Relationship between Sensory Attributes and Chemical Composition

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Chemistry and Biology of Aroma and Taste

The Relationship between Sensory Attributes and Chemical Composition of Different Mango Cultivars Jeehye Sung, Joon Hyuk Suh, Alan H Chambers, Jonathan Crane, and Yu Wang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.9b01018 • Publication Date (Web): 12 Apr 2019 Downloaded from http://pubs.acs.org on April 15, 2019

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Journal of Agricultural and Food Chemistry

The Relationship between Sensory Attributes and Chemical Composition of Different Mango Cultivars

Jeehye Sung†, Joon Hyuk Suh, Alan H. Chambers‡, Jonathan Crane‡, Yu Wang*†

† Department

of Food Science and Human Nutrition, Citrus Research and Education Center,

University of Florida, 700 Experiment Station Rd, Lake Alfred, FL 33850, USA ‡Tropical

Research and Education Center, University of Florida, IFAS, 18905 SW 280 St.,

Homestead, FL 33031, USA

*Corresponding Author: Yu Wang, Ph.D. Department of Food Science and Human Nutrition Citrus Research and Education Center University of Florida 700 Experiment Station Rd, Lake Alfred, FL 33850 USA Tel: +1-863-956-8673

E-mail: [email protected]

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ACS Paragon Plus Environment


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Abstract

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The present study investigated the relationship between the chemical composition and

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sensory quality of different mango (Mangifera indica L.) cultivars by multivariate statistical

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analysis. The results showed that the high hedonic rating of mango was due in part to its flavor

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profile such as fruity, pineapple, and coconut with sweetness. High hedonic liking and positive

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flavors of mango could be responsible for the volatile compounds including fruity esters, 1-

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octanol, (E,Z)-2,6-nonadienal and γ-octalactone with high contents of sugars. On the other hand,

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turpentine-like and green flavors of mangoes are attributed to the relatively low hedonic liking

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of mango, which correlated with high contents of amino acids and terpenes. These findings

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demonstrated that interaction between individual chemical compounds within mango could be

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responsible for the specific sensory qualities of mango cultivars provided insight into a

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paradigm for the selection and development of new and more desirable mango cultivars in the

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future.

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KEYWORDS: mango, sensory, flavor, LC-MS/MS, SPME-GC/MS, multivariate analysis

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INTRODUCTION

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Mango (Mangifera indica L.) ranks fifth in world-wide production (55.6 million tones)

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after banana, apple, grapes, and oranges from Food and Agriculture Organization of the United

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Nations FAOSTAT database for 2019.1 As one of the most popular fruits, mango is consumed

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fresh, juiced, dried, or processed into candies and deserts. The distinctive flavor of mango has

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led to continued consumer growth in the consumption of mango fruit.2 A balanced combination

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of sweet taste and pleasant aroma can be the major characteristics contributing to the sensory

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appeal of mango fruits.3-4 The sugars and acids are associated with the sweetness variation, as

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well as the perception of mango flavor attributes.5 In addition, numerous studies have reported

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that hexanal, (E)-2-hexenal, ethyl butanoate, (E,Z)-2,6-nonadienal, (E)-2-nonenal, decanal, δ-

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3-carene, γ-terpinene, (Z)-β-ocimene, and terpinolene are characteristic aroma compounds in

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mango fruits.6-8 Although the diverse chemical composition including sugars, acids, and

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volatile flavor compounds might have an influence on hedonic sensory perception of mango,

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the impact of these compounds on sensory properties of the fruit still has not yet been described.

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The palatability of fruit can bebetter understood by examining characteristic

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components involved in the flavor attributes. Many of the most important flavor-associated

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volatile compounds in fruits are derived from sugars, organic acids, and amino acids.9-10 The

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unique flavor profile of mango might also be generated by integration of multiple sugars and

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acids with their volatile emission. It is assumed that the chemical composition of mango plays

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a critical role in sensory acceptability. Therefore, understanding the relationships between

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mango chemical composition and flavor profiles is needed to elucidate the flavor chemistry of

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mango fruits. Recent studies have suggested that an omics approach in flavor research is a good

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strategy to elucidate the major sensory elicitors of tastes and aromas, which contribute to the 3



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sensory descriptors and hedonic perception of this fruit. These tastes and aromas are derived

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from the various chemical components such as sugars, organic acids, amino acids and volatile

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compounds.11-13

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Many previous studies have only included single mango cultivars when investigating

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fruit quality.2, 4-5, 7, 14 While this can provide essential data, comparing multiple cultivars allows

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for greater separation of traits that might be linked to consumer liking. Additionally, fruit

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quality can be significantly impacted by growing environment, and, therefore, understanding

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fruit quality for mangoes grown in southern Florida is important for the domestic industry.

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Finally, understanding mango fruit quality at the cultivar level is essential for recommending

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superior types for premium markets and for the development of new, high-quality mango

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cultivars. Therefore, the objectives of this study were (1) to determine the hedonic perception

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and flavor attributes of three mango cultivars by consumers and trained sensory panels, (2) to

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estimate the chemical composition of mango fruits by targeted analysis of sugars, organic acids,

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amino acids, and volatiles, and (3) to investigate the influence of mango flavor-associated

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chemical composition on the hedonic perception by multivariate statistical analysis.

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MATERIALS AND METHODS

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Chemicals. Volatile chemical reference standards (octyl butyrate, ethyl acetate, 2-

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methylbutyraldehyde, ethyl propionate, methyl butanoate, α-pinene, ethyl butanoate,

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camphene, ethyl-3-methylbutanoate, hexanal, δ-3-carene, α-pellandrene, α-terpinene, β-

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myrcene, limonene, (E)-2-hexenal, γ-terpinene, (Z)-β-ocimene, p-cymene, terpinolene, octanal,

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(Z)-3-hexenyl acetate, 1-hexanol, (Z)-3-hexenol, nonanal, n-hexyl butanoate, (E)-2-octenal,

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p,α-Dimethylstyrene, ethyl octanoate, (E)-3-hexenyl butanoate, decanal, α-gurjunene, ethyl 34


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hydroxybutanoate, benzaldehyde, (E)-2-nonenal, linalool, 1-octanol, β-caryophyllene, (E,Z)-

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2,6-nonadienal, α-caryophyllene, ethyl phenylacetate, and γ-octalactone) and non-volatile

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chemical reference standards (sucrose, fructose, glucose, raffinose, myoinositol, sorbitol, citric

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acid, isocitric acid, malic acid, shikimic acid, quinic acid, succinic acid, ketoglutaric acid, gallic

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acid, malonic acid, phenylalanine, leucine, isoleucine, methionine, tryptophan, proline, valine,

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tyrosine, alanine, threonine, glutamine, serine, glutamic acid, asparagine, aspartic acid, D-

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glucose-13C6, citric-2,2,4,4,-d4 acid and d3-L-aspartic acid) were purchased from Sigma-

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Aldrich Co. (St. Louis, MO, U.S.A.). All LC-MS/MS-grade was purchased from Fisher

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Scientific Co. (Waltham, MA, U.S.A.).

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Plant Materials. Mango fruits of ‘Glenn’, ‘Mamme’ and ‘Saigon’ were harvested from the

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Tropical Research and Education Center, University of Florida in June 2018. A total of 20−30

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fruits were randomly collected from three clonal replicate trees for ‘Glenn’ and ‘Saigon’. Only

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one tree of ‘Mamme’ was available at the time of harvest. These mangoes were selected based

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on their distinct quality profiles including variability for aroma, sweetness, and texture. ‘Glenn’

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has excellent eating quality, smooth flesh and pale internal color. ‘Mamme’ is a heavy producer

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with a slightly gritty texture.15 ‘Saigon’ has good eating quality with smooth flesh. The

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mangoes were picked at horticultural maturity (fruit easily separated from tree with clear or no

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sap flowing from stem) and ripened at room temperature (24 ± 1 °C) based on conventional

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ripeness indices such as soft to touch and appropriately colored skin.

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Sample Preparation. The mangoes were used within four days after harvesting for sensory

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analysis. For the consumer sensory acceptance study, five fruits representing ‘Glenn’,

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‘Mamme’, and ‘Saigon’ were sorted. The mangoes were washed, peeled, and cut into the

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uniform mango cubes (1 × 1× 0.5 cm). All mango cubes from the same cultivar were pooled 5



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together and then transferred to polyethylene containers. The samples were stored at 4°C until

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the sensory analysis. For sensory profile analysis and chemical analysis, three fruits (n=3) from

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each cultivars were sampled and the mango fleshes were divided two parts: (1) For flavor

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profile analysis by the trained panels, the mangoes from the same cultivar were collectively

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treated as one replicate and then homogenized to pastes with a Blender (MAINSTAYSTM

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Personal Blander; Walmart, Bentonville, AK). The paste batches were prepared on the day

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before each of the duplicate sensory evaluation session and then transferred to polyethylene

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containers. The samples were stored at -20 °C until further analysis and were thawed at 4 °C

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just before the sensory evaluation. (2) For chemical analysis, the mangoes were placed in

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Ziploc®bags, frozen at −20 °C and tested within a month of preparation. The pulp of each

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mango cultivar was homogenized in liquid nitrogen using a mortar and pestle to make mango

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pastes.

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Sensory Evaluation. For consumer testing, a group of 47 mango consumers were recruited

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from the Citrus Research and Education Center, at the University of Florida, and were between

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the ages of 18 and 65 with 60% being women. Panelists self-classified themselves as 16

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Asian/Pacific, 24 White/Caucasian, and 7 other race/ethnicity. During the test sessions,

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evaluations took place in individual sensory testing booths under artificial daylight and

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constant temperature (22 °C) conditions. Each sample was labeled with random 3-digital

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numbers and was served with a cup of water and unsalted crackers as palate cleansers between

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samples. All panelists went through a training session to familiarize them with scaling systems

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and procedures and then fruit pulp samples were rated on an anchored line scale,

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using Compusense® software (Compusense, Inc., Guelph, Ontario, Canada). Hedonic ratings

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and sensory intensity ratings used the hedonic general labeled magnitude scale (gLMS) and the 6


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sensory gLMS, respectively.16-17. Hedonic scales accessed the overall liking and color liking

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for mango in the context of all pleasure/displeasure experiences: 0 = neutral; −100 = strongest

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disliking of any kind experienced; +100 = strongest liking of any kind experienced. Sensory

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intensity scales accessed texture (firmness, juiciness, and fibrousness), taste (sweetness,

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sourness, and astringent) and flavor sensation (tropical flavor and overall flavor) for mango in

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the context of all sensory experiences: 0 = no sensation; 100 = strongest imaginable sensation

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of any kind experienced.18

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For sensory profile analysis, all procedures involving the human participants were in

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accordance with the ethical standards of the institutional and national research committees and

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with the 1964 Helsinki declaration. The study protocol and consent procedure received ethical

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approval from the Institutional Review Board (IRB) of the University of Florida.19 Fourteen

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trained panel members (9 females, 5 males; age 32 ± 6 years) were participated in each sensory

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analysis. The training sessions and test sessions were completed in one month. The ability of

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assessors to recognize different taste samples (sweet, sour, bitter, and water) and to rank the

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taste solution according to sweetness (5 and 10% sucrose) and sourness (0.1 and 0.2% citric

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acid) were tested. During training sessions the panelists were familiarized with the usage of the

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flavor attributes and the sensory gLMS. Ten flavor attributes were chosen for evaluation and

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standard references were used where appropriate to ensure agreement of the descriptive terms

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chosen (Table S1). The samples of different mango cultivars with random 3-digital numbers

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were served with a cup of water and unsalted crackers. Panelists were asked to score each

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attribute on anchored line scales with the sensory gLMS. Sensory intensity scales accessed

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taste (sweetness, sourness, and bitterness) and flavor (fruity, pineapple, coconut, caramel,

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terpene-like, green-like, and sweaty) sensation for mango in the context of all sensory 7



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experiences: 0 = no sensation; 100 = strongest imaginable sensation of any kind experienced.

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Physicochemical Analysis. The color was determined using a digital colorimeter (Model CR-

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400, Minolta-Konica Sensing Inc., Osaka, Japan), calibrated with a standard white plate.

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Mango flesh was measured on two opposite sides in L*a*b* mode. L*, a*, b* and a*/b* express

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lightness, green to red, blue to yellow and intensity of orange coloration, respectively.2 Total

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soluble solids (TSS, °Brix) and titratable acidity (TA, % citric acid) were determined using by

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a digital refractometer (PAL-BXIACID1, ATAGO, Tokyo, Japan). Each sample included three

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replicates.

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Analysis of Sugars, Organic Acids and Amino Acids. One hundred milligrams of mango

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pastes were mixed with 1 mL of 80% methanol containing internal standard (D-glucose-13C6,

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citric-2,2,4,4,-d4 acid and d3-L-aspartic acid). Suspensions were quickly vortexed and extracted

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using a multi-tube vortex mixer (Fisher Scientific, Ottawa, ON) for 30 min at room temperature.

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After centrifugation at 10,000 g for 15 min at 4 °C, the supernatants were filtered through 0.22

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μm nylon clarinet syringe filters (Bonna-Agela Technologies Inc, Wilmington) and analyzed

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using liquid chromatography with tandem mass spectrometry (LC-MS/MS; TSQ Quantiva,

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Thermo Fisher Scientific, San Jose, CA, USA). Analytes were chromatographed on a SeQuant

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ZIC®-pHILIC column (100 mm × 2.1 mm, 5.0 μm particle size, Merck SeQuant, Umeå,

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Sweden) with an appropriate guard column at a column temperature of 40 °C using (A)

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acetonitrile−10 mM ammonium acetate, pH 9.2 (90:10, v/v) and (B) acetonitrile as mobile

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phases. A gradient elution was carried out as follows: 0−1 min 100% B, 1–15 min 100–65%

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B, 15–30 min 65–0% B and 35–46 min 0–100% B. The column was re-equilibrated with the

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initial mobile phase before subsequent runs. The flow rate was 0.2 mL/min. The mass

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spectrometer was operated in positive and negative electrospray ionization (ESI+ and ESI–) 8


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modes depending on the target analytes with selected reaction monitoring (SRM). The

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parameters of ESI source were as follows: spray voltage, 3500 V (ESI+) and 2500 V (ESI–);

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ion transfer tube temperature, 325°C; vaporizer temperature, 275°C; sheath gas, 35 Arb; aux

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gas, 10 Arb; and sweep gas, 0 Arb. Collision-induced dissociation (CID) gas pressure was 2

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mTorr, and dwell time was 100 msec. An external standard method for sugars (sucrose, fructose,

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glucose, raffinose, myoinositol and sorbitol), organic acids (citric acid, isocitric acid, malic

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acid, shikimic acid, quinic acid, succinic acid, ketoglutaric acid, gallic acid and malonic acid),

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and amino acids (phenylalanine, leucine, isoleucine, methionine, tryptophan, proline, valine,

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tyrosine, alanine, threonine, glutamine, serine, glutamic acid, asparagine, and aspartic acid)

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were used for the quantitation of the analytes of interest. Data analysis was performed using

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Xcalibur software (Ver. 3.0). Each sample included three replicates.

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Analysis of Volatile Compounds. Volatiles of mango paste sample were collected and

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concentrated using headspace solid phase microextraction (HS-SPME) and analyzed using gas

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chromatography-mass spectrometry/olfactometry (GC-MS/O). The GC-MS/O system

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consisted of a Clarus 680 GC (Perki-nElmer, Inc., Waltham, MA) equipped with a Clarus SQ

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8T MS and a SNFR olfactory port. HS-SPME analysis was performed following a modified

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procedure previously reported.19 Four grams of mango paste samples were placed into 40 mL

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headspace vials containing internal standard (octyl butyrate) and 1 mL of distilled water.

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Samples were equilibrated at 40 °C for 10 min in a thermostatically controlled water bath

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followed

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(DVB/CAR/PDMS) SPME fiber (50/30 μm film thickness, Supelco, Bellefonte, PA, USA) to

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the headspace of each vial for 30 min. Volatile compounds were adsorbed on the SPME fibrer

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were desorbed for 10 min at 250 °C in the splitless injector of the GC combined with a mass

by

exposure

the

Divinylbenzene/Carboxen/Polydimethylsiloxane

9



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spectrometer operated in electron impact mode (MS-EI, 70 eV ionization energy) with a scan

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range from m/z 50 to 300 in the positive mode with a 2.5 min solvent delay. Separation was

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achieved on a TR-FFAP capillary column (30 m × 0.25 mm, 0.25 μm film thickness; Thermo

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Fisher Scientific, Walthan, MA) with a constant pressure, using helium as carrier gas. The

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column temperature was programmed to increase from 40 °C (after 2 min hold) to 64 °C at a

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rate of 2 °C/min with a hold time of 1 min and then increased to 200 °C at a rate of 4 °C/min

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with a final hold time of 10 min. A Swafer™ S2 mode was used to split the sample into the

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MS and the olfactory port (240 °C). Aroma quality was perceived through the sniffing port. A

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series of n-alkanes (C7−C30) was used to determine linear retention indices (RI) for each

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compound. Compound identifications were based on matching mass spectra from the standard

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national institute of standards and technology (NIST) 2014 library and on RIs of the

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authenticated standards. When authenticated standards were not available, tentative

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identifications (TI) were based on the NIST 2014 library and a comparison of RI in the

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literature. The relative content of each volatile in samples was calculated based on comparison

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with leak area of internal standard. Compounds were quantitated using an internal standard of

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octyl butyrate. Standard substances employed for identification were of analytical grade and

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purchased from different suppliers. Each sample included three replicates.

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Statistical Analysis. All sensory and analytical data were performed by one-way analysis of

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variance (ANOVA) followed by Tukey’s Honestly Significant Difference (HSD) test using

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SPSS Statistics (version 20.0; SPSS Inc., Chicago, IL) to compare sensory and analytical

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variances of different cultivars. The results were considered statistically significant for value

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of p < 0.05. Pearson’s correlations were determined using GraphPad Prism (version 5;

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GraphPad Software Inc., San Diego, CA) and visualized as a heatmap using R software. Partial 10


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least-squares-discriminate analysis (PLS-DA) was utilized to monitor the relationship between

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mango different cultivars and the experimental data using SIMCA-P (version 12.0; Umetrics,

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Umeå, Sweden). The PLS-DA models was also validated by the R2Y and Q2 from a random

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permutation test (n=100) in SIMCA-P. PLS regression analysis was used to investigate

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relationship between compositional variables (x data) and the sensory attributes (y data) in

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different mango cultivars using SIMCA-P. The quality of the PLS model was depicted by the

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cross-validation parameters, R2 and Q2, representing the explained variance and the predictive

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capability of the model, respectively. Within the context of PLS-DA and PLS regression, the

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variable importance in the projection (VIP) scores reflect the relative importance of each x

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variable for each x variate in the prediction model. 20 In this study, variables with VIP values

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higher than one were considered of potential interest, which can verify discriminating

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compounds in PLS models.

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RESULTS AND DISCUSSION

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Fruit Characteristics of the Mango Cultivars. The physicochemical characteristics of

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‘Glenn’, ‘Mamme’, and ‘Saigon’ mangoes are shown in Table 1. The flesh of ripe mangoes

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ranges from pale yellow to orange.21 In this study, ‘Saigon’ had markedly lower red coloration

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(a* value) and orange coloration (a*/b* ratio) than other cultivars, while lightness (L* value) had

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no significant difference between the cultivars.

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Mangoes are generally considered higher quality if they combine a low fibrousness

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with a strong sweet taste, a balanced acidity, and an aroma profile high in fruity and low in

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turpentine-like notes.22 In this study, the sensory characteristics of the mango cultivars were

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evaluated to find their distinct sensory quality profiles in terms of consumer liking for color 11



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and overall liking, and sensory attributes for texture, taste, and flavor (Table 2). The overall

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liking ratings of the mangoes were ranked in the following manner, ‘Glenn’ > ‘Saigon’ >

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‘Mamme’ (p < 0.05). ‘Glenn’ had the highest quality with low firmness, low fibrousness, high

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juiciness, high sweetness, high tropical flavor, and overall high flavor compared to the other

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mangoes tested with significant differences (p < 0.05) leading to the highest hedonic rating.

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However, the sensory attributes of ‘Mamme’ were shown to have the opposite sensory

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attributes. ‘Mamme’ had the highest scores for firmness and fibrousness, and the lowest scores

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for sweetness, tropical flavor, and overall flavor (p < 0.05). Among these mango cultivars, no

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significant differences were observed in color liking and taste attributes of sourness and

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astringent. The TSS, TA and TSS/TA ratio have been regarded as sensory quality parameters

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to evaluate sweetness of mango fruits.23-24 However, our results indicated that ‘Saigon’ had

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similar intensity to ‘Mamme’ on sweetness although ‘Saigon’ had the lowest TSS and TSS/TA

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ratio. This observation suggested that the TSS, TA, and TSS/TA ratio were not completely

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informative when measuring these mango sensory qualities.

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The present study also determined the relationship between the sensory attributes by

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the Pearson method with Pearson r and two-tailed p values (Table S2 and Figure 1). Overall

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liking was positively correlated with sweetness (r = 0.43, p < 0.01), tropical flavor (r = 0.69, p

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< 0.01), and overall flavor (r = 0.74, p < 0.01), and negatively correlated with sourness (r = -

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0.26, p < 0.01) and astringent (r = -0.23, p < 0.01). Interestingly, sweetness had not only a

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highly positive correlation with tropical flavor (r = 0.83, p < 0.01) and overall flavor (r = 0.82,

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p < 0.01), but also a negative correlation with sourness (r = -0.18, p < 0.05). Overall liking had

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a positive correlation with juiciness (r = 0.54, p < 0.01), but no correlation with firmness and

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fibrousness. Juiciness also was strongly and positively correlated with sweetness (r = 0.78, p < 12


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0.01), tropical flavor (r = 0.73, p < 0.01), and overall flavor (r = 0.71, p < 0.01). Even though

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mango fresh color had a slight influence on several sensory attributes, it was not a reasonable

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predictor of the overall liking by consumer. This result imply that mango flavor could play a

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crucial role in the hedonic perception of mango.

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The taste and flavor profiles of mango cultivars were assessed by trained panels. There

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were significant differences (p < 0.05) among cultivars for tastes of sweetness and sourness,

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and the flavors of fruity, pineapple, coconut, and green-like (Figure 2A). The overall flavor of

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‘Glenn’ was characterized mango-like attributes including high intensities of sweetness, fruity,

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pineapple and coconut. On the other hand, ‘Mamme’ had lower intensities for sweetness,

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sourness, fruity, pineapple, and coconut, and a higher intensity for green-like. ‘Saigon’ had the

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highest intensity of sourness compared to the other cultivars but also higher pineapple and

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fruity intensities than ‘Mamme'. We also investigated whether the flavor profile of mango was

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similar among different cultivars. Using PLS-DA as a multivariate data analysis technique, the

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values of samples and loadings of the variables on the two PLS-DA components were

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graphically illustrated in a biplot to describe the contribution of individual flavor attributes to

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variation between cultivars (Figure 2B). The examination of the bidimensional plot emphasized

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that there was excellent separation of three clusters representing the different mango cultivars.

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The observed PLS-DA model had good coefficient fractions with R2Y = 0.946, Q2 = 0.845

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(positive prediction ability), and variables explained 0.844 (R2X) of total variation.

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Furthermore, R2Y-intercept and Q2Y-intercept of the random permutation test were 0.399 and

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-0.307, respectively. The criteria for validity of a certain model are: all the Q2 and R2 values on

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the permuted data sets should be lower than the values on the actual data set.25-26 Therefore,

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the permutation test showed good predictability and no overfitting of non- PLS-DA model on 13



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flavor attributes to variation between cultivars. This plot also indicated that mango-like flavor

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attributes such as pineapple, fruity, caramel, and coconut with high sweetness influenced the

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distinctive flavor of ‘Glenn’. However, ‘Mamme’ located in the left lower part of the plot was

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characterized by terpene-like and green-like flavors. These results suggest that a balanced

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combination of sweetness, fruity, pineapple, coconut, and sourness could contribute to the

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flavor profile in relation to positive hedonic perception of mango.

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The Chemical Diversity within the Mango Cultivars. Flavor perception of foods is a

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complex process that involves the senses of smell and taste, and chemesthesis. During the

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eating process, different types of chemical stimuli including non-volatile and volatile

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components are released. Saliva facilitates the movement of non-volatile compounds to taste-

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and irritatant-sensitive regions of oral cavity, while volatile compounds are transported

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retronasally from the mouth to the nasal cavity and its olfactory receptors through the

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nasopharynx.27 The congruent interaction of tastants and olfactory stimuli can cause enhanced

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neural responses in parts of the brain that code for the hedonic value of food.28 Mango flavor

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is primarily generated by a diverse set of chemicals including sugar, acids, and volatile

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compounds, which may be considered as chemical stimulus for flavor perception.2,

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understand on what chemical components are responsible for flavor perception of mango,

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chemical profiles of three mango cultivars were analyzed. The sugar and acid profiles and

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volatile profiles of mangoes were analyzed by LC-MS/MS and SPME-GC-MS/O, respectively.

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In this study, four sugars (sucrose, fructose, glucose, and raffinose) and two sugar alcohols

289

(myoinositol and sorbitol) were identified (Table 3). The total amount of sugar ranged from

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160.02 to 225.98 g/kg of fresh weight in mangoes. Glucose (39.1–40.7% of total sugars),

291

fructose (32.9–35.9% of total sugars), and sucrose (23.2–27.7% of total sugars) were the major 14


6-7

To

Page 15 of 40


292

sugars in all the samples. The total amount of organic acid ranges from 5.43 to 11.74 g/kg of

293

fresh weight in mangoes. The major organic acids were citric acid (27.9–55.4% of total organic

294

acids), quinic acid (7.0–34.7% of total organic acids), shikimic acid (22.2–29.9% of total

295

organic acids), malic acid (4.6–12.0% of total organic acids), and isocitric acid (1.5–3.0% of

296

total organic acids). Succinic acid, ketoglutaric acid, gallic acid, and malonic acid were present

297

at less than 1% of total organic acids.

298

A total of 15 amino acids including phenylalanine, leucine, isoleucine, methionine,

299

tryptophan, proline, valine, tyrosine, alanine, threonine, glutamine, serine, glutamic acid,

300

asparagine and aspartic acid ranged from 79.66 to 302.94 mg/kg of fresh weight in mangoes.

301

Alanine (11.3–47.2% of total amino acids), phenylalanine (3.1–36.8% of total amino acids),

302

proline (9.6–22.9% of total amino acids), glutamic acid (8.7–24.8% of total amino acids), and

303

methionine (2.2–7.2% of total amino acids) were the predominant amino acids of mangoes.

304

PLS-DA methods were applied as a multivariate data analysis technique to display the

305

non-volatile pattern of the three mango cultivars (Figure 3A). ‘Glenn’ had the highest total

306

sugar, sucrose, fructose, glucose, and sorbitol content compared to the other two cultivars. The

307

content of total acid in ‘Saigon’ was significantly higher than the other cultivars, especially

308

shikimic acid, quinic acid, succinic acid, ketoglutaric acid and gallic acid. In contrast,

309

‘Mamme’ had the highest amounts of amino acids, followed by ‘Glenn’, and ‘Saigon’. All

310

cultivars were divided into 3 groups on the basis of the first two components in a biplot, which

311

were consistent with the result of qualitative profiling analysis (p < 0.05, R2X = 0.725, R2Y =

312

0.982 and Q2 = 0.924). The y intercepts of R2 and Q2 in the permutation test were 0.403 and -

313

0.236, respectively, indicating a valid model. ‘Glenn’ was positioned in upper right quadrant

314

of the biplot which was characterized by relative high concentrations of fructose, glucose, 15



315

isocitric acid, and ketoglutaric acid. Quinic acid, shikimic acid, phenylalanine, and raffinose

316

appeared to be linked to ‘Saigon’ cultivar. Most of the discriminative composition in ‘Mamme’

317

was characterized by the presence of amino acids, such as serine, isoleucine, leucine, tyrosine,

318

leucine, alanine, valine, proline, threonine, and aspartic acid. Moreover, the VIP values were

319

calculated from the non-volatile compositions of three mango cultivars (p < 0.05) (Figure S1A).

320

In total 31 non-volatile compounds, three organic acids (isocitric acid, citric acid, and

321

ketoglutaric acid), three sugars (fructose, raffinose, and glucose), and an amino acid (glutamic

322

acid) had VIP score higher than 1. It highlights the importance of these non-volatile compounds

323

that could be most influential in discriminating among the different mangoes cultivar.

324

The 45 most abundant volatile compounds were identified in three mango cultivars.

325

These compounds included 10 aldehydes, 3 alcohols, 19 terpenes, 12 esters, 1 lactone, and 1

326

acid, all of which have been previously reported in mangoes except for 2-methylbutyraldehyde

327

(Table 4).6-7, 14, 29-30 2-methylbutyraldehyde has been described as malty in malted barley.31 Our

328

results showed that ‘Glenn’ had higher amount of esters including ethyl acetate, ethyl

329

propionate, methyl butanoate, ethyl butanoate, ethyl-3-methylbutanoate, cis-ethyl crotonate,

330

(Z)-3-hexeenyl acetate, ethyl octanoate, ethyl 3-hydroxybutanoate, and ethyl phenylacetate

331

than other cultivars. α-Pinene, camphene, δ-3-carene, α-phellandrene, α-terpinene, β-myrcene,

332

limonene, β-phellandrene, γ-terpinene, (Z)-β-ocimene, α-gurjunene and β-selinene were

333

exclusively found in ‘Mamme’. α-Copaene, n-hexyl butanoate and (E)-3-hexenyl butanoate

334

were found only in the ‘Saigon’ cultivar. The biplot of PLS-DA on the volatile compositions

335

revealed a clear separation between the different mango cultivars on the basis of the first two

336

latent variables with good coefficient fractions (p < 0.05, R2X = 0.706, R2Y = 0.908 and Q2 =

337

0.813) (Figure 3B). After the permutation test was performed, y intercepts for R2 and Q2 were 16


Page 16 of 40

Page 17 of 40


338

0.408 and -0.207, respectively, indicating a valid model. ‘Glenn’ was characterized by elevated

339

levels of linalool (floral, citrus), 1-octanol (floral), (E,Z)-2,6-nonadienal (cucumber), γ-

340

octalactone (coconut), β-caryophyllene (sweet, floral), 2-butenoic acid (fruity), ethyl butanoate

341

(fruity), cis-ethyl crotonate (floral, fruity), ethyl acetate (pineapple), ethyl propionate (fruity),

342

methyl butanoate (fruity, sweet), ethyl butanoate (fruity), ethyl-3-methylbutanoate (fruity), (Z)-

343

3-hexenyl acetate (banana), ethyl octanoate (peach), ethyl 3-hydroxybutanoate (marshmallow),

344

and ethyl phenylacetate (fruity, sweet), which accounts for the general fruity/floral attributes

345

in mango aroma profile.6,

346

characterized by high levels of n-hexyl butanoate (apple peel), (E)-3-hexenyl butanoate

347

(creamy), terpinolene (lemon) and α-copaene (floral).32 ‘Mamme’ located in the left lower part

348

of the plot was mainly linked to the compounds having terpeny/green note including hexanal

349

(green), 2-methylbutyraldehyde (malt), (E)-2-octenal (green), octanal (green), α-pinene

350

(terpeny), camphene (camphor), δ-3-carene (resinous), α-phellandrene (terpeny), α-terpinene

351

(lemon), β-myrcene (terpeny), β-phellandrene (terpeny), γ-terpinene (terpeny), (Z)-β-ocimene

352

(terpeny), α-gurjunene (green), and β-selinene (herb).6 In addition, the VIP values were

353

calculated from PLS-DA model on the volatile compositions of three mango cultivars (p < 0.05)

354

(Figure S1B). The VIP of terpinolene, 2-butenoic acid, ethyl propionate, ethyl phenylacetate,

355

ethyl 3-hydroxybutanoate, (E,Z)-2,6-nonadienal, ethyl-3-methylbutanoate, γ-octalactone, 1-

356

octanol, ethyl acetate, α-terpinene, p,α-dimethylstyrene, hexanal, camphene, α-pinene, (E)-2-

357

octenal, β-myrcene, (Z)-β-ocimene, cis-ethyl crotonate, δ-3-carene, methyl butanoate, and β-

358

phellandrene were larger than 1, which revealed high discriminative power between different

359

mango cultivars.

360

14

‘Saigon’ was located in upper part of the biplot, which is

Relationship between Mango Flavor Attributes and Chemical Constituents. PLS 17



361

regression model was used to investigate the contribution of non-volatile compounds, such as

362

sugars, organic acids, and amino acids (x variables, n = 30) or volatile compounds (x variables,

363

n = 46) to various taste and flavor attributes (y variables, n = 10) in three mango cultivars. In

364

the correlation loading plot for the non-volatile compounds and the flavor attributes (Figure 4),

365

the x variables (R2X = 0.749) explained the variation in the y variables (R2Y = 0.824) according

366

to the first two factors (p < 0.05, Q2 = 0.574). The loading plot allow the cultivars to be

367

classified into uniquely defined sub-groups (Figure 4A). The chemical parameters plotted in

368

the vicinity of the flavor attribute were positively associated with that attribute (Figure 4B).

369

The taste of sweetness and sourness and the flavors of pineapple, fruity, caramel, and coconut

370

were located on a right part of loading plot together with ‘Saigon’ and ‘Glenn’. The taste of

371

sweetness and the flavors of pineapple, fruity, coconut, and caramel adjacent to the lower right

372

quadrant of the loading plot were positively correlated with the non-volatile chemical

373

composition of ‘Glenn’ including sucrose, fructose, glucose, sorbitol, isocitric acid and

374

ketoglutaric acid. ‘Saigon’ was located on the upper right quadrant of the loading plot together

375

with the sourness attribute, which was correlated with shikimic acid, phenylalanine, quinic acid,

376

succinic acid and raffinose. On the other hand, ‘Mamme’ was located on a left part of the

377

loading plot together with the taste attribute of bitterness and the flavor attributes of terpene-

378

like, green-like, and sweaty, which were associated with most of the amino acids except for

379

phenylalanine that was closely linked to ‘Saigon’. Moreover, the VIP values were calculated

380

from the PLS regression model on the taste and flavor characteristics and the non-volatile

381

compositions of three mango cultivars (p < 0.05) (Figure S2A). The VIP scores of fructose,

382

glucose, raffinose, sorbitol, isocitric acid, citric acid, shikimic acid, phenylalanine, ketoglutaric

383

acid, and glutamic acid had higher than 1, which can be considered as being responsible for

384

differences in the non-volatile compounds and taste and flavor characteristics among three 18


Page 18 of 40

Page 19 of 40

385


mango cultivars.

386

These results imply that fructose, glucose, and raffinose may be involved in the non-

387

volatile chemical stimuli of mango for sweet taste receptor cells clustered in taste bud on the

388

tongue, contributing to intense of sweetness.33 Previous researches have reported that free

389

amino acids may affect the tastes of fruits, such as tomato and strawberry by increasing

390

sweetness with glycine, alanine, or proline and increasing sourness with aspartic acid.34-37

391

Nevertheless, our results showed that ‘Mamme’ had the highest concentration of most of amino

392

acids except for phenylalanine, but was the lowest in sweetness and sourness. The interesting

393

was that ‘Saigon’ had higher taste of sweetness and sourness with stronger flavor of fruity and

394

pineapple than ‘Mamme’, although they had similar intensities of green-like, terpene-like and

395

coconut flavors. In addition, the higher levels of shikimic acid and phenylalanine were found

396

in ‘Saigon’ than ‘Mamme’. Phenylalanine, the final product of the shikimate pathway, is

397

known as one of the most important flavor precursor in fruits.38 Phenylalanine metabolism

398

produce floral and fruity volatile compounds such as phenylethyl alcohol, and phenylacetate,

399

which may contribute to the fruity and pineapple-like flavor of mango.39 It has been reported

400

that olfactory stimuli that have regularly been paired with sweet or sour-tasting foods can

401

induce the enhancement of the associated taste quality.28 These findings assume that fruity odor

402

derived from shikimate/phenylalanine pathway may have play a role of olfactory stimuli of

403

mango for the aroma-induced sweetness enhancement.

404

In the correlation loading plot for the volatile compounds and the flavor attributes

405

(Figure 5), the two first principal components explained the x variables (R2X = 0.821) and the

406

y variables (R2Y = 0.805) (p < 0.05, Q2 = 0.545). The VIP values were calculated from the PLS

407

regression model on the taste and flavor characteristics and the volatile compositions of three 19



408

mango cultivars (p < 0.05) (Figure S2B). Volatile compounds having VIP scores lager than 1

409

were highly relevant for discriminating different mango cultivars on the volatile compounds

410

and taste and flavor attributes. The volatile profile of mango analyzed were variable with

411

different cultivars, which contributed to different flavor characteristics. ‘Glenn’ had not only

412

high fruity intensity, but also a strong correlation with caramel and coconut flavors along with

413

1-octanol, (E,Z)-2,6-nonadienal, and γ-octalactone as well as several esters derived from

414

fruity/floral/sweet flavors. Remarkably, ethyl propionate, methyl butanonate, ethyl butanoate,

415

cis-ethyl crotonate, ethyl 3-hydroxybutanoate, and 2-butenoic acid were only perceived as a

416

fruity note in ‘Glenn’ through the sniffing port of GC-MS/O. Ethyl butanoate and ethyl-3-

417

methylbutanonate have been regarded as potent aroma-active compounds for fruity notes in

418

mango.40 Lactones such as γ-octalactone have been responsible for the coconut-like note in

419

mangoes.41 Our results also suggested that these compounds could be responsible for desirable

420

sensory quality of mango.

421

In contrast, ‘Mamme’ was strongly linked to the volatile compounds involved in

422

terpene/green flavor notes (hexanal, β-selinene, β-phellandrene, octanal, (E)-2-octenal,

423

camphene, α-pinene, β-myrcene, (Z)-β-ocimene, δ-3-carene, γ-terpinene, α-gurjunene and α-

424

phellandrene), a citrusy note (α-terpinene, p-cymene, nonanal and limonene) and a malt note

425

(2-methylbutyraldehyde), all of which are statically correlated with terpene flavor. Even though

426

more study is needed to determine the impact of citrus/malt flavors on the hedonic perception,

427

our results suggested that volatile compounds involved in citrus/malt notes including α-

428

terpinene, p-cymene, nonanal, limonene, and 2-methylbutyraldehyde could affect negative

429

hedonic perception of mango.

430

The sourness of ‘Saigon’ was correlated to n-hexyl butanoate, (E)-3-hexenyl butanoate, 20


Page 20 of 40

Page 21 of 40


431

and α-copaene. Our results indicated that ‘Saigon’ had high flavor intensities of fruity and

432

pineapple and high amount of shikimic acid and phenylalanine, leading to higher overall liking

433

score of ‘Saigon’ than that of ‘Mamme’. Volatile and non-volatile flavor compounds derived

434

from phenylalanine metabolism could result in the flavor and scent of many fruits.42 It can be

435

a potential prerequisite for the formation of volatile metabolites including 2-phenylethanol, 2-

436

phenylethyl ester, and phenylacetate, whose derivatives have pleasant fruity and pineapple-like

437

flavors.43-44 Even though 2-phenylethanol, 2-phenylethyl ester, and phenylacetate were not

438

found in ‘Sagon’, phenylalanine metabolism presumably play the crucial role for the

439

development of fruity and pineapple-like flavor of ‘Saigon’. These findings assume that the

440

derivatives of 2-phenylethanol and phenylacetate may interact with olfactory receptor neurons,

441

leading to partially enhanced neural responses in parts of the brain that code for the hedonic

442

perception of mango.28

443

Fatty acids have been regarded as the major precursors of volatile compounds

444

responsible for the aroma of most plant products.43-44 Several studies reported that the pulp of

445

ripe mango has lipoxygenase (LOX) and hydroperoxide lyase (HPL).45-46 It is widely predicted

446

that the biosynthesis pathway of the key aroma compounds in mango might be implicated in

447

fatty acid metabolism. LOX produces hydroperoxide isomers of polyunsaturated fatty acids,

448

which are subsequently cleaved by HPL to form C6 aldehydes. The aldehydes can be converted

449

to C6 alcohols by alcohol dehydrogenase.47-48 The saturated and unsaturated C6-alcohols

450

formed through the LOX/HPL pathway can be esterified with acyl-CoA moieties to produce

451

hexyl esters such as (E)-2-hexenyl and (Z)-3-hexenyl ester, that lead to the formation of esters

452

or lactones.44,

453

attractive aroma compounds such as 2-butenoic acid, (Z)-hexenyl acetate, and γ-octalactone.

47

This metabolism of fatty acids might be attributed to the presence of the

21



454

Moreover, consumer negative perception of mango associated the terpene flavor profile was

455

found to be affected by high concentrations of terpene compounds such as terpinolene, δ-3-

456

carene, caryophyllene, α-pinene, limonene, and β-myrcene. Mango terpene compounds are

457

derived from the C5 prenyl diphosphate precursors (isopentenyl diphosphate and its allylic

458

isomer dimethylallyl diphosphate) by short-chain isoprenyl diphosphate synthases (IDS) in

459

terpenoid biosynthesis.49 This supported the postulate that the terpene compositions involved

460

in terpene/green flavors might be biosynthesized via isoprenoid pathway in mango. Further

461

studies on the additional metabolomics profiling of mango flavor-associated chemical

462

precursors such as phenylalanine, fatty acids, and isoprenoids would be helpful to explore

463

potential biomarker for high sensory quality of mango.

464

Collectively, the interaction between individual chemical compounds within mango

465

can be correlated with the distinct sensory qualities of mango cultivars. The present study

466

provides a better understanding of the framework for the relationship of the chemical factors

467

and the sensory attributes of different mango cultivars and could be used in the future selection

468

and breeding of superior mango cultivars.

469 470

ABBREVIATIONS USED gLMS TSS TA SRM IRB LC-MS/MS CID ESI HS-SPME

General labeled magnitude scale Total soluble solids Titratable acidity Selected reaction monitoring Institutional review board Liquid chromatography with tandem mass spectrometry Collision-induced dissociation Electrospray ionization Headspace solid phase microextraction 22


Page 22 of 40

Page 23 of 40


GC-MS/O DVB/CAR/PDMS RI PLS-DA ANOVA LOX HPL IDS

Gas chromatography-mass spectrometry/olfactometry Divinylbenzene/Carboxen/Polydimethylsiloxane Linear retention indices Partial least-squares-discriminate analysis One-way analysis of variance Lipoxygenase Hydroperoxide lyase Isoprenyl diphosphate synthases

471 472

Supporting Information Description

473

Mango flavor attributes, definitions, and standard references for the sensory analysis by trained

474

panels; Pearson correlation matrix of hedonic scale and sensory attributes in mangoes by

475

consumer test; The composition of non-volatile compounds in three mango cultivars; The

476

composition of volatile compounds in three mango cultivars.

477 478

CONFLICT OF INTEREST DISCLOSURE

479

Corresponding Authors

480

*Telephone: +1-863-956-8673. E-mail: [email protected]

481

ORCID

482

Yu Wang: 0000-0002-2003-270X

483

Funding

484

This research was supported by the USDA National Institute of Food and Agriculture (USDA-

485

NIFA 2018-51181-28375).

23



486

Notes

487

The authors declare no competing financial interest.

488

24


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relevance as stress indicators under NaCl salinity. Food Chem. 2008, 111 (3), 642-647.

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ten tropical fruits by gas-liquid chromatography. J. Agric. Food Chem. 1980, 28 (6), 1217-21.

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convert phenylalanine into the flavor volatile 2-phenylethanol. Fungal. Genet. Biol. 2015, 77, 22-30.

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aroma. Flavour Fragr. J. 2006, 21 (2), 207-213.

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amino acid decarboxylases participate in synthesis of the flavor volatiles 2-phenylethanol and 2-

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phenylacetaldehyde. Proc. Natl. Acad. Sci. U.S.A. 2006, 103 (21), 8287-92.

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compounds. Plant J. 2008, 54 (4), 712-32.

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Pino, J. A.; Mesa, J.; Munoz, Y.; Marti, M. P.; Marbot, R., Volatile components from mango Beal, A. D.; Mottram, D. S., Compounds contributing to the characteristic aroma of malted Jordan, M. J.; Margaria, C. A.; Shaw, P. E.; Goodner, K. L., Volatile components and aroma

Lee, A. A.; Owyang, C., Sugars, Sweet Taste Receptors, and Brain Responses. Nutrients 2017, Keutgen, A. J.; Pawelzik, E., Contribution of amino acids to strawberry fruit quality and their Sorrequieta, A.; Ferraro, G.; Boggio, S. B.; Valle, E. M., Free amino acid production during Kato, H.; Rhue, M. R.; Nishimura, T., Role of free amino-acids and peptides in food taste. Moing, A.; Renaud, C.; Gaudillere, M.; Raymond, P.; Roudeillac, P.; Denoyes-Rothan, B.,

Hall, N. T.; Smoot, J. M.; Knight, R. J., Jr.; Nagy, S., Protein and amino acid compositions of Masuo, S.; Osada, L.; Zhou, S. M.; Fujita, T.; Takaya, N., Aspergillus oryzae pathways that Pino, J. A., Odour-active compounds in mango (Mangifera indica L. cv. Corazon). Int. J. Pino, J. A.; Mesa, J., Contribution of volatile compounds to mango (Mangifera indica L.) Tieman, D.; Taylor, M.; Schauer, N.; Fernie, A. R.; Hanson, A. D.; Klee, H. J., Tomato aromatic

Schwab, W.; Davidovich-Rikanati, R.; Lewinsohn, E., Biosynthesis of plant-derived flavor Song, J.; Forney, C. F., Flavour volatile production and regulation in fruit. Can. J. Plant Sci. 27



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Flores, S.; Sanchez-Flores, A.; Kuhn, D. N.; Islas-Osuna, M. A., Mango (Mangifera indica L.) cv. Kent

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fruit mesocarp de novo transcriptome assembly identifies gene families important for ripening. Front.

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in red delicious and granny smith apples using deuterium-labeled precursors. J. Agric. Food Chem.

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genes associated with aroma formation derived from the fatty acid pathway during peach fruit

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ripening. J. Agric. Food Chem. 2010, 58 (10), 6157-6165.

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Gupta, V., Characterization of three novel isoprenyl diphosphate synthases from the terpenoid rich

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Rowan, D. D.; Allen, J. M.; Fielder, S.; Hunt, M. B., Biosynthesis of straight-chain ester volatiles

Zhang, B.; Shen, J. Y.; Wei, W. W.; Xi, W. P.; Xu, C. J.; Ferguson, I.; Chen, K. S., Expression of

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617

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618

Figure captions

619

Figure 1. Heat map of the correlation between hedonic scale and sensory attributes in mango.

620

The correlation was determined by Pearson method and the heat map was drawn by R.

621

Figure 2. (A) Taste and flavor profiles of three mango cultivars and (B) the loading plot of

622

partial least-squares discriminant analysis scores for of three mango cultivars with taste and

623

flavor attributes. The flavor profiles were assessed by trained panels.

624

Figure 3. The loading plot of partial least-squares discriminant analysis for three mango

625

cultivars with (A) non-volatile compounds and (B) volatile compounds. The sugar and acid

626

profiles and aroma volatile profiles of mangoes analyzed by LC-MS/MS and SPME-GC-MS/O,

627

respectively.

628

Figure 4. Relation of flavor attributes and non-volatile compounds of three mango cultivars.

629

(A) The distribution of three mango cultivars and (B) the loading plot for three mango cultivars

630

with non-volatile compounds.

631

Figure 5. Relation of flavor attributes and volatile compounds of three mango cultivars. (A)

632

The distribution of three mango cultivars and (B) the loading plot for three mango cultivars

633

with volatile compounds.

29



Table 1. Physicochemical characteristics of three mango cultivars. Glenn Mamme Saigon TSS (°Brix)A 15.93a 16.40a 13.82b c b TA (%) 0.65 0.89 1.06a TSS/TA ratio 24.41a 18.43b 13.04c * b b L value 59.05 58.07 66.60a * a a a value 7.26 9.92 -0.62b * ns b value 44.11 44.65 40.96 a*/b* ratio 0.16a 0.23a -0.02b AMean values. nsNot significant (P ≤ 0.05). Different letters in the same row indicate significant statistical differences (Tukey's HSD, P ≤ 0.05).

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Table 2. Sensory characteristics of three mango cultivars assessed by consumer test. Sensory variables Glenn Mamme Hedonic liking Color likingA 47.82a 47.69a a Overall liking 42.19 3.56b Texture Firmness 28.43b 42.61a a Juiciness 32.73 22.22b Fibrousness 18.31bc 38.52a Taste Sweetness 38.83a 22.70c ns Sourness 12.86 16.78 Astringentns 13.27 17.88 Flavor Tropical 45.10a 26.40c a Overall flavor 49.04 28.57c AMean values. nsNot significant (P ≤ 0.05). Different letters in the same statistical differences (Tukey's HSD, P ≤ 0.05).

31


Saigon 35.09ab 24.91a 27.31b 31.96a 26.86b 28.61bc 17.04 14.58 36.47b 34.51bc row indicate significant


Table 3. The composition of non-volatile compounds in three mango cultivars Glenn Mamme Saigon Sugar Sucrosens 52492.35 37874.73 53692.38 Fructose 80991.17a 56549.99b 64329.72ab ns Glucose 91890.64 65170.45 76233.18 Raffinose 323.64b 348.12b 649.92a ns Myoinositol 281.55 274.05 282.26 Sorbitol 5.30a 4.17b 3.24b a b Total sugars 225984.64 160221.50 195190.70ab Organic acid Citric acidns 2769.33 3026.48 3269.22 Isocitric acid 234.37a 135.71b 179.22ab ns Malic acid 563.03 639.78 536.81 Shikimic acid 1911.59b 1202.08b 3517.88a b c Quinic acid 2249.61 386.26 4082.46a Succinic acid 60.35ab 32.38b 72.84a a b Ketoglutaric acid 60.87 4.40 42.50a a b Gallic acid 33.15 4.04 39.34a ns Malonic acid 0.85 0.81 0.80 Total organic acids 7882.29b 5431.13c 11740.27a Amino acid Phenylalanine 18.87b 9.27c 29.35a b a Leucine 1.52 4.00 0.75b b a Isoleucine 1.42 2.70 0.80c ns Methionine 6.44 6.60 5.73 Tryptophanns 3.05 2.68 2.00 Proline 12.35b 69.28a 7.61b Valine 3.29b 9.86a 1.70b b a Tyrosine 2.13 4.79 1.04b b a Alanine 29.08 143.02 9.04b b a Threonine 0.90 2.35 0.84b ns Glutamine 2.43 5.20 3.86 Serine 2.91b 7.62a 1.22b Glutamic acid 29.06a 26.31a 12.94b ab a Asparagine 2.24 2.91 1.64b b a Aspartic acid 1.31 6.36 1.15b b a Total amino acids 116.99 302.94 79.66b AMean concentration values (mg/kg of fresh mango fruit). Retention indices were determined nsNot significant (p ≤ 0.05). Different letters in the same row indicate significant statistical differences (Tukey's HSD, p ≤ 0.05).

32


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Table 4. The composition of volatile compounds in three mango cultivars. RIA

Glenn

Mamme

Saigon

856

1.225a

0.386b

0.345b

Aroma descriptsB Pineapple

2-Methylbutyraldehydens

889

ndD

0.435E

0.089

Malt

R, MS, O

Ethyl propionatens

934

0.11

nd

nd

Fruity

R, MS, O

Methyl butanoatens

959

0.114

nd

nd

Fruity, sweet

R, MS, O

α-Pinene

993

0.381b

2.214a

0.356b

Terpeny

R, MS, O

Ethyl butanoate

1016 4.010a

ndb

ndb

Fruity

R, MS, O

Camphene

1021 ndb

0.242a

0.019b

Camphor

R, MS

Ethyl-3-methylbutanoatens

1039 0.061

nd

nd

Fruity

R, MS

Hexanal

1054 ndb

0.999a

0.383ab

Green

R, MS, O

2-Butenoic acid

1078 3.269a

ndb

ndb

Fruity

MS, O, TI

214.474a

18.707b

Resinous

R, MS, O

Ethyl acetate

IdentificationC R, MS, O

δ-3-Carene

1114

α-Phellandrene

1124 1.272b

3.289a

ndb

Terpeny

R, MS

α-Terpinenens

1128 nd

2.627

2.076

Lemon

R, MS, O

11.841a

0.988b

Terpeny

R, MS

43.255b

1.373b

β-Myrcene

1131

cis-Ethyl crotonatens

1139 4.729

nd

nd

Floral, fruity

MS, O, TI

Limonenens

1151 42.241

64.091

34.246

Citrusy

R, MS

3.860a

ndb

Terpeny

MS, TI

ndb

β-Phellandrene

1157

(E)-2-Hexenal

1195 0.232ab

ndb

0.337a

Green

R, MS

γ-Terpinenens

1210 0.554

1.305

0.521

Terpeny

R, MS

0.496a

0.044b

Terpeny

R, MS

0.088b

(Z)-β-ocimene

1225

p-Cymenens

1238 0.97

1.222

1.342

Citrusy

R, MS

Terpinolenens

1250 4.508

22.381

50.919

Lemon

R, MS, O

Octanalns

1255 0.19

0.48

0.217

Green

R, MS, O

(Z)-3-Hexenyl acetate

1287 0.591a

0.059b

0.661b

Banana

R, MS

1-Hexanolns

1334 0.027

0.053

0.07

Green

R, MS

(Z)-3-Hexenolns

1361 0.141

0.166

0.173

Moss

R, MS

Nonanalns

1367 0.254

0.435

0.14

Citrusy

R, MS, O

ndb

0.096a

Apple peel

R, MS

ndb

n-Hexyl butanoate

1388

(E)-2-Octenal

1397 ndb

0.109a

0.009b

Green

R, MS

p,α-Dimethylstyrenens

1405 nd

0.982

1.499

Pine

R, MS, O

ndb

ndb

Peach

R, MS, O

1.162a

Ethyl octanoate

1408

(E)-3-Hexenyl butanoate

1408 ndb

ndb

0.432a

Creamy

R, MS, O

α-Copaenens

1449 nd

nd

1.024

Floral

MS, TI

Decanalns

1470 0.071

0.009

0.056

Soapy

R, MS, O

33



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α-Gurjunene Ethyl 3hydroxybutanoatens Benzaldehyde

1480 0.306b

0.683a

0.177b

Green

R, MS, O

1487 0.066

nd

nd

Marshmallow

R, MS, O

1495 0.039b

0.143a

ndb

Burnt sugar

R, MS

(E)-2-Nonenalns

1503 0.056

0.057

nd

Cucumber

R, MS, O

Linaloolns

1523 0.157

0.114

0.103

Floral, citrus

R, MS

1-Octanol

1531 0.161a

ndb

ndb

Floral

R, MS

3.891a

1.782b

Sweet, floral

R, MS, O

β-Caryophyllene

1547

(E,Z)-2,6-Nonadienal

1553 0.339a

ndb

ndb

Cucumber

R, MS

α-Caryophyllenens

1618 1.587

1.388

0.222

Sweet, floral

R, MS

4.161a

0.079b

Herb

MS, TI

β-Selinene

1674

5.470a

0.180b

Ethyl phenylacetate 1751 0.150a ndb ndb Fruity, sweet R, MS a b b γ-Octalactone 1881 0.148 0.024 nd Coconut R, MS ARetention indices were determined on TR-FFAP capillary column using n-alkanes C -C as external 7 30 BFlavor reference. descriptors from the Cornell University Flavornet (http://www.flavornet.org/flavornet.html) and the Good Scents Company (http://www.thegoodscentscompany.com/index.html). CThe reliability of the identification proposal is indicated by the following: R, mass spectrum and retention index were consistent with those of an authentic standard; MS, mass spectrum was consistent with that of the NIST library; O, Odor quality perceived at the sniffing-port; TI, tentatively identified from the NIST library and a comparison of retention indices reported in the literature. DNot detected. nsNot significant (p ≤ 0.05). Different letters in the same row indicate significant statistical differences (Tukey's HSD, p ≤ 0.05).EMean concentration values (μg/kg, referred to octyl butyrate).

34


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Figure 1.

35



Figure 2.

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Figure 3.

37



Figure 4.

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Figure 5.

39



For TOC graphic

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Relationship between Sensory Attributes and Chemical Composition

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