Fruit Quality Evaluation Research Articles

​Process Optimisation and Quality Evaluation of Passion Fruit and Pineapple based Probiotic Drink

Background: The functions of food has extended from satisfying hunger and providing nutrients to the body, health maintenance, well being and prevention of diseases. Probiotics are such functional food and when they are incorporated to locally available foods, it helps to improve the nutritional profile and therapeutic value. Hence, the study entitled “Process optimisation and quality evaluation of passion fruit and pineapple probiotic drink” was undertaken with the objective of standardising probiotic fruit drink with passion fruit and pineapple and also to evaluate the nutritional and organoleptic qualities of these developed passion fruit and pineapple probiotic drinks. Methods: In the present study 5 treatments along with one control with 3 replications were standardized. Passion fruit juice (PFJ) was used as the major ingredient and used in varying proportions starting from 50 to 90 per cent with 10 to 50 per cent of pineapple juice (PJ). The best treatment was selected through sensory evaluation along with control by using a score card with nine point hedonic scale. In the selected treatments optimization for the growth of Lactobacillus acidophilus with regard to substrate concentration, time of incubation, temperature of incubation and inoculum concentration were done. The probiotic drinks and their respective controls were then analysed for their nutrient composition like TSS, titratable acidity, energy and ascorbic acid. Result: Among the various treatments, highest scores for organoleptic qualities was observed in treatment having 70 per cent passion fruit juice and 30 per cent pineapple juice (T3) with a mean score of 8.52 for overall acceptability. The selected juice was optimized for the growth of Lactobacillus acidophilus and had a viable count of 13.38 log cfu ml-1. The probiotic and non probiotic drinks had TSS content of 12.8 and 13.5° Brix, titratable acidity of 2.28 and 2.03 per cent, energy of 59.32 and 68.96 Kcal and ascorbic acid of 10 and 12.8 mg 100g-1 respectively.

Optimization of flaxseed cake pectin extraction and Shelf-life prediction model for pear fruits preserved by pectin edible coating

The aim of this study was the possibility of pectin flaxseed cake extraction by using organic and mineral acids, and improves the edible coating formation from flaxseeds pectin and sodium alginate (1%) for pear fruits. Pectin characterization ( Equivalent Weight, Methoxyl Content, Total anhydrouronic acid content and Degree of Esterification) was estimated, also characterized according to their fingerprint from the FT-IR spectroscopy whether flaxseed pectin extracted by citric and hydrochloric acid ( FPE1 and FPE2, respectively). The substance used in these experimented were the pear fruits coated with pectin extraction by citric and hydrochloric acid (CEP1 and CPE2, respectively) compared with uncoated fruits. The effect of edible coating on quality attributes of fruits storage at 4±1°C and relative humidity of 90-95% was determined. The shelf-life of pear fruits was determined by using different mathematical analyses such as statistical and kinetics models. The results of this study demonstrated that the beast edible coating of pear fruit was CEP2 followed by samples CEP1 as compared with uncoated fruits. The fruit quality evaluation revealed that the coating treatments were more effective in retention of the weight, antioxidant activity and total anthocyanins content in pear fruits during storage periods. Pear fruits coated with pectin extraction two (CEP2) retains an acceptability consumption for a longer period than other tested fruits, and the pear fruit's quality was maintained for 28.75 and 52.65 days for CEP1 and CEP2, respectively. Finally, it was evident from results the incorporation of flaxseed pectin with an edible coating solution improved the quality of fruits and antioxidant stability

Is the Consumer Ready for Innovative Fruit Wines? Perception and Acceptability of Young Consumers.

The consumption of traditional wine has decreased in Europe during the last fifteen years. In parallel, new wine alternatives obtained by blending wines and fruit juices or by flavoring wines with artificial or natural flavors have appeared on the market. Recently, an innovative fruit wine obtained by co-fermentation of grape must and kiwi juice has been proposed and its potential of attraction for consumers should be exploited. To assess the potential consumer acceptability and expectations towards this new product, an online choice experiment has been conducted involving a consumer group of young adults (18–35 years old; n = 373). After the data collection, participants were divided into two groups according to whether they had already tasted a fruit wine (neophiles) or had never tasted it (new entries). For each group, the individual’s responses (on wine consumption habits, expectations and willingness to consume and pay a fruit wine) were analyzed through Principal Component Analysis. Different consumption styles and expectation patterns were defined in the two groups. However, in general, neophiles showed consumption patterns based on the evaluation of fruit quality, sales format, alcoholic content and the presence or not of bubbles, not giving importance to the brand. In contrast, new entries’ responses identified consumption patterns driven by the willingness to pay for a new product, the product value for money and packaging features. Differences between the two groups in expectations about the product sensory characteristics also emerged. These findings should contribute to this area of study by integrating environmental, economic and social dimensions and addressing food innovation and sustainability in the fruit and wine chains.

Fruit Scar Incidence and Its Effect on Guava ‘Kristal’ Fruit Quality (Psidium guajava L.) at Low- and Middle-altitude Orchards in Bogor, Indonesia

Information on scar incidence and its effect on fruit quality of ‘Kristal’ guava (Psidium guajava L.) grown on different altitudes is currently limited. The aim of this study was to evaluate the fruit scar incidence and fruit quality of 'Kristal' guava var. grown on low- and middle-altitude orchards. The research was conducted by collecting 50 samples of fruit harvested from each orchard from January to June 2019. Fruit quality evaluation was carried out at Postharvest Laboratory, Department of the Agronomy and Horticulture, IPB University, whereas scarring pest observation was conducted at Insect Biosystematics Laboratory, Department of Plant Protection, IPB University. Our results showed that the low-altitude orchard produced more fruits with medium, high, and very high scar intensity, while the middle-altitude orchard produced more fruits with low and very low scar intensity. Fruit scar was caused by fruit scarring pests, especially thrips and mites. Fruit tissue damage only occurred on the epidermis of fruit pericarps where the tissue turned brownish and thickened. Additionally, there was no expansion of the damage into the pulp. The peel damage did not affect the fruit taste as indicated in the level of total soluble solids (TSS), titratable acidity (TA), TSS/TA ratio, vitamin C, and total flavonoids content. Fruit external quality was varied in response to altitude, where middle-altitude orchard produced a heavier, a bigger and a lower fruit softness than low-altitude ones. Present findings could be the baseline information for determine the best growth site and adjustment of pest control to maintain fruit quality.

Postharvest Storage Techniques and Quality Evaluation of Fruits and Vegetables for Reducing Food Loss

Fresh fruits and vegetables have always made an important contribution to the human diet [...]

Smart fingertip sensor for food quality control: Fruit maturity assessment with a magnetic device

Automated technologies for quality inspection of fruits have attracted great interest in the food industry. The development of nondestructive mechanisms to assess the quality of individual fruit prior to sale may lead to an increase in overall product quality, value, and consequently, producer competitiveness. However, the existing methods have limitations. Herein, a texture sensor based on highly sensitive hair-like cilia receptors, to allow a quick quality evaluation of fruit is proposed. The texture sensor consists of up to 100 magnetized nanocomposite cilia attached to a chip with magnetoresistive sensors in a full Wheatstone bridge architecture. In this paper we demonstrate the use of ciliary sensors in scanning fruits (blueberries and strawberries) in different maturation stages. The contact of the cilia with the fruit skin provided qualitative information about its texture in terms of ripeness stage. Less mature fruits exhibited, on average, a highest peak voltage of 0.14 mV for blueberries and 0.12 mV for strawberries, while overripe fruits exhibited 0.58 mV and 0.56 mV, respectively. The results were confirmed by sensorial assessment of the fruit freshness, and therefore attesting the application potential of the sensing technology for fruit quality control.

Automatic procedure to contactless and non-destructive quality evaluation of fruits and vegetables through a computer vision system

Automatic procedure to contactless and non-destructive quality evaluation of fruits and vegetables through a computer vision system

Non-destructive methods for fruit quality evaluation

This work studies the evolution in time of several varieties of apples with application in quality storage maintenance. Two different methods were used to evaluate long-stored apples for better sorting and degradation assessment. The first method was laser photoacoustic spectroscopy for the detection of ethylene and ethanol compounds from the internal atmosphere of apples. The second method was multispectral imaging that measures the image and the spectrum combined and also can be used to address features such as ripening and external defects. The experiments showed that, the ethylene value decreases and the value of ethanol increases, which sometimes we may associate with a drift of the images toward darker tones, because the apple is slowly degrading. Non-invasive, real-time inspection can reveal when the degradation process begins, improving the capability of sorting, maintaining their quality and storability.

Physico-chemical quality and sensory evaluation of pummelo fruit as influenced by potassium fertilization

This study aimed to determine the influence of potassium (K) fertilization on the physico-chemical and sensory qualities of ‘Magallanes’ pummelo [Citrus maxima (Burm. Ex Rumph.) Merr.] fruit. The field experiment was conducted for 12 months at South Davao Corporation (SODACO) farm in Davao City. Five treatments with increasing K levels were applied per tree: control, no K, 150g K basal, 225g K basal, and 225g K basal + foliar application. The fruit physico-chemical qualities and sensory attributes were analyzed the following harvest. Data were analyzed using analysis of variance and honest significance difference tests. Application of 225g K rates positively influenced the fruit quality but not the sensory attributes of pummelo. Fruit pulp diameter increased by 36% while peel thickness decreased by 29-75%. An increase of 39% juice weight per fruit was obtained in 150g K. The yield of juice per tree increased up to 11 times with 225g K level. The 225g K rates also increased juice pH by 8-12%, titrable acidity by 9 times, and total soluble solids per tree by 6 times than no application. The application of 225g K basal + foliar resulted to higher fruit weight, TA, and TSS in pummelo fruit. The results of the study indicated the important role of K in improving the fruit physico-chemical qualities in ‘Magallanes’ pummelo.

Classification and Grading of Multiple Varieties of Apple Fruit

Fruit safety plays an important role in the economy of the world for the agriculture field. Recently, it has been noticed that fruits are affected by various diseases. This creates economic failure in the agriculture field across the world. The manual investigation of multiple varieties of an apple fruit is a burdensome task that can be minimized for quality evaluation for fresh and rotten fruits using automatic computerized methods. In this work, a novel method is implemented for multiple varieties of apple fruit quality evaluation. The six different varieties of apples i.e. Fuji, York, Golden Delicious, Red Delicious, Granny Smith, and Jonagold are used for image acquisition. Firstly, images are segmented by the grab-cut method and fuzzy c-means clustering. Secondly, multiple features statistical, textural, geometrical, discrete wavelet transform, a histogram of the oriented gradient, and Laws’ texture energy are extracted and selected by principal component analysis from the feature space. Lastly, the classification of fresh and rotten apples is done by applying k-NN, LR, SRC, and SVM classifiers. The cross-validation technique with distinct values of k is used to validate the performance of the system. The proposed method achieves 92.90% (k = 5), 98.42% (k = 10), and 95.27% (k = 15) accuracy by SVM classifier. It has been seen that the extraction of proper features and selection of features results in upgraded performance. Also, the state of the art techniques are comparable with the proposed algorithm showing the probability to use for multiple fruits.

Sensor coating employed to preliminarily evaluate the banana ripeness

Herein, a new Schiff-base interaction coating material for fruit preservation and sensing was successfully fabricated. The new material was characterized by Fourier transform infrared (FTIR) spectra, contact angle (CA), 3-D reconstruction, and so on. Combined with the gas barrier performance and the evaluation of fruit quality, including weight loss, firmness, and iodine-starch-system test; CD-0 (coating fabricated with Chitosan and dialdehyde starch) film and CD-0.4 film could delay fruit ripening effectively. Cracks caused by volatilel-menthol crystals in CD-0.1 and CD-0.2 coatings accelerated physiological activities of banana. Trend in electromechanical performance monitored by CD-Al sensor were consistent with the respiration rate and ethylene production. Therefore, the CD-0 film and coatings containingl-menthol is not only an excellent material to extend the shelf-time of banana but also a sensing material to construct CD-Al sensor. This type of gas-film-Al sensor provides a promising approach for low-cost and portable sensing devices.

Eleven-year Correlation of Physical Fruit Texture Traits between Computerized Penetrometers and Sensory Assessment in an Apple Breeding Program

Fruit texture is a major target of apple (Malus domestica) breeding programs due to its influence on consumer preference. This multitrait feature is typically rated using sensory assessment, which is subjective and prone to biases. Instrumental measurements have predominantly targeted firmness of the outer region of fruit cortex using industry standard Magness–Taylor-type penetrometers, while other metrics remain largely unused. Additionally, there have been limited reports on correlating sensory attributes with instrumental metrics on many diverse apple selections. This report is the first to correlate multiyear historical fruit texture information of instrumental metrics and sensory assessment in an apple breeding program. Through 11 years of routine fruit quality evaluation at the Washington State University apple breeding program, physical textural data of 84,552 fruit acquired from computerized penetrometers were correlated with sensory assessment. Correlations among various instrumental metrics are high (0.63 ≤ r ≤ 1.00; P < 0.0001). In correlating instrumental outputs with sensory data, there is a significant correlation (r = 0.43; P < 0.0001) between the instrumental crispness value and sensory crispness. Additionally, instrumental hardness traits are significantly correlated (0.61 ≤ r ≤ 0.69; P < 0.0001) with sensory hardness. Outputs from two versions of computerized penetrometers were tested and shown to have no statistical differences. Overall, this report demonstrates potential use of instrumental metrics as firmness and crispness estimates for selecting apples of diverse backgrounds in a breeding program. However, in testing a large number and diversity of fruit, experimenters should perform data curation and account for lower limits/thresholds of the instrument.

Nondestructive identification of pesticide residues on the Hami melon surface using deep feature fusion by Vis/NIR spectroscopy and 1D‐CNN

AbstractNondestructive identification of pesticide residues remains a challenge in terms of fruit safety assessment. In this study, a novel method based on visible/near‐infrared (Vis/NIR) spectroscopy (348.45–1,141.34 nm) combined with deep feature fusion was proposed, achieving nondestructive identification of pesticide residues on the Hami melon surface. The spectra of Hami melons with clear water and three kinds of pesticide residues (chlorothalonil, imidacloprid, and pyraclostrobin) were collected in the diffuse reflectance mode. The one‐dimensional convolutional neural network (1D‐CNN), with increased width and depth through parallel convolution modules and concatenate layers, was presented to capture multiple deep features from Vis/NIR spectra and fuse them. This model had a better performance for four‐class identification as the accuracy of 95.83%, and outperformed other CNN models and conventional approaches (partial least squares discriminant analysis and support vector machine). Moreover, the proposed 1D‐CNN model could accurately differentiate whether there were pesticide residues with the identification accuracy as 99.17%. However, the prediction of imidacloprid and pyraclostrobin residues was not accurate due to the similar spectral features. The overall studies indicated that the 1D‐CNN model with deep feature fusion looked promising for nondestructive identification of pesticide residues on the Hami melon surface based on Vis/NIR spectroscopy.Practical applicationsVisible and near‐infrared (Vis/NIR) spectroscopy, as a nondestructive technique, looks promising for evaluation of fruit quality and safety. One‐dimensional convolutional neural network, with deep feature fusion structure to capture multi‐scale spectral information, has a better identification of pesticide residues on the Hami melon surface. Vis/NIR spectroscopy with deep feature fusion can be applied in research and development of a nondestructive detector for pesticide residues on the thick‐skinned fruit surface in the future.

Pawpaw Hybrid Genotypes (Asimina triloba (L.) Dunal) Cultivated in the Bucharest Area

Pawpaw or Northern banana (Asimina triloba (L.) Dunal) is the only representative of the Annonaceae family that can be cultivated in temperate areas. The increasing demands from the consumers for this nearly unknown fruit with high nutraceutical potential require specific researches. The aim of this study is to present the fruits pomological characteristics for 23 genotypes analyzed, cultivated in the Bucharest area. For each genotype yield, fruit size, average number of seeds per fruit, average weight of seeds and seeds size were measured. Fruit biochemical analyses as dry matter, total soluble solids, ascorbic acid content, acidity, were done for several genotypes. Fruit quality evaluation through sensorial analyses was conducted for 13 genotypes. The most valuable genotypes from the Experimental field according to the analyses performed and the consumer’s preferences are taken in consideration for further research.

Rapid Field Assay for Pineapple Fruit Acidity

The sugar-to-acid ratio of pineapple (Ananas comosus L.) contributes toward giving the fruit its unique flavor. This ratio is an important indicator of both commercial and organoleptic ripeness, and it is useful in determining a harvest date. Citric acid is the major acid in pineapple and usually is determined by titration to a specific pH endpoint, while sugars are determined as total soluble solids by refractometry. Both acid and sugar levels vary with the season in the year-round production cycle. Acid titration is slow and difficult to perform in the field. A digital acidity meter based upon diluted juice conductivity was evaluated for potential field use. The readings obtained from the meter varied with clone and fruit potassium concentration. The meter had utility for field use to evaluate fruit quality and harvest date. Because fruit potassium levels can vary between harvests, the meter should be recalibrated on a regular schedule to adjust for potential crop management and seasonal effects.

Estimation Method of Soluble Solid Content in Peach Based on Deep Features of Hyperspectral Imagery.

Soluble solids content (SSC) is one of the important components for evaluating fruit quality. The rapid development of hyperspectral imagery provides an efficient method for non-destructive detection of SSC. Previous studies have shown that the internal quality evaluation of fruits based on spectral information features achieves better results. However, the lack of comprehensive features limits the accurate estimation of fruit quality. Therefore, the deep learning theory is applied to the estimation of the soluble solid content of peaches, a method for estimating the SSC of fresh peaches based on the deep features of the hyperspectral image fusion information is proposed, and the estimation models of different neural network structures are designed based on the stack autoencoder–random forest (SAE-RF). The results show that the accuracy of the model based on the deep features of the fusion information of hyperspectral imagery is higher than that of the model based on spectral features or image features alone. In addition, the SAE-RF model based on the 1237-650-310-130 network structure has the best prediction effect (R2 = 0.9184, RMSE = 0.6693). Our research shows that the proposed method can improve the estimation accuracy of the soluble solid content of fresh peaches, which provides a theoretical basis for the non-destructive detection of other components of fresh peaches.

Optimal irrigation and fertilizer amounts based on multi-level fuzzy comprehensive evaluation of yield, growth and fruit quality on cherry tomato

The accurate and efficient management of irrigation and fertilizer is essential for the effective intensive production of greenhouse cherry tomato. In this study, we evaluated the effects of irrigation and fertilizer combinations on yield, growth, and nutritional and taste quality of cherry tomato. More specifically, we applied a quadratic orthogonal rotation combination design with four experimental factors at five levels (-1.68, -1, 0, 1, 1.68) for a total of 23 treatments over two consecutive growing seasons in 2018. A multi-level fuzzy comprehensive evaluation (MFCE) was constructed, including four factors and 14 subfactors, as well as a water and fertilizer multi-factor regulation model for the integrated growth of cherry tomato. Single experimental factor effects included irrigation in the spring season (2018S), with the other experimental factors following a downward opening parabola with integrated cherry tomato growth for both seasons. The integrated growth increased with irrigation, and exhibited a rise and subsequent fall with phosphate (P2O5) and potash (K2O) in 2018S, as well as with irrigation and nitrogen (N) levels in the fall season (2018 F). The experimental factor interaction values of 1.68 for irrigation (1978.0 m3/ha), 0.94 for N (482.2 kg/ha), -0.69 for P2O5 (104.4 kg/ha) and -0.65 for K2O (181.3 kg/ha) were observed to be optimal for the integrated growth of cherry tomato in 2018S. The corresponding combination for 2018 F was determined as 0.70 for irrigation (1082.9 m3/ha), 0.51 for N (287.9 kg/ha), 0 for P2O5 (126.5 kg/ha) and -0.41 for K2O (159.7 kg/ha). Furthermore, the irrigation, N, P2O5, and K2O intervals that maximized cherry tomato growth over the two seasons were as follows: i) 1780.2–1978.0 m3/ha, 434.0–482.2 kg/ha, 94.0–104.4 kg/ha, and 163.2–181.3 kg/ha for 2018S; and 974.6–1082.9 m3/ha, 259.1–287.9 kg/ha, 113.9–126.5 kg/ha and 143.7–159.7 kg/ha for 2018 F, respectively. Comprehensively understanding the growth of cherry tomato can potentially enhance cherry tomato production in the arid regions of northwestern China.

Prediction of Fruit Free Amino Acids by Foliar Nutrient Diagnosis in Longan (Dimocarpus longan Lour.)

Free amino acid (FAA) profile is an important indicator of the quality of fruit and fruit product. Foliar nutrient diagnosis has been used for crop yield prediction for decades but not for fruit quality evaluation. Concentrations of 11 leaf nutrients including N, P, K, Ca, Mg, S, Fe, Mn, Cu, Zn, and B at stages of terminal shoot maturation and fruit development and fruit FAA profile at harvest were examined in longan in South China. The relation between leaf nutrient and fruit FAA was then investigated by multiple stepwise regression analysis. Foliar N content was greatest among the nutrients among the detected elements at both stages. Twenty-nine FAAs were determined in longan flesh, with alanine (19.9%), γ-aminobutyric acid (17.5%), glutamic acid (15.2%), and asparagine (10.7%) as the main components. Flesh individual FAA, essential amino acid (AA), umami-, and sweet and bitter taste AA strongly depended on foliar nutrients. However, the relation between flesh FAAs and foliar nutrients varied with FAA species. Leaf N was the dominant indicator for most pulp FAAs at two growth stages, while other nutrients (e.g., B, Zn, P, K, Ca, Mg) also played versatile roles on flesh FAAs. This work provides a novel tool to predict fruit FAAs via foliar nutrient diagnosis, which supports the practicality of producing specific target fruit or improving fruit quality through regulation of fertilization strategies in fruit production.

Non-destructive assessment of flesh firmness and dietary antioxidants of greenhouse-grown tomato (Solanum lycopersicum L.) at different fruit maturity stages.

Non-destructive methods have been widely recognized for evaluating fruit quality traits of many horticultural crops and food processing industry. Destructive (analytical) test, and non-destructive evaluation of the quality traits were investigated and compared for ‘Red Rose’ tomato (Solanum lycopersicum L.) fruit grown under protected environment. Fresh tomato fruit at five distinctive maturity stages namely; breaker (BK), turning (TG), pink (PK), light-red (LR), and red (RD) were labeled and scanned using the handheld near infra-red (NIR) enhanced spectrometer at a wavelength range of 285–1200 nm. The labeled tomato samples were then measured analytically for flesh firmness, lycopene, β-carotene, total phenolic content (TPC) and total flavonoids content (TFC). The results revealed that quality traits could be estimated using NIR spectroscopy with a relatively high coefficient of determination (R2): 0.834 for total phenolic content, 0.864 for lycopene, 0.790 for total flavonoid content, 0.708 for β-carotene; and 0.679 for flesh firmness. The accumulation of Lyco and β-Car rapidly increased in tomatoes harvested between the TG and the LR maturity stages. Harvesting tomatoes at BK maturity stage resulted in significantly higher flesh firmness than harvesting at the later maturity stages. Tomato fruits had the lowest TPC and TFC contents at the earliest maturity stage (BK), while they had intermediate TPC and TFC levels at LR and RD maturity stages. NIR spectroscopic measurements of fruit firmness and lipophilic antioxidants in tomato fruit at various maturity stages were partially in accordance with those estimated by destructive (analytical) methods. Based on these findings, we recommend using non-destructive NIR spectroscopy as an effective tool for predicting tomato fruit quality during harvest stage and postharvest processing.

Multivariate Cherry Quality Assessment Using Morphological, Biochemical and Volatile Compound Traits

ABSTRACT This study was carried out to evaluate fruit quality of five sweet cherry cultivars grown in Morocco, namely, Burlat, Van, Cerisette, Napoleon and Coeur de pigeon. Significant differences (p˂0.05) were observed across the five cultivars in fruit weight (5.24–8.72 g), geometric mean diameter (14.22–16.36 mm), pH (3.48–4.12), soluble solid content (17.70–24.50 °Brix), total phenolics (426.44–485.69 mg GAE/100 g fresh weight (fw)), total proanthocyanidins (51.17–131.20 mg CE/100 g fw) and total anthocyanins (194.53–267.67 mg cya-3-glu/100 g fw). The antioxidant activity was evaluated by three assays. The values were 11.96–21.04, 16.48–63.96 and 9.62–15.65 mmol TE/g for DPPH scavenging test, FRAP and ABTS, respectively. Volatile compounds were identified and semi-quantified in sweet cherry fruit using solid-phase microextraction in combination with gas chromatography/mass spectrometry (SPME-GC/MS). Nine volatile compounds (benzaldehyde, nonanal, ethyl hexanoate, ethyl octanoate, γ-terpinene, β-pinene, limonene, linalool and 2-ethyl-1-hexanol) were detected in all sweet cherry cultivars. Aldehydes compounds were the most abundant in sweet cherry aroma, followed by terpenes and esters. Correlation between all parameters showed varying trends.