

These improvements were most evident after the application of both concentrations of the seaweed-based biostimulant E. maxima and treatment GB 0.40%, which positively influenced the performance of cherry trees.

These findings indicate the potential of biostimulants to mitigate the impact of environmental stressors and enhance physiological processes in sweet cherry cultivation, contributing to improved crop performance. Further research is warranted to elucidate the underlying mechanisms and optimize biostimulant applications for sustainable cherry production.