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Article

Exploring the Role of Biostimulants in Sweet Cherry (Prunus avium L.) Fruit Quality Traits

by
Sílvia Afonso
1,*,
Ivo Oliveira
1,
Carlos Ribeiro
2,
Alice Vilela
3,
Anne S. Meyer
4 and
Berta Gonçalves
1
1
Centre for the Research and Technology for Agro-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-food Production, Inov4Agro, Department of Biology, University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal
2
Centre for the Research and Technology for Agro-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-food Production, Inov4Agro, Department of Agronomy, University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal
3
Chemistry Research Centre, CQ-VR, Department of Agronomy, University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal
4
Department of Biotechnology and Biomedicine, Technical University of Denmark, DTU Building 221, 2800 Kongens Lyngby, Denmark
*
Author to whom correspondence should be addressed.
Agriculture 2024, 14(9), 1521; https://doi.org/10.3390/agriculture14091521
Submission received: 17 August 2024 / Revised: 29 August 2024 / Accepted: 2 September 2024 / Published: 4 September 2024
(This article belongs to the Special Issue Innovative Solutions for Sustainable Agriculture: From Waste to Biostimulants, Biofertilisers and Bioenergy)
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Versions Notes

Abstract

:
Sweet cherries are among consumers’ preferred fresh fruits, known for their attractive organoleptic properties and high nutritional value. Agronomical practices, which are now shifting to more environmentally sustainable options, can influence several key quality traits of sweet cherries. In this context, reducing conventional agrochemicals and increasing the application of preharvest biostimulants has emerged as an innovative strategy. This approach can not only enhance cherry production and quality but also ensure the economic and environmental sustainability of the cherry supply chain. Hence, this work is aimed at studying the effect of the application of two concentrations of glycine betaine (GB) and Ecklonia maxima-based (EM) biostimulants, and their combination, in two cultivars of sweet cherry: the early-maturing ‘Early Bigi’ and the late-maturing ‘Lapins’, both grafted onto SL-64 rootstock. Evaluated parameters included fruit weight and dimensions, color, firmness, total soluble solids (TSS), titratable acidity (TA), phenolic and anthocyanin contents, and sensory profile. Key findings highlight that, with a few exceptions, biostimulant treatments had a positive impact on the studied parameters, although the responses varied between cultivars. For instance, fruit size increased by 13.41% in ‘Early Bigi’ and 47.20% in ‘Lapins’. Additionally, reduced color values, coupled with higher TSS/TA ratios, indicate advanced fruit maturation, which could allow for an earlier harvest. The total phenolic content rose by 56.88% in ‘Early Bigi’ and 30.24% in ‘Lapins’, while anthocyanin levels surged by 88.28% and 36.10%, respectively. Fruit firmness also improved following biostimulant application. Sensory analysis further revealed enhancements in key descriptors such as “overall aspect”, “firmness”, and “cherry flavor”, underscoring the beneficial effects of these treatments. These combined results indicate that the preharvest application of glycine betaine or Ecklonia maxima-based (EM) biostimulants significantly improves key quality traits of sweet cherries. This approach offers benefits not only from a commercial perspective but also for the sweet cherry supply chain sustainability by reducing the application of chemical-based products and replacing them with ecofriendly substances while enhancing the quality of the fruit.

1. Introduction

Sweet cherries are among the preferred fresh fruits for consumers owing to their appealing organoleptic properties, high nutritional value, and recognized health benefits, which are attributed to their rich antioxidant content [1,2,3,4]. These quality features, associated with fruit size, uniform skin color, firmness, sweetness, absence of defects, and a green stem, give this fruit substantial economic viability [5].
According to FAOSTAT (2024), the world cherry production reached 2,765,827 tons in 2022, with a substantial increase of 137% in Portugal over the last decade [6]. This growth highlights sweet cherry cultivation’s significance in the country’s agricultural landscape. In particular, the Entre Douro e Minho region plays a crucial role in cherry cultivation, particularly in the municipality of Resende, due to its unique edaphoclimatic conditions, resulting in the early market availability of sweet cherries with superior quality and excellent flavor [7]. However, this crop faces some challenges and constraints related to its sensitivity to climate conditions [8]. Climatic fluctuations throughout its vegetative cycle can affect fruit formation, flowering, and fertilization, resulting in production losses. Additionally, physiological disorders can compromise its quality and, consequently, its market value [9,10]. As such, several agronomic strategies have been employed to enhance cherry production and quality, with recent emphasis placed on the use of novel biostimulants [3,11,12]. These are considered environmentally friendly and promising alternatives, and their application has proven to be highly effective in mitigating both abiotic and biotic stresses, thereby improving tree productivity and performance while enhancing the overall quality [3,13]. Among the entire categories of biostimulants, glycine betaine (GB) and seaweed extracts have garnered attention from the scientific and agronomic community [3,14] and according to Colla et al. [15,16], they represent the two most important categories of biostimulants.
Despite the limited studies on the effects of the foliar application of the osmoregulatory GB, it emerges as a promising alternative to enhance cherry tree performance [17,18]. Moreover, it shows potential to improve fruit quality, particularly in increasing fruit size, total soluble solids, pH, and reducing acidity [3,19,20]. Recently, foliar applications of seaweed extracts have demonstrated potential effects on fruit, including increases in organic acid concentration and resistance to fruit cracking [20,21,22]. However, little literature is available regarding the foliar application of these two biostimulants in sweet cherry fruit quality. Therefore, this study aimed to assess the preharvest application effects of GB and seaweed-based Ecklonia maxima extract on the cherries’ quality, and the sensory attributes of the early-maturing ‘Early Bigi’ and the late-maturing ‘Lapins’.

2. Materials and Methods

2.1. Site Description and Weather Conditions

Experiments were performed in a commercial sweet cherry orchard located at Quinta da Alufinha, Municipality of Resende (latitude 41°06′ N and longitude 7°54′ W) in three consecutive years: 2019, 2020, and 2021. The orchard was seven years old and located at a low elevation (140 m above sea level). The spacing was 2.5 m between trees in a row and 3.0 m between rows. Irrigation was applied through a drip irrigation system between each tree in the row. All trees were treated with standard fertilizer, herbicides, and pesticides, ensuring similar agronomic practices throughout the trial years.
An automatic weather station was installed near the orchard, and the meteorological data from the 2019, 2020, and 2021 growing seasons were recorded.

2.2. Plant Material, Treatments, and Sampling

This research specifically concentrated on the two most representative cultivars of the region: the early-maturing ‘Early Bigi’ and the late-maturing ‘Lapins’, both grafted onto SL-64 rootstock.
Eight trees from each cultivar were selected for each treatment. Six different formulations were applied: two concentrations of glycine betaine (GB 0.25% and 0.40%), two concentrations of Ecklonia maxima seaweed-based biostimulants (EM 0.15% and 0.30%), a combination of the lowest concentrations of both biostimulants (Mix-GB 0.25% and EM 0.15%), and the control (C), which was performed using tap water.
The treatments were applied using a backpack sprayer and repeated at three different stages of the sweet cherry tree growth cycle, according to the BBCH scale (Biologische Bundesanstalt, Bundessortenamt, and Chemical industry scale) [23]: stage 77 (representing 70% of final fruit size), stage 81 (the beginning of fruit coloring), and stage 86 (indicating advanced coloring, three days before fruit harvesting). Table 1 shows the dates of the treatment applications over the three years. However, due to the COVID-19 pandemic, in 2020 it was not possible to harvest the fruit and thus, results from the present study are focused only on data collected for 2019 and 2021.
In 2019, cv. ‘Early Bigi’ was harvested on 3 May and cv. ‘Lapins’ on 27 May, whereas in 2021, cv. ‘Early Bigi’ was harvested on 27 April and cv. ‘Lapins’ on 3 June.
For quality measurements, 100 fruits from each tree, treatment, and cultivar were randomly collected at commercial maturity, transported in a portable freezer under refrigeration to the laboratory, and then carefully divided into three groups. The first group was designated for biometric measurements, epidermis rupture force (ERF), flesh firmness (FF), skin color, total soluble solids (TSS), and titratable acidity (TA). The second group was used to determine total phenolics and anthocyanins. The third group was allocated for sensory analysis. Fruits from the second group were frozen in liquid nitrogen, lyophilized (SCANVAC 55-4 Pro, LaboGene, Lynge, Denmark) for 120 h at −55 °C, and then ground into a dried powder using a commercial blender (Model BL41, Waring Commercial, Torrington, WY, USA).

2.3. Physical Characteristics of Sweet Cherries

Weight, Dimensions, Texture, and Skin Color

Fruit weight (g), length (mm), width (mm), and diameter (mm) were measured in 30 fruits per treatment.
The epidermis rupture force (ERF, N) and flesh firmness (FF, N mm−1) were determined using a TA.XTPlus texture analyzer (Stable Micro Systems, Godalming, Surrey, UK), employing a 5 kg loading cell and a 2 cm diameter cylindrical probe, with a total displacement of 5 mm at a speed of 1 mm s−1.
The fruit color was measured on opposite sides of the fruit using a colorimeter (Model CR-300, Minolta, Osaka, Japan) and expressed in CIE Lab* values. Before measurement, the fruit surfaces were gently cleaned with a dry cloth to remove any residues that could affect the accuracy of the readings. In this color space, L* represents lightness (0 = black, 100 = white), a* represents the green-red spectrum (negative values indicate greenness, positive values indicate redness), and b* represents the blue-yellow spectrum (negative values indicate blueness, positive values indicate yellowness). Subsequently, the hue angle (Hue°), which indicates color intensity (purity), was determined using the formula Hue° = arctan(b*/a*). Additionally, the chroma (C*), representing color saturation, was calculated using the formula (a*² + b*²)1/2 (calculations performed using Microsoft Excel 365, version 2407).

2.4. Chemical Properties of Sweet Cherries

2.4.1. Total Soluble Solids, pH, and Titratable Acidity

Thirty fruits from the first group were divided into three sub-groups of ten fruits each. The juice was extracted from each group using an electrical extractor (ZN350C70, Tefal Elea, China) for 1 min.
The juice’s total soluble solids content (TSS, °Brix) was measured using a digital refractometer (PR-101, Atago, Japan) at ±20 °C. Titratable acidity (TA, % malic acid) was determined by automatic titration (Schott Easy Titroline automatic titrator, Germany) with 0.1 N NaOH to pH 8.2 after diluting 10 mL of juice with 10 mL of distilled water.
The maturity index, calculated as the ratio of TSS and TA, was expressed as the average of three replicates with standard deviation (SD).

2.4.2. Bioactive Compounds

For total phenolic content, the methods of Singleton and Rossi [24] and Dewanto et al. [25] were applied with minor modifications. Forty milligrams of the freeze-dried sample were dissolved in 1 mL of 70% (v/v) aqueous methanol, heated to 70 °C, and vortexed every 5 min for 30 min. The extracts were centrifuged at 13,000 rpm (Centrifuge 5804R, Eppendorf, Hamburg, Germany) at 1 °C for 15 min. The supernatants were filtered through a 0.2 µm, 13 mm diameter PTFE filter (Teknokroma, Spain). Subsequently, 20 µL of each extract was added to 100 µL of Folin–Ciocalteu phenol reagent (1:10 in bidistilled H2O) and 80 µL of 7.5% Na2CO3 in a 96-well microplate (Multiskan™ FC Microplate Photometer, Waltham, MA, USA). The microplate was incubated for 15 min at 45 °C in the dark. Absorbance values against a blank were recorded immediately at 765 nm using a microplate reader (Multiskan GO Microplate Spectrophotometer, Thermo Scientific, Vantaa, Finland). A standard curve using gallic acid at various concentrations was created, and the total phenolic content was expressed as mg gallic acid equivalent (GAE) per gram of dry weight (DW), with results presented as the mean ± standard error (SE) of three replicates.
Total anthocyanins were quantified according to Nicoué et al. [26]. Methanolic extracts were prepared by dissolving 0.5 g of the freeze-dried sample in 5 mL of acidified methanol (1% HCl, v/v) and keeping the solution at 4 °C for 1 h. The extracts were then centrifuged at 4000 rpm at 4 °C for 15 min (Centric 250, UniEquip, Munich, Germany) and filtered using Whatman™ No. 1 90 mm filter paper. The supernatants were diluted with 0.025 M of KCl buffer (pH 1) and 0.4 M of sodium acetate (CH3COONa) buffer (pH 4.5) at a ratio of 1:6 and allowed to stand for 10 min. Absorbance readings at 541 nm and 700 nm were then taken spectrophotometrically for both pH 1 and pH 4.5 buffers (U-2000, serial 121-0120, Hitachi Ltd., Tokyo, Japan). Net anthocyanin absorbance was calculated as (A541–A700) pH 1.0—(A541–A700) pH 4.5, and anthocyanin content was determined using the molar absorptivity (Ɛ = 26,900) and molecular weight (MW = 449.2) of cyanidin-3-O-rutinoside. Results are expressed as cyanidin-3-O-rutinoside equivalents (mg cy-3-rut g−1 DW), reported as the mean ± standard error (SE) of three replicates.

2.5. Sensory Evaluation of Sweet Cherries

Fifteen cherry attributes (Chauvin et al. [27]) (Table S2) were evaluated by a trained panel of twelve experts. Sensory evaluation sessions were conducted annually in a laboratory for sensory analysis maintained at approximately 20 °C (ISO 6658 [28]), specifically once a year in 2019 and 2021. The attributes were rated on a five-point scale, with 1 indicating that the attribute was not present and 5 that it was present at the highest intensity (ISO 4121 [29]).
For each session, three randomly coded cherries per treatment were presented to each panelist on white Pyrex plates. To ensure consistent conditions, cherries were equilibrated at room temperature for 2 h before the sessions. Panelists cleansed their palates with a sip of water or a bite of a low-salt cracker between samples. To maintain the integrity of the sensory evaluation, panelists refrained from wearing perfume and avoided consuming food, drink, or smoking for one hour before the tasting.

2.6. Statistical Analysis

The statistical analysis was performed using SPSS version 27 (SPSS-IBM Corp., Armonk, NY, USA). Before conducting the study, the assumptions for an analysis of variance (ANOVA) were verified, including the homogeneity of variances using Levene’s mean test and normality using the Shapiro–Wilk test. Statistical differences among treatments within each variety and year were assessed using a one-way ANOVA, followed by Tukey’s post hoc test for multiple comparisons. To evaluate the main effects of treatment, year, and their interactions, a multivariate analysis of variance (MANOVA) was performed, utilizing Pillai’s trace as the test statistic. Differences were considered statistically significant at p < 0.05. Sensory data were analyzed using a one-way ANOVA and Duncan’s multiple range test for post hoc comparisons (p < 0.05).

3. Results

3.1. Weather Conditions

Weather conditions are summarized in Figure 1. Based on data from 2019 to 2021, there was a clear trend of hot and dry summers followed by wetter winters. The year 2020 was the warmest, with maximum temperatures reaching 32.1 °C in July and 23.3 °C in May, surpassing the values recorded in 2019 and 2021. In opposition, 2019 stood out as the rainiest year, with significant precipitation levels that exceeded those observed in 2020 (1091 mm) and 2021 (1076 mm), making 2019 the year with the highest rainfall (1163 mm).

3.2. Biometric and Physical Characteristics of Sweet Cherries

For both cultivars, treatment and year significantly influenced the biometric parameters of sweet cherries, as well as the interaction between these two factors (Table S1). The application of GB and EM biostimulants significantly influenced fruit weight and dimensions for both cultivars (Table 2), with a low concentration of biostimulants and their combination being particularly effective for the cv. ‘Early Bigi’. For cv. ‘Lapins’, the best overall results were observed with the higher concentrations of both biostimulants.
This positive effect on fruit weight and dimension from biostimulants is well-documented in several species, including sweet cherry [3]. For instance, increases in weight and dimension have been documented in cvs. ‘Skeena’, ‘Sweetheart’, ‘Simone’, ‘Ziraat’, ‘Kordia’, and ‘Regina’, following the application of various biostimulants [17,20,21,30,31,32]. Glycine betaine has been shown to increase these parameters in fruits of cv. ‘Skeena’ [21], while Ecklonia maxima-based biostimulants produced a similar effect in the fruits of cv. ‘Bing’ [22].
Cherry fruit growth follows a double-sigmoid growth curve consisting of three distinct stages: stage I, with mesocarp growth consisting of both cell division and cell enlargement; stage II, a lag period coinciding with endocarp hardening and embryo development; and stage III, a second period of exponential fruit growth with rapid cell expansion, classically referred to as cell division, endocarp lignification, and cell expansion, respectively [33]. The first application of biostimulants, in the present work, was performed when cherries were in the BBHC stage 77, with fruits about 70% of final size [23], and within the first phase of growth (stage I), which includes cellular division. Considering this timing of application, our results suggest that these biostimulants might have induced cytokinin-like effects, an activity previously described for other biostimulants [34,35].
The brown seaweed Ecklonia maxima extracts are rich in organic and mineral compounds. They contain unique and complex polysaccharides found exclusively in seaweeds, as well as a variety of plant hormones, including cytokinins, auxins, abscisic acid, gibberellins, and hormone-like compounds such as sterols and polyamines [3]. To date, there are limited studies on the effects of Ecklonia maxima extract on cherry fruits. However, Ureta Ovalle [22] conducted a study over three consecutive years on ‘Bing’ cherry trees and observed notable improvements in fruit-related biometric parameters following the application of this seaweed extract. The increase in cherry fruit size can be attributed to both the regulation of growth hormones [36] and endogenous hormonal homeostasis, which is influenced by the presence of polysaccharides [3,37]. These polysaccharides can activate biochemical pathways responsible for synthesizing secondary metabolites, thus contributing to the increase in fruit size and the overall improvement in plant quality. However, the exact mechanisms involved are not fully understood [37].
More complex interaction with fruit growth can be linked to the effect of glycine betaine on the expression of auxin-responsive IAA gene levels [38], which is linked to fruit dimensions and weight in sweet cherries [39,40,41].
Regarding color characteristics, results indicate that, for cv. ‘Early Bigi’, both treatment and year significantly influence L* (p < 0.01 and p < 0.05, respectively). At the same time, C* and Hue° were mainly affected by the year (p < 0.05), with no significant interaction between treatment and year. For cv. ‘Lapins’, treatment had a strong impact on L* and C* (p < 0.001), and the significant interaction between treatment and year suggests that treatment effects on color parameters vary by year, particularly for L* and C* (Table S1). Overall results show that the application of biostimulants decreased the L*, C*, and Hue° values compared to control samples (Table 3). Usually, lower values of these parameters indicate darker, redder, and mature fruit with lower water content and increased concentration of anthocyanins [42,43,44,45]. Furthermore, other studies point out the link between chroma reduction and increases in polyphenols, higher TSS, and reduced acidity of the fruits [46]. Considering that C* values usually decrease as ripening progresses, the present results may indicate earlier ripening due to the application of biostimulants [20]. Similar effects on color parameters have been recorded elsewhere when using biostimulants in sweet cherries. For instance, Ecklonia maxima seaweed-based biostimulants change the color of sweet cherries cv. ‘Bing’ [22], while glycine betaine and Ascophyllum nodosum-based extract reduced the values of L*, C*, and Hue° values in cv. ‘Stacatto’ [20].
A possible explanation for variations in fruit color might be linked to gene expression changes caused by hormones or hormone-like compounds present in the biostimulants that can upregulate, for instance, anthocyanin regulatory and biosynthetic genes [40]. Otherwise, exogenous applications of ABA are known to improve fruit color [47] but also indirectly affect color through the influence of auxin and cytokinin biosynthesis [48]. Even so, differences in color development occur naturally between cultivars with different ripening times [49] but also when using exogenous compounds, depending on the timing of application [50].
Observing cv. ‘Early Bigi’, the year had a significant effect on both epidermis rupture force (ERF) and flesh firmness (FF) (p < 0.01). However, the treatment and the interaction between treatment and year were not significant for ERF (p > 0.05). On the other hand, a significant interaction effect was observed for FF (p < 0.05), suggesting that the impact of treatments on firmness might vary across different years. For cv. ‘Lapins’, the year influenced both ERF and FF (p < 0.001), but neither the treatment nor the interaction between the treatment and year was significant for either parameter (p > 0.05). (Table S1).
Epidermis rupture force (RF) and flesh firmness (FF) were, in both cultivars, significantly affected by the treatments (Figure 2). Regarding RF, all treatments resulted in a higher force needed to cause a rupture of the epidermis of the fruits, with particular relevance to GB sprays, in cv. ‘Early Bigi’ and EM applications for cv. ‘Lapins’. Positive effects of using biostimulants were also observed for FF, where almost all treatments resulted in firmer fruit compared to the control. Positive effects of foliar-applied compounds have been reported in sweet cherry [51], including the use of glycine betaine [19] and seaweed-based biostimulants [52]. Even so, other works did not find any influence of treatments on this specific parameter of sweet cherries [20]. The positive effects of such treatments in firmness appear to be linked to calcium metabolism. Indeed, it is known that calcium pectin cross-links have a crucial part in the physical and structural properties of fruit [53,54], including firmness, and several studies point out an increase in calcium concentration in cherry fruits after the application of exogenous compounds, like glycine betaine or plant extracts [1,52]. These increases in fruit firmness are of significant importance, as this parameter is strongly correlated to consumers’ acceptance of cherries and with improved suitability for handling during postharvest operations [55,56], and to a reduced susceptibility to fruit cracking by a higher concentration of calcium within the fruit [57].

3.3. Chemical Properties of Sweet Cherries

For both ‘Early Bigi’ and ‘Lapins’ cultivars, the treatments, year, and their interaction significantly affected the total soluble solids (TSS), titratable acidity (TA), and the maturity index (MI) (p < 0.001) (Table S1), highlighting the impact of biostimulants on the chemical characteristics of the fruits (Table 4), despite these values remaining within the expected range for sweet cherries [58,59,60,61].
For cv. ‘Early Bigi’, values of TSS between 10% and 18% have been reported [62,63,64,65,66], while for cv. ‘Lapins’, values between 13 and 20% [62,65,67,68,69] are common. In the present work, the use of biostimulants increased TSS when compared to control samples in either cultivar, with overall results pointing out the use of the Mix treatment. Several previous works have shown the effect of biostimulants in TSS, namely its increased content. TSS increase has been found with the use of gibberellins [33], auxins [39,40], a tropical plant extract biostimulant [1], salicylic acid, Ascophyllum nodosum seaweed extract [20], but, more importantly, the biostimulants studied in the present work, Ecklonia maxima seaweed product [22] and glycine betaine [20]. This effect on sugars is probably linked to changes caused in the metabolism through the alteration of the expression of some genes [70,71,72,73], by increasing their translocation to the fruit [74], or by increments in net photosynthesis and stomatal conductance [75]. Different effects of the use of biostimulants, depending on the cultivars, have already been described, linked to the different sensitivities of the cultivars to the application of biostimulants or a differential response on fruit set, determining source–sink relations that were less favorable for carbon partitioning to fruits [1].
Titratable acidity (TA) varied from 0.36 to 0.62 in cv. ‘Early Bigi’, and between 0.45 and 0.76, in cv. ‘Lapins’ (Table 4) values well within the usual ranges for these cultivars [66,68,69]. The effect of the use of biostimulants was more evident in cv. ‘Lapins’, than in cv. ‘Early Bigi’, where no significant effect of spraying was observed in 2021. Overall results show that biostimulant application reduces the TA of sweet cherries, even though higher values were found for some treatments, such as the lower concentrations or the mixed treatment. Variations in the TA of sweet cherries have been reported, either increasing or decreasing when using different compounds [39,76,77,78,79]. Previous results using glycine betaine and an algae-based biostimulant also showed a decrease in TA (even though not significant) in sweet cherries of cv. ‘Stacatto’ [20]. The authors suggested that this reduction might have been caused by the influence of exogenous compounds on normal metabolism and gene expression related to acid [77,80].
The maturity index (TSS/TA) varied from 17.97 to 27.07 in cv. ‘Early Bigi’, and for cv. ‘Lapins’, from 24.03 to 36.25, usual values for sweet cherry [59], with an increase in this parameter recorded in all treatments for both cultivars and years. Previous work regarding the use of exogenous compounds, including glycine betaine and algae-based products, in sweet cherries has shown an increase in the maturation index [19,20,21,40,78], which has also been observed in the present. Some of these compounds can modulate gene expression related to the anthocyanin synthesis pathway and promote ethylene synthesis and fruit ripening [81]. This increased maturation index can be significant if aiming at anticipation of harvest to allow an earlier availability of sweet cherries to consumers.

3.4. Bioactive Compounds

As with the previous parameters, the total phenolic content was significantly affected by the exogenous application of biostimulants for both cultivars, ‘Early Bigi’ and ‘Lapins’ (Table S1 and Table 5), even though the overall values are similar to those in previous works [4,52,61,82,83]. Significant increases in total phenolic content were found in fruits of cv. ‘Early Bigi’ treated with EM 0.30% and GB 0.40% in 2019, and in 2021, this increase was noticeable for treatments with GB 0.25% and EM 0.15%. The latter treatment also increased the total phenolic content in cv. ‘Lapins’ in 2019, along with GB 0.40% treatment, while in 2021, GB 0.40% and seaweed-based biostimulant sprays presented a higher content of these compounds. In contrast, the control fruits consistently had the lowest phenolic content for both sweet cherry cultivars. Furthermore, the application of biostimulants, either algae-based products, glycine betaine, or others [20,52], has proven to increase the presence of phenolic compounds in sweet cherries. This increase might be due to the reported rise in carbon metabolism and to the stimulation of the biosynthesis of secondary metabolites [84] or the activated expression of two pathways, the flavone biosynthesis pathway, and ascorbate-glutathione [85,86], hence enhancing antioxidant content via synthesis and decreasing the depletion of these compounds.
The anthocyanin content was also significantly affected by the exogenous application of biostimulants (Table S1 and Table 5). Overall, anthocyanin content increased with the application of EM by 0.30% for both cultivars and years. In contrast, fruits from the control treatment presented the lowest contents. Seaweed Ecklonia maxima extracts contain several phytohormones, including high levels of auxins [36]. Auxin application has already been reported to increase anthocyanin amounts in sweet cherries by modifying gene expression [40]. The positive effects of GB in anthocyanin content have already been reported elsewhere [20]. These effects can be linked to changes in enzyme activity, specifically phenylalanine ammonia-lyase (PAL) [87] and gene expression [88].

3.5. Sensory Evaluation

The different treatments affected both cultivars’ sensory profiles in distinct manners (Figure 3). The cv. ‘Early Bigi’ was less prone to changes due to the use of biostimulants. Indeed, in this cultivar, only the attributes “color intensity”, “sweet taste”, and “cherry flavor” in 2019 and “color intensity” and “overall aspect” in 2021 showed significant differences across different treatments. For “color intensity”, the control fruit exhibited significantly lower intensity, which correlates with the reduction in measured color parameters (Table 3) and decrease in anthocyanins (Table 5), compounds responsible for the color in sweet cherries [45], and for the delay in the maturation process [81] caused by the use of biostimulants. Additional attributes of cv. ‘Early Bigi’ fruits were enhanced by the exogenous application of biostimulants, namely “sweet taste” and “cherry flavor” (with all treatments increasing the values compared to control), and “overall aspect” (only in 2021), with C and GB 0.40% displaying similar and lower values compared to the remaining treatments. The evaluation of “sweet taste” in sensory tests, as well as the “acidic taste”, aligns with the trend observed in the chemical analysis (Table 4), as their chemical composition largely affects the sensory quality of fruits [89].
The effect of biostimulants on the sensory traits of sweet cherries was more pronounced for cv. ‘Lapins’ than for cv. ‘Early Bigi’. In 2019, six attributes were significantly different when comparing treatments, with fruits from C treatment obtaining lower scores for “overall aspect”, “epidermis softness”, “color intensity”, “color uniformity”, and “firmness”, and higher scores for “strange taste”. In contrast, data from the 2021 analysis showed significant differences only for three attributes, specifically “overall aspect”, “cherry flavor”, and “firmness”, with sweet cherries from the control treatment presenting the lowest scores. Similar variations in these quality parameters have been documented when using hydrogen cyanamide or gibberellic acid, with sweeter fruit, increased cherry flavor observed in ‘Bing’ cherries [90], or enhancement of several traits in fruits of cvs. ‘Skeena’ and ‘Sweetheart’, with foliar application of GB or gibberellic acid [21]. Significant correlations were observed between physical and chemical parameters and sensory traits. For cv. ‘Early Bigi’, color parameters (L*, C*, and Hue°) showed positive correlations with the “Overall aspect” rating, with correlation coefficients of 0.233 for L*, 0.256 for C*, and 0.233 for Hue°. In cv. ‘Lapins’, fruit weight and anthocyanin content were positively correlated with “Overall aspect”, with coefficients of 0.227 and 0.543, respectively. Additionally, “Acidic taste” was positively correlated with total acidity (TA) values (0.476) and negatively correlated with the maturity index (MI) (TSS/TA) (−0.344). “Firmness” showed a positive correlation with RF (0.240), and “Color intensity” was associated with L* values (0.219).
The improvement of fruit sensory quality through the application of specific plant biostimulants can be achieved and has also been observed for several other fruits, with implications in firmness, coloration, carotenoid, and soluble solids content [91]. Hence, biostimulants have the potential to improve the sensory characteristics of sweet cherries, aiming at higher consumer acceptability [92,93].

4. Conclusions

The present results highlight the positive effects of the preharvest application of exogenous compounds, such as glycine betaine and Ecklonia maxima-based biostimulants, on enhancing quality-related physical, chemical, and sensory traits of sweet cherry fruits in cultivars ‘Early Bigi’ and ‘Lapins’. Ecklonia maxima seaweed-based biostimulant, at a concentration of 0.30%, proved to be the treatment that, overall, yielded the most favorable results in the assessed parameters. Seaweed-based biostimulants may offer a more sustainable and environmentally friendly approach to sweet cherry production, with additional benefits expected in sweet cherry trees’ physiology and abiotic stress tolerance.
Given the increasing interest in the preharvest application of biostimulants, this research fills a notable gap in the scientific literature regarding their impact on cherry culture. By elucidating the effects of these biostimulants on fruit quality, this study contributes valuable insights and enhances the current understanding of sustainable practices in cherry production.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriculture14091521/s1. Table S1: Statistical analysis of the effects of Treatment (T), Year (Y), and their interaction on sweet cherry quality parameters. Table S2: Adapted vocabulary from Chauvin et al. [27] and reference standards for the descriptive sensory analysis of cherries.

Author Contributions

Conceptualization, S.A., A.S.M. and B.G.; methodology, S.A., I.O., C.R. and A.V.; software, S.A.; formal analysis, S.A.; investigation, S.A.; data curation, S.A.; writing—original draft preparation, S.A.; writing—review and editing, S.A., I.O., C.R., A.V., A.S.M. and B.G.; supervision, A.S.M. and B.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by “Fundo Europeu Agrícola de Desenvolvimento Rural (FEADER)” and by “Estado Português” in the context of “Ação 1.1 «Grupos Operacionais»”, integrated in “Medida 1. «Inovação» do PDR 2020—Programa de Desenvolvimento Rural do Continente—Grupo Operacional para a valorização da produção da Cereja de Resende e posicionamento da subfileira nos mercados (iniciativa no. 362)”. (https://doi.org/10.54499/UIDB/04033/2020 (accessed on 11 July 2014)) and LA/P/0126/2020, Inov4Agro (https://doi.org/10.54499/LA/P/0126/2020 (accessed on 11 July 2014)).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

Sílvia Afonso is grateful to FCT, MCTES, and FSE for the PhD Fellowship SFRH/BD/139922/2018.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agriculture 14 01521 g001
Figure 1. Monthly maximum (Tmax) and minimum (Tmin) air temperature (°C) and precipitation (mm) in 2019, 2020, and 2021.
Figure 1. Monthly maximum (Tmax) and minimum (Tmin) air temperature (°C) and precipitation (mm) in 2019, 2020, and 2021.
Agriculture 14 01521 g001
Agriculture 14 01521 g002
Figure 2. Epidermis rupture force (N) and flesh firmness (N mm−1) of ‘Early Bigi’ and ‘Lapins’ cherries after applying different preharvest treatments. Values presented are expressed as mean ± standard error (SE). Different letters indicate significant differences between treatments within the sampling year. The absence of letters indicates that no significant differences were observed. C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%.
Figure 2. Epidermis rupture force (N) and flesh firmness (N mm−1) of ‘Early Bigi’ and ‘Lapins’ cherries after applying different preharvest treatments. Values presented are expressed as mean ± standard error (SE). Different letters indicate significant differences between treatments within the sampling year. The absence of letters indicates that no significant differences were observed. C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%.
Agriculture 14 01521 g002
Agriculture 14 01521 g003
Figure 3. Spider plot of the sensory profile of the ‘Early Bigi’ and ‘Lapins’ cherries after spray treatment application in 2019 and 2021. * p < 0.05 represents significant differences between treatments by Duncan’s test. The absence of superscripts indicates no significant differences. C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%.
Figure 3. Spider plot of the sensory profile of the ‘Early Bigi’ and ‘Lapins’ cherries after spray treatment application in 2019 and 2021. * p < 0.05 represents significant differences between treatments by Duncan’s test. The absence of superscripts indicates no significant differences. C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%.
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Table 1. Biostimulant treatments applied to sweet cherry cultivars ‘Early Bigi’ and ‘Lapins’.
Table 1. Biostimulant treatments applied to sweet cherry cultivars ‘Early Bigi’ and ‘Lapins’.
CultivarsBiostimulantsConcentrationsSweet Cherries Developmental StagesDate of Spraying
‘Early Bigi’Glycine betaine (GB) Ecklonia maxima extract (EM)GB 0.25% and GB 0.40%
EM 0.15% and EM 0.30%		 201920202021
BBCH 7711 April1 April6 April
BBCH 8119 April11 April15 April
BBCH 8630 April16 April24 April
‘Lapins’Glycine betaine (GB) Ecklonia maxima extract (EM)GB 0.25% and GB 0.40%
EM 0.15% and EM 0.30%		BBCH 7711 April1 April6 April
BBCH 8116 May4 May11 May
BBCH 8624 May12 May31 May
Table 2. Physical parameters of ‘Early Bigi’ and ‘Lapins’ cherries after different preharvest treatments, with results for 2019 and 2021.
Table 2. Physical parameters of ‘Early Bigi’ and ‘Lapins’ cherries after different preharvest treatments, with results for 2019 and 2021.
CultivarParameterYearCEM 0.15%EM 0.30%GB 0.25%GB 0.40%MixTreatment Effect
‘Early Bigi’Weight
(g)		20199.44 ± 0.74 ab7.67 ± 0.74 c7.46 ± 0.62 c9.57 ± 0.83 a8.84 ± 0.89 b8.00 ± 0.70 c***
20218.65 ± 0.69 c9.54 ± 0.70 ab9.06 ± 0.71 bc9.49 ± 0.87 ab8.83 ± 0.87 c9.81 ± 0.86 a***
Length
(mm)		201924.84 ± 0.58 a23.46 ± 0.85 cd22.83 ± 0.61 d24.47 ± 0.66 ab24.12 ± 0.71 bc23.67 ± 0.89 c***
202122.40 ± 1.46 c23.48 ± 0.78 b22.82 ± 0.94 bc23.35 ± 1.07 b23.26 ± 0.95 b24.33 ± 0.77 a***
Diameter (mm)201922.87 ± 0.76 ab21.40 ± 0.70 c20.60 ± 0.59 d23.18 ± 1.01 a22.14 ± 0.97 bc21.84 ± 0.96 c***
202122.11 ± 0.87 bc22.66 ± 1.08 ab21.69 ± 1.06 c22.40 ± 1.02 abc22.63 ± 0.84 ab23.02 ± 1.08 a***
Width
(mm)		201928.48 ± 0.98 ab26.07 ± 0.92 c26.48 ± 1.01 c28.79 ± 0.88 a27.66 ± 1.34 b26.47 ± 1.01 c***
202128.09 ± 1.2128.13 ± 1.1427.68 ± 1.1228.57 ± 1.6727.66 ± 0.9828.09 ± 1.16n.s.
‘Lapins’Weight
(g)		20198.41 ± 1.12 d11.12 ± 1.23 c12.00 ± 0.75 ab11.62 ± 1.12 bc12.76 ± 1.08 a11.82 ± 1.10b c***
20217.50 ± 1.30 d10.37 ± 0.76 b11.04 ± 0.83 a10.35 ± 0.83 b9.25 ± 0.82 c8.89 ± 0.58 c***
Length
(mm)		201926.65 ± 0.99 ab23.41 ± 0.97 d26.03 ± 0.75 bc26.08 ± 1.33 bc26.84 ± 0.98 a25.81 ± 0.99 c***
202123.09 ± 1.30 d25.01 ± 0.81 ab25.31 ± 0.89 a25.36 ± 0.94 a24.26 ± 0.61 c24.34 ± 0.89b c***
Diameter (mm)201925.03 ± 1.16 a22.24 ± 1.06 d24.88 ± 0.67 ab24.18 ± 0.99 bc24.88 ± 0.91 ab24.00 ± 0.97 c***
202121.42 ± 1.22 d24.02 ± 1.06 a23.88 ± 0.86 a23.74 ± 0.64 ab23.12 ± 0.75 bc22.58 ± 0.70 c***
Width
(mm)		201929.00 ± 1.29 ab25.91 ± 1.45 c29.06 ± 1.03 ab28.68 ± 0.98 b29.71 ± 0.89 a29.10 ± 1.06 ab***
202124.64 ± 1.72 c27.61 ± 1.00 a28.25 ± 1.07 a27.89 ± 0.89 a26.63 ± 0.99 b26.53 ± 0.87 b***
C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%. Data are the mean ± SD. For each row, different letters indicate significant differences between treatments (*** p < 0.001). n.s.—Not significant.
Table 3. Color parameters (L*, C*, and Hue°) of ‘Early Bigi’ and ‘Lapins’ cherries after applying different preharvest treatments.
Table 3. Color parameters (L*, C*, and Hue°) of ‘Early Bigi’ and ‘Lapins’ cherries after applying different preharvest treatments.
CultivarParameterYearCEM 0.15%EM 0.30%GB 0.25%GB 0.40%MixTreatment Effect
‘Early Bigi’L*201951.02 ± 2.89 a37.37 ± 1.81 c40.43 ± 4.42 bc43.16 ± 4.17 b43.25 ± 4.17 b40.33 ± 3.81 bc***
202148.69 ± 2.27 a45.40 ± 2.97 c47.90 ± 2.85 cb46.52 ± 2.94 abc45.83 ± 4.36 bc42.84 ± 3.31 d***
C*201941.60 ± 1.65 ab34.92 ± 3.69 d37.20 ± 5.31 cd42.23 ± 3.09 a40.56 ± 4.32 abc37.98 ± 4.72 bcd***
202142.06 ± 2.19 b44.01 ± 1.95 a42.50 ± 2.01 ab42.02 ± 2.26 b41.86 ± 3.09 b41.77 ± 2.77 b***
Hue°201935.09 ± 1.14 a27.14 ± 2.61 c30.03 ± 2.13 b31.40 ± 2.13 b30.88 ± 3.06 b30.12 ± 2.32 b***
202133.97 ± 2.07 a33.39 ± 1.42 a33.83 ± 1.88 ª33.29 ± 1.82 a32.98 ± 2.27 a31.45 ± 2.28 b***
‘Lapins’L*201941.58 ± 3.52 a36.89 ± 3.40 b34.99 ± 2.21bc33.47 ± 2.40 c34.17 ± 3.09 c33.85 ± 1.81 c***
202135.46 ± 1.84 b38.40 ± 1.98 a38.18 ± 2.59 ª37.61 ± 1.89 a37.78 ± 2.54 a36.95 ± 2.28 ab***
C*201942.22 ± 3.57 a35.37 ± 4.96 b35.01 ± 3.52 b31.33 ± 4.47 c34.83 ± 4.95 b30.29 ± 4.05 c***
202138.58 ± 2.3938.55 ± 2.3139.69 ± 2.5638.98 ± 2.4838.78 ± 2.2837.97 ± 2.73n.s.
Hue°201929.89 ± 2.08 a25.87 ± 3.82 b25.61 ± 1.96 b23.12 ± 2.76 c26.36 ± 2.01 b22.85 ± 2.34 c***
202126.79 ± 2.5927.62 ± 2.0328.09 ± 2.6426.33 ± 2.5826.81 ± 2.7626.88 ± 2.62n.s.
C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%. Data are the mean ± SD. For each row, different letters indicate significant differences between treatments (*** p < 0.001). n.s.—Not significant.
Table 4. Chemical parameters (TSS—total soluble solids, TA—titratable acidity, and MI—maturity Index) of ‘Early Bigi’ and ‘Lapins’ cherries after the application of different preharvest treatments.
Table 4. Chemical parameters (TSS—total soluble solids, TA—titratable acidity, and MI—maturity Index) of ‘Early Bigi’ and ‘Lapins’ cherries after the application of different preharvest treatments.
CultivarParametersYearCEM 0.15%EM 0.30%GB 0.25%GB 0.40%MixTreatment Effect
‘Early Bigi’TSS
(°Brix)		201910.38 ± 0.13 c12.50 ± 0.28 a11.60 ± 0.23 b12.38 ± 0.34 a11.65 ± 0.19 b12.03 ± 0.40 ab***
20218.58 ± 0.03 c9.93 ± 0.12 ab9.53 ± 0.29 b9.50 ± 0.56 b10.17 ± 0.23 ab10.47 ± 0.32 a*
TA
(% malic acid)		20190.58 ± 0.01 ab0.54 ± 0.06 ab0.49 ± 0.020.62 ± 0.03 a0.53 ± 0.06 b0.53 ± 0.01 b***
20210.36 ± 0.010.39 ± 0.010.39 ± 1.780.37 ± 0.010.48 ± 0.050.39 ± 0.03n.s.
MI
(TSS/TA)		201917.97 ± 0.09 b23.92 ± 1.34 a23.35 ± 0.92 a19.96 ± 0.99 b23.59 ± 0.81 a22.64 ± 0.47 a***
202123.89 ± 0.32 ab25.03 ± 0.50 a26.05 ± 0.59 a25.51 ± 1.53 a21.17 ± 2.32 b27.07 ± 1.36 a*
‘Lapins’TSS
(°Brix)		201915.13 ± 0.25 d19.37 ± 0.07 b18.18 ± 0.16 c19.32 ± 0.79 b19.42 ± 0.41 b21.20 ± 0.23 a***
202114.28 ± 0.19 c16.13 ± 0.50 ab16.30 ± 0.36 a15.93 ± 0.42 ab15.23 ± 0.2 bc16.33 ± 0.38 a***
TA
(% malic acid)		20190.63 ± 0.02 bc0.70 ± 0.02 ab0.59 ± 0.04 c0.57 ± 0.04 c0.62 ± 0.02 c0.76 ± 0.02 a***
20210.49 ± 0.01 a0.46 ± 0.01 b0.45 ± 0.01 b0.50 ± 0.02 a0.46 ± 0.01 b0.45 ± 0.01 b***
MI
(TSS/TA)		201924.03 ± 0.56 b27.70 ± 0.68 bc31.00 ± 1.96 ab34.26 ± 2.34 a31.39 ± 1.39 ab27.80 ± 0.89 bc***
202128.59 ± 0.61 d34.91 ± 0.75 ab36.27 ± 1.18 a31.65 ± 0.31 c33.43 ± 1.14 bc36.25 ± 0.93 a***
C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%. Data are the mean ± SD. For each row, different letters indicate significant differences between treatments (*** p < 0.001 and * p < 0.05). n.s.—Not significant.
Table 5. Total phenolic (mg GAE g−1 DW) and total anthocyanin (mg cy-3-rut g−1 DW) contents of ‘Early Bigi’ and ‘Lapins’ cherries after applying different preharvest treatments.
Table 5. Total phenolic (mg GAE g−1 DW) and total anthocyanin (mg cy-3-rut g−1 DW) contents of ‘Early Bigi’ and ‘Lapins’ cherries after applying different preharvest treatments.
CultivarParametersYearCEM 0.15%EM 0.30%GB 0.25%GB 0.40%MixTreatment Effect
‘Early Bigi’Total phenolics
(mg GAE g−1 DW)		20197.19 ± 0.26 c8.22 ± 0.63 bc9.54 ± 0.71 a8.08 ± 0.38 bc9.09 ± 0.76 ab7.45 ± 0.84 c**
20215.82 ± 0.35 d9.13 ± 0.27 a8.31 ± 0.28 b8.58 ± 0.31 ab7.95 ± 0.26 b6.89 ± 0.11 c***
Total anthocyanin (mg cy-3-rut g−1 DW)201914.18 ± 0.63 e37.77 ± 1.39 a38.52 ± 1.89 a25.04 ± 0.32 c31.32 ± 1.28 b18.88 ± 0.63 d***
202131.11 ± 2.93 c54.13 ± 2.29 ab58.57 ± 3.72 a47.26 ± 3.32 b58.42 ± 0.95 a33.35 ± 2.14 c***
‘Lapins’Total phenolics
(mg GAE g−1 DW)		20195.96 ± 0.51 b7.77 ± 0.50 a6.78 ± 0.52 b6.28 ± 0.57 b8.07 ± 0.42 a6.45 ± 0.30 b***
20218.20 ± 0.38 c10.04 ± 0.51 ab10.68 ± 0.89 a8.96 ± 0.15 bc9.68 ± 0.52 ab8.93 ± 0.91 bc**
Total anthocyanin (mg cy-3-rut g−1 DW)201964.03 ± 1.04 b80.15 ± 2.02 a84.35 ± 3.53 a81.95 ± 6.61 a82.92 ± 1.31 a76.03 ± 1.95 a***
202182.68 ± 2.59 c102.54 ± 4.60 b112.53 ± 3.64 a88.64 ± 1.74 c107.61 ± 2.89 b91.63 ± 2.22 c***
C—Control treatment; EM 0.15%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.15%; EM 0.30%—Ecklonia maxima seaweed-based biostimulant applied at a concentration of 0.30%; GB 0.25%—Glycine betaine applied at a concentration of 0.25%; GB 0.40%—Glycine betaine applied at a concentration of 0.40%; Mix—EM 0.15% plus GB 0.25%. Data are the mean ± SD. For each row, different letters indicate significant differences between treatments (*** p < 0.001 and ** p < 0.01).
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Afonso, S.; Oliveira, I.; Ribeiro, C.; Vilela, A.; Meyer, A.S.; Gonçalves, B. Exploring the Role of Biostimulants in Sweet Cherry (Prunus avium L.) Fruit Quality Traits. Agriculture 2024, 14, 1521. https://doi.org/10.3390/agriculture14091521

AMA Style

Afonso S, Oliveira I, Ribeiro C, Vilela A, Meyer AS, Gonçalves B. Exploring the Role of Biostimulants in Sweet Cherry (Prunus avium L.) Fruit Quality Traits. Agriculture. 2024; 14(9):1521. https://doi.org/10.3390/agriculture14091521

Chicago/Turabian Style

Afonso, Sílvia, Ivo Oliveira, Carlos Ribeiro, Alice Vilela, Anne S. Meyer, and Berta Gonçalves. 2024. "Exploring the Role of Biostimulants in Sweet Cherry (Prunus avium L.) Fruit Quality Traits" Agriculture 14, no. 9: 1521. https://doi.org/10.3390/agriculture14091521

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