What Do We Know about the Chemistry of Strawberry Aroma

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What do we know about the chemistry of strawberry aroma? Detlef Ulrich, Steffen Kecke, and Klaus Olbricht J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b01115 • Publication Date (Web): 13 Mar 2018 Downloaded from http://pubs.acs.org on March 13, 2018

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Journal of Agricultural and Food Chemistry

What do we know about the chemistry of strawberry aroma?

Detlef Ulrich1 Steffen Kecke2and Klaus Olbricht3,4

1

Julius Kühn-Institute, Institute for Ecological Chemistry, Plant Analysis and Stored Product

Protection, Quedlinburg, Germany 2

Julius Kühn-Institute, Data Processing Unit, Quedlinburg, Germany

3

Hansabred GmbH Co. KG, Dresden, Germany

4

Humboldt-Universität zu Berlin, Albrecht Daniel Thaer-Institute, Berlin, Germany

Corresponding Author: 1

(D.U.) Phone: (49) 3946-47231. Fax: (49) 3946-47300. Email: [email protected]

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ABSTRACT 1

The strawberry, with its unique aroma, is one of the most popular fruits worldwide. The demand for

2

specific knowledge of metabolism in strawberries is increasing. This knowledge is applicable for

3

genetic studies, plant breeding, resistance research, nutritional science, and the processing industry.

4

The molecular basis of strawberry aroma has been studied for more than 80 years. Thus far, hundreds

5

of volatile organic compounds (VOC) have been identified. The qualitative composition of the

6

strawberry volatilome remains controversial though considerable progress has been made during the

7

past several decades. Between 1997 and 2016, twenty-five significant analytical studies were

8

published. Qualitative VOC data were harmonized and digitized. In total, 979 VOC were identified,

9

590 of which were found since 1997. However, 659 VOC (67 %) were only listed once (single

10

entries). Interestingly, none of the identified compounds were consistently reported in all of the studies

11

analyzed. The present need of data exchange between ‘omic’ technologies requires high quality and

12

robust metabolic data. Such data are unavailable for the strawberry volatilome thus far. This review

13

discusses the divergence of published data regarding both the biological material and the analytical

14

methods. The VOC extraction method is an essential step that restricts inter-laboratory comparability.

15

Finally, standardization of sample preparation and data documentation are suggested to improve

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consistency for VOC quantification and measurement.

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KEYWORDS: Fragaria ×ananassa Duch., volatile organic compounds, gas chromatography, mass

19

spectrometry, identification

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INTRODUCTION

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The garden strawberry (Fragaria ×ananassa) is one of the most popular fruits and represents a

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significant global economic market. In 2014, the worldwide production was 8.1 million tons

25

(FAOSTAT).1 The unique flavor of strawberries is the primary reason for its high popularity.2

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The garden strawberry emerged in the mid-1700s in Versailles, from an accidental

27

hybridization of the American octoploids, F. chiloensis and F. virginiana.3,4 The hybridization

28

combined some of the most important characteristics of the garden strawberry: large fruits from the

29

Chilean landrace, and a unique, pleasant sweetish aroma deriving from the smaller-fruited, red wild

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Virginia strawberry. This combination cannot be found in other species of the genus although

31

Fragaria species have unique and diverse aroma patterns.5 Due to the combination of high sensory

32

popularity and high nutrition, the health value of the garden strawberry can provide an important

33

component for healthy human nutrition.

34

The chemical basis of strawberry aroma has been a frequently researched topic. The volatile

35

organic compounds (VOC) and their subset, the aroma compounds, were intensively identified and

36

quantified. Early analytical investigations were performed by Coppens and Hoejenbos6 for F.

37

moschata (syn. F. eliator) at the end of the 1920s, and were published about 1939. In his compendium

38

from 1991, Latrasse7 evaluated 54 studies on garden and wild strawberries and reported about 360

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aroma compounds. For the garden strawberry, the review of Zabetakis and Holden8 lists over 80

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studies with about 280 volatiles. Since the end of the 1960s, the number of VOC identified has

41

increased due to improved analytical technology, i.e., gas chromatography-mass spectrometers (GC-

42

MS) coupling. The online database of the Nutrition and Food Research Institute of the Netherlands9

43

(TNO) currently lists 323 VOC for strawberries from 15 substance classes. These have been identified

44

by quadrupole and ion trap mass spectrometers. From the intensity of activities in the field of

45

metabolomics and the introduction of new powerful analytical techniques the identification of more

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‘new’ metabolites are expected10.

47



48

A higher demand for metabolite data also results from modern breeding strategies. The goals

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of many breeding programs now include development of specific individual secondary metabolites or

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metabolite profiles responsible for the health value or sensory quality11,12 .

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Few of the strawberry VOC are consistently identified between studies. For example, in Ulrich

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and Olbricht11 and Schwieterman et al.13, only 28 of 116 total VOC identified were reported in both

53

studies. To date, a comprehensive inventory of the published strawberry volatilome is incomplete,

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despite more than 80 years of metabolite research. Today's analytical techniques provide detailed

55

chemical profiles but compounds are inconsistent between reports. This lack of reliability is an

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obstacle for plant genetics, research, and breeding programs. The identification of metabolic

57

quantitative trait loci (QTL), the candidate genes for valuable metabolites and transcription studies, are

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based on metabolite analysis. Modern breeding strategies for creating new cultivars with a high

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resistance against diseases, high health value, and high sensory quality depend on the implementation

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of powerful and consistent chemical analyses.

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The aims of this review are to provide a detailed overview of strawberry volatilome

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identification and to highlight potential causes of the apparent irreproducibility. Twenty-five studies

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from the past 21 years that have not previously been summarized in review have been included here.

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Based on published methodological information, factors influencing the confirmation of the substance

65

identification are discussed with regard to the sample collection, preparation, and analytical methods.

66 67

Methods

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From 1997 to 2016, more than 250 papers were published concerning strawberry VOC in the context

69

of sensory quality (Web of Science search with descriptor ‘strawberr*’ AND (‘aroma’ OR ‘volatiles’);

70

www.webofknowledge.com; web access 2017-10-20). Of the published manuscripts, 25 studies were

71

chosen for evaluation10,11,13-35. The studies were chosen based on 1) the VOC analyses performed by

72

the authors and 2) reports of strawberry VOC identification. Studies that described the quantitation of

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few individual compounds or a compound class were excluded.36 This approach ensured that studies

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with comparable objectives were included, and that the research focused on the elucidation of the

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strawberry volatilome. 4 ACS Paragon Plus Environment

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Because the evaluated literature covered the past 21 years, a review of Zabetakis and Holden8

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and the TNO database9 were also included to contrast with previous findings. The TNO data contained

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references from 1956 to 1995, plus one publication from Du et al.23 Du et al. did not contain ‘new’

79

compounds in comparison to Zabetakis and Holden8. An approximation for the state of knowledge

80

about VOC identification previous to 1996 was obtained by constructing an association set from both

81

VOC lists.

82

Most published substance sets listed the VOC by chemical name. Because the spelling of the

83

chemical names was inconsistent, each entry was transferred manually into the internationally

84

common chemical abstract service (CAS) registry numbers (http://www.cas.org/content/chemical-

85

substances/). Online databases were searched for the CAS numbers (The Flavornet,

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http://www.flavornet.org/flavornet.html, The Good Scents Company,

87

www.thegoodscentscompany.com/data, The NIST WebBook, https: //www.nist.gov/, PubChem,

88

https://pubchem.ncbi.nlm.nih.gov/, ChemSpider, http://www.chemspider.com/). Obvious literal errors

89

in the names were corrected.

90

For substances with stereo isomers, the unspecified substance name was listed if no reliable

91

isomer determination was possible by mass spectrometric identification. In principle, both CAS

92

numbers for the respective stereo isomers as well as a separate number for the unspecified form are

93

available. If only the unspecified form was mentioned, e.g., hexenal, the compound was assigned to

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the trans-form, i.e., (E)-2-hexenal, to avoid the unspecified substance being counted as a separate

95

entry. In analogy, unspecified lactones were added to the gamma-form. Substance names for which no

96

CAS number was available were included in the overall list under the chemical names given in the

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original study. For statistical analysis, the association set (set union) was constructed from the 27

98

substance lists using an in-house web application (FindIntersection).

99

From the viewpoint of accurate chemical analysis the data on substance identification were not

100

strictly handled in the evaluated literature. For this review, we have adopted the guidelines from

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Molyneux and Schieberle (2007)37 for the nomenclature in the text (Table 2), even though these have

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been used in the original work in a different way. This guideline includes two steps for identification:

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a) mass spectrometric fragmentation and retention indices must be determined on at least two 5 ACS Paragon Plus Environment


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separation columns of different polarity (Table 2, footnotes 1 and 2), and b) comparison of the mass

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spectra and retention indices (RI) with those of authentic reference substances as a so-called co-elution

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(Table 2, footnote 3). Identification on the basis of a simple search in mass spectrometric libraries

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cannot be considered sufficient. Therefore, substances were ‘identified’ when the requirements of

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points a) and b) were met on at least one separation column. Otherwise the substances were described

109

as ‘tentatively identified’.

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For substance quantitation (which is not the main topic of this review), the published studies

111

were also inconsistent. Using gas chromatography-flame ionization detector (GC-FID) or gas

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chromatography-mass spectrometry (GC-MS), the term ‘quantitation’ could be used when

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accompanied by a stable isotope dilution analysis (SIDA) or by the standard addition method. In these

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cases, the terms ‘quantitation’ or ‘quantified’ were used. In other cases, the terms ‘semi-quantitation’

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or ‘semi-quantified’ were applied. Thus, the specification of absolute, quantitative values, such as

116

µg/kg or ng/g is inadmissible if based only on a single internal standard.

117 118 119

Objectives of the VOC analyses

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Strawberry VOC analyses can be grouped into five categories (Table 1)

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1. Sensory quality (aroma, flavor)

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2. Interactions of genes with environment (G x E)

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3. Bioactivity of VOC as signaling or defense substances

124

4. Metabolic analyses for plant genetics and plant cultivation and

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5. Methodological work in the area of VOC analysis

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Schieberle and Hofmann34,39 determined the character impact compounds in strawberry juice by means

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of quantitative measurements (SIDA). Their sensory activity was assessed using the aroma value

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concept which was based on the comparison of metabolite concentrations with their odor thresholds.58

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A total of 15 VOC were fully identified, with no new substances being published in comparison with

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that in the TNO database9 or the review by Zabetakis & Holden.8 For the comparison of the 25

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publications from the methodological point of view38, Schieberle and Hofmann34 was the only 6 ACS Paragon Plus Environment

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comprehensive assessment of the sensory quality of the VOC, including complete identification, exact

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quantitation, flavor concept, and recombination experiments. This study was based on a previous work

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by Schieberle39 using a gas chromatograph-olfactory (GC-O) study in which identical VOC list was

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mentioned except for the mesifuran (2,5-dimethyl-4-methoxy-3(2H)-furanone). Further studies by Ulrich et al.35, Gomes da Silva et al.32, Nuzzi et al.28, Fukuhara et al.30,

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Jouquand et al.27, Zhang, Y.T. et al.26, Li et al.25, Du et al.23, Vandendriessche et al.19, Samykanno et

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al.18, Cannon et al.10, Schwieterman et al.13, and Ulrich and Olbricht11 investigated the VOC patterns

139

with regard to strawberry aroma. The two recent studies by Schwieterman et al.13 and Ulrich and

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Olbricht11 pursue an extended and comparable objective by using adequate instrumental analysis for

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VOC and non-VOC (or aggregate parameters). They also correlated data with a consumer test to

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obtain consumer preference (acceptance).

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GC is the method of choice for VOC analyses. For this purpose sample preparation is of

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crucial importance. In sample preparation, the analytes are isolated from a complex, aqueous matrix

145

and transferred to a water-free GC-capable sample. Concentration of the aroma compounds in

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essential because the VOC occur in the parts per million (ppm) or sub-ppm range. Initially, liquid-

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liquid extraction with organic solvents was used for VOC extraction. Schieberle & Hofmann34, Ulrich

148

et al.35 and Zhang J.J. et al.24 used this method. The bulk of research was carried out by adsorption

149

methods such a solid phase micro extraction (SPME), purge and trap (P&T) and stirbar-sorptive

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extraction (SBSE). Li et al.25 and Cannon et al.10 used isolation of the VOC by solid phase extraction

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(SPE).

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Ozcan and Barringer22 applied static headspace extraction in combination with selected-ion

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flow-tube mass spectrometry (SIFT-MS) and without GC separation. However, the static headspace

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extraction is unsuitable for detecting aroma relevant VOC in the ppm range or below because this

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method has no concentration step.

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A further objective for VOC analysis of strawberries was the determination of specific

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methodological questions in sample preparation, separation, or detection. Nuzzi et al. (2008)28

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evaluated six strawberry genotypes as a model system for comparative analysis of qualitative and

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semi-quantitative results on the aroma activity of VOC obtained on the basis of GC-O, and the 7 ACS Paragon Plus Environment


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calculation of odor activity values. A total of 38 identified VOC were included in the comparison.

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Both methods for the determination of the aroma patterns yielded comparable results. Deviating from

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other studies, Ozcan & Barringer (2011)22 used SIFT-MS as a detection and identification method. A

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total of 41 VOC were examined depending on the variety, the frost storage, and the VOC release in

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mouthspace and nosespace. Measurement of the VOC in the respiratory air was possible because the

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SIFT-MS can be used without pre-concentration and removal of water. Vandendriessche et al.20 used

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an unconventional separation and detection method for investigating the impact of an infection on

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VOC patterns by using the headspace multi-capillary column-ion mobility spectrometry (HS MCC-

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IMS). With this approach, 97 VOC were semi-quantified to identify biomarkers for infection by

169

Botrytis cinera.

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Over the past twenty years, gas chromatography time-of-flight mass spectrometry (GC-

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TOFMS) systems have become increasingly useful as powerful analyzers for substance identification.

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For strawberry, three applications have been described using this technique. In the studies of Song33,

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the application note N. N.17 and Samykanno18, 31, 74, and 124 VOC were identified.

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A major component of strawberry metabolite patterns is genotypically determined. Therefore,

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comparative studies of strawberry varieties were performed (Table 3). In the 25 reviewed studies, 76

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cultivars and 24 breeding clones were analyzed. Fragaria ×ananassa `Camarosa´ (5 times), `Albion´,

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`Chandler´, `Festival´ and `Toyonoka´ (4 times each) were examined most frequently. The analyses of

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cultivars and breeding lines shows that VOC analysis played a major role for breeding research and

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practical cultivation of strawberries.

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Further questions for VOC analysis that are related to both sensorial quality research and

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breeding include ontogenic effects22 and the interaction of genotype by environment (G x E). The

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latter was considered by Jouquand et al.27 and Samykanno et al.18. This work is a prerequisite for a

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metabolite-directed selection in the breeding process, because environmentally dependent metabolites

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are unsuitable as separate breeding objectives.

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General survey of the identified VOC The TNO database9 and the review by Zabetakis and Holden8 were state of the art 8 ACS Paragon Plus Environment

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determinations for VOC identification until 1996, with 307 and 275 substances listed. By creating the

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association set from the lists of both publications, 389 VOC were identified in strawberries previous to

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this review.

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The 25 studies evaluated for this review listed between 15 and 124 identified VOC. In

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contrast, Cannon et al.10, observed 553 substances (Figure 1). For their analysis, 100 kg fruit of the

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cultivar `Ciflorette´ were extracted by means of dichloromethane and then separated into 125 fractions

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using solid phase extraction (SPE). Subsequently, fractions were separated by means of two-

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dimensional GC (2D-GC) on two separation columns of different polarity and detected by quadrupole

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MS. Out of the 553 VOC, six substances could be fully identified by co-elution and the remaining 547

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VOC were tentatively identified by means of a library search and retention index (RI) comparison.

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Thus, Cannon et al.10 provided the most comprehensive identification of the strawberry volatilome,

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listing 322 compounds which were (tentatively) identified in strawberry for the first time.

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The complete strawberry volatilome to date, including those compounds found previous to

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1996 (389 VOC), totals to 979 VOC. Thus, the strawberry is one of the most thoroughly studied fruits

202

in the plant kingdom. The frequency of the 30 most often identified VOC is summarized (Table 4).

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The most frequently found substances in strawberries are the methyl and ethyl esters of hexanoic and

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butanoic acids with 24 to 22 entries. The thirty most frequently analyzed compounds included esters

205

(17, 15 straight chain and 2 branched), acids (4), lactones (2), aldehydes (2), furans (2), alcohols (1),

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ketones (1) and terpenoids (1), while on the other extreme, 670 substances occurred only once.

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Surprisingly, none of the 979 VOC was co-mentioned in all of the 27 evaluated literature sources; 959

208

compounds were co-mentioned in fewer than half of the reports. Thus, only a partial consensus

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concerning the qualitative composition of the strawberry volatome was reached among researchers,

210

despite their intensive analytical work. Possible causes for this discrepancy are subsequently

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discussed.

212 213 214 215

Studies using GC-O and the flavor value concept In seven studies, the aim was to separate the aroma-active VOC, called character impact compounds or key compounds, from a larger number of identified substances10, 21, 23, 28, 30, 34, 35. For this 9 ACS Paragon Plus Environment


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purpose, the aroma value concept58 including the determination of odor activity values as well as the

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GC-O approach were applied. Both methods lead to an improvement of the compound identification

218

because reference substances must be used, or because the odor quality is added as an additional filter

219

for identification when using GC-O. Nuzzi et al.28 and Schieberle and Hofmann34 compared the odor

220

activity values (OAV) using GC-O. These two studies showed that the different methods provided

221

similar results for the character impact compounds. Nuzzi et al.28 confirmed this although only semi-

222

quantitative data were used to determine the OAV.

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Between 12 and 48 VOC were determined as character impact compounds in individual

224

studies (Figure 2). Seven publications listed 105 character impact compounds. Only one substance,

225

ethyl butanoate, was co-listed in complete consensus in these seven studies. While 36 VOC were

226

found more than in one study, 69 compounds were single entries. Thus, the research on character

227

impact compounds also exhibited the same trend as for the general VOC identification without

228

consideration of the olfactory properties. Only a few substances were listed in consensus. Between 66

229

% and 67 % of the identified compounds are single entries, i. e. they were only identified in one study

230

(69 out of 105 in the seven GC-O studies and 659 out of 979 of all 27 reviewed literature sources).

231 232 233

Influencing factors on substance identification The quantitative and qualitative composition of the plant metabolome is subject to complex

234

influencing factors. These include, on the one hand, factors which determine the quality of the test

235

material, such as the genotype and the environmental influences. The environmental influences

236

(‘outside’ influences) include cultivation, harvesting, storage conditions, maturity and

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phytopathological status. On the other hand, the results of metabolic analyses are also known to be

238

influenced by the analytical method. Important parameters are VOC extraction (cleanup), gas

239

chromatographic separation, detection and data processing. Some of the essential parameters are

240

summarized in Table 2.

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Genotype. VOC data from 71 cultivars and 30 breeding clones have been published since 1997

242

(Table 3). In all studies that investigate several genotypes, the genotype has been described as a key

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influencing factor on the quality and quantity of the aroma patterns. The most commonly analyzed 10 ACS Paragon Plus Environment

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cultivars were F. ×ananassa ‘Albion’11, 13, 16, 22, ‘Chandler’11, 14, 22, 32, ‘Festival’11, 13, 14, 23, 27, and

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‘Toyonoka’24, 25, 26, 30 which were evaluated in four independent studies and ‘Camarosa’11, 13, 14, 21, 22 in

246

five. However, the lists of the identified VOC for the respective cultivars also show only a low

247

qualitative correspondence. This is an indication that other variables beside the genotype influenced

248

the results.

249

Sampling size. Obtaining a consistent representative sample is an important prerequisite for

250

chemical analysis. The minimum sample size in chemical analysis depends on the accuracy of the

251

method, particle size, and homogeneity.40,41 If guidelines from the area of solids analytics were to be

252

adopted for a typical strawberry fruit size of about 30 mm, a sample in the range of ten kg to several

253

hundred kg would be needed.41 The actual sample sizes reported were between 0.5 g and 100 kg

254

(Table 2). Four of the 25 studies used a sample size in the kilogram range but other sample sizes were

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in the range of a single fruit or the size of few grams. Fruit-to-fruit variations have been published for

256

VOC content and dry mass.42,43 These effects are more quantitative than qualitative. However,

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qualitative effects may occur if a sample size was too small and results dropped below detection limit.

258

Maturity. Fruit composition varies during maturation.22,57 Differences in the results may be

259

due to differential fruit maturity. Strawberries are not commonly evaluated using Brix value. Though

260

Nuzzi28 evaluated the total soluble solids (TSS) values as ‘ripening index’, he did not use this as a

261

consistent harvest criteria. In several studies18, 20, 22, 23, 24, 25, 28 fruit color was judged prior to harvest.

262

Harvest influence within the season. Environmental influences cause qualitative and

263

quantitative effects on the metabolite patterns and also on the results of substance identification.44 A

264

partly solution for this special problem can be the analysis of a batch sample containing all mature and

265

healthy fruits of the season.16,44 Thus, the influence of the harvesting time during the season could be

266

eliminated. Investigations on material of unknown provenance, species designation and cultivation site

267

(Table 3) are basically problematic with regard to reproducibility.

268

Storage. Studies on the aroma of the strawberries were mostly performed on fresh fruit. In 9 of

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24 studies, frozen material was used. Freezing was used to bridge the period between harvest and

270

instrumental analysis. Regarding the VOC patterns, proper freezing at -25 °C is a viable option



271

because, contrary to the sensory quality, the patterns of the volatiles are less influenced by this

272

process.45

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Homogenization. For the cleanup step, the fruits were mostly homogenized and mixed with

274

inorganic salts (calcium chloride, sodium chloride, tin chloride, and sodium flouride) to suppress

275

enzyme activity. Some studies used quartered and some undamaged fruits. With whole fruits used for

276

VOC analysis, the analogy to sensory quality in consumption was lost, because the process of

277

homogenization affects the VOC patterns, e. g. by influencing lipoxygenase activity (LOX). In this

278

case 17,33, the VOC pattern corresponds more to the orthonasal perception (smell) rather than the flavor

279

when consumed (retronasal).

280

VOC isolation. The method of choice for VOC analysis is GC. The preparation of a GC-

281

capable sample is associated with isolation and concentration as well as transfer into a water-free

282

matrix. The cleanup process is the decisive and most complex step regarding the result of the analysis.

283

For this reason, a number of attempts were made to develop effective methods for VOC analysis

284

without time-consuming cleanup. These techniques have not been established for a well-founded

285

metabolome analysis, but they can be used for certain purposes, such as the determination of

286

maturity.46,47

287

The classical method for VOC isolation is liquid-liquid extraction (LLE). Here the extraction

288

power depends on the polarity of the extraction solvent. The disadvantages are the high workload, the

289

lack of automation, and the extraction of non-volatile compounds. The LLE is unsuitable for a high

290

throughput method and is therefore used for basic investigations with a small sample number.

291

Nevertheless, the best results with regard to quality (number of extracted VOC) and quantity (high

292

recovery rates) can be achieved by means of LLE.

293

In addition to LLE, adsorption methods are used for VOC isolation. These include purge-and-

294

trap methods (dynamic headspace), solid-phase extraction (SPE), and stirbar-sorptive extraction

295

(SBSE). Since the market launch of solid phase micro extraction (SPME) for water analysis in 1993,

296

this technique has been used in many applications, and is widely used in the VOC analysis of plant

297

material. Ten out of the 25 evaluated studies used this technique for isolation. The wide distribution of

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the SPME technique is due to its easy handling without solvent use, including the possibility of 12 ACS Paragon Plus Environment

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automation. A disadvantage of the SPME, as with all adsorption methods, is the strong discrimination

300

effect for individual substances or substance classes in complex matrices. This effect is particularly

301

pronounced for SPME due to its design and leads to insufficient extraction of polar compounds like

302

acids and furanones because of very low recovery rates. Exact quantitation of VOC in complex

303

matrices is impossible due to the bias in combination with the limited adsorption capacity of the

304

SPME fibers. A comparison of SPME with other isolation techniques was published for strawberry

305

and other crops.48-50 Although the SPME technique is subject to severe restrictions for complex

306

systems, such as the strawberry matrix, this technique is often used in a completely uncritical manner,

307

without accounting for the limitations on the recovery rates or substance identification.

308

Separation. Apolar, medium-polar and polar separation columns were used for

309

chromatographic separation. For a complete substance identification by means of MS in the sense of a

310

good analytic practice, independent separation and identification was required on two separation

311

columns of different polarities.37 This approach reduces the likelihood of false identifications due to

312

peak overlapping, particularly in the case of automatic library searches. These requirements were not

313

fully met by any of the 25 studies.

314

Mass spectrometric detection. For identification, quadrupole-, ion trap-, TOF- and a SIFT-MS

315

were used. Due to its high mass resolution and high scan rate, the TOF-MS technique is preferred for

316

the identification of a large number of mass fractions. At the same time, the limitation of the

317

chromatographic separation capacity of the GC column can be counteracted by deconvolution. GC-

318

TOF-MS systems were used in three studies in which 31, 74, and 124 VOC were identified. 17,18,33

319

However, the largest number of identified VOC (553) was obtained by Cannon et al. 10 using

320

quadrupole-MS detector, by means of a complex cleanup method in combination with a 2D GC.

321

Details on the quality of the reported substance identification are given in the following section.

322

Quantitation. An exact quantitation in gas chromatography is only possible by co-elution of

323

isotope-labeled references (stable isotope dilution analysis) or by the standard addition method. In the

324

studies considered here, Schieberle and Hofmann (1997)34 and Li et al. (2009)25achieved these

325

conditions. The remaining reports share semi-quantitative data, even if the original work did not

326

provide any information or (incorrectly) specify a concentration unit. 13 ACS Paragon Plus Environment


Page 14 of 36

327

Artifacts. One problem is the distinction between genuine VOC and artifacts. For this purpose,

328

the execution of suitable blank analyses, possibly using statistical evaluation methods, must be carried

329

out. Some lists contain ethanol and acetone, which are possible artifacts. Thermal reactions can also be

330

a cause of artifact formation in the GC injector. Thus, when the SPME technique is not applied

331

appropriately (fruit particles on the fiber surface), by thermal degradation, furanones maybe formed

332

from sugars51 adhering to the fiber or injection needle of the SPME device. At > 160 °C, furanones

333

may decompose into a variety of small molecules, including acetone and other ketones, as well as

334

alkylfuranones.52 The formation of furans was reported as artifacts when using SPME as sample

335

preparation method.59 The reviewed lists of identified VOC also contain phthalates and biphenyl

336

which may originate from plasticizers, agrochemicals or food additives. Because no information is

337

given on the blank-analyses in most studies, it cannot be ruled out that the list of the 979 identified

338

VOC in strawberry contains a series of artifacts.

339 340

Quality of GC-MS identification in the evaluated studies

341

Coupling GC and MS is the method of choice for VOC identification. Identification

342

techniques provide different confidence levels. The highest level is reached when the identity of the

343

molecule is validated by co-elution of an authentic standard substance and subsequent MS analysis

344

(confirmed identification or fully identified). A lower level is achieved when a structure is proposed

345

only by spectral similarities present in a database (tentative, provisional or putative identification).

346

Table 2 shows the level of mass spectrometric identification in three stages. Using co-elution of

347

authentic references with proof of origin of reference compounds (Table 2, level 3) represents the

348

highest level and corresponds to the requirements of Molyneux and Schieberle37 for an exact

349

identification on one column type. None of the studies provided full results of identifications on two

350

separation columns of different polarities. Furthermore, some of the studies are based solely on the

351

comparison of mass spectrometric fragmentation with library data or do not provide any information

352

for identification (Table 2).10,13,17,22,32,35 The inclusion of retention data for the qualification of the MS

353

identification was carried out in the remaining papers. The co-elution of authentic reference substances

354

is mentioned in 15 studies, but only a part of the published VOC could be covered in some papers. 14 ACS Paragon Plus Environment

Page 15 of 36


355

Information on the reference substances used and their origin or synthesis is only available in two

356

studies.10,34 More detailed identification studies for chiral compounds are not reported. The addition of

357

odor qualities for flavor-active VOC, as discussed for GC-O, is another way to improve the

358

identification of flavor substances.

359 360

Conclusion

361 362

In conclusion the most important reasons for the low conformity in the substance identification which was documented here are the following:

363

-

use of different genotypes

364

-

influence of different environmental settings (G x E)

365

-

sample preparation inconsistencies

366

-

use of different MS types

367

-

uncritical use of identification methods

368

-

artifacts

369

The progress in analytical techniques and bioinformatics has led to the development of

370

metabolomics and thus to the increased application of this approach in many areas. The exchange of

371

data with other "omics approaches" is currently boosting scientific progress. A key issue for chemical

372

analysis is substance identification, which represents a challenge for the analysis of VOC in complex

373

biological systems.

374

In the last twenty years, many more VOC substances in strawberries have been identified

375

(Figure 1). The volatilome of the strawberry is one of the most frequently investigated plants. Prior to

376

2016, more than 979 VOC were identified, As literature has shown, however, publications have little

377

consensus on defining primary compounds. This situation is scientifically unsatisfactory and leads to

378

inconsistent results in analyses using metabolite data. This inconsistent information is

379

disadvantageous, especially for plant genetics and breeding. Metabolic data are increasingly being

380

sought for functional genomics and breeding for flavor. Because approximately 67 % of the published

381

VOC were reported in only one study and no single substance was found in all of the 27 evaluated

382

sources, the reproducibility becomes a serious question. 15 ACS Paragon Plus Environment


Page 16 of 36

383

The qualitative and quantitative factors influencing the results of the VOC analyzes, as

384

discussed above, can be grouped into two classes: a) the biological system through internal (genotype)

385

and external (environment) factors causes a considerable diversity of the metabolite patterns. b) the

386

results are significantly influenced by the analytical method used.

387

a) The influences on biological variability are complex because of the gene-by-environment

388

interactions (GxE) and inherent to the system. Both variables (G x E) can produce both quantitative

389

and qualitative variability, individually and in their combination. This influence cannot be eliminated

390

and must be statistically verified by means of an adequate test design (multi-year, multiple-order,

391

number of biological repetitions). In the 25 studies, 18 used only a single sample from a single harvest

392

date for analysis which can be the reason for qualitative differences.44 A partial solution for this

393

problem was suggested by Ulrich and Olbricht16,44 using the analysis of a batch sample containing all

394

mature and healthy fruits of the season (pooling). Thus, the influence of the harvesting time during the

395

season could be mitigated. Investigations on material of unknown provenance, species designation and

396

cultivation site (Table 3) are basically problematic with regard to reproducibility.

397

b) The influences introduced by the chosen analytical method are significant. All of the

398

influencing factors discussed above can cause quantitative and qualitative effects on the result and can

399

reinforce each other. To minimize the methodological problems an adequate test design has to be

400

chosen. The basis for reproducible analysis is taken during sampling and clean-up. Errors that are

401

introduced in this step cannot be eliminated in the further process of analysis by applying sophisticated

402

detectors and algorithms for data processing. If sufficient material is available, a maximum sample

403

size should be selected with a subsequent sample division. When investigating the strawberry

404

volatiles, sample sizes of 0.5 g to 100 kg were used. However, sometimes analytical experiments with

405

very small sample sizes, especially in genetics and breeding, in single plant experiments of a

406

population or of wild material are necessary. Often, biological replicates may not be possible. If

407

metabolic analysis is carried out, the analytical reliability of the results must be discussed. The

408

extraction method appeared to exert the greatest influence. A reference to this was the large number of

409

identified substances in the work of Cannon et al.10, in which more than 500 VOC could be detected

410

by applying a large sample quantity in combination with an elaborated extraction technique. In 16 ACS Paragon Plus Environment

Page 17 of 36


411

comparison, the use of fast and simple isolation methods such as the headspace SPME must be viewed

412

critically. Even the most widely used detection by MS can be seen as a cause of divergent results. The

413

technically complex MS detectors often have lower stability than GC standard detectors, e.g., flame

414

ionization detector. Even mass spectrometers of the same manufacturer and type can produce different

415

results depending on the degree of pollution and tune-set. In the totality of the methodological

416

variables discussed above, these factors are a cause of the high inter-laboratory variability.

417

Completely standardized methods such as proposed in the Metabolomics Standards Initiative (MSI)

418

have so far not been used in the field of aroma analysis.53,54 However, the scientific methodology

419

requires the development and exchange of reproducible and falsifiable data, which is obviously not the

420

case for the 659 single entries in the strawberry volatilome. The compound patterns recorded by

421

instrumental analysis are highly dependent on the procedures used. Therefore, the use of a

422

standardized method for the production of test material (genotype, cultivation method) can be useful

423

for studies on genetics and breeding (marker, transcriptomics).

424

Distinct analytical techniques cannot cover the full metabolome and any other characteristic of

425

the plant material. Until now standard operating procedures (SOP) for analysis have not been widely

426

accepted.55 The standardization of protocols to guide data production, quality and robustness is central

427

to coordinating efforts between scientists working in different laboratories. In chemical analysis, SOP

428

can help narrow down the divergence. The focus here must be on sample preparation and VOC

429

extraction. The occurrence of artifacts must be examined by careful methodological experiments.

430

Finally, the quality of generated data must be evaluated. The level of substance identification by MS

431

(confirmed or tentative identification) should be indexed. Also results which are cited in secondary

432

literature should indicate the quality of substance identification to prevent an inflationary increase of

433

tentatively identified substances in substance lists and databases. The consequence is repeated

434

misidentification and misapplication in other areas of science. These errors would misdirect the

435

mapping of metabolic QTLs, the study of candidate genes, the transcriptomics, and the marker-

436

assisted selection in plant breeding.

437 438 439



440

Page 18 of 36

Abbreviations Used

441 442

2D-GC – two-dimensional gas chromatography

443

CAS – chemical abstracts service

444

FID – flame ionization detector

445

GxE – gene by environment interaction

446

GC – gas chromatography

447

GC-O – gas chromatography olfactometry

448

LLE – liquid-liquid-extraction

449

LOX - lipoxygenase

450

MS – mass spectrometry

451

OAV – odor activity values

452

P&T – purge and trap

453

Q-MS – quadrupol mass spectrometry

454

QTL – quantitative trait loci

455

RI – retention index

456

SBSE – stir bar sorptive extraction

457

SIFT-MS – selected ion flow tube-mass spectrometry

458

SPE – solid phase extraction

459

SPME – solid phase microextraction

460

SOP – standard operation procedure

461

SQ – semi-quantitation

462

TOF – time of flight

463

VOC – volatile organic compounds

464 465

Acknowledgment

466

The authors wish to thank Kirsten Weiß for the careful analysis of the original data.


Page 19 of 36

467


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468 469

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(28) Nuzzi, M.; Lo Scalzo, R.; Testoni, A.; Rizzolo, A. Evaluation of Fruit Aroma Quality: Comparison Between Gas Chromatography-Olfactometry (GC-O) and Odour Activity Value (OAV) Aroma Patterns of Strawberries. Food Analytical Methods 2008, 1, 270-282.

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(30) Fukuhara, K.; Li, X. X.; Okamura, M.; Nakahara, K.; Hayata, Y. Evaluation of odorants contributing to 'Toyonoka' strawberry aroma in extracts using an adsorptive column and aroma dilution analysis. J. Jpn. Soc. Hortic. Sci. 2005, 74, 300-305.

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612 613 614

(57) Aharoni, A.; Giri, A. P.; Verstappen, A. P. G.; Bertea, C. M.; Sevenier, R.; Sun, Z.; Jongsma, M. A.; Schwab, W.; Bouwmeester; H.J. Gain and Loss of Fruit Flavor Compounds Produced by Wild and Cultivated Strawberry Species. The Plant Cell 2004, 16, 3110-3131.

615 616 617 618

(58) Rothe , M. Aroma values – a useful concept? Die Nahrung 1976, 20, 259-266. (59) Adams, A.; Van Lancker, F., De Meulenaer, B., Owzarek-Fendor, A.; De-Kimpe, N. On-fiber furan formation from volatile precursors: a critical example of artefact formation during Solid-Phase Microextraction. J Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2012, 897, 37-41.

619 620 621


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622 623

Figure captions

624 625

Figure 1: Cumulative sum of the number of VOC identified in strawberries.

626 627

Figure 2: Character impact compounds identified in strawberries using GC-O. Studies: A - Ulrich et

628

al.35; B - Schieberle and Hofmann34; C - Fukuhara et al.30; D - Nuzzi et al.28; E - Du et al.23; F - Cannon

629

et al.10; G – Ubeda et al.21. Red bars – tentatively or complete identified compounds.

630



Page 24 of 36

Tables Table 1: Compilation of scientific aims for F. ×ananassa VOC measurements no ref study year aim 1 34 Schieberle & Hofmann 1997 Quantitation of selected key flavor compounds 2 35 Ulrich et al. 1997 VOC analysis for flavor breeding (key compounds) 3 33 Song et al. 1998 Test of SPME as rapid method 4 32 Gomes da Silva et al. 1999 VOC profile of ‘Oso Grande’ in comparison to ‘Selva’ and ‘Chandler’ (aroma properties) 5 31 Hakala et al. 2002 VOC profile of ‘Senga sengana’ in comparison to 5 others. Geographical origin, processing 6 30 Fukuhara et al. 2005 VOC profile of ‘Toyonoka’ by SPE 7 29 de Boishebert 2006 Characterization of varieties (SPME and data processing like Kohonen map) 8 28 Nuzzi et al. 2008 Comparison of GC-O with OAV 9 27 Jouquand et al. 2008 Eating quality and harvest date GxE (genotype & harvest date) 10 26 Zhang,YT et al. 2009 VOC profile comparison (aroma) 11 25 Li, et al. 2009 Estimation of key compounds in ‘Toyonoka’ 12 24 Zhang, JJ et al. 2010 Aroma development during maturation 13 23 Du et al. 2011 VOC-profiles of 2 varieties (aroma) 14 22 Ozcan &Barringer 2011 VOC-profiles depending on varieties, storage, ripening stages. SIFT-MS 15 20 Vandendriessche et al. 2012 SPME IMS and SPME-fastGC-MS 16 21 Ubeda et al. 2012 Study of glycosidic precursors and free aroma compounds 17 19 Vandendriessche et al. 2013 VOC-analysis for flavor breeding 18 17 N. N. 2013 Odour profiling with TOF-MS 19 16 Samykanno et al. 2013 GxE interaction on VOC. Flavor breeding and production 20 15 Ulrich & Olbricht 2013 Metabolic diversity for breeding 21 14 Mishra & Kar 2014 Quality changes during storage 22 10 Cannon et al. 2014 In-depht analysis of VOC, VSC 23 11 Schwieterman et al. 2014 VOC-analysis and acceptance for breeding 24 13 Oz et al. 2016 VOC-profiles of 8 cultivars (aroma) 25 12 Ulrich & Olbricht 2016 VOC-profiles and acceptance for breeding

24


Page 25 of 36


Table 2: Compilation of material and methods for F. ×ananassa VOC measurements no ref 1 34 2 35 3 33 4 32 5 31 6 30 7 29 8 28 9 27 10 26 11 25 12 24 13 23 14 22 15 20 16 21 17 19 18 17 19 16 20 15 21 14 23 11 22 10 24 13 25 12

study

year

material

storage

homogenisation

sample size

Schieberle & Hofmann Ulrich et al. Song et al. Gomes da Silva et al. Hakala et al. Fukuhara et al. de Boishebert Nuzzi et al. Jouquand et al. Zhang,YT et al. Li, et al. Zhang, JJ et al. Du et al. Ozcan & Barringer Vandendriessche et al. Ubeda et al. Vandendriessche et al. N. N. Samykanno et al. Ulrich & Olbricht Mishra & Kar Schwieterman et al. Cannon et al. Oz et al. Ulrich & Olbricht

1997 1997 1998 1999 2002 2005 2006 2008 2008 2009 2009 2011 2011 2011 2012 2012 2013 2013 2013 2013 2014 2014 2015 2016 2016

1 unknown cultivar 3 cultivars (and 1 F. vesca accession) unknown cultivar 3 cultivars 7 cultivars 1 cultivar 14 cultivars and 8 breeding clones 4 cultivars and 2 breeding clones 3 cultivars and 5 breeding clones 4 cultivars 1 cultivar 1 cultivar 2 cultivars unknown cultivar 1 cultivar 4 cultivars 1 cultivar 1 cultivar 2 cultivars 5 cultivars (and 16 F. vesca accessions) 2 cultivars 35 cultivars and 3 breeding clones 1 cultivar 8 Cultivars 10 cultivars and 6 breeding clones

fresh fresh fresh frozen frozen frozen frozen fresh fresh frozen frozen frozen fresh fresh fresh fresh fresh fresh frozen frozen fresh fresh fresh ? fresh

yes, with CaCl2 yes, with NaCl no, whole fruit yes yes yes yes quartering yes, with CaCl2 yes yes quartering yes, with NaCl/NaF yes, with SnCl2 no whole fruit yes yes, with NaCl whole fruit ? yes, with NaCl yes yes yes, with CaCl2 ? yes

1 berry to 500 g 200 g 100 g 100 g 200 g 50 g 100 g 1500 g 80 g 8.3 g ? 0.5 g 200 g 55 g 1 fruit 80 g ? 1 fruit 5 fruits 10 g to 300 g 10 000 g 7 fruits or 100 g 100 000 g ? > 1 000 g

VOC isolation LLE (diethyl ether) LLE (Freon) HS-SPME (DVB) P&T (Tenax) P&T (OV-1 and OV-25) SPE (Porapak Q) HS-SPME (DVB) P&T (Anasorb CSC) HS-SPME (DVB/Car/PDMS) HS(?)-SPME SPE (Porapak Q) LE4) HS-SPME (DVB/Car/PDMS) static-HS HS-SPME (DVB/Car/PDMS) P&T (Lichrolut EN) HS-SPME (DVB/Car/PDMS) P&T (Tenax) HS-SPME (PDMS/DVB) imm-SBSE (HS?)-SPME (PDMS) P&T (HaySep) SPE (silica) HS-SPME imm-SBSE

25



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Table 2 (continued): Compilation of material and methods for strawberry VOC measurements no ref GC separation MS identification quantitation sum of VOC1) new VOC1) IT-MS 1, 2, 3 µg/kg by SIDA 15 0 1 34 polar and mid polar 2 Q-MS 1 SQ, IST 23 1 35 polar 3 TOF-MS 1, 2 SQ in % 31 5 33 mid polar polar and mid polar IT-MS 1 SQ in % 95 31 4 32 5 Q-MS 1, 2, (3) SQ, relative peak areas 39 3 31 mid polar Q-MS 1, 2, (3) no 48 9 6 30 polar 7 IT-MS 1, 2, (3) SQ, peak heights 23 1 29 mid polar 8 Q-MS 1, 2 EST2) 32 6 28 unpolar 9 Q-MS 1, 2 SQ, IST 69 7 27 mid polar 10 26 mid polar Q-MS 1, 2, (3) SQ in % 50 12 11 25 polar 20 1 Q-MS 1, 2, (3) µg/kg by EST5) 12 24 mid polar Q-MS 1, 2, (3) µg/g by IST5) 50 43 13 23 polar Q-MS 1, 2, (3) SQ, relative concentrations 54 5 14 22 no SIFT-MS 16) ppb on the basis of kinetic data 41 4 15 20 unpolar Q-MS 1, 2 SQ, absolute peak areas 97 22 16 21 polar IT-MS 1, 2, (3) µg/kg2) 28 7 17 19 unpolar Q-MS 1, 2 SQ, relative peak areas 62 3 18 17 mid-polar Q-MS and TOF-MS 1 SQ, peak areas and ‘approx. conc.’ in ng/g 74 14 19 16 unpolar and polar (2D) TOF-MS 1, 2, (3) SQ, relative peak areas 124 40 20 15 polar Q-MS 1, 2, (3 partly) SQ, peak areas 65 21 21 14 mid-polar Q-MS 1, 2, (3) SQ, IST 24 2 23 11 mid polar Q-MS 1, 2, (3) ng/gFW*h by EST5) 75 6 22 10 apolar and mid polar (2D) Q-MS 17) SQ, relative percentage 553 322 24 13 ? Q-MS ? SQ in % 63 23 25 12 polar Q-MS 1, 2, (3 partly) SQ, peak areas 64 6 Abbreviations: IT-MS: ion trap MS; Q-MS: quadrupol MS, SIFT-MS: flow tube MS; TOF-MS: time of flight MS: SQ: semi-quantitation. Identification: 1: MS library search, 2: retention indices from literature, 3: co-elution of authentic references with proof of origin of reference compounds. Number in brackets means that no details and/or no origin are reported. 1) Counting of substance numbers is in accordance with the JKI data base. These quantities sometimes differ from those which are given in the original publications.

26


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2)

No details or recovery rates are given. 3) ‘Troyonoko’ possibly is a scribal error of the Japanes cultivar ’Toyonaka’. 4) Freezing with liquid nitrogen and grinding following by liquid extraction of the frozen powder with petroleum ether and cyclohexane. 5) No recovery rates are given. 6) Identification on the basis of positive charged product ions. 7) Out of 563 VOC 6 new compounds were fully identified by synthesis and NMR characterization.

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Table 3: Cultivars of F. ×ananassa used for VOC analysis no ref study year material 1 34 Schieberle & Hofmann 1997 unknown cultivar (Spain) from local market 2 35 Ulrich et al. 1997 Elsanta, Polka, Senga Gourmella (and 1 accession of F. vesca) 3 33 Song et al. 1998 unknown cultivar 4 32 Gomes da Silva et al. 1999 Chandler, Oso Grande, Selva 5 31 Hakala et al. 2002 Bounty, Honeoye1), Jonsok1), Korona, Polka1), Senga Sengana 6 30 Fukuhara et al. 2005 Toyonaka 7 29 de Boishebert 2006 Cal Giant3, Capitola, Ciflorette, Cifrance, Cigaline, Cigoulette, Cilady, Ciloe, Cireine, Darselect, Earliglow, Madeleine, Naiad, Pajaro and 8 breeding clones 8 28 Nuzzi et al. 2008 Alba, Darselect, Dora, Eva and 2 breeding clones 9 27 Jouquand et al. 2008 Festival, Rubigem, Sugarbaby and 5 breeding clones 10 26 Zhang,YT et al. 2009 Allstar, Toyonoka, Xingdu1, Xingdu2 11 25 Li, et al. 2009 Toyonaka 12 24 Zhang, JJ et al. 2010 Troyonoka2) 13 23 Du et al. 2011 Festival, Radiance 14 22 Ozcan 2011 Albion, Camarosa, Chandler, Sweet Charlie 15 20 Vandendriessche 2012 Elsanta 16 21 Ubeda 2012 Camarosa, Candonga, Fuentepina, Sabrina 17 19 Vandendriessche 2013 Charlotte 18 17 N. N. 2013 unknown cultivar 19 16 Samykanno 2013 Albion, Juliette 20 15 Ulrich & Olbricht 2013 Alba, Elegance, Frau Mieze Schindler, Mara de Bois, Polka (and 16 F. vesca accessions) 21 14 Mishra 2014 Camarosa, Chandler 22 10 Cannon 2014 Ciflorette 23 11 Schwieterman 2014 Albion, Benicia, Camarosa, Camino Real, Chandler, Charlotte, Darselect, Elyana, Evie2, Festival, Galetta, Mara des Bois, Mojave, Monterrey, Portola, Proprietary1, Proprietary2, Proprietary3, Proprietary4, Proprietary5, Proprietary6, Radiance, Red Merlin, Rubygem, San Andreas, Sweet Anne, Sweet Charlie, Treasure, Ventana, Winter Dawn, Winterstar and 3 breeding clones 24 13 Oz 2016 Albion, Camarosa, Festival, Fortuna, Rubygem, Sabrosa, Sweet Ann 25 12 Ulrich & Olbricht 2016 Clery, Daroyal, Elegance, Elianny, Elsanta, Evie2, Frau Mieze Schindler, Honeoye, Rumba, Sonata and 6 breeding clones 28


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1)


in addition also from organic cultivation, 2) scribal error of ‘Toyonoka’

29



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Table 4: Most frequently identified VOC in strawberries # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

substance methyl hexanoate ethyl hexanoate ethyl butanoate methyl butanoate linalool γ-decalactone hexyl acetate γ-dodecalactone DMMF (E)-2-hexenal butyl acetate DMHF ethyl 3-methylbutanoate ethyl 2-methylbutanoate hexanoaic acid methyl octanoate 2-methyl butanoic acid ethyl acetate hexanal butanoic acid (E)-2-hexen-1-ol ethyl octanoate butyl butanoate octyl butanoate 2-heptanone benzyl acetate (E)-2-hexenyl acetate methyl pentanoate pentyl acetate acetic acid

CAS 106-70-7 123-66-0 105-54-4 623-42-7 78-70-6 706-14-9 142-92-7 2305-05-7 4077-47-8 6728-26-3 123-86-4 3658-77-3 108-64-5 7452-79-1 142-62-1 111-11-5 116-53-0 141-78-6 66-25-1 107-92-6 928-95-0 106-32-1 109-21-7 110-39-4 110-43-0 140-11-4 2497-18-9 624-24-8 628-63-7 64-19-7

entries1 24 24 23 22 22 21 19 18 18 18 17 17 16 16 15 14 14 14 14 13 13 12 12 12 12 12 12 12 12 12

sum of entries in 25 studies from 1997 to 2016, in the review of Zabetakis (1997)8 and in the TNOdatabase9. DMMF - 2,5-dimethyl-4-methoxy-3(2H)-furanone , DMHF - 2,5-dimethyl-4-hydroxy3(2H)-furanone. 1)


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Figure 1



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Figure 2


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TOC Graphic



Progress of number of VOCs identified in strawberries. 254x190mm (96 x 96 DPI)


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Character impact compounds identified in strawberries using GC-O. Studies: A - Ulrich et al. (1997)35; B Schieberle and Hofmann (1997)34; C - Fukuhara et al. (2005)30; D - Nuzzi et al. (2008)28; E - Du et al. (2011)23; F - Cannon et al. (2014)10; G – Ubeda et al. (2012)21. Red bars – tentatively or complete identified compounds. 190x254mm (96 x 96 DPI)



TOC Graphic 254x190mm (96 x 96 DPI)


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What Do We Know about the Chemistry of Strawberry Aroma

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