Impaginato 47 Adv. Hort. Sci., 2024 38(1): 47­62 DOI: 10.36253/ahsc­15033 A biostimulant complex comprising molasses, Aloe vera extract, and fish­ hydrolysate enhances yield, aroma, and functional food value of strawberry fruit K. Wise 1, 2, J. Selby­Pham 1, 2 (*), T. Simovich 3, 4, H. Gill 1 1 School of Science, RMIT University, Bundoora, VIC 3083, Australia. 2 Nutrifield, Sunshine West, Victoria, VIC 3020, Australia. 3 School of Engineering, RMIT University, Melbourne, VIC 3000, Australia. 4 PerkinElmer Inc., Glen Waverley, VIC 3150, Australia. Key words: Antioxidant, Fragaria, hydroponics, phenolics, super food. Abbreviations: A = achromatic; ATC = automatic temperature compensation; B = blue; BC = Biostimulant complex; C = cyan; EC = electrical conductivity; F­C = Folin­Ciocalteu; FTIR = Fourier transformed infrared; G = green; GAE = gallic acid equivalent; GLM = general linear model; GM = genetic modification; M­IR = mid­ infrared; O = orange; PCA = principle component analysis; Pi = pink; PLS­DA = par­ tial least squares­discriminant analysis; Pu = purple; QE = quercetin equivalent; R = red; RWC = relative water content; sPLS­DA = sparse partial least squares­dis­ criminant analysis; SSC = soluble solids content; TP = total phenolics; UATR = uni­ versal attenuated total reflectance; W = white; Y = yellow. Abstract: Strawberry is a popular functional food due to the presence of antiox­ idant and anti­inflammatory phytochemicals. Enhancing this functional food value is an opportunity to improve consumer health, but strategies to do so cannot compromise yield or organoleptic properties, which are highest priori­ ties for farmers and consumer, respectively. One promising strategy is the sup­ plementation of fertiliser regimens with biostimulants, which are non­nutritive substances associated with species­specific improvements to crop growth, yield, and quality. Accordingly, the impacts of a biostimulant complex (BC) con­ taining molasses, Aloe vera extract, and fish­hydrolysate is characterised herein for its potential to impact strawberry growth, yield, quality, and functional food value. Results indicated that BC treatment significantly increased (p < 0.05) plant biomass and canopy area (growth), total fruit count and weight per plant (yield), fruit aroma and colour (quality), and antioxidant potential (func­ tional food value). The results presented highlight the potential utility of bios­ timulants to the strawberry sphere, providing a strategy to enhance the fruit to the benefit of both farmers and consumers. (*) Corresponding author: jamie@nutrifield.com Citation: WISE K., SELBY­PHAM J., SIMOVICH T., GILL H. 2024 ­ A biostimulant complex comprising molas‐ ses, Aloe vera extract, and fish‐hydrolysate enhances yield, aroma, and functional food value of strawberry fruit. ‐ Adv. Hort. Sci., 38(1): 47­62. Copyright: © 2024 Wise K., Selby­Pham J., Simovich T., Gill H. This is an open access, peer reviewed article published by Firenze University Press (http://www.fupress.net/index.php/ahs/) and distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Competing Interests: The authors declare no competing interests. Received for publication 9 August 2023 Accepted for publication 21 September 2023 AHS Advances in Horticultural Science https://doi.org/10.36253/ahsc-15033 http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ Adv. Hort. Sci., 2024 38(1): 47­62 48 1. Introduction The genus Fragaria is comprised of 25 species of small flowering plants known as strawberries, which are widely cultivated for their edible fruits (Hirakawa et al., 2014). Of these 25 species, the hybrid octo­ ploid Fragaria x ananassa, is the most popular vari­ ety, accounting for 60% of the worlds strawberry fruit production (Amil­Ruiz et al., 2011). The global strawberry industry is a profitable and growing indus­ try, with world production outputs in 2020 equal to 40.76 million tonnes (FAO, 2022). Whilst strawberry fruits are primarily consumed as a fresh fruit, they are also popular additions to processed foods such jams, juices, dairy products, and flavoured drinks, making strawberries one of the most popular and versatile global agricultural products (Moraga et al., 2006; Basu et al., 2014). The drivers of consumer perception of strawberry fruit quality are their physical features, organoleptic properties, nutritional value, and added secondary health benefits (functional food properties) such as antioxidant, anti­inflammatory, and anti­hyperten­ sive activities (Basu et al., 2014). Improving these measures is therefore desirable to consumers who would experience higher quality produce and poten­ tially added health benefits from increased functional food properties. The antioxidant activity of strawber­ ry fruits is a particular driver of the fruit’s popularity, as this functional food property is associated with a range of benefits including improvements to cardio­ vascular health (Giampieri et al., 2015), neurodegen­ eration (Esposito et al., 2002), cancer (Zhang et al., 2008), and type 2 diabetes (da Silva Pinto et al., 2010). The antioxidant activity of the fruit is attribut­ ed to the high concentrations of polyphenols includ­ ing flavonoids, anthocyanins, and ellagitannins, and vitamins such as ascorbic and folic acid, which have been shown to vary in concentration in fruits depending on cultivar, storage, processing, and culti­ vation system (Basu et al., 2014; Afrin et al., 2016). In addition to improving the functional properties of the fruit, strawberry yield and organoleptic improve­ ments are also significant opportunities to benefit the strawberry industry. Processing (Moraga et al., 2006), plant breeding (Diamanti et al., 2012), and cultivation practises (Akhatou et al., 2014) have all been shown to impact fruit sensory properties such as firmness and taste, however, breeding is slow and costly, and processing is unsuitable to the fresh fruit sector. Therefore, modifications to farming practises could be potential­ ly fast and versatile interventions to strawberry culti­ vation, to improve fruit quality metrics ­ functional food potential and organoleptic desirability ­ and thereby enhance customer perception of quality and value returned to farmers. Accordingly, implementa­ tion of biostimulants continues to generate interest as a fast and environmentally friendly improvement to cultivation practises, as these inputs are non­nutri­ tive compounds or substances which beneficially impact plant growth, development, or yield (Du Jardin, 2015). Various biostimulants have been asso­ ciated with improvements to fruit quality in a range of species, however effects are plant­species and dosage dependent, requiring further exploration of these effects in target crops such as strawberry (Rodrigues et al., 2020; Wise et al., 2020). Molasses is a by­product from the sugar industry, which is rich in simple and complex carbohydrates, proteins, amino acids, organic acids, and Maillard reaction by­products (melanoidins) (Najafpour and Shan, 2003; Chandra et al., 2008). It has been used as an additive in agriculture and has demonstrated bios­ timulant effects including increasing yield in beetroot (Nadeeka and Seran, 2020), sugar cane (Srivastava et al., 2012) and spinach (Pyakurel et al., 2019), improved biomass growth in maize (Shahzad et al., 2018) and sorghum (Suliasih and Widawati, 2016), enhanced salinity tolerance in thyme (Koźmińska et al., 2021), and improvements to disease resistance in various species (Welbaum et al., 2004). Similarly, molasses distillery effluent, which is more dilute but similarly comprised to molasses, also has demon­ strated biostimulant benefits such as increased yield in banana (Thakare et al., 2013) and sweet pepper (Gaafar et al., 2019), increased nutrient uptake in radish (Hatano et al., 2016), improved growth and development of rapeseed (Li et al., 2020), altered antioxidant activity in cabbage (Bimova and Pokluda, 2009) and black bean (Elayaraj, 2014), as well as increased heavy metal uptake by common reed and sedge for potential applications to bioremediation (Nagy et al. , 2020). Accordingly, utilisation of molasses as a biostimulant input for strawberry farm­ ing may be expected to positively impact a range of yield, growth, and quality measures. Aloe vera extracts are also complex mixtures con­ taining plant nutrients, vitamins, enzymes, amino acids, sugars, hormones, and hormone­like com­ pounds (Ishartati et al., 2019; Cortés et al., 2021). The biostimulant effects associated with application Wise et al. ‐ Biostimulant complex improves strawberry quality 49 of Aloe vera extracts are varied, including increased propagation efficiency and growth of Populus tree clones (El Sherif, 2017), eucalyptus tissue cultures (Hendi, 2021), and grape vine cuttings (Uddin et al., 2020), improved growth, biomass, and oil content of sweet basil (Hamouda et al., 2012), increased growth, yield, oil content, and nutritional content of caraway (Khater et al., 2020), improved growth and chlorophyl content of fenugreek (Al­Yasiri et al., 2021), increased leaf growth and terpene content in lavender (El Sherif et al., 2020), enhanced fruit yield and nutritional content of okra (Hemalatha et al., 2018 a, b), and dose­dependent positive and nega­ tive effects on cereal germination (Baličević et al., 2018). Accordingly, Aloe vera extracts are utilised as fertiliser additives to improve plant growth and have the potential to improve a range of attributes when added to strawberry plants during cultivation. Agricultural amino acids can be purified or com­ plex mixtures, which are often extracted (hydrolysed) from animal, plant, or microbial products (Calvo et al., 2014). Legume­derived hydrolysates are common sources of amino acids and have a range of beneficial effects associated with their use during cultivation including increased vegetative growth, yield, and sec­ ondary metabolite production in capsicum (Ertani et al., 2014), and increased yield (Colla et al., 2017), nutritional content (Colla et al., 2017; Rouphael et al. , 2017), firmness (organoleptic property) (Mirabella et al., 2021), and antioxidant activity (Caruso et al., 2019) in tomato. Furthermore, amino acids derived from fish­hydrolysate have demonstrat­ ed increased yield in tomato (García­Santiago et al., 2021), pig blood­hydrolysate increased phenolic and antioxidant properties of lettuce (Zhou et al., 2022), and a commercial amino acid product was shown to increase antioxidant activity in the leaves of Aloe vera (Ardebili et al., 2012). Amino acids are also asso­ ciated with improved nutrient uptake in plants, either directly through provision of organic­N or indi­ rectly through stimulation of soil microbes or chela­ tion of nutrients (Callahan et al., 2007; Halpern et al., 2015). Accordingly, addition of amino acids during strawberry cultivation may demonstrate biostimulant effects to improve a range of measures and thereby benefit consumers and/ or farmers. Noting the potential benefits of molasses, Aloe vera extract, and fish­hydrolysate as biostimulants during strawberry cultivation, the aim of this study was to explore impacts to strawberry growth, yield, and quality associated with the supply of a complex of these biostimulants. This involved the hydroponic growth of strawberry plants with application of the biostimulant complex, followed by temporal assess­ ment to impacts to fruit yield, in addition to end point fruit quality measures such as fruit antioxidant potential, and fruit sensory profile. Characterisation of the effect of these biostimulants to strawberry has the potential to benefit both strawberry farmers and consumers by providing a cost efficient and easily implemented farming strategy to enhance the value of strawberry yields. 2. Materials and Methods Plant materials and growth conditions Stock tubes of strawberry plants (Fragaria x ananassa ‘Albion’), supplied by Sunny Ridge Strawberry Farm Pty Ltd. (Boneo, VIC, Australia), were planted into 15 cm pots in Coco perlite sub­ strate (Nutrifield Pty Ltd., Melbourne, VIC, Australia) and maintained in indoor growth rooms for 5 weeks with Coco A&B nutrients (Nutrifield Pty Ltd., Melbourne, VIC, Australia) at pH = 5.8, and EC = 1.0. Fertigation was delivered via a flood and drain sys­ tem, wherein trays containing potted plants were filled with fertigation liquid to 75% the height of the pots and subsequently drained. Plants were grown under 315W ceramic metal­halide horticultural lamps (315W CMH Pro 4200K, Indoor Sun, Melbourne, VIC, Australia), with a Recom 315W Ballast (Lucius, Melbourne, VIC, Australia), and light:dark (L:D) pho­ toperiod of 12 hours day and 12 hours night. Environmental conditions were restricted to day tem­ perature and relative humidity of 21.5°C, and 70%, respectively, and night temperature and relative humidity of 18°C, and 51%, respectively. After 5 weeks, plants were separated into treatment groups and re­potted into 30 cm square pots with Coco per­ lite substrate and a top layer (2 cm) of Hydro Clay (Nutrifield Pty Ltd., Melbourne, VIC, Australia). Treatment and fertigation programme Twelve plants were split into 2 groups (n = 6): con­ trol group, receiving Coco A&B nutrients as per usage instructions, and treatment group, receiving Coco A&B nutrients as per usage instructions plus the bios­ timulant complex (BC) comprising molasses (10% w v­ 1), Aloe vera extract (2.5% v v­1), and fish­hydrolysate (5% v v­1) at 2 mL L­1 during weeks 10­18. Fertigation was delivered to plants via a recirculating drip­irriga­ Adv. Hort. Sci., 2024 38(1): 47­62 50 tion system (4 × 4 L h­1 dripper­1 plant­1) as described in Table 1. The elemental composition, phytohor­ mone profile, and metabolite profile of the biostimu­ lant complex is provided in supplemental tables S1, S2, and S3, respectively. Vegetative measurements Leaf colour (L*a*b*) was measured using a CR­ 400 Chroma Meter colourimeter (Konica Minolta, Tokyo, Japan). Canopy area was measured using the smartphone application Easy Leaf Area Free (Easlon et al., 2014). At the conclusion of the harvest period leaf and crown number were counted, and final fresh­ and dry­weight measurements were taken for leaf and non­leaf tissues. Vegetative tissues were dried in an ED 53 oven (BINDER, Tuttlingen, Germany) at 70°C for 3 days. Harvesting and fruit measures Ripe fruit ­ defined as BBCH = 87 according to Wise et al. (2022) ­ were harvested, immediately measured (weight and length), and placed into a DT5600 Food Dehydrator (Sunbeam, FL, USA) at 55°C for 7 days. Strawberry fruit length at harvest was measured as the perpendicular distance from the centre of the calyx to the tip of the receptacle. Fruit width at harvest was measured by image analysis using ImageJ (Schneider et al., 2012). In short, image global pixel scale was set based on known fruit length and the ‘measure’ feature within the ROI manager was utilised to measure the widest fruit diameter. Determination of pH and Brix of crude fruit extract A crude extract was prepared by pressing fresh strawberry fruits through four layers of muslin cloth and subsequently passing the filtrate through an additional single layer of muslin cloth. An automatic temperature compensation (ATC) portable refrac­ tometer (Sugar/Brix Refractometer 0­32% 300001, Super Scientific Ltd., Scottsdale, AZ, USA) was used to measure Brix (°Bx) of the pure crude extract. A 1/1000 dilution of the crude extract in water was used to measure pH (Sension+ MM 374 GLP 2 chan­ nel Laboratory Meter with Sension + 5014T pH liquid combination electrode with silver ion barrier, HACH, Loveland, CO, USA). Fruit phytochemical extraction Whole fruit extraction was carried out with adap­ tations to the method described in Chandra et al. (2014). In short, the dried strawberry fruits were pul­ verised in a ‘multigrinder II’ (Sunbeam, FL, USA) and then extracted in 8 mL ethanol (100%) per g pul­ verised fruit. The extraction was carried out in a soni­ cator at 40°C for 10 min and then filtered through 7­ 10 µm membrane filter paper with 0.1% ash content (Westlab, Ballarat, VIC, Australia). The ethanol filtrate was evaporated in a 100°C water bath to achieve a dried extract, which was then resolubilised in 5 mL 5% methanol in a sonicator at 40°C for 10 min. Determination of total phenolic and flavonoid con‐ tent Total phenolic (TP) and flavonoid content was determined as per the Folin­Ciocalteu (F­C) method, and the aluminium chloride colorimetric method, respectively, which were adapted from those described in Chandra et al. (2014). In short, TP con­ tent was determined by combining 100 µL of resolu­ bilised extract with 100 µL F­C reagent, 300 µL 8% w v­1 saturated sodium carbonate solution, and 1.5 mL distilled water. Solutions were reacted under light in a PS­10A sonicator (Jeken, Dongguan, China) at 40°C for 30 min. The absorbance was measured at 765 nm and phenolic content was calculated as gallic acid equivalent per gram dry fruit (GAE g g­1 d.w.). Total flavonoid content was determined by combining 1 mL of the resolubilised extract with 1 mL 10% (w v­1) aluminium chloride. The solutions were reacted at room temperature for 1 h, and then absorbance was measured at 420 nm. The results were calculated as quercetin equivalent per gram dry fruit (QE mg g­1 d.w.). All absorbance measurements were analysed using the DR 5000™ UV­Vis Spectrophotometer (HACH, Loveland, CO, USA). Sensory perception testing A blinded test was conducted to explore if the biostimulant treatment was associated with changes to sensory perception of fruits. Participants (n = 6) were asked to score the fruits (on a 9­point scale) Table 1 ­ Fertigation programme for strawberry plants during treatment (weeks 6­18) Weeks Fertigation programme (split evenly throughout the day) 6­11 3 × 10 min 12­13 4 × 10 min 14­18 6 × 10 min Wise et al. ‐ Biostimulant complex improves strawberry quality 51 based on their texture, taste, and aroma (Table 2). Plant image colour analysis Colour data of strawberry fruit images was extracted as per Wise et al. (2022), wherein individu­ al pixels were categorised as either achromatic (A, light grey­black), blue (B), cyan (C), green (G), orange (O), pink (Pi), purple (Pu), red (R), white (W), or yel­ low (Y), based on maximal similarity to predefined colours. Mid‐infrared (M‐IR) analysis Infrared spectra of the dried strawberry fruits were collected using a Spectrum 2 FTIR spectropho­ tometer (PerkinElmer Inc., Waltham, MA, USA) equipped with a Universal Attenuated Total Reflectance (UATR) accessory with diamond crystal. Spectra were collected with a 4 cm­1 resolution over the 500­7000 cm­1 range with four accumulations to produce an averaged spectrum. For data analysis the 4000­7000 cm­1 range was excluded. Spectral data were standardised to 1875 cm­1 prior to analysis, cor­ responding with the region of the sample spectra which has minimal influence from the presence of water as indicated by the water absorption spectra (NIST, 2022), presented in the NIST Chemistry WebBook (Linstrom and Mallard, 2001). Statistical analysis Analyses implemented during exploration of treatment effects on individual measures included general linear model (GLM), Tukey’s test 95% confi­ dence grouping analyses, Anderson­Darling normality test, and Mood’s median test in the Minitab 19 sta­ tistical software package (Minitab Inc., State College, PA, USA). Analyses implemented to explore treat­ ment effects on the profiles of plant measures (and fruit M­IR spectra) were heatmap analysis, dendro­ gram, principle component analysis (PCA), partial least squares­discriminant analysis (PLS­DA), sparse PLS­DA (sPLS­DA), and fold change (1.3­fold thresh­ old), using the web­tool Metaboanalyst 5.0 (Chong et al., 2019). The profiles of plant measures were nor­ malised within Metaboanalyst using the cube root transformation and pareto scaling functions, while M­IR data was transformed by auto­scaling. Mean changes in sensory perception was assessed by a repeated­measures t­test, performed in Minitab 19. Replicates per analysis are presented in supplemen­ tal table S1. 3. Results Profile analyses (vegetative, yield, and quality) A range of growth, yield, and quality measures were taken per plant (27 measures total) to assess the impact of the BC treatment on strawberry plants (Table S4). Principal component analysis (Fig. 1A) and PLS­DA (Fig. 1B), identified clearly distinct 95% confi­ dence regions in the trait profiles between BC and control treated plants, which is consistent with the clustering of sample profiles by treatment within the dendrogram (Fig. 1C) and heatmap (Fig. S1). Heatmap analysis (Fig. S1 and Table S5) identified two clusters within the 27 plant measures (13 vege­ tative, 7 yield, and 8 quality), one cluster with mini­ mal difference between treatments (6 vegetative, 5 Table 2 ­ Sensory perception scoring matrix Sensory perception Poor Acceptable Optimal Aroma ­ Desirability 1 2 3 4 5 6 7 8 9 Taste ­ Desirability 1 2 3 4 5 6 7 8 9 Low Moderate High Mouthfeel ­ Firmness 1 2 3 4 5 6 7 8 9 Mouthfeel ­ Juiciness 1 2 3 4 5 6 7 8 9 None Moderate Strong Aroma ­ Intensity 1 2 3 4 5 6 7 8 9 Taste ­ Sweet 1 2 3 4 5 6 7 8 9 Taste ­ Sour/acid 1 2 3 4 5 6 7 8 9 Taste ­ Intensity 1 2 3 4 5 6 7 8 9 52 Adv. Hort. Sci., 2024 38(1): 47­62 yield, and 4 quality), and one cluster of measures with large difference between treatments (7 vegeta­ tive, 2 yield, and 4 quality). The cluster associated with large differences was comprised of the mea­ sures: leaf count (number), leaf fresh weight (g f.w.), leaf dry weight (g d.w.), above ground (non­leaf) fresh weight (g f.w.), above ground (non­leaf) dry weight (g d.w.), canopy area (cm2), and leaf colour­a (V2, V3, V4, V6, V7, V9, and V11, respectively), total fruit harvested (g) and fruit harvested (number) (Y5 and Y6, respectively), and fruit GAE per fruit dry weight (g·g­1 d.w.), Brix %, fruit pH, and fruit water % (Q1, Q2, Q3, and Q5, respectively). Vegetative analyses Treatment with BC had significant impacts on sev­ eral vegetative measures (Table S4). The greatest effect was seen for leaf measures including: leaf number (p < 0.001) which increased by 107.4% (over two­fold) from 15.67 in control to 32.5 in treatment (Fig. 2A), leaf dry weight (p = 0.002) which increased by 66.7% from 7.4 g d.w. in control to 12.4 g d.w. in treatment (Fig. 2B), and canopy area (p = 0.001) which increased by 51.8% from 401.4 cm2 in control to 609.3 cm2 for treatment (Fig. 2C). Whilst vegeta­ tive measures tended to increase, no significant change (p = 0.205) was identified for leaf water con­ tent (Table S4). Furthermore, the BC treatment increased (p = 0.001) non­leaf aerial dry weight by 64% from 5.7 g d.w. for control to 9.4 g d.w. for treatment (Table S4), and with marginal significance (p = 0.057) increased crown number by 35% from 3.3 to 4.5 (Fig. 2D), whilst not significantly affecting leaf Fig. 1 ­ Effect of biostimulant complex (BC) on strawberry (Fragaria x ananassa ‘Albion’) trait profiles. (A) Principal component analysis (PCA), and (B) partial least squares­ discriminant analysis (PLS­DA), with shading indicating 95% confidence regions. C) Dendrogram indicating hie­ rarchical clustering (Ward clustering algorithm) based on Euclidean distance of plants based on measured traits. Trait values measured from 6 biological replicates. Fig. 2 ­ Effect of biostimulant complex (BC) treatment on vegeta­ tive growth measures of strawberry (Fragaria x ananassa ‘Albion’). A) Number of leaves, (B) leaf dry weight, (C) canopy area, and (D) number of crowns compared between control and BC treated plants. Data presented mean ± standard deviation of 6 biological replicates. Significant differences are indicated by ‡ for p < 0.1; * for p < 0.05; ** for p < 0.01; *** for p ≤ 0.001 calculated by Student’s t­test. Wise et al. ‐ Biostimulant complex improves strawberry quality 53 colour measures L*, a*, and b* (Table S4). Yield analyses The biostimulant complex significantly increased the yields of strawberry plants in terms of total weight of fruits per plant (p = 0.038), and number of fruits per plant (p = 0.035), whilst not significantly (p = 0.666) affecting individual fruit weight (Table S4). The average weight of total fruits harvested per plant increased by 50.7% from 128.3 g for control to 193.3 g for treatment (Fig. 3A), while the average number of fruits harvested per plant increased by 56.9% from 12.0 for control to 18.8 for treatment (Fig. 3B). Whilst no changes were observed for individual fruit weight, changes to fruit shape were observed wherein BC treatment significantly (p = 0.013) increased fruit length (Table S4) from 30.33 mm to 35.48 mm (17% increase), whilst fruit width was unchanged (p = 0.446). Harvest timing was normally distributed for control plants (p = 0.268) but not for treatment plants (p = 0.038), however no significant difference between treatments was identified in median fruit harvest timing (p = 0.971, Fig. 3C). Fruit quality analyses Chemical analysis of strawberry fruits identified that BC treatment significantly increased fruit water content (p = 0.001) wherein fruit water content from treatment plants was 90.2%, whilst fruits from con­ trol plants had 89.06% water content (Fig. 4A). Additionally, the BC treatment resulted in significant changes to fruit image colour profiles, wherein R% increased from 29.66% for control to 39.22% (p = 0.001), G% increased from 0.38% for control to 1.01% (p = 0.001), and O% decreased from 28.90% for control to 20.79% (p = 0.006), whilst Y% (p = 0.371) and A% (p = 0.186) were not significantly impacted (Fig. 4B). The fruit colour measures B, Pi, C, W, and Pu accounted for on average less than 0.01% of pixels within images and so were not explored dur­ ing analyses. No significant difference was observed for Brix content (p = 0.941) between treatment or control plants (Fig. 4C). The biostimulant complex treatment resulted in a marginally (defined as 0.1 < p < 0.05) significant (p = 0.055) increase to pH of dilut­ ed crude fruit extract, from 4.2 to 4.4 (Table S4). It was identified that the BC treatment had signifi­ cant affects (p = 0.029) on TP content (Fig. 4D) with a 32% increase from 0.0139 GAE g·g­1 d.w. for control to 0.0184 GAE g g­1 d.w. for treatment, whilst not signifi­ cantly (p = 0.534) affecting flavonoid content (Fig. 4E). Fruit quality perception was analysed by a blinded sensory perception test on a 9­point scale, which identified that the BC treatment significantly (p = 0.043) increased fruit mouthfeel firmness (‘firmness’), from 4.2 for control to 5.5 for treatment, whilst not significantly impacting mouthfeel juiciness (‘juici­ ness’), or fruit taste measures (Table S6). Fig. 3 ­ Effect of biostimulant complex (BC) treatment on yield and harvest timing of strawberry fruits (Fragaria x ananassa ‘Albion’). Fruit yield per plant by (A) weight, and (B) count compared between control and BC treated plants. A­B) Data presented as mean ± standard deviation of 6 biological replicates. Significant differences are indicated by * for p < 0.05 calculated by Student’s t­ test. C) Histogram of harvest timing from 72 fruits from control plants and 97 fruits from BC treated plant. Adv. Hort. Sci., 2024 38(1): 47­62 54 nent analysis (PCA: Fig. S2) and PLS­DA (Fig. S3) did not identify significant differences between the pro­ file of spectral bins between treatment groups, while sPLS­DA (Fig. 4H) indicated significant differences in a subset of the wavelength’s measured. Comparison of the average spectra of each treatment (Fig. S4), iden­ tified a region between 1024­1048 cm­1 with the high­ est fold change (>1.3) between treatments (Fig. S5). Furthermore, the BC treatment significantly (p = 0.040) increased fruit aroma intensity from 3.5 to 5.2, and had a marginally significant (p = 0.067) effect to aroma desirability which increased from 5.0 to 6.7 (Fig. 4F). Mid­infrared spectrometry analysis between 500­ 4000 cm­1 identified biostimulant induced changes to fruit chemical composition (Fig. 4G). Principle compo­ Fig. 4 ­ Effect of biostimulant complex (BC) treatment on quality and sensory perception of strawberry (Fragaria x ananassa ‘Albion’) fruits. A) Fruit water (22 and 27 biological replicates for control and BC, respectively), (B) colour profile (22 and 27 biological replicates for control and BC, respectively with each colour represented as their respective colour), (C) Brix (6 and 13 biological replicates for control and BC, respectively), (D) total phenolics (22 and 27 biological replicates for control and BC, respectively), and (E) total flavonoids (22 and 27 biological replicates for control and BC, respectively) compared between control and BC trea­ ted plants. A, C­E) Data represented as mean ± standard deviation. F) Comparison of mean scores (6 participants) for blind sen­ sory perceptions of fruit from control and BC treated plants. A­E) Solid bars represent control and dashed bars represent BC treatment. A, C­F) Significant differences are indicated by ‡ for p < 0.1; * for p < 0.05; ** for p < 0.01; *** for p ≤ 0.001 calculated by Student’s t­test (A­E), and repeated­measures t­test (F). G) Mid­infrared (M­IR) spectra of dehydrated strawberry fruits analy­ sed between 500­4000 cm­1 (7 and 11 biological replicates for control and BC, respectively). H) Sparse partial least squares­discri­ minant analysis (sPLS­DA) of M­IR spectra with shading indicating 95% confidence regions. Wise et al. ‐ Biostimulant complex improves strawberry quality 55 was observed from application of the BC. Changes to fruit size and shape can be impactful to farmer sales due to the compliance standards imposed by super­ markets. For strawberry fruits, compliance is general­ ly determined according to diameter (USDA, 2006; Woolworths Supermarkets Ltd, 2010), which is also the highest correlating size measurement (R2 = 0.93) with consumer preference, however, length is the second highest correlation (R2 = 0.77) (Lewers et al., 2020), suggesting that longer fruits of unchanged width may be considered preferable by consumers. Accordingly, application of this biostimulant complex to strawberries during growth can benefit farmers by improving yield and improve customer perceptions of quality through altered fruit size. Whilst the aforementioned changes to fruit size are likely to be impactful to consumer perception of fruit quality, organoleptic properties and colour fea­ tures are also highly correlative with strawberry qual­ ity perception (Lewers et al., 2020). Organoleptic measures include taste, texture, mouthfeel, and aroma, which are conferred to the fruit through its chemical composition (Saliba­Colombani et al., 2001). Common measures associated with taste include sol­ uble solids content (SSC), titratable acidity (Wozniak et al., 1996), and pH (Gunness et al., 2009). Herein no significant change was detected for brix (p = 0.941), a measure of SSC (Saranwong et al., 2003), which is consistent with the results from the sensory assess­ ment wherein no significant change (p = 0.822) was observed in the correlated measure, sweetness (Jouquand et al., 2008). Similarly, sour perception may have been expected to change with pH (Jouquand et al., 2008), and whilst a marginally sig­ nificant change was observed for fruit pH (p = 0.055), no significant change was reported from panellists for the sensory measure sour (p = 1.000). This may be explained by the apparently small change of 0.11 pH of diluted extract, which is consistent with the find­ ings of Harker et al. (2002) wherein a minimum shift of 0.14 pH of apple extract was required for partici­ pants to perceive a change in apple acidity. These results suggest that utilisation of the BC during straw­ berry cultivation may increase yield without compro­ mising quality. Noting that a growing point of con­ sumer dissatisfaction is the reduction in food flavour and aroma due to the prioritisation of more prof­ itable crop attributes such as yield and visual aesthet­ ic (Klee, 2010; Tieman et al., 2017), these results sup­ port the utilisation of biostimulants as being advanta­ geous to both farmers and consumers. 4. Discussion and Conclusions Crop productivity is an important factor in food production when considering the growing global pop­ ulation and uncertainties associated with climate change (Lobell and Gourdji, 2012). Accordingly, new strategies to increase crop outputs are highly sought after, with a focus on fast acting benefits which do not contribute to environmental degradation. Whilst genetic modification (GM) continues to benefit many crop sectors, the costs, time, and resources required to develop approved GM food crops is a significant hurdle. Accordingly, biostimulants are becoming increasingly popular additives during plant growth due to their benefits to crop productivity, natural ori­ gin, cost, and ease of use (Parađiković et al., 2019). Herein a naturally derived biostimulant complex comprising molasses, Aloe vera extract, and fish­ hydrolysate exemplifies these beneficial effects by increasing the growth and yield of strawberry. Application of the BC was shown to increase vege­ tative biomass and canopy area measures (Fig. 2A­C), potentially associated with the provision of zeatin (cytokinin) ­ the only phytohormone detected in both the BC concentrate and its associated reservoir solu­ tion (Table S2) ­ which has been shown to increase shoot and root growth when applied exogenously to strawberry (Debnath, 2006). Additionally, the BC treatment resulted in a marginally significant (p = 0.057) increase to crown number (Fig. 2D). The crown is the central node of the strawberry plant from which roots, leaves, inflorescence, and addition­ al crowns form (Savini et al., 2005; Poling, 2012). As crowns are the base of future inflorescence forma­ tion, their number correlates strongly with fruit yield (Strik and Proctor, 1988; Kadir et al., 2006) and is therefore an important factor for strawberry cultiva­ tion. Additionally, application of the BC was observed to increase both yield­weight (Fig. 3A, p = 0.038) and yield­number (Fig. 3B, p = 0.035) per plant ­ poten­ tially associated with the increased crown number ­ which are crucial measures of profitability for farm­ ers. Accordingly, the increases in yield outputs reported herein (Fig. 3A and 3B) support the utilisa­ tion of these biostimulants by the strawberry indus­ try and thereby presents as a low­cost, effective, and easily integrated farming strategy to improve growth and yield. Furthermore, changes to strawberry shape ­ increased length (Fig. S6A, p = 0.013) but not weight (Fig. S6B, p = 0.666) or width (Fig. S6C, p = 0.446) ­ Adv. Hort. Sci., 2024 38(1): 47­62 56 Fruit mouthfeel and texture are associated with cell wall composition (Caner et al., 2008) and thick­ ness (Szczesniak and Smith, 1969), water content (Cordenunsi et al., 2002), and pH (Plotto et al., 2010). Additionally, Salentijn et al. (2003) and Wang et al. (2021) have shown that increased expression of genes associated with lignin production is associated with increased firmness of strawberry fruit. Accordingly, the significant increase in mouthfeel­ firmness (p = 0.043) may relate to the presence of caffeic acid in the BC (Table S3), which may internally translocate via the phloem and xylem (Zhang and Hamauzu, 2004; Ishimaru et al., 2011) and has been shown to increase lignin production in soybean (Bubna et al., 2011). Richter (1978) identified that plant cell turgidity is highly sensitive to changes in relative water content (RWC), with flaccidity (loss of turgidity) to full turgor occurring over the narrow range of 5% RWC. Accordingly, as fruit firmness is impacted by turgidity (Szczesniak and Smith, 1969; Raharjo et al., 1998), the 1% increase in fruit water content (p = 0.001) identified from the BC treatment may explain the observed increase in the sensory measure for firmness. Whilst this apparently minor change in fruit water content (Fig. 4A) may have impacted perceived firmness (Fig. 4F), it is however not surprising that this small change in fruit water volume (150 µL, based on 1% of 10.5 g average fruit fresh weight) was below sensory perception thresh­ olds to impact perceived juiciness, as juiciness is gen­ erally considered as the amount of liquid released during chewing (Roger Harker et al., 2003; Harker et al., 2006). Aroma ­ also referred to as odour ­ is the detec­ tion and recognition of compounds within the olfac­ tory system and is conferred by the presence of volatile compounds (El Hadi et al., 2013). In strawber­ ry, aroma is predominantly attributed to esters, fura­ nones, terpenes, and sulfur compounds (Yan et al., 2018). As with fruit flavour, aroma is often seen by consumers as a sacrifice for higher yields (Klee, 2010; Tieman et al., 2017), which necessitates the need for methods to improve aroma, or improve yields with­ out compromising this measure. Herein a significant difference (p = 0.040) was observed for aroma inten­ sity and a marginally significant (p = 0.067) difference was observed for aroma desirability (Fig. 4F), sug­ gesting that the BC treatment may have altered the volatile contents or profiles of the fruits. The M­IR analysis presented in figure 4G revealed a narrow region between 1024–1048 cm­1 with a high fold change, which has been associated with chemicals in the classes of phenolic alkyl­aryl ethers, aryl phenolic ester tannins (Abbas et al., 2017), pyranose rings (saccharides), alkyl amines, and alcohols (Lingegowda et al., 2012). Furthermore, of these classes of com­ pounds, esters are one of the most abundant volatiles in strawberries (Yan et al., 2018) and have been shown to correlate strongly with strawberry fruit liking (Fan et al., 2021). Whilst the scoring of odour desirability alone herein was only marginally significant, this association with overall fruit liking combined with the other changes reported herein, is likely to contribute to an overall improvement to fruit quality perception from the BC treatment. Accordingly, BC treatment may have resulted in changes to ester levels to enhance the sensory aroma properties of strawberry fruits, which is also reflected by M­IR profile changes over a narrow region. These outcomes address consumer concerns for losses in aroma associated with prioritisation of more profitable traits, by demonstrating that BC treatment increases both yield and aroma. Finally, fruit appearance, which includes colour (Crisosto et al., 2003) and damage (Jaeger et al., 2018), is a major impactor to consumer perception of quality and purchasing decision, as it is the first impression of a fruit. Biostimulant complex treat­ ment resulted in significant increases to the colour measures for red (p = 0.001) and green (p = 0.001) and reductions in orange (p = 0.006). Strawberry colour is conferred by the presence (amount and types) of anthocyanins, which have a strong pH­ colour relationship (Holcroft and Kader, 1999). The predominant anthocyanins in strawberry are pelargonidins and cyanidins (Andersen et al., 2004) which appear red at low pH and with increasing pH change to colourless, yellow, or blue forms which affects the overall appearance of the fruit (Holcroft and Kader, 1999). Whilst a marginally significant (p = 0.055) increase of 0.11 pH in diluted fruit extract was associated with the BC treatment, this degree of change is small relative to the change observed in Wang et al. (2015) wherein pH shifts of 1.0 were associated with noteworthy changes to colour. Accordingly, pH is l ikely not the driver of the observed changes in fruit colour, which may instead be attributed to changes in the concentrations or ratios of anthocyanins present (Yoshida et al., 2002). Nevertheless, strawberry colour is a driver of con­ sumer preference, as evidence by Wang et al. (2017) wherein an ‘ideal red’ colour was the preference for Wise et al. ‐ Biostimulant complex improves strawberry quality 57 fresh strawberry fruit, and by Wendin et al. (2019) which showed that red colour intensity had a signifi­ cant positive impact to consumer preference for woodland strawberries. These studies suggest that the increased red from BC treatment reported herein (Fig. 4B) for common garden strawberries may also be associated with increased consumer preference. Unlike organoleptic measures and colour features which are directly detectible by consumers and therefore impactful to quality perception and prefer­ ence, other properties such as nutritional and func­ tional food value should also be considered as targets for improvement during production and cultivation as their increased presence may benefit consumer health (Selby­Pham et al., 2017; Topolska et al., 2021). Due to the presence of many beneficial polyphenols and vitamins, strawberries are consid­ ered to be a functional food which can reduce hyper­ tension, postprandial oxidative stress, inflammation, and hyperglycaemia when consumed (Giampieri et al., 2015). Furthermore, agricultural practises such as fertiliser form (Tomic et al., 2016), cultivation system (D’evoli et al., 2010), and beneficial microbes (Rahman et al., 2019) have been shown to impact phytochemical profiles and antioxidant activities in strawberries. Accordingly, the results presented herein are similar to these observations, wherein altered cultivation conditions through application of the BC was shown to impact phytochemical concen­ trations which are associated with functional activity when consumed. Herein two methods were utilised to measure functional compounds in strawberry, and whilst the aluminium chloride method has relatively good speci­ ficity for flavonoid quantification (Mabry et al., 1970), the F­C method is a non­specific method, which quantifies total reducing capacities (antioxidant activ­ ity) rather than specific classes of compounds (Magalhães et al., 2008). Accordingly, the 32% increase (p = 0.029) in TP and unchanged (p = 0.534) flavonoid contents (Fig. 4D and 4E, respectively) reported herein indicates that the biostimulant treat­ ment increased the antioxidant activity of the fruits in the non­flavonoid portion of the phytochemical profile. Aaby et al. (2007) identified that the largest contributors to strawberry antioxidant activity were ascorbic acid, and the polyphenolics ellagitannins, and anthocyanins, which accounted for 24%, 19%, and 13% of strawberry antioxidant capacities, respec­ tively. Anthocyanins are also the class of compounds conferring the majority of strawberry colour (Yoshida et al., 2002), which also changed in response to the biostimulant application (Fig. 4B), discussed above. As noted, changes in anthocyanin concentrations or ratios may explain the changes in colour observed for biostimulant treated fruits, and changes to antho­ cyanins may also affect antioxidant activities of the fruit extracts (Cerezo et al., 2010). The distinguishing feature of anthocyanins, is their multiple aromatic rings with hydroxyl groups (phenolic) structure, derived from the flavylium ion (Khoo et al., 2017). Whilst the carbon bonds of these aromatic rings (C=C) and the hydroxyl groups (OH) are associated with IR absorption at 1654 cm­1 and 677 cm­1, and 3385 cm­1, respectively, the C­O bond connecting the hydroxyl to the aromatic ring is associated with wavenumber 1029 cm­1 (Wahyuningsih et al., 2017), which is contained within the range of wavenumbers (1024­1048 cm­1) identified herein as having increased from the BC treatment (Fig. 4H and S5). Accordingly, it appears that the BC treatment induced changes in the strawberry anthocyanin con­ tent or profile, which would be consistent with the changes observed for TP (Fig. 4D), colour (Fig. 4B), and M­IR spectra (Fig. 4G). Furthermore, the changes in TP (antioxidant activity) correspond with improved functional food potential of these fruits (Giampieri et al., 2015), which may impart greater health benefits than control strawberries when consumed. Implementation of this complex is therefore a promising improvement to strawberry cultivation practises and may be an additional tool available to farmers to improve yields and quality of produce for consumers. Biostimulants are an exciting development in agriculture which have the potential to improve crop yields and quality, whilst not requiring signifi­ cant time and money to substantially alter crop out­ puts, by contrast to alternative strategies such as genetic modification and selective breeding. However, species­specific efficacies of popular bios­ timulants even when applied to commonly grown food crops are often not well understood. Accordingly, this project characterised the impacts of a complex containing the biostimulants molasses, Aloe vera extract, and fish­hydrolysate when applied to strawberry in a hydroponic, environmental­con­ trolled growth system. 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