Standardization of bunch load in relation to juice quality in Manjari Medika grapevine grafted on Dogridge rootstock

Introduction

Grapes (Vitis vinifera L.) represent one of the most significant export-oriented fruit crops in the country, playing a crucial role in the international market owing to their exceptional flavor and premium quality. Cultivated across approximately 1.76 lakh hectares, annual grape production stands at 3896.40 tons (Anonymous, 2024) [2] . Grapes are globally recognized as a highly nutritious, refreshing and commercially favoured fruit crop (Kedage et al., 2007) [3] . In India, grape cultivation is predominant, with about 78% of the total production for table consumption, 17-20% processed into raisins and the remaining 2% utilized for juice and wine production (Somkuwar et al., 2020) [4,20] . Growing consumer health awareness has encouraged the development of grape processing industries to harness the fruit's health-promoting properties. Grapes exhibit beneficial effects in mitigating diabetes mellitus, cardiovascular disorders and digestive issues, attributed to their antioxidant, antimicrobial and anti-inflammatory properties (Imran et al., 2017) [7] . Both fresh grapes and dried forms (raisins) possess high antioxidant activity, with the majority of these compounds concentrated in the berry skin and seeds. Coloured grape varieties contribute more antioxidants due to their anthocyanin content, which imparts colour to the berries (Paun et al., 2022) [9] . A positive correlation has been reported between phenolic content and antioxidant activity (Khan et al., 2021) [8] . Vineyard yield and grape quality are significantly influenced by viticultural practices, particularly canopy management (Somkuwar et al., 2014a) [5,22] . Among these, bunch load management is a critical cultural practice, as it not only maintains and enhances productivity but also regulates the distribution of photo assimilates and the source-sink relationship between leaves and fruits, thereby balancing development and yield (Somkuwar et al., 2014) [5,22] . Excessive crop load can delay harvest and diminish fruit and wine quality (Sharma et al., 2018; Somkuwar et al., 2020) [10,4,20] .

Materials and Methods

The experiment was performed at the farm of ICAR National Research Centre for Grapes Pune during 2023-2025. Pune (18.32°N and 73.51°E) has warm and dry climate with temperature ranging from 20 to 28 °C. Sevenyear-old vines of Manjari Medika grafted onto Dogridge rootstock were selected for the study. The vines were planted in N-S direction with spacing of 3.0 × 1.83 m between the rows and vines with the vine density of 1815 vines per hectare. These vines were trained onto Y-trellises with four cordons in horizontal orientation and vertical shoot positions. The fruit pruning was done in first week of October during the years. Shoot thinning was done to maintain the canopy size before inflorescence emergence. Bunch thinning was completed after berry setting (at pea size) under each treatment. The bunch load was maintained by retaining 80, 70, 60, 50 and All bunches per vine (80-120 bunches/vine), respectively. The experiment was laid out in randomized block design (RBD) with five replications. Five vines were selected under each replication to record the observations. To study the effect of bunch load treatments on yield, quality, fruit compositions and biochemical constituents, bunches under each treatment were harvested on the same date. All bunch and berry observations were recorded at uniform level of total soluble solids (20-21 o Brix).

Yield and quality parameters

At harvest, data on yield and quality parameters such as average bunch weight, berry diameter, yield per vine, acidity, total soluble solids (TSS), juice recovery and phenological stages (days to veraison, colour development and harvest) were recorded. Average bunch weight was determined from five randomly selected healthy bunches per replication using a digital weighing balance and expressed in grams. Berry diameter was measured in millimeters using a Vernier caliper from ten berries collected across five bunches per vine. Yield per vine (kg) was calculated from the total bunch weight of five representative vines in each treatment. Acidity (%) was estimated by titrating 10 mL of juice, extracted from fifty berries, against 0.1 N NaOH using phenolphthalein as an indicator. Juice recovery (%) was determined by manually crushing destemmed berries in a sieve with a pestle (Dumas et al., 2020) [11] , weighing the extracted juice and expressing it as a percentage of fresh berry weight. The number of days to veraison, colour development and harvest (20 °Brix) were recorded from the date of fruit pruning and the mean values were calculated for each vine.

Biochemical parameters

The biochemical parameters were analysed in berries. The total carbohydrate content was estimated by Anthrone method (Hedge and Hofreiter, 1962) [13] , reducing sugar by DNSA method (Miller, 1959) [14] , the total phenolic content using Folin-Ciocalteu method (Singleton and Rossi, 1965) [15] , the protein content (Lowry et al., 1951) [16] , the proline content (Bates et al., 1973) [17] , the colour intensity (Glories, 1984) [18] and total anthocyanins (Lee, 2005) [19] .

Statistical Analysis

The experiment was conducted using a Randomized Block Design (RBD) with five bunch loads as treatments which were replicated five times. Data collected during the experiment was analyzed using the standard method of analysis of variance described by Panse and Sukhatme (1985) [12] .

Results and Discussion

Manjari Medika grapevine grafted on Dogridge rootstocks had significant effect on phenological stages (Table 1). During both the year and in pooled analysis, significantly minimum number of days taken for veraison, colour development and harvesting were recorded in vines with 50 bunches (76.26, 95.95 and 125.16 days, respectively) which was found significantly superior over all other treatments. It was followed by 60 bunches (79.83, 98.02 and 126.50 days, respectively) while, the maximum number of days taken for veraison, colour development and harvesting were observed in the all-bunches treatment (86.21, 103.68 and 139.30 days, respectively). The present study demonstrated that the minimum number of bunches per vine significantly reduced the days taken to veraison, colour development and harvesting while, retaining all bunches delayed veraison, colour development and harvesting in Manjari Medika grafted on Dogridge. Somkuwar et al., (2020) [4,20] reported that Manjari Naveen with higher bunch load took extra one week to attain veraison and harvesting. This aligns with reports that cluster or bunch thinning advances maturity and increased TSS and enhanced colour development by improving assimilate availability and canopy microclimate (Pastore et al., 2011; Petrie and Clingeleffer, 2006) [32,31] . Similar trends have been reported across cultivars and climates were reducing cluster load advanced ripening (higher TSS) which enabling earlier harvest in Chenin Blanc and Syrah (Somkuwar et al., 2018) [21] and in Tempranillo heavy loads slightly delayed harvest dates by ~3 days when LA: Y fell below 1 m² kg⁻¹ (Uriarte et al., 2016) [30] . The average bunch weight, berry diameter and yield was significantly influenced by the bunch load during both years of study and in pooled data ( [5,22] . Somkuwar et al., (2020) [4,20] [21,3]. [4,20] . Acidity in grape berries affected by crop load, vine vigor, canopy microclimate and water status. The reduced bunch load lowers titratable acidity (TA) and heavier crop loads maintain higher TA through slower ripening and greater malate retention (Somkuwar and Ramteke, 2006c; Somkuwar et al., 2020) [25,28,4,20] . Similar patterns are reported in Chenin Blanc and Syrah under tropical conditions where lower clusters increased TSS and reduced TA, with higher cluster loads elevating TA and must pH (Somkuwar et al., 2018) [21] . The sugar: acid ratio is a pivotal integrator of grape maturity and juice balance, rising as sugars accumulate and titratable acidity declines and it is strongly modulated by crop load and canopy-source dynamics across cultivars and climates (Somkuwar et al., 2018; Al-Saif et al., 2023) [21,26] . Similar crop-load benefits on TSS and acidity were reported in Chenin Blanc and Syrah, where reduced cluster number increased soluble solids, decreased TA and improved must composition, aligning with classic source-sink theory (Somkuwar et al., 2018) [21] . The juice pH was not significantly influenced by bunch load during both year and pooled data, as differences were statistically non-significant. However, juice recovery was significantly influenced by bunch load treatments (Table 4).

In pooled data, the maximum juice recovery was recorded in all bunch treatment (70.20%) which was followed by 70 bunches (68.88%) while, the least recovery was noted in 50 bunches per vine (60.35%). Juice recovery in grapes is strongly modulated by bunch load, berry size, skin to pulp ratio and associated compositional changes, with consistent evidence that higher bunch loads increase percent juice yield at the expense of solute concentration and berry mass, [25,28,21,4,20] . This trade-off aligns with increased cluster numbers elevate yield and juice volume per vine but dilute sugars and reduce average berry and bunch weight whereas thinning boosts TSS, sugar: acid ratio, phenolics, anthocyanins and colour, all of which correlate with lower juice percent due to thicker skins and denser cellular matrices (Uriarte et al., 2016; Wang et al., 2018) [30,33] . [25, 28, 5, 22] . Complementary studies by Somkuwar et al., (2020) [4,20] in Thompson Seedless for raisins also observed increasing total phenols, with higher bunch load. Similar patterns have been reported in Chenin Blanc and Syrah where lower cluster load increased soluble solids and berry carbohydrates (Somkuwar et al., 2018) [21] . The proline content in grape berries was significantly influenced by different bunch load levels during both years and in the pooled data (Table 6). In pooled analysis, the lowest proline accumulation was recorded in vines with 50 bunches per vine (2.50 µmol/) which was significantly superior to all other treatments. It was followed by 60 bunches (2.56 µmol/g) while, the highest value was observed in all bunches (3.21 µmol/g). Whereas, the maximum colour intensity anthocyanins were recorded in 50 bunches per vine (2.23% and 237.15 mg/100g respectively) which was significantly superior to all other treatments. It was followed by 60 bunches (2.08% and 232.20 mg/100g respectively) while, the lowest intensity was observed in the all-bunches treatment (1.46% and 235.26 mg/g respectively). Proline serves as an osmoprotectant and ROS scavenger thus, vines under higher metabolic or environmental stress often show greater proline in fruit tissues during late development (Jackson and Lombard, 1993) [29] . Lower crop load typically improves leaf area per fruit and light-air penetration, hastening ripening and phenolic development while moderating stress signaling which can depress proline biosynthesis or accumulation in berries (Somkuwar et al., 2018; Somkuwar et al., 2020) [21,4,20] . Colour intensity in grape berries is profoundly shaped by crop load mediated shifts in source: sink balance, canopy microclimate and phenolic biosynthesis, with consistent evidence that moderate thinning elevates colour metrics via enhanced anthocyanin and co-pigment accumulation while excessive loads depress them through delayed ripening and dilution effects (Somkuwar and Ramteke, 2006c; Somkuwar et al., 2020) [25,28,4,20] . Somkuwar et al., (2018) [21] and Wang et al., (2018) [33] reported that cluster thinning improves light interception and lowers canopy competition, accelerating veraison and colour development, while raising berry skin phenolics including total phenols and flavonoids that contribute to optical density and co-pigmentation. Anthocyanin accumulation in grape berries is strongly modulated by crop load, microclimate and hormonal cues, with bunch thinning at lower loads consistently elevating total anthocyanins and color intensity by improving source: sink balance and light exposure (Somkuwar et al., 2014) [5,22] . [4,20] . In Thompson Seedless, reducing sugar in raisins declined from 7.80 to 5.10 mg g -1 as bunch load increased from 50 to 125 clusters per vine (Somkuwar et al. 2020a) [4,20] .

Effect of different bunch load on organoleptic properties of Manjari Medika grapevine juice

The sensory evaluation of Manjari Medika grape juice from grapevines grafted on Dogridge rootstock showed that varying bunch load significantly impacted the overall sensory attributes, including colour, flavor, consistency, taste and overall acceptability during both the year and pooled data are graphically presented in Fig. 1. Among the different bunch load treatments, the juice from vines retained with 50 bunches per vine consistently received the highest scores across all sensory parameters in both 2023-24 and 2024-25 seasons as well as pooled data. Specifically, 50 bunches treatment recorded superior colour (7.8), flavor (8.8), consistency (8.5), taste (8.5) and overall acceptability (8.8). This suggests that moderate thinning of bunches enhances desirable sensory qualities likely due to improved ripening, higher sugar accumulation and better phenolic concentration enhancing flavor and mouthfeel. The 60 bunches treatment followed closely with good sensory acceptability highlighted that moderately reduced crop load balances yield and quality well. In contrast, the all-bunches treatment represented highest crop load which showed the lowest sensory ratings with colour (6.6), flavor (8.0), consistency (7.3), taste (7.2) and overall acceptability (7.6).

The moderate bunch load thinning (around 50-60 bunches per vine) significantly improved grape juice quality by enhancing sensory traits. This improvement is due to better ripening, sugar accumulation and phenolic content achieved by reducing competition among berries within the vine (Jackson and Lombard, 1993; Somkuwar et al., 2020) [29,4,20] . Excessive bunch load delays maturity, dilutes flavor compounds and reduces sensory quality (Reynolds et al., 2007). Thus, managing bunch load balances yield and sensory excellence by optimizing physiological and biochemical fruit attributes (Somkuwar and Ramteke, 2006) [25, 28] .

Conclusion

The study on Manjari Medika grapevines grafted to Dogridge rootstocks demonstrates that standardization of bunch load is critical for balancing yield and juice quality. Retention of 60-70 bunches per vine consistently resulted in superior berry weight, higher sugar and phenolic concentrations, improved organoleptic characteristics of the juice and accelerated berry maturity compared to all bunch treatment. While increasing bunch load boosts overall yield and juice recovery, but lower the berry quality parameters and overall acceptability. These findings emphasize that careful bunch load management produce quality grape juice and improve nutritional and market value of grape juice in Manjari Medika Grapevine.

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