Experimental farm and genotype selected

The aonla genotypes were planted at the farm of ICAR-CISH Lucknow, Uttar Pradesh during 2005. The site is located at 26°45′ N latitude and 80°30′ E longitude, at an elevation of 123 m above sea level. Field experiments were carried out in open-experimental fields for 2 consecutive years (2021–2022 and 2022–2023), utilizing a randomized block design with three replications, with the goal of identifying and characterizing aonla accessions for alkalinity tolerance, high yield and better fruit quality based on 2 years of data. Each genotype was represented by three plants and total number of plants was maintained at 33. Data on the morphological, quality and yield parameters were recorded in both the years of study and statistical analysis was done on the basis of 2 year mean data.

Eleven accessions i.e. CISH-A 1, CISH-A 2, CISH-A 3, CISH-A 4, CISH-A 13, CISH-A 15, CISH-A 17, CISH-A 19, CISH-A 27, CISH-A 31 (CISH-Aonla-2) and CISH-A 33 (CISH-Aonla-1) were taken for characterization and evaluation. These accessions were collected from different districts of the M.P., India. The genotypes and their respective area of origins are presented in Table 1. Grafted aonla trees of the above accessions were planted at a spacing of 8 m × 8 m and plants are maintains under cultural practices. Furthermore, observations on morphological, yield and biochemical attributes of aonla were recorded during winter season in the month of November (2nd fortnight). Standardized cultural practices were employed for all aonla trees throughout the experiment.

Table 1.

List of aonla genotypes and their corresponding source

The soil samples were collected from a depth of 25–35 cm in the experimental field before pit preparation. The soil's chemical properties were then measured according to AOAC guidelines (Reference AOAC2006). The experimental field soil had a pH of 7.73 ± 0.12, an EC of 0.16 ± 0.02 dS/m, organic carbon content of 0.72 ± 0.03%, available nitrogen (N) 271.60 ± 3.92 kg/ha, available phosphorus (P) 4.69 ± 1.10 kg/ha and available potassium (K) 189.55 ± 2.95 kg/ha, respectively. Besides, the soil was dominated by kankars (hand soil masses) of calcium carbonate and bicarbonate (Deshmukh, Reference Deshmukh2012).

Distinctness uniformity stability descriptors were used to record their consistent expression and stability throughout the duration of the study. Detailed descriptors for 19 attributes of aonla cultivar genotypes were examined, encompassing various aspects, i.e. growth habit, foliage, leaf size, leaf shape, leaf apex, leaf surface, trunk colour, branchlet colour, inflorescence colour, fruit surface, fruit shape and colour, fruit stalk, stem end, fruit-bearing tendency, stone size and shape, seed colour and harvest maturity (online Supplementary Table S1).

Chemicals and reagents

Sodium nitrite, sodium hydroxide and gallic acid were procured from Merck (India). Meta-phosphoric acid, 2,6-dichlorophenol, indophenol, Fehling's solutions ‘A’ and ‘B’, glucose, methylene blue indicator, potassium persulphate, Folin–Ciocalteu (FC) reagent, aluminium chloride, sodium bicarbonate, sodium chloride, boric acid, rutin trihydrate and sodium carbonate were purchased from Himedia (India). Water from a water purification instrument (Merck Millipore Academic, USA) was used for various analyses. All other chemicals are of analytical grade and were purchased from Rankem, Loba Chemie and Qualigens Fisher Scientific.

Yield and biochemical attributes of aonla

The collection of 12 fruits (three fruits from each direction, viz. east, west, north and south) from each replicated tree of genotypes was randomly harvested for assessing the average fruit weight. The fruit yield was recorded by harvesting the total fruits per tree and weighed. Additionally, 12 fresh fruit samples from each replicated tree of the genotypes were stored at 4°C for subsequent biochemical analysis. Each quantitative test was run three times.

Determination of total soluble solids and titratable acidity

Total soluble solids (TSS) content of aonla fruit pulp was measured by using a hand refractometer with a range of 0–32°B (Brix) (Bulo et al., Reference Bulo, Nimbolkar, Singh, Sahu, Wangchu, Das and Pandey2024).

Titratable acidity was determined by using Chandra et al.'s (Reference Chandra, Rawat, Singh, Khanduri and Riyal2020) method with 0.1 N NaOH solution using phenolphthalein as an indicator. The percentage titratable acidity was computed and reported as per cent citric acid equivalent using the following formula:

$${\eqalign{ &{\rm Acidity\;}( {\rm \% } ) \cr &= \displaystyle{{{\rm Titre}\;{\rm value\;}( {{\rm ml}} ) \times {\rm Normality}\;{\rm of}\;{\rm NaOH} \times 64 \times {\rm Volume}\;{\rm made}\;{\rm up\;}( {{\rm ml}} ) } \over {{\rm Aliquot\;}\;{\rm taken}( {{\rm ml}} ) \times {\rm Weight}\;{\rm of}\;{\rm sample\;}( {\rm g} ) \times 1000}} \cr & \times 100}}$$

Determination of ascorbic acid

To quantify vitamin ‘C’ (ascorbic acid), 5 g of sample fruit pulp was extracted into a 50 ml volumetric flask and diluted with 3% HPO₃ (metaphosphoric acid) solution (Yadav et al., Reference Yadav, Koley, Tripathi and Singh2019). A 5 ml sample was then titrated against a dye solution containing 2,6-dichlorophenol and indophenol. Pink colour appeared for at least 15 s, indicating the termination point (Poojan et al., Reference Poojan, Dwivedi, Pandey, Singh, Siddiqui, Pandey and Rajan2024). The ascorbic acid content was expressed in mg/100 g pulp of sample after calculation using the following formula:

$$\eqalign{ &{\rm Ascorbic}\;{\rm acid\;}( {{\rm mg}/100{\rm g\;pulp}} ) \cr & = \displaystyle{{{\rm Titre}\;{\rm value} \times {\rm Dye}\;{\rm factor} \times {\rm Volume}\;{\rm made}\;{\rm up}} \over {{\rm Aliquot}\;{\rm taken} \times {\rm Volume}\;{\rm of}\;{\rm sample}\;{\rm taken} \times 100}}}$$

Estimation of total sugars, reducing sugar and non-reducing sugar

The total sugar was determined using the phenol sulphuric acid method, with some modifications (Prajapati et al., Reference Prajapati, Nema and Rathore2011). Five grams of fruit pulp were extracted into a 100 ml volumetric flask and diluted with distilled water to keep the volume constant. A 0.8 ml of sample was taken, then added 0.2 ml of distilled water, 0.5 ml of phenol solution (10%) and 5 ml of concentrated sulphuric acid. The sample tube was placed in a water bath (30–35°C) for 20 min. Following that, the sample was measured using a spectrophotometer at 485 nm. The results were expressed as a percentage of glucose equivalents by using the following formula:

$$\eqalign{ &{\rm Total\;}\;{\rm sugar\;}( {\rm \% } ) \cr & = \displaystyle{{{\rm Conc}.\;{\rm of}\;{\rm std} \times {\rm dilution} \times 100 \times {\rm OD}\;{\rm value}\;{\rm of}\;{\rm sample}} \over {{\rm OD}\;{\rm of}\;{\rm std} \times {\rm Weight}\;{\rm of}\;{\rm sample}\;{\rm taken} \times 1000 \times 1000}}}$$

To determine the reducing sugars, 5 g of fruit pulp was extracted into a 100 ml volumetric flask and the volume was kept at 100 ml with distilled water. Five milligrams aliquot were placed in a conical flask, and 5 ml of Fehling's solutions ‘A’ and ‘B’ (Prajapati et al., Reference Prajapati, Nema and Rathore2011; Poojan et al., Reference Poojan, Dwivedi, Pandey, Singh, Siddiqui, Pandey and Rajan2024) were added and titrated against a 1.0% glucose (dextrose) solution in boiling water using methylene blue as an indicator. The appearance of light brick colour was designated as the endpoint. A blank sample was also titrated against 1% glucose (dextrose). The computation was performed using the following formula, and the results were expressed as a percentage of reducing sugars:

$${\eqalign{ &{\rm Reducing\;}\;{\rm Sugar\;}( {\rm \% } ) \cr & = \displaystyle{{{\rm Blank}\;{\rm titre\;}( {{\rm ml}} ) -{\rm Sample}\;{\rm titre\;}( {{\rm ml}} ) \times 0.0025 \times {\rm Volume\;}\;{\rm made}\;{\rm up\;}( {{\rm ml}} ) } \over {{\rm Aliquot}\;{\rm taken\;}( {{\rm ml}} ) \times {\rm Weight}\;{\rm of}\;{\rm sample\;}( {\rm g} ) }} \cr & \times 100}}$$

$${\rm Non}\hbox{-}{\rm reducing}\;{\rm sugar\;}( {\rm \% } ) = {\rm Total}\;{\rm sugar\;}( {\rm \% } ) -{\rm Reducing}\;{\rm sugar\;}( {\rm \% } ) $$

Estimation of total phenol content

The total phenol content was estimated by using FC's reagent technique with some modification (Saini et al., Reference Saini, Sharma, Kumar, Kumar and Singh2018; Poojan et al., Reference Poojan, Dwivedi, Pandey, Singh, Siddiqui, Pandey and Rajan2024). One gram fresh sample was used for estimation, and it was crushed in 10 ml of ethanol (80%) and 1 ml of HCl. Following that, the sample was centrifuged for 20 min at 10,000 rpm at 4°C and the supernatant was collected. Subsequently, 0.5 ml of 2 N Folin reagents was added to 2.9 ml of distilled water and 0.1 ml of sample (supernatant). A total of 2 ml of Na₂CO₃ solution were added to the sample solution after 3 min. After a while, the solution was allowed to turn blue-black in colour and was measured in a spectrophotometer at 760 nm wavelength. The results were expressed in mg of gallic acid equivalent (GAE)/g pulp.

Estimation of ferric reducing antioxidant power

The ferric reducing antioxidant power (FRAP) assay was performed following the method outlined by Shukla et al. (Reference Shukla, Kumar, Bhardwaj, Pandita, Patel, Thakur and Saxena2024) and Poojan et al. (Reference Poojan, Dwivedi, Pandey, Singh, Siddiqui, Pandey and Rajan2024), with slight modifications. The FRAP solution was prepared by mixing 300 mM acetate buffer (pH 3.6), 20 mM TPTZ solution (in 40 mM HCl) and 20 mM FeCl₃ (in water) in a 10:1:1 ratio. This solution was then reacted with the samples or standard (10.000 mg/ml) at a 1:30 ratio and incubated in the dark for 30 min at 37°C. The resulting blue complex (ferrous tripyridyltriazine) was measured at 593 nm wave length using a spectrophotometer, and the results were expressed as mg/g of ferrous sulphate.

Statistical analysis

All analytical tests were conducted three times, and the findings were calculated as mean ± SD. Data from both of the studies of successive years were combined. One-way analysis of variance and post-hoc analysis using Duncan's multiple range tests (P ≤ 0.05) were used in SPSS 16.0 (SPSS Corporation, Chicago, IL) to assess the significance of the data, particularly the results of various morphological and biochemical parameters of aonla sample collected from experimental fields. The association between related components was ascertained using correlation analysis at the significance level (P ≤ 0.05). Principal component analysis (PCA) and dendrogram were used to determine the overall morpho-biochemical variability among the genotypes by using SRPLOT software.