Avocados Australia

HAL Project AV06025

Australian consumers’ perceptions and preferences for ‘Hass’ Avocado

Coordinated and Managed by: Joanna Embry. Avocados Australia Limited PO Box 8005 Woolloongabba QLD 4102 P: 07 3846 6566 F: 07 3846 6577 E: admin@avocado.org.au

July 2007

Project details Project Name: Australian consumers’ perceptions and preferences for ‘Hass’ Avocado Project Number: AV06025 Date: July 2007 Funding: This project was funded by levies from the Australian avocado growers

and matched by the Australian Government through Horticulture Australia Limited

DISCLAIMER Any recommendations contained in this publication do not necessarily represent current HAL or Avocados Australia Limited policy. No person should act on the basis of the contents of this publication, whether as to matters of fact or opinion or other content, without first obtaining specific, independent professional advice in respect of the matters set out in this publication.

Australian consumers’ perceptions and preferences for ‘Hass’ Avocado

Harker FR, Jaeger SR, Hofman P, Bava C, Thompson M, Stubbings B, White A, Wohlers M, Heffer M, Lund C, Woolf A

June 2007 Report to Horticulture Australia Ltd, Project AV06025 HortResearch Client Report No. 21796 HortResearch Contract No. 21627

Harker FR, Jaeger SR, Bava C, Thompson M, White A, Wohlers M, Heffer M, Lund C, Woolf A The Horticulture and Food Research Institute of New Zealand Ltd HortResearch Mt Albert Private Bag 92 169 Auckland Mail Centre Auckland 1142 NEW ZEALAND Tel: +64-9-815 4200 Fax: +64-9-815 4201

Hofman P, Stubbings B Department of Primary Industries and Fisheries Maroochy Research Station PO Box 5083, SCMC (Mayers Road) Nambour Qld 4560 AUSTRALIA Tel: +61- 7- 5444 9647 Fax: +61-7- 5441 2235

DISCLAIMER

Unless agreed otherwise, HortResearch does not give any prediction, warranty or assurance in relation to the accuracy of or fitness for any particular use or application of, any information or scientific or other result contained in this report. Neither HortResearch nor any of its employees shall be liable for any cost (including legal costs), claim, liability, loss, damage, injury or the like, which may be suffered or incurred as a direct or indirect result of the reliance by any person on any information contained in this report.

This report has been prepared by The Horticulture and Food Research Institute of New Zealand Ltd (HortResearch), which has its Head Office at 120 Mt Albert Rd, Mt Albert, AUCKLAND. This report has been approved by:

_____________________________ ___________________________ Research Scientist Group Leader, Health and Food Date: 22 June 2007 Date: 22 June 2007

AV06025 (completion 22 June 2007)

Australian consumers’ perceptions and preferences for ‘Hass’

Avocado

Harker FR, et al

The Horticulture and Food Research Institute of New Zealand

Ltd

HAL Project AV06025

Project Leader: Harker FR The Horticulture and Food Research Institute of New Zealand Ltd Hawke's Bay Research Centre Private Bag 1401 Havelock North Hastings 4157 NEW ZEALAND Tel: +64-6-877 8196 Fax: +64-6-877 4761

Key Personnel: Jaeger SR, Bava C, Thompson M, White A, Wohlers M, Heffer M, Lund C, Woolf A

The Horticulture and Food Research Institute of New Zealand Ltd HortResearch Mt Albert Private Bag 92 169 Auckland Mail Centre Auckland 1142 NEW ZEALAND Tel: +64-9-815 4200 Fax: +64-9-815 4201 Hofman P, Stubbings B Department of Primary Industries and Fisheries Maroochy Research Station PO Box 5083, SCMC (Mayers Road) Nambour Qld 4560 AUSTRALIA Tel: +61- 7- 5444 9647 Fax: +61-7- 5441 2235

The aim of this project was to determine, in more detail than available from existing research, the level of fruit quality that negatively impacts on consumer purchasing behaviour.

Disclaimer

Any recommendations contained in this publication do not necessarily represent current HAL Limited policy. No person should act on the basis of the contents of this publication, whether as to matters of fact or opinion or other content, without first obtaining specific, independent professional advice in respect of the matters set out in this publication. Date: 22 June 2007

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CONTENTS Page

MEDIA SUMMARY..................................................................................................................2

TECHNICAL SUMMARY ........................................................................................................3

INTRODUCTION ......................................................................................................................5

Objectives ...............................................................................................................................6

MATERIAL AND METHODS..................................................................................................7

Fruit Sources ...........................................................................................................................7

Fruit Assessments ...................................................................................................................8

Consumers ..............................................................................................................................9

Consumer Testing Facility....................................................................................................10

Questions on Edible Quality and Ripeness...........................................................................11

RESULTS AND DISCUSSION...............................................................................................21

Consumer preferences for avocados with differing DM content..........................................21

Interpretation and implications of DM study........................................................................25

Consumer preference for avocados of differing firmness ....................................................26

Consumer vocabulary and uses of avocados after tasting fruit with differing firmness.......30

Consumer judgements of firmness of whole avocados ........................................................33

Consumer vocabulary and uses of avocados based on assessments of firmness of whole avocados................................................................................................................................35

Interpretation and implications of firmness study ................................................................36

Reasons for using conjoint analysis to determine consumer responses to bruising .............37

Impact of price, severity and incidence of bruising on consumer purchase intentions ........38

Interpretation and implications of study on consumer responses to bruising.......................42

CONCLUSIONS ......................................................................................................................43

RECOMMENDATIONS..........................................................................................................44

REFERENCES .........................................................................................................................45

ACKNOWLEDGEMENTS......................................................................................................46

APPENDIX 1. CONJOINT STUDY ON BRUISING: ANALYSIS OF CONSUMER SEGMENTS .............................................................................................................................47

Within-segment main effects models ...................................................................................47

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MEDIA SUMMARY

Consumers handled and tasted avocados in a study designed to identify characteristics of fruit that are perceived as being of optimum quality. In all cases, the quality was quantified using tightly defined objective measurements: % dry matter content, puncture force, area of damaged/bruised flesh and frequency with which damage/bruising occurred. Avocados were obtained from orchards throughout Queensland and as far away as Western Australia. This ensured that a wide range of different levels of quality were available for consumers to taste. Avocados were carefully ripened and sorted into distinct groups based on quality characteristics. The first quality characteristic examined was the dry matter content. Dry matter content of avocados represents the amount of carbohydrates and nutrients that have been transported from the tree into the fruit. The longer the avocado remains on the tree the higher the dry matter, and consequently, dry matter is used by growers to decide when avocados are ready to harvest. Consumers showed a progressive increase in liking and willingness to buy avocados as the dry matter content increased. The second quality characteristic examined was ripeness. Consumers gently squeezed the fruit to identify the softer, ripe avocados. In this study, consumers assessed firmness of whole fruit by hand squeezing as well as tasting samples of flesh from fruit of known firmness/ripeness. The consumers indicated that of the whole fruit they squeezed, they would leave the hard avocados to eat/use on a later date. After tasting the avocado samples, consumers indicated that they preferred to eat avocados that could be squeezed using moderate to gentle hand pressure. Finally, the study used images of fruit to examine how consumers react when they cut open an avocado and find that the flesh has been damaged by bruising. The consumer responses strongly suggest that bruises need to be minimised in order to maintain consumer confidence. Only the lowest levels of damage (less than 10% of the flesh) occurring very infrequently (1 in 10 fruit) were tolerated. Together the findings from this study can be used by industry to ensure that they deliver the best quality avocados to the Australian consumer.

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TECHNICAL SUMMARY

This research project addresses three strategic questions for the Australian avocado industry:

1. To determine the minimum maturity, as measured by % dry matter (DM), that produces ‘Hass’ avocados which are of acceptable eating quality to Australian consumers.

2. To determine the level of ripeness (firmness) that is preferred by consumers at the time of consumption.

3. To determine the maximum acceptable level of internal defects (bruising) at different price points above which future consumer purchasing decisions are negatively influenced.

Research was undertaken in Brisbane using 107 consumers from the target demographic for Avocados Australia Ltd, and recruited on the basis that a third fell into each of the categories of ‘high frequency’, ‘medium’ and ‘occasional’ eaters of avocados. The ‘Hass’ avocados were sourced from a wide range of locations (South East, Tablelands, Bundaberg and Atherton localities within Queensland, and WA) in order to ensure DM levels varied from about 17% to about 44%. All fruit were successfully ripened and sorted into four distinct DM bands (~20%, ~22%, ~26% and ~38% DM) of similar firmness, and three distinct firmness bands (~1.05, ~0.65 and ~0.45 kfg puncture force) of similar DM content. Consumers tasted avocados from all these ‘quality’ categories, and also assessed firmness of whole fruit. For the latter, additional avocados from a firmness category of ~5 kgf puncture force were also provided. Consumers showed a progressive increase in liking and intent to buy avocados as the DM content increased. Consumers were unsure if they would purchase an avocado with a DM of 20% but indicated they would probably buy (~80% chance) the avocados with 38% DM. Consumer acceptance of the quality of avocados was relatively high at about 90–95%, but declined significantly to 70% if the DM was lower than 22%. Consumers assessed firmness of whole fruit as well as the tasting of the avocado flesh. After handling (squeezing) avocados from the hardest firmness categories (~5 and ~1.05 kgf firmness) the consumers indicated that they would leave the avocados to eat/use on a later date. Consumers who tasted avocados indicated that on average the fruit that were about 1.05 kgf firmness were significantly less liked, less likely to be purchased and less acceptable than fruit that were 0.65 kgf or 0.45 kgf. Avocados from these two softer firmness categories were not significantly different from each other according to any of the consumer responses measured. A conjoint study approach was used explore the impact of bruising on consumer preferences. The study has demonstrated that all three experimental factors (i.e., price, level of bruising and incidence of bruising) significantly lower consumers’ future purchase decision. The impact of price (relative importance = 28.8%) was significantly lower than the negative impact of level of bruising (relative importance = 36.6%) and frequency of bruising occurring (relative importance = 34.6%). Further, the difference in relative importance between level of bruising and incidence of bruising is not statistically significant.

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The recommendations are (in brief):

1. There are three options in terms of the minimum maturity to ensure acceptable quality avocados: (A) a minimum of 22% DM which would exclude avocados that are of low taste acceptability; or (B) a maximum of 28% DM which would exclude avocados that do not attract optimum consumer purchase intent; or (C) a minimum between 22% DM and 28% DM to ensure an appropriate competitive advantage in the marketplace. There first two options are based on the observation of DM thresholds that were associated with marked changes in consumer responses. The third option reflects the approximately linear increase in liking and purchase intent that occurs as DM increases from 22% to 28%. Thus, improvements in DM in this region have the potential to stimulate consumer demand and consequently increase prices or increase volume of sales. However, decisions on where to set a minimum in option C would require additional information to establish the desired competitive positioning of the Australian avocado industry.

2. The ripeness (firmness) of avocados that was preferred by consumers was 0.65 kgf or softer (measurement of flesh texture using Effigi penetrometer with an 11 mm diameter probe). This firmness level usually relates to Firmometer value of about 80 and a hand firmness of about 5 (i.e. whole avocado deforms with moderate hand pressure).

3. Bruising of avocados needs to be minimised in order to maintain high future purchase probability. Generally, only the lowest levels of bruising (e.g. 10% flesh damage) at very low incidences (e.g. 1 in 5 or 1 in 10 avocados) were acceptable in terms of not reducing consumers’ purchase intent below 70% (‘probably buy’). A higher level of bruising (25% flesh damage) was acceptable if it occurred at a very low incidence (1 in 10 avocados), but only at the lowest prices.

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INTRODUCTION

One of the objectives identified in the Australian Avocado Industry Strategic Plan was that by 2010, 90% of fruit at retail level will meet or exceed the fruit quality expectations of Australian consumers. Retail surveys of Avocado quality conducted in 2001 showed that up to 20% of ripe fruit had at least 25% of the flesh volume that is unusable (Hofman & Ledger 2001). Rots and bruising were the main causes of poor flesh quality. It was recommended that to increase quality of the fruit on the retail shelf improvements needed to be made at all steps in the chain to control rots and reduce bruising. Consumer research conducted in 2005 indicated that some level of wastage takes place in 1/3 of all avocado purchases. The two biggest reasons for wastage were “over ripeness and going off” (83% of respondents who experienced wastage cited these reasons) and bruising (31% of respondents who experienced wastage cited this as a reason). The research also showed that ‘poor quality’ (17% of consumers) and ‘too many problems with ripeness’ (17% of consumers) were among the reasons for consumers not buying avocados. The research indicated that there are still problems with both the quality of avocados reaching the consumer and the ability of consumers to determine when the product is ripe (neither under nor over ripe) for consumption. Fifty-five percent of the consumers who cited poor quality as an issue preventing them from purchasing avocados more frequently were medium frequency purchasers or below. Similarly, 59% of consumers who cited “ripeness issues” as an issue preventing them from purchasing avocados more frequently were medium frequency purchasers or below. These statistics indicate that by addressing these issues there may be significant gains made in moving these consumers into higher frequency buying brackets and thereby increasing overall consumption and revenue for industry. All available research regarding avocado maturity has recently been collated and analysed by HortResearch in a report commissioned by Avocados Australia and Horticulture Australia Ltd (Johnston et al. 2006). From the sensory research there was a number of consumer acceptability issues associated with immature avocados. These relate to texture: rubbery, unevenly ripe, too soft and stringy; and flavour: watery, green and slightly bitter. For this reason it is important to minimise the amount of immature fruit in the market. In their report, Johnston et al. (2006) highlighted a gap in available research linking the current industry accepted minimum of 21% dry matter (DM) as an indicator of maturity with consumer acceptability especially for Australia’s most common commercial cultivar, ‘Hass’. In light of significantly higher standards in other countries – in particular the suggested move of California from 20.8% to 23%, there is a need to review the Australian minimum maturity standard. The aim of this project was to determine, in more detail, the level of fruit quality that negatively impacts on consumer purchasing behaviour.

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OBJECTIVES

This report considers three objectives that were addressed in the HortResearch-led study:

1. To determine the minimum maturity, as measured by % dry matter, that produces ‘Hass’ avocados which are of acceptable eating quality to Australian consumers.

2. To determine the level of ripeness (firmness) that is preferred by Australian consumers at the time of consumption.

3. To determine the maximum acceptable level of internal defects (bruising) at different price points above which future purchasing decisions among Australian consumer are negatively influenced.

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MATERIAL AND METHODS

FRUIT SOURCES

The study required three sets of ‘Hass’ avocado fruit:

• Set 1: Effect of maturity (dry matter; DM) on consumer preferences. These fruit had to be harvested at different maturities (assessed by DM) and served to consumers at the same stage of ripeness (Research Objective 1).

• Set 2: Effect of ripeness stage on consumer preferences. The fruit needed to be of similar maturity (DM) and served to consumers at a range of ripeness stages (Research Objective 2).

• Set 3: The firmness/ripeness stage at which consumers eat the fruit. These fruit were not to be tasted and DM was not required. The avocados were ripened under differing conditions to provide fruit at a range of ripeness (Research Objective 2).

Avocados were harvested at different times from different states and locations around Australia on the assumption that they would provide the required range of maturity levels required for the trial (Table 1). For Sets 1 and 2, fruit were either harvested straight into trays, or obtained at the end of the packing line, and road or airfreighted to the Department of Primary Industries and Fisheries postharvest laboratory at the Maroochy Research Station (MRS) at Nambour within 24 h of harvest. For Set 3, fruit were commercially picked and packed from Walkamin, North Queensland, road-freighted to Brisbane under refrigeration

(7°C set temperature), then taken by car to MRS. The fruit were packed on Monday 16th April, road-freighted the next day, arrived in Brisbane on Thursday 19th April, early morning, and arrived at MRS at 11.00 am on the same day. Table 1. Sources of avocados for consumer study in Brisbane, including location, date and number of fruit harvested.

DM category Targeted DM Grower Location Region Date harvested No of fruit

Set 1

Immature 18-21% Thomas Crowsnest SEQ 9 Apr 40

Mosley Maleny SEQ 9 Apr 40

Donovan Bellthorpe SEQ 9 Apr 40

Newell Beerwah SEQ 9 Apr 40

Early 21.5-24% Webb Nambour SEQ 13 Apr 40

Donovan Bundaberg Bundaberg 16 Apr 40

Simpson Childers Bundaberg 16 Apr 40

Jonsson Tablelands Tablelands 18 Apr 40

Kochi Kairi Tablelands 18 Apr 40

Mid 24.5-27% Kochi Kairi Tablelands 18 Apr 60

Lavers Walkamin Tablelands 18 Apr 60

Late 35% Franceschi Pemberton WA 19 Apr 200

Sets 2 and 3

Mid 24.5-27% Lavers Walkamin Tablelands 16 Apr 1100

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FRUIT ASSESSMENTS

Sorting for Dry Matter (~Maturity)

Avocados for Sets 1 and 2 were numbered on arrival at MRS to allow individual fruit to be tracked from the start of DM testing to consumption by individual consumers. Each fruit was assessed for DM within two days of arrival and placed in a cold store at 5°C until the DM results were obtained (2–3 days at the most). Dry matter was assessed using the Hofshi plugger to remove a core of tissue from the fruit equator (Arpaia et al. 2001). Skin and seed

coat were removed from the core, and the cores halved and dried to constant weight at 65°C. Fruit were sorted into four DM categories (Table 1) ensuring that there were at least 150 fruit in each category for Set 1 and approximately 280 fruit of similar DM (22 – 26%) for Set 2.

Ripening Treatments

To provide ripe fruit over the four days of tasting and to account for the expected different ripening times of fruit with differing maturities, the fruit were harvested at differing times (Table 1) and ripened under different conditions. Avocados from each DM category were split into five groups. Each group was subjected to different ethylene ripening treatments (0–

3 days in a flow through system that constantly provided 10 µL/L ethylene) and different ripening temperatures (17 or 21oC) in order to stagger the ripening (Table 2). For Sets 2 and

3, fruit were held at 5°C, then ripening commenced at different days to provide fruit of differing firmness on each day of the consumer testing. Final stages of fruit ripening was accelerated (higher temperatures) or decelerated (lower temperatures) to ensure fruit were on target for consumer testing. Ripe fruit were held at 2 or 5°C at the near ripe/ripe stage, as necessary. Table 2. Ripening treatments used for ‘Hass’ avocados used in consumer assessments of DM (i.e. Fruit Set 1) that were harvested at different dates. DM = dry matter, E = ethylene.

Anticipated days to ripe

DM category Targeted DM 17oC 21oC

no E 1 day E 3 days E no E 1 day E 3 days E

Immature 18-21% 25 21 18 20 17 15

Early 21.5-24% 19 16 14 15 13 11

Mid 24.5-27% 15 12 10 12 10 8

Very late Approx 35% 12 10 8 9 7 6

Table 3. Ripening treatments used for avocados used in consumer assessments of firmness (Fruit Sets 2 and 3) that were harvested on 16th April and received at MRS on 19th April; E = ethylene.

Tasting date

30-Apr 1-May 2-May 3-May 4-May Ripening treatment Start of ripening

Days Firmness Days Firmness Days Firmness Days Firmness Days Firmness

17C 3E, then 21°C 19 Apr 11 6

17C 3E, then 21°C 21 Apr 9 5 10 6 11 6

17°C 2E 23 Apr 7 4 8 5 9 5 10 6

17°C 2E 25 Apr 5 2 6 4 7 4 8 5 9 6

17°C 2E 27 Apr 4 2 5 2 6 4 7 5

17°C 2E 29 Apr 4 2 5 4

17°C 2E 30 Apr 4 2

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Selection of fruit for consumer evaluations

One day before the start of consumer taste testing, all avocados were transported by car to the Department of Primary Industries and Fisheries Redlands Research Station (RRS; Delancey Street, Cleveland, Australia) located in the outer eastern suburbs of Brisbane (~3 h drive). Two transportable cold rooms located at RRS were held at either 2ºC or 17ºC. This allowed avocado ripeness to be manipulated within the period of consumer taste testing. All fruit needed to be sorted for ripeness prior to presentation to consumers for tasting or firmness assessment. This was done initially by hand by one expert (A.W.), who has over 15-years experience in assessing the postharvest condition of avocados. Hand firmness evaluations were based on relationships between hand assessment and instrumental texture measurements established in earlier studies (White et al. 1999), and modified for the current study. Hand-based ripeness assessments for fruit served to consumers for tasting at a range of ripeness stages were confirmed by a single operator (A.W.) using a hand-held Effegi penetrometer (Effegi, Alphonsine, Italy) with an 11 mm diameter Effegi probe (Harker et al. 1996). Avocados from Set 1 were sorted to be within a narrow firmness range 4.5 to 5.5 hand firmness (White et al. 2005). Avocados from Set 2 were sorted into three distinct categories:

• Hand rating 3–4, 0.9 to 1.25 kgf (“Firm ripe”)

• Hand rating 5, 0.6 to 0.8 kgf (“Ripe”)

• Hand rating 6, 0.5 or less kgf (“Soft ripe”) Avocados from Set 3 were sorted into four distinct categories which include the three described above with the addition of Hand rating 2, 5 kgf (“Sprung”). Prior to each consumer panel, fruit from each of the four DM bands and three firmness categories were cut into quarters and the seed removed. As there are large spatial differences in DM within a ‘Hass’ avocado (Schroeder 1985), the top (proximal) and bottom (distal) ends of each quarter were removed. The remaining mid pericarp section, which is less variable in DM, was then cut in half longitudinally (~2 cm wide by 3–4 cm high) and the skin removed. Care was taken to avoid the area of the fruit where the core was removed for DM assessment, and only fruit free of bruising and rots were used. Flesh from a single fruit was shared between a minimum of two panellists. Samples of avocado flesh were placed into clear plastic cups, which were labelled with 3-digit codes that represented the respective fruit treatment. Details of the condition (DM and firmness) of individual fruit could be related to responses of an individual consumer. The process of selecting appropriate avocados, confirming ripeness with formal postharvest assessments and preparing the fruit to serve to consumers took the team of five (A.W., B.S., C.B., M.T., J.E.) about three hours for each consumer tasting session (~12 consumers / session).

CONSUMERS

One hundred and seven consumers from the greater Brisbane area were recruited by TNS on the basis that they met demographics targeted in Avocados Australia sales promotions. They needed to be between the ages of 20 and 40 years, solely or jointly responsible for the majority of their household’s grocery shopping, and have purchased avocados in the last

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three months. In addition, the consumers were then recruited on the basis that about a third of them fell within one of the following categories of frequency of avocado consumption:

1. High frequency consumers (one or more avocados each week) 2. Medium frequency consumers (about one avocado each fortnight) 3. Occasional consumers (about one avocado each month)

Table 4. Demographic profile of consumers (N = 107).

Factor Demographic Percentage

Gender Female 74% Male 26% Age 20-24 28% 25–29 23% 30-34 19% 35-39 26% 40–44 4% Main purchaser for household Yes 93% No 7% Frequency of avocado consumption One or more each week 36% One each fortnight 38% One each month 24% One or two each 3 months 2% Income less than $20 000 7% $20 000 to $34 999 14% $35 000 to $54 999 14% $55 000 to $74 999 18% $75 000 to $99 999 24% $100 000 to $119 999 13% $120 000 or more 10% Hours of work Full time - 30 h or more 41% Part time - less than 30 h 39% Not in paid employment 20%

CONSUMER TESTING FACILITY

Consumer evaluations of Avocados were undertaken at a recently completed conference facility at RRS, located in the outer suburbs of Greater Brisbane. The conference facility included two separate areas, one of which was used for fruit preparation and the other area was set up to handle up to 14 consumers per session with two consumers sharing each table (Figure 1).

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Figure 1. Facilities used for consumer study.

QUESTIONS ON EDIBLE QUALITY AND RIPENESS

The tasks given to consumers were broken into four segments; (1) assessment of taste of avocados of differing DM content, (2) assessment of taste of avocados of differing ripeness, (3) assessment of firmness of whole fruit (no tasting involved), (4) assessment of how purchase intentions are influenced by symptoms and incidence of flesh bruising (no tasting involved). In each of these segments a range of questions were asked. Consumers were briefed on the details of questionnaires and the task they were being asked to undertake prior to each of the four segments (Figure 1), and were encouraged to ask questions if they were at any time unsure of what was needed. The questionnaires were finalised after piloting in a small study (12 consumers) in New Zealand.

Tasting of avocados with different DM content

Consumers tasted fruit of the same ripeness from each of the four DM categories. Each consumer was provided with an A3 answer sheet as shown in Figure 2, and asked to indicate how much they liked each sample using a hedonic scale:

• Like extremely

• Like very much

• Like moderately

• Like slightly

• Neither like nor dislike

• Dislike slightly

• Dislike moderately

• Dislike very much To control for presentation order effect, the order in which fruit from different DM categories were tasted varied across consumers. The order in which fruit were tasted was according to a randomised complete block statistical design that accounted for order and carryover effects. The consumers were asked to taste the fruit using the following instructions:

“Please take your time when tasting these avocados, and answering the questions. You should taste one of the pieces of avocado from each of the containers. First, please taste the samples in the order that appears at the top of your scoring sheet. After that, you can go back and re-taste each avocado. Place each container of fruit in the position that represents how much you like its taste. You can change the

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position of the containers as you progressively taste and re-taste all the avocados. Only when you are certain of your decisions, and the relative liking for all the fruit, should you mark the boxes with a tick.”

Consumers were provided with water crackers (Arnott’s Original, Arnott’s Biscuits Ltd, Homebush, NSW) and water (600 ml commercially bottled) as palette cleansers between tastings. Once the consumers had indicated how much they liked the fruit, they were asked to re-taste each fruit and answer two supplemental questions, as follows:

1. “Is the quality of the fruit (identified by 3-digit code) acceptable or unacceptable?” (Yes/No)

2. “During the year avocados generally vary in price between $1.29 and $2.99 for an average sized fruit”. If you knew that the next avocado you bought was going to taste like fruit (identified by 3-digit code) and had a price of $1.99 would you buy it?”

The consumers responded by ticking a multi-choice answer:

• Definitely will buy (90 to 100% chance)

• Probably will buy (70 to 89% chance)

• Possibly will buy (50 to 69% chance)

• Possibly will not buy (30 to 49% chance)

• Probably will not buy (10 to 29% chance)

• Definitely will not buy (0 to 9% chance)

Figure 2. Forms and fruit sample containers used for tasting Avocados of differing DM

Tasting of avocados of differing levels of ripeness

Consumers tasted fruit of similar DM content from each of the three ripeness categories. Each consumer was provided with an A3 answer sheet (similar to that shown in Figure 2), and asked to indicate how much they liked each sample using a hedonic scale:

• Like extremely

• Like very much

• Like moderately

• Like slightly

• Neither like nor dislike

• Dislike slightly

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• Dislike moderately

• Dislike very much To control for presentation order effect, the order in which fruit from different DM categories were tasted varied across consumers. The order in which fruit were tasted was according to a randomised complete block statistical design that accounted for order and carryover effects. The consumers were asked to taste fruit from each of the ripeness categories using the following instructions:

“Please take your time when tasting these avocados, and answering the questions. You should taste one of the pieces of avocado from each of the containers. First, please taste the samples in the order that appears at the top of your scoring sheet. After that, you can go back and re-taste each avocado. Place each container of fruit in the position that represents how much you like its taste. You can change the position of the containers as you progressively taste and re-taste all the avocados. Only when you are certain of your decisions, and the relative liking for all the fruit, should you mark the boxes with a tick.”

Consumers were provided with water crackers and water as palette cleansers as described above. Once the consumers had indicated how much they liked the fruit, they were asked to re-taste each fruit and answer two supplemental questions. Firstly they were asked:

1. “Is the quality of the fruit (identified by 3-digit code) acceptable or unacceptable?” (Yes/No)

2. “During the year avocados generally vary in price between $1.29 and $2.99 for an average sized fruit”. If you knew that the next avocado you bought was going to taste like fruit (identified by 3-digit code) and had a price of $1.99 would you buy it?”

The consumers responded by ticking a multi-choice answer:

• Definitely will buy (90 to 100% chance)

• Probably will buy (70 to 89% chance)

• Possibly will buy (50 to 69% chance)

• Possibly will not buy (30 to 49% chance)

• Probably will not buy (10 to 29% chance)

• Definitely will not buy (0 to 9% chance) After completing all of the questions asked on the A3 questionnaire, consumers were asked to fill in a supplemental multi-choice questionnaire. The consumers were asked (1) how they would describe each of the avocados and (2) how they would use the fruit from the various ripeness categories:

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(1) How would you describe each of the avocados? Multi-choice options were (tick as many as apply):

• Unripe • Mushy • Buttery

• Ripe • Finger or thumb soft • Spreadable

• Overripe • Hand soft • Watery

• Rotten • Ready to eat • Rubbery

• Soft • Pasty • Creamy

• Firm • Pulpy

• Springy • Mealy

• Other (Please describe below)

• Hard • Oily

(2) What would you usually use these avocados for? Multi-choice options were (tick as many as apply):

• As a spread

• With baked potatoes • I would not eat it

• On bread • As a topping on a casserole

• I would leave it to use on a later date

• On crackers

• With sushi • Give it to a pet

• As an ingredient in a salad

• In a prawn cocktail • Compost it

• As a dip / guacamole

• With soup • I would throw it away

• With nachos • For a baby • I would freeze it for future use

• With other Mexican foods

• On a platter • Give it to another family member

• With risotto and/or pasta

• I would eat it as a fruit on its own

• Other (Please describe below)

Assessment of ripeness / firmness of whole avocados

Consumers were provided with four whole fruit of differing firmness (presented in order of decreasing firmness) to explore how they judged and/or predicted when fruit were ready to consume. The three softest categories of fruit matched the categories used in the tasting trial above. Each fruit was labelled with a 3-digit code, and consumers were asked to handle and examine the avocados in the manner that they normally used to assess avocados. Following this they were asked:

• To identify which one of the avocados would be most suitable if they wanted to eat it today, and how certain they were that this avocado would be ready to eat today:

o Extremely certain o Very certain o Moderately certain o Slightly certain o Neither certain nor uncertain

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o Slightly uncertain o Moderately uncertain o Very uncertain o Extremely uncertain

• To identify which one of the avocados would be most suitable if they wanted to eat it in three days time, and how certain they were that the avocado would be ready to eat in three days time:

o Extremely certain o Very certain o Moderately certain o Slightly certain o Neither certain nor uncertain o Slightly uncertain o Moderately uncertain o Very uncertain o Extremely uncertain

• To indicate which of the avocados was most similar to the ones they usually bought, with addition answer options: “Much harder than any of these fruit” and “Much softer than any of these fruit”

Then consumers were asked (1) how they would describe each of the avocados and (2) how they would use the fruit from the various ripeness categories: (1) How would you describe each of the avocados? Multi-choice options were (tick as many as apply):

• Unripe • Soft • Finger or thumb soft

• Medium ripe • Firm • Hand soft

• Nearly ripe • Springy • Ready to eat

• Ripe • Hard • Rubbery

• Overripe • Mushy

• Rotten • Other (Please

describe below)

(2) What would you usually use these avocados for? Multi-choice options were (tick as many as apply):

• As a spread • With baked potatoes • I would not eat it

• On bread • As a topping on a casserole

• I would leave it to use on a later date

• On crackers • With sushi • Give it to a pet

• As an ingredient in a salad

• In a prawn cocktail • Compost it

• As a dip / guacamole • With soup • I would throw it away

• With nachos • For a baby • I would freeze it for future use

• With other Mexican foods

• On a platter • Give it to another family member

• With risotto and/or pasta

• I would eat it as a fruit on its own

• Other (Please describe below)

16

Conjoint Study of impact of Bruising and Price on Purchase Intent

The impact of flesh bruising and price on purchase intentions was investigated using a conjoint study approach. Conjoint analysis is a standard marketing research methodology (Green & Rao 1971; Green & Srinivasan 1978). It builds on the assumption that a product can be viewed as a bundle of attributes. The value of conjoint analysis is that it forces consumers to trade these attributes against each other when making a decision about which product to buy. By systematically manipulating selected attributes, the relative importance of the attributes to the overall purchase decision is deduced. This study used the well-established full-profile approach in a manner where each stimuli profile was rated sequentially on the focal dependent variable (which in this study was purchase intention). The experimental design shown in Table 5 defines 64 stimuli (4×4×4), but this constitutes too great a burden for an individual participant. Therefore it was decided that each participant would evaluate 16 stimuli. This number was chosen as it was possible to define four sub-designs (i.e., fractional factorial designs) from the total of 64 in such a manner that each set of 16 stimuli enabled estimation of individual level main effect models. That is, each set of 16 stimuli was defined by an orthogonal main effects plan. In the analyses reported later, results based on both individual and aggregate level models are provided.

Table 5. Experimental design underlying the conjoint analysis study.

Factor Level 1 Level 2 Level 3 Level 4

Price per avocado

$1.29 $1.99 $2.49 $2.99

Level of bruising

10% 25% 33% 50%

Incidence of bruising1

Very infrequent occurrence (1 in 10 times)

Infrequent occurrence (1 in 5 times)

Quite frequent occurrence (3 in 5 times)

Persistent occurrence (5 in 5 times)

1 Percentage of flesh in each fruit that had internal bruising 2 Frequency of experiencing fruit with bruising

It is possible for the type of conjoint analysis implemented in the current study be executed using either product ratings or rankings. Rating-based evaluations of the relevant product stimuli were adopted, because they tend to have high applicability in market segmentation research. The rating scale, which measured purchase intention, was constructed such that higher ratings represented higher scores on the dependent variable, implying greater perceived utility. Such higher utility levels, in turn, translate into larger part-worths for relevant attribute levels. Specifically, participants were instructed to indicate their intention to buy an avocado fruit on the following six-point probability scale, with anchors: 1= Definitely will not buy (less than 10% chance), 2= Probably will not buy (10–29% chance), 3= Possibly will not buy (30–49% chance), 4= Possibly will buy (50–69% chance), 5 = Probably will buy (70–89% chance) and 6= Definitely will buy (90–100% chance). This response scale was regarded as approximately interval in nature and permitted the use of ordinary least squares (OLS) multiple regression for data analysis (see later for further details).

Each consumer was given a questionnaire booklet. The cover page explained the tasks and provided a reference image of an avocado that was of very high internal quality (Figure 3a). Each subsequent page included an image of a cut avocado showing a bruise (Figure 3)

17

together with information about the incidence at which bruising is observed in fruit and the price. The consumers were asked:

• Please imagine that you have purchased an avocado and cut it open ready to eat or use in a recipe.

• The photo shows what this avocado looks like.

• Further, please imagine that it is a ___________ occurrence (__________) that you experience fruit of this quality. On the other occasions, the avocados you eat are of very high internal quality (please refer to front page of this questionnaire booklet to see a photo of such a fruit).

• Now imagine that following the experience above, you have gone shopping and are considering buying another avocado. In the shop you are in, they cost _____ per fruit. Please indicate your intention to buy an avocado in this instance.

Images of the avocados were created using photographs taken from the International Avocado Quality Manual (White et al. 2005). The appropriate shape of the avocado was initially selected, and then the level of bruising was manipulated using Photoshop 6.0. The Photoshop cloning tool was used to transfer the bruise from an original avocado photograph onto the newly created image. Care was taken in selecting appropriate areas of original images in order to ensure that the final image was as realistic as possible. Examples of the images are shown in Figure 3. The images were then exported to MS Word 2003, where they were inserted into the questionnaire booklet. The word document was printed on a colour photocopier (model DocuColor 1250, Fuji Xerox Co. Ltd, Japan).

Statistical methods used to analyse conjoint study

Conjoint analysis is based on the premise that consumers evaluate a product’s total utility, which is expressed in the dependent variable, by aggregating the amounts of utility provided by individual attributes. Further, part-worths represent estimates of the utility placed on each level of each of the experimental factors. The primary objective of the analysis of conjoint evaluations is therefore to determine part-worths. For the type of conjoint analysis used in this study, multiple OLS regression analysis represents a commonly-used technique for obtaining relevant betas; from which corresponding part-worths and relative importances are derived for the factors used in the conjoint design. Essentially, it is desired to estimate the following model: Purchase Intention = Intercept + β1 Price + β2 Level of internal defect + β3 Incidence of defect occurring. However, because the levels of the attributes do not all vary linearly, it was decided to use dummy variables to represent each level of each experimental factor. Further, this enabled more in-depth insight to the change in utility associated with changes from one attribute level to another. To represent four attribute levels, three dummy variables are needed (Table 6). In the coding scheme below, dummy variable 1 represents the difference in utility between attribute level 1 and level 2.

18

Table 6. Example of dummy variable coding scheme for four attribute levels.

Attribute

level

Dummy 1 Dummy 2 Dummy 3

Level 1 0 0 0 Level 2 1 0 0 Level 3 0 1 0 Level 4 0 0 1

If the prefix P is used to represent the experimental factor Price, the prefix D is used to represent the experimental factor Internal Defect and the prefix I is used to represent the experimental factor relating to the Incidence of the defect occurring, then the above model when fully specified by dummy variables becomes: Purchase Intention = Intercept + β1 P1 + β2 P2 + β3 P3 + β4 D1 + β5 D2 + β6 D3 + β7 I1 + β8 I2 + β9 I3 In accordance with the above specified model equation, the estimated model was additive and included main effects only. The additive model represents the most frequently-used conjoint technique, sufficing for most applications (Hair et al. 2006).

Once the models had been estimated, standard measures of model fit were considered – whether the overall model was significant and the level of R2 values. Then, also following standard procedures as described, for example in Hair et al. (2006) (or see Gil & Sánchez (1997) for a detailed example), the betas were used for calculating the relative importances of the three factors for purchase intention. Briefly, for each attribute the highest and lowest utility values (i.e., part-worths) were first determined. The difference between these values is the attribute utility range, and this value determines the relative importance (RIi) for an attribute i as defined by the equation below.

∑=

=n

i

i

ii

rangeutilityattribute

rangeutilityattributeRI

1

__

__

Further to estimating models on the aggregate dataset, the interest of Avocado Australia in understanding more about the difference between consumer ‘segments’ defined by the frequency of eating avocado was addressed through segment-wise analyses and comparisons. Specifically, within each of the three eating frequency segments (i.e., ‘high’, ‘medium’ and ‘occasional’) main effects models were estimated and additional analyses were then carried out to determine if the relative importance of the experimental factors differed between segments. However, statistical estimation techniques relying on known underlying data distributions, such as t-tests for proportions, could not be used for these comparisons since the standard errors associated with the relative factor importances could not be calculated. Instead, nonparametric bootstraps, the most frequently used type of bootstrapping (Chernick 1999) were used.

Briefly, bootstrapping represents a technique for estimating the sampling distribution of relevant coefficients by resampling with replacement from the original sample, enabling assessments of the statistical significance of the differences in the relative importances

19

obtained for the three factors across the relevant segments (Efron 1979, 1981, 1982; Efron and Tibshirani 1993). Resampling with replacement implies that a single sample gives rise to many others, with the number of observations for each resample equalling that of the original sample size. In other words, it is possible to generate large numbers of resamples (e.g. 10 000) from relatively small samples because sampling with replacement is used, implying that each unit may be selected across various resamples multiple times. The rationale underlying bootstrapping is that a sufficient number of resamples from the empirical distribution (e.g. 1000) may be used to generate an approximation of the underlying data distribution. Having generated these empirical distributions, 95% confidence intervals of difference in an attribute’s relative importance between segments were developed. In cases where such a difference confidence interval includes the value zero it indicates that the mean values of the two relative importances are the same.

To test whether, within a sample the relative importance of the three factors differed, a different statistical approach was needed. Within participants, a main effects model was estimated and the relative factor importances calculated. These individual levels estimates were used in pair-wise comparisons of differences in factor importances (i.e., a comparison of two factors at a time using data paired on participants). However, because the factor importances are bounded by 0 and 1 (recall that the relative importances across the three factors sum to 100%), they do not have a normal distribute. To overcome this, a log transformation was applied, and the subsequent t-test therefore tested if the odds ratio between a pair of factor importances was different from 1. Where evidence was found that the odds ratio differed from 1, it could be concluded that the relative importances were also significantly different. All questionnaires and processes used for Objectives 1, 2 and 3 were signed off by Avocados Australia.

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(A) No Bruise (B) 10% Bruise (C) 25% Bruise

(D) 33% Bruise (E) 50% Bruise

Figure 3. Images used to represent the different levels of bruising in the Objective 3 conjoint analysis task

21

RESULTS AND DISCUSSION

CONSUMER PREFERENCES FOR AVOCADOS WITH DIFFERING DM CONTENT

It is important to demonstrate that avocados used in this study represent distinct DM categories before we can place any level of reliance on the consumer responses that were collected. The process of sorting avocados into different DM categories was very successful. All categories were significantly different from each other (F3,192 = 1175, p < 0.0001 and all 6 pairwise comparisons using Tukey HSD were significantly different, p < 0.0001). The median DM for each category was 20%, 22%, 26% and 38% for ‘immature’, ‘early’, ‘mid’ and ‘late’ maturity categories (Figure 4A). The process of allocating avocados to individual consumers ensured no overlap in DM categories for any set of four avocados tasted by an individual consumer. This was confirmed by plots of differences in DM values between adjacent DM categories provided to individual consumers (Figure 4B). There are no pairs of fruit with negative differences in DM values (i.e. no fruit from a higher DM category that were actually lower in DM) and no fruit that had no (zero) difference between DM categories. Rather, the average DM difference going from ‘immature’ to ‘early’, from ‘early’ to ‘mid’ and from ‘mid’ to ‘late’ maturities were 3%, 3.5% and 13%, respectively. All the avocados that were presented to consumers fell within a narrow band of firmness/ripeness values. The mean firmness by hand assessment was 5.2 (standard deviation = 0.3; range = 4 to 5.5), where 5 indicates that the whole fruit deforms with moderate hand pressure (Figure 5). (A)

(B)

Figure 4. The distribution of DM content in individual avocados from each DM category (A), and the difference in DM between pairs of avocados from adjacent DM categories that were presented to individual consumers (B). Graphs are box plots in which the median is represented by the thick black horizontal line; the region between the upper and lower quartiles (square box) contains 50% of the data; 99% of the data lie between the horizontal lines that are connected by a vertical line; and the outlying data points are unfilled circles.

22

0

10

20

30

Immature Early Mid Late

Maturity

Fre

qu

en

cy

4

4.5

5

5.5

Figure 5. The distribution of firmness (hand assessments) of individual avocados in each DM category. The consumers were asked to taste avocados of differing DM content and indicate their absolute level of liking of each fruit, and to pay attention to the relative pattern of liking between these different avocados. We consider this as critical baseline information because this task is not cognitively challenging and consumers usually know exactly what they like and dislike (e.g. Harker et al. 2005, 2007). For example, it is increasingly well recognised that while consumers are good at identifying when something is wrong with a food (i.e. they dislike it), they will struggle to identify or explain what sensory attributes they disliked. In the current study, there was a significant increase in consumer liking for avocados as the fruit DM category increased (F3,318 = 52.20, p < 0.0001 and pairwise comparisons using Tukey HSD were significant, p < 0.0001 except between ‘early’ [22% DM] and ‘mid’ [26% DM] treatments were p = 0.0017). Average scores for consumer liking for the avocados was score = 4.4 (i.e. between ‘Neither liked nor dislike’ and ‘Like slightly’) for ‘immature’ (20% DM) category, score = 5.3 (i.e. between ‘Like slightly’ and ‘Like moderately’) for ‘early’ (22% DM) category, score = 5.9 (i.e. close to ‘Like moderately’) for ‘mid’ (26% DM) category and score = 7 (‘Like very much’) for ‘late’ (38% DM) category (Figure 6). There was no significant difference in liking for DM between any of the three consumer segments (i.e. ‘high frequency’, ‘medium’ and ‘occasional’ eaters of avocados). For the supplementary question (was the quality of the fruit acceptable or unacceptable?), the acceptability of all DM categories was relatively high, and even the lowest DM avocados (‘immature’ = 20% DM) were considered acceptable by more than 70% of consumers (Figure 6). DM categories had a significant influence on acceptability of avocados (χ2=36.941, 2 d.f., p < 0.0001, likelihood ratio test). There was a significant increase in consumer acceptance of the quality of the fruit as DM increased from ‘immature’ (20% DM) to ‘early’ (22% DM) (p < 0.0001), but not between any other pair of maturity/DM categories (NS). The increase in acceptability of avocados between ‘immature’ (20% DM) and ‘early’ (22% DM) categories may be important commercially as it indicates a level of disappointment associated with consumption of low DM fruit.

23

There were significant increases in consumers’ intention to purchase avocados at the stated price of $1.99 for each stepwise increase in DM band (Friedman's statistic adjusted for ties = 90.68, 3 d.f., p < 0.001, using chi-square approximation, Figure 6). Analysis using Wilcoxon Matched-Pairs Test confirmed differences between all DM/maturity categories. In Figure 6, the mean purchase intent is based on an analysis in which each category (e.g. ‘Probably will buy’; 70 to 89% chance) is converted to the average chance (e.g. 80%). This means that the maximum possible purchase intention (i.e. ‘Definitely will buy’) represents 95% chance rather than 100% chance. Average purchase intent of consumers increased from 47% (half way between ‘Possibly will’ and ‘Possibly will not buy’; i.e. unsure) for ‘immature’ avocados with 20% DM to 82% (~ ‘Probably will buy’) for ‘late’ avocados with 38% DM.

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Immature Early Mid Late0

20

40

60

80

100

b

aa

Accep

tab

ilit

y (

%)

a(A)

Immature Early Mid Late0

1

2

3

4

5

6

7

d

cb

Lik

ing

(S

co

re 1

to

8)

a(B)

Immature Early Mid Late0

20

40

60

80

(38% DM)(26% DM)(22% DM)

d

cb

Pu

rch

as

e i

nte

nt

(% c

ha

nc

e)

Maturity

a(C)

(20% DM)

Figure 6. Consumers scores for acceptability, liking and purchase intent for avocados from the different DM categories. Bars with different letters are significantly different from each other (see text).

25

Analysis of categories shown in Figure 6 suggests a linear relationship between increasing DM content of avocados and increasing consumer intentions to purchase fruit. This relationship was confirmed in Figure 7 where the curve (Loess smoother) was generated using all individual consumers’ responses and the points represent mean purchase intent as was calculated for discrete bands of DM (Note that the scatter plot produces a grid pattern because of the categorical nature of the data). Figure 7 shows a that consumers purchase intent increases in an approximately linear fashion up to about 28% DM, after which further increases in DM do not result in further increases in purchase intent. There is a suggestion that as DM increases over about 40% there is a slight decline in purchase intent. This might indicate that avocados with extremely high DM content were over-mature at harvest which resulted in poorer quality once the fruit was ripened (perhaps some rancidity). Thus, consumers provided lower liking scores and were less likely to purchase this fruit.

Figure 7. Relationship between DM of avocados and consumers’ purchase intentions

INTERPRETATION AND IMPLICATIONS OF DM STUDY

The objective of this part of the study was:

To determine the minimum maturity measurement as measured by % Dry Matter that

produces ‘Hass’ avocados which are of acceptable eating quality to Australian

consumers.

Australian consumers showed a progressive increase in liking and intent to buy avocados as the DM content increased. Consumers were unsure if they would purchase (~50% chance) an avocado with a DM of 20% when the price was $1.99 (i.e. the average price for avocados). When the DM increased to 38%, consumers indicated they would probably buy (~80% chance) the avocados. Consumer acceptance of the quality of avocados was relatively high at about 90–95%, but declined significantly to 70% if the DM was lower than 22%.

26

The data suggests two DM levels at which there are marked changes in consumer responses. The first occurs at 22% DM. Avocados with DM lower than 22% were significantly less acceptable to consumers than avocados with a DM of 22% or higher (Figure 6). The second DM threshold at which there was a change in consumer responses was at 28% DM. This was the DM level at which purchase intent was maximised and further increases in DM did not result in further improvement in consumers’ willingness to buy the avocados when examining the data points and curve in Figure 7. Based on these observations there are two obvious DM benchmarks that relate to eating quality:

• Minimum of 22% DM to exclude avocados that are of low taste acceptability.

• Maximum of 28% DM to exclude avocados that do not attract optimum consumer responses in terms of purchase intent.

There is a substantial gap between these two potential DM thresholds and it is important to consider what is happening in terms of consumer responses in this DM region. Average liking scores increased from 5.3 to 5.9 (i.e. increased by 0.6 units) as DM increased from 22% DM to 26% DM. Information on relationships between liking scores and choices of food products (Foley & Lancaster, 2003), predict that about 70% of consumers would choose the 26% DM avocados over the 22% DM avocados. This is confirmed to some extent in the current study by the increase from 60% to 68% in consumer indications of purchase intent (Figure 6). In essence, the gap between 22% DM and 28% DM represents a region were competitive advantage is gained by providing consumers with higher rather than lower DM avocados. Establishing a DM minimum in the region from 22% to 28% DM requires additional information on competitive advantages/disadvantages, including: (1) the extent that the industry wants to stimulate consumer demand in order to increase prices and/or increase volume of sales, (2) the risk that avocados supplied by competitors will erode sales of Australian avocados, (3) the impact of higher DM on entry dates for Australian avocados supplied into the marketplace, (4) impact on logistics and grower returns. The caveat in this interpretation of results is that all research was based on a fixed price of $1.99 per avocado (a representative average price). We do not know how these results would extend into different price points.

CONSUMER PREFERENCE FOR AVOCADOS OF DIFFERING FIRMNESS

As in the previous research on DM, it is important to demonstrate that the avocados used in this study represent distinct firmness categories before we can place any level of reliance on the consumer responses that were collected. The process of sorting avocados into different firmness categories was very successful. All categories were significantly different from each other (F2,151 = 614.1, p < 0.0001 and all six pairwise comparisons using Tukey HSD were significant p < 0.0001) The medium firmness values (puncture force values) were 1.05 kgf, 0.65 kgf and 0.45 kgf for ‘firm’, ‘medium’ and ‘soft’ avocados respectively (Figure 8A). The process of allocating avocados to individual consumers ensured no overlap in firmness categories for any set of three avocados tasted by an individual consumer. This was confirmed by plots of differences in firmness values between adjacent firmness categories provided to individual consumers (Figure 8B). There are no pairs of fruit with negative differences in firmness (i.e. no fruit from a firmer category was actually softer), and no fruit that had no (zero) difference between firmness categories (i.e. they were the same firmness when they should be different firmness). Rather, the average firmness difference going from ‘soft’ to ‘medium’ and from ‘medium’ to ‘firm’ were 0.25 kgf and 0.35 kgf, respectively. All the avocados that were presented to consumers fell within a narrow band of DM values. The mean DM content was 24% (standard deviation = 1.2%), and ranged from 22% to 27% (Figure 9).

27

The instrumental measurements of firmness were made using a penetrometer. While these measurements are widely used in many fruit crops, the avocado industry may be more familiar with instruments that measure deformation of whole fruit such as the Firmometer and/or hand assessments (e.g. measurements described in the IAQ manual; White et al. 2005). In the current study, both these more widely used measures of avocado firmness were available, but the batch of avocados had unusually thick and hard skins. Thick and hard skins occur with reasonable frequency in Australian-grown avocados (Hofman, pers. comm.). The presence of these types of skins alters our ability to predict the texture of the flesh using the pre-existing knowledge of Firmometer or hand measurements. With hard skinned avocados, the flesh tends to be much softer than one would expect on the basis of a Firmometer value or by squeezing the whole fruit. As part of our contingency plan, we had taken an Effegi penetrometer to make direct measurements of flesh firmness, and we ended up using this instrument to assess fruit texture. Pre-existing information on the relationships between Effegi penetrometer, Firmometer, and hand assessments were available from earlier HortResearch studies (White et al. 2005). This means that we can use penetrometer values in Figure 8 to infer firmness of avocados in units that may make more intuitive sense to readers from industry. Avocados with a penetrometer firmness of about 0.45 kgf usually equate to Firmometer values of 100 and a hand firmness of 6 (“very ripe”), penetrometer firmness of about 0.65 kgf usually equate to Firmometer values of 80 and a hand firmness of 5 (“eating ripe”) and penetrometer firmness of 1.05 kgf usually equate to Firmometer values of 60 and a hand firmness of 4 (“minimally ripe”). (A)

(B)

Figure 8. The firmness of individual avocados from each firmness category (A), and the difference in firmness between pairs of avocados from adjacent firmness categories that were presented to individual consumers (B). Graphs are box plots in which the median is represented by the thick black horizontal line; the region between the upper and lower quartiles (square box) contains 50% of the data; 99% of the data lie between the horizontal lines that are connected by a vertical line; and the outlying data points are unfilled circles.

28

Figure 9. The DM of individual avocados from each firmness category. Graphs are box plots in which the median is represented by the thick black horizontal line; the region between the upper and lower quartiles (square box) contains 50% of the data; 99% of the data lie between the horizontal lines that are connected by a vertical line. The consumers were asked to taste avocados of differing firmness and indicate their absolute level of liking of each fruit, and to pay attention to the relative pattern of liking between these different avocados. In the current study, there was a significant difference in consumer liking for avocados of differing firmness (F2,212 = 18.4, p < 0.0001). Pairwise comparisons using Tukey HSD indicated that ‘firm’ (1.05 kgf) avocados were significantly less liked than ‘medium’ (0.65 kgf) or ‘soft’ avocados (0.45 kgf; p < 0.0001), but that there was no significant difference in consumer liking of the two softer categories of fruit (i.e. 0.45 & 0.65 kgf; NS) (Figure 10). However, at a practical level, the change in the average consumer liking scores did not change markedly as the fruit softened, with all firmness treatments being scored between 5.1 (i.e. close to ‘Like slightly’) and 6.2 i.e. (i.e. close to ‘Like moderately’) (Figure 10). There was a significant difference in liking of avocados between the three consumer segments (p = 0.047). While all consumers provided similar relative response to changes in firmness/ripeness, overall the ‘high frequency eaters’ provided higher liking scores on average than ‘occasional eaters’ of avocados. Consumer acceptability of avocados of differing firmness was significantly different (χ2=6.82, 2 d.f., p = 0.033 using likelihood ratio test), with a significant increase in acceptability as fruit softened from ‘firm’ (1.05 kgf) to ‘medium’ (0.65 kgf) (p = 0.037) but no further increase in acceptability as the fruit softened from ‘medium’ (0.65 kgf) to ‘soft’ (0.45 kgf) (NS, p = 0.712). There was a significant difference in consumers’ purchase intent for the different firmness categories (Friedman's statistic adjusted for ties = 33.77, 2 d.f. p < 0.001, using chi-square approximation). Pairwise comparisons using Wilcoxon Matched-Pairs Test indicated that avocados with a firmness of 1.05 kgf elicited significantly lower purchase intention scores than avocados from either of the 0.65 kgf or 0.45 kgf categories (p < 0.001), which were not significantly different to each other (NS, p = 0.67). From a practical perspective, the

29

lower acceptance and purchase intention associated with firmer (1.05 kgf) avocados was relatively small: acceptance = 87% for the ‘firm’ avocados and 95% for ‘soft’ avocados, purchase intent = 58% chance (~ ‘Possibly will buy’) for the ‘firm’ avocados and 72% chance (~ ‘Probably will buy’) for ‘soft’ avocados (Figure 10).

Soft Medium Firm0

20

40

60

80

100 ba

Acce

pta

bil

ity (

%)

a(A)

Soft Medium Firm0

2

4

6 b

a

Lik

ing

(s

co

re =

1 t

o 8

)

a(B)

Soft Medium Firm0

10

20

30

40

50

60

70

(1.05 kgf)(0.65 kgf)

b

a

Pu

rch

ase I

nte

nt

(%)

Ripeness

a(C)

(0.45 kgf)

Figure 10. Consumers’ scores for acceptability, liking and purchase intent for avocados from the different firmness categories. Bars with different letters are significantly different from each other (see text).

30

Analysis of categories shown in Figure 10 suggests a linear relationship between increasing firmness of avocados and decreasing consumer intentions to purchase fruit. This relationship was confirmed in Figure 11 where the curve (Loess smoother) was generated using all individual consumers’ responses and the points represent mean purchase intent as was calculated for discrete firmness bands (Note that the scatter plot produces a grid pattern because of the categorical nature of the data). Figure 11 shows that the optimum firmness that attracts the maximum purchase intent is about 0.5 kgf. There was an almost linear decrease in purchase intent as consumers tasted progressively firmer avocados. However, the data suggest that as fruit soften beyond the 0.5 kgf optimum, there are also slight decreases in consumer purchase intention. This might suggest that the fruit were becoming over-ripe and developing slight off-flavours.

Figure 11. Relationship between increasing firmness (soft = 0.4 kgf and firm = 1.2 kgf) of avocados and decreasing consumers’ purchase intentions.

CONSUMER VOCABULARY AND USES OF AVOCADOS AFTER TASTING FRUIT WITH

DIFFERING FIRMNESS

From a list of words/phrases associated with uses of avocado, those chosen by more than 30 consumers were: ‘unripe’, ‘ripe’, ‘soft’, ‘firm’, ‘finger / thumb soft’, ‘buttery’, ‘spreadable’ and ‘creamy’ (Figure 12A). Avocados that were 1.05 kgf were more frequently described as being ‘unripe’ by 1/3 of all consumers and were described as being ‘ripe’ at a lower frequency than observed for softer fruit. The words ‘firm’ and ‘soft’ were well used by consumers although ‘ready to eat’ and ‘spreadable’ were used at higher frequencies (i.e. by about ¾ of all consumers). However, while ‘firm’ or ‘soft’ seemed to differ in a logical sequence between 1.05, 0.65 and 0.45 kgf categories, ‘ready to eat’ and ‘spreadable’ only differentiated the firmer treatment (i.e. 1.05 kgf fruit) from the two softer treatments (i.e. 0.65 and 0.45 kgf fruit). The only words that related solely to texture in the mouth and were used by more than 30 consumers were: ‘buttery’ and ‘creamy’. Both seemed to differentiate among all firmness categories.

31

The intended uses of avocados that attracted responses from over half the consumers were: ‘as a spread’, ‘on bread’, ‘on crackers’, ‘as an ingredient in a salad’, ‘as a dip / guacamole’ and ‘with nachos’ (Figure 12B). Uses that were identified by more than a quarter of all consumers included: ‘with sushi’, ‘on a platter’ and ‘I would leave it to use on a later date’. These more frequently identified uses (i.e. identified by > ½ or > ¼ of consumers) were equally appropriate for medium and soft avocados (i.e. 0.65 and 0.45 kgf fruit). Generally the firm avocados (~1.05 kgf) were less likely to be associated with any of these uses, with the exceptions: ‘as an ingredient in a salad’ and ‘I would leave it to use on a later date’. Firm, medium and soft avocados were equally likely to be identified as being used ‘as an ingredient in a salad’. However, ‘I would leave it to use on a later date’ was mostly associated with firm avocados. Indeed, about a third of consumers indicated that they would leave the firmer fruit (i.e. 1.05 kgf) to use at a later date. This is a relatively clear indication that that they thought it was not ripe enough to eat, and confirms data collected on liking, acceptability and purchase intentions (Figure 10). Another important observation is that few consumers indicated that they would dispose of the fruit (i.e. ‘give it to a pet’, ‘compost it’ or ‘I would throw it away’; Figure 12B) even when the fruit was as soft as 0.46 kgf. This is an intriguing observation given that earlier studies have indicated high levels of wastage associated with poor quality and difficulties with ripeness. It may be that the quality / wastage problems are due to rots and bruising more than over-ripe fruit and those soft avocados are acceptable to consumers as long as they don’t have rots or bruises.

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(A) Vocabulary

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(B) Uses

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Firm

Medium

Soft

Figure 12. Consumer vocabulary (A) and uses of avocados (B) as indicated after tasting fruit of differing firmness. Avocados tasted were from firm (1.05 kgf), medium (0.65 kgf) and soft (0.46 kgf) firmness categories.

33

CONSUMER JUDGEMENTS OF FIRMNESS OF WHOLE AVOCADOS

Consumers indicated three techniques for assessing the condition/ripeness of avocados. The first and slightly more common technique involved consumers considering the colour (green through black) and then squeezing the avocados (39% of consumers). The second technique involved consumers squeezing the avocado to assess its firmness before checking its colour (24% of consumers). It is possibly semantic to separate these two categories on the basis of the order in which colour or squeezing is used to assess ripeness. In practice, consumers may assess colour and squeeze simultaneously. Yet clearly the majority (63%) of consumers use both colour and squeezing to determine ripeness. The alternative technique relied solely upon squeezing as the method for assessing ripeness (37% of consumers). Consumers generally chose ‘medium’ (0.65 kgf) or ‘soft’ (0.45 kgf) avocados to eat today, and were ‘very certain’ if not ‘extremely certain’ about their decision (Figure 13a). When asked to select a fruit to eat in 3–4 days time, most consumers chose avocados that were ‘medium’ (0.65 kgf) firmness, about half as many consumers chose the ‘firm’ (1.05 kgf) fruit and a much smaller number of consumers selected the ‘soft’ (0.45 kgf) avocados (Figure 13a). Certainty around these decisions was reduced, but most consumers retained moderate certainty that they selected the right avocado to eat in 3–4 days time. It is not possible to infer how good the consumers are at selecting fruit that will be eaten in 3–4 days time unless something is known about how they normally handle avocados in their homes. While 70.5% of consumers indicated that they left avocados at room temperature, 18% kept them in a refrigerator. The remaining 11% of consumers had a range of storage techniques: 13 consumers stored avocados with other fruit to accelerate ripening and five consumers stored them in a dark place. It was established that 75% and 7% of consumers stored their ‘hard’ avocados at room temperature and in the refrigerator, respectively. However, for ‘medium’ firmness avocados fewer consumers stored their fruit at room temperature (64% of consumers) and more stored them in the refrigerator (27% of consumers). This suggests that consumers are modifying handling procedure in the home depending on firmness of fruit, but, in our opinion, these percentages suggest that for a substantial number of consumers there is little or no control over ripening of avocados in the home. In addition to asking what firmness categories consumers usually bought, the consumers were asked when they usually planned to eat the avocados from each of the categories they had indicated they bought (Figure 14). Relatively few consumers indicated that they selected fruit because it was all there was available. Consumers selecting ‘hard’ fruit (~5 kgf1) generally planned to eat them in 3–4 days or in one week. The majority of consumers who bought ‘firm’ (1.05 kgf) avocados planned to eat them in 3–4 days, with a smaller number planning to eat them on the day they were purchased. Consumers who bought ‘medium’ firmness (0.65 kgf) avocados mostly planned to eat them on the day they were purchased with a smaller number planning to eat them in 3–4 days time. Consumers who bought ‘soft’ fruit almost exclusively planned to eat them on the day they were purchased. These results suggest that consumers are astute in planning when they will eat avocados based on the firmness of the fruit they purchase. However, they provided a strong indication that their preference was to purchase fruit that were ready to eat/use immediately (91 consumers) or would be ready to eat/use in 3–4 days time (61 consumers). There were only three consumers who responded that they preferred to buy avocados that would be ready to eat/use in about a week’s time.

1 Estimated value (see methods)

34

(A)

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Figure 13. Percentage of consumers who (A) identified avocados of defined firmness (Hard = ~5 kgf. Firm = 1.05 kgf, Medium = 0.65 kgf and Soft = 0.45 kgf) as the fruit they would eat today, in 3-4 days time and the fruit that they usually buy; and (B) the consumers level of certainty in their decisions.

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Figure 14. The percentage of consumers indicating when they planned to eat the avocados they usually purchase (Hard = ~5 kgf. Firm = 1.05 kgf, Medium = 0.65 kgf and Soft = 0.45 kgf).

35

CONSUMER VOCABULARY AND USES OF AVOCADOS BASED ON ASSESSMENTS OF

FIRMNESS OF WHOLE AVOCADOS

The words/phrases chosen to describe the different firmness categories were often quite definitive as can be seen in Figure 15. Consumers used the words ‘unripe’ and ‘hard’ to describe the hardest avocados (~5 kgf) and rarely used ‘unripe’ and ‘hard’ when describing avocados from any other firmness category (Figure 15a). Consumers used the words/phrases ‘medium ripe’, ‘nearly ripe’ and ‘firm’ to describe firm (1.05 kgf) avocados (Figure 15a). However, only ‘medium ripe’ was used principally to describe these avocados over avocados from other firmness categories. ‘Ripe’ and ‘ready to eat’ were used by consumers to describe the medium firmness category (0.65 kgf), but these were also used to describe the softest avocados. The softest avocados (0.45 kgf) were differentiated principally by the use of ‘soft’ and ‘mushy’ as descriptors of avocado firmness. The hard avocados (~5 kgf) were almost universally identified by consumers as needing to be left until a later date (92 consumers responded in this way; these data are not presented in Figure 15b in order to improve visualisation of data for other firmness categories). Softer avocados (i.e. 1.05 kgf, 0.65 kgf, 0.45 kgf) attracted responses from over half the consumers for uses: ‘as a spread’, ‘on bread’, ‘on crackers’, ‘as an ingredient in a salad’, ‘as a dip / guacamole’, and ‘with nachos’ (Figure 15). The ‘firm’ avocados (1.05 kgf) attracted the response: ‘I would leave it to use on a later date’ from more than half of consumers. More than a quarter of consumers identified uses such as ‘with other Mexican foods’, ‘with sushi’, ‘in a prawn cocktail’ and ‘on a platter’ and ‘for a baby’. Consumers were more frequently indicating that they would discard the soft (0.45 kgf) avocados (i.e. ‘I would throw it away’) on the basis of their evaluation of the firmness/ripeness of whole fruit (Figure 15) than when they actually tasted the flesh (Figure 12). However for almost all other uses and all firmness categories the number of consumer responses increased after tasting (Figure 15 cf. Figure 12).

36

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Figure 15. Consumer vocabulary (A) and uses of avocados (B) as indicated after assessing firmness of whole avocados. Avocados were from hard (~5 kgf), firm (1.05 kgf), medium (0.65 kgf) and soft (0.45 kgf) firmness categories. 92 consumers responded solely that they would leave ‘hard’ avocados to use on a later date – these data are not presented in order to improve visualisation of data for other firmness categories.

INTERPRETATION AND IMPLICATIONS OF FIRMNESS STUDY

The objective of this part of the study was:

To determine the level of ripeness (firmness) that is preferred by consumers at the time

of consumption

In responding to this objective it was necessary to consider consumers’ preferences based on their assessments of whole fruit as well as the taste of the avocado flesh. After handling (squeezing) avocados from the hardest firmness category (~5 kgf firmness), 86% of the consumers indicated that they would leave the avocados to eat/use on a later date. The firm

37

fruit (1.05 kgf firmness), were also judged as needing to be left to eat/use on a later date by 50% of consumers after handling the fruit. For both these firmness categories (~5 kgf and 1.05 kgf), it is likely that fewer consumers would actively select them to eat compared with softer avocados. Consumers who tasted avocados indicated that on average the fruit that were about 1.05 kgf firmness were significantly less liked, less likely to be purchased and less acceptable than fruit that were 0.65 kgf or 0.45 kgf. Avocados from these two softer firmness categories were not significantly different from each other according to any of the consumer responses measured. However, the softest category (0.45 kgf) was slightly more likely to be identified as needing to be thrown away during squeezing of whole fruit, but not when the flesh was consumed. Collectively these results indicate that consumers’ preferred ripeness (firmness) for avocados was 0.65 kgf. The preferred avocado firmness of 0.65 kgf (puncture force) usually equates to a Firmometer value of about 80 and a hand firmness of about 5 (i.e. whole fruit deforms with moderate hand pressure), although the relationships between flesh texture and whole fruit deformation will change if the fruit has a particularly hard or thick skin.

REASONS FOR USING CONJOINT ANALYSIS TO DETERMINE CONSUMER

RESPONSES TO BRUISING

To determine the maximum acceptable level of internal defects at different price points above which future consumer purchasing decisions are negatively influenced (i.e. Objective 3), the methodology of conjoint analysis was used. Before detailing the empirical application and its findings, some background information on conjoint analysis is provided. The seminal theoretical contribution to conjoint analysis was made by Luce and Tukey (1964), who developed procedures for simultaneously measuring the joint effects of a set of independent variables on the ordering of a dependent variable. Today, the term conjoint analysis is used to refer to any decompositional method used in the modelling of consumer choices among multi-attribute alternatives. In essence, conjoint methodology allows discovery of how consumers value different product features and attributes. Specifically, it allows estimation of the structure of a consumer's preferences given his or her overall evaluation of a set of alternatives that are pre-specified in terms of levels of different attributes (Green & Srinivasan 1978; p. 104). The conjoint analysis approach assumes that products generate particular levels of perceived utility (e.g. preference or value) to individual consumers based on specific attributes and associated levels and a product’s total utility is decomposed into the contributions of individual product attributes, which are termed part-worths. Further computations using these part-worths allow for the establishment of the relative importances of factors used in the research design. Thus conjoint analysis represents a suitable technique for determining the maximum acceptable level of internal defects at different price points above which future consumer purchasing decisions are negatively influenced. By quantifying how consumers trade defect against price, insight into the maximum level of defect that is accepted at a given price level can be gained. In application conjoint analysis resembles an experimental design because both the independent variables and their levels are pre-specified in the design through establishment of relevant multi-attribute stimuli. Because conjoint analysis has few statistical assumptions and instead relies more heavily on conceptual assumptions, the reliability of conjoint designs hinges on the selection of realistic and relevant attributes and levels (Hair et al. 2006). In this study, following extensive consultation with Avocado Australia, it was decided to include

38

three factors in the conjoint experiment: price per avocado, level of internal defect (bruising) and frequency of defect occurring in recent past purchases. The four price levels were based on common price points in the Australian retail market. To enable a more realistic representation of the consumer decision process it was decided to explore tolerance to internal defects through two separate experimental factors: the level of internal defect in a given fruit, and the frequency with which the consumer experiences this level of defect. It was thought that the extent to which internal defects negatively impacts future purchases is determined not only by the level of defect in the current fruit, but rather that tolerance is moderated by the frequency with which this level of defect is experienced. Bruising was chosen as the focal internal effect, because it is the type of internal defect Australian consumers are most likely to experience. In the study, this factor was operationalised through high quality colour images of half cut avocado fruit with the stone removed (Figure 3). Specifically, the photographs were digitally manipulated to vary only the level of internal defect, while keeping fruit shape and colour of fruit flesh constant. This ensured that level of defect was the only way in which the photographs varied and control over experimental manipulation was hereby retained.

IMPACT OF PRICE, SEVERITY AND INCIDENCE OF BRUISING ON CONSUMER

PURCHASE INTENTIONS

One of the initial targets of this research was to determine if the different consumer segments (‘High’, ‘Medium’ and ‘Occasional eating frequency’ consumption rates) responded differently to bruising. Comparison of relative factor importance across the three eating frequency segments indicated there was no statistical differences in the responses of the three segments. (see Appendix 1 for analysis of individual segments and comparison between segments). All further analyses were thus performed on the aggregate sample, and these results are presented in the following two sub-sections. Using all 107 participants as input, a highly significant main effects model was estimated (F9,614 = 73.2, p < 0.0001) with R2=0.44. All beta coefficients were significant (p < 0.0001) and the signs of part-worths associated with the levels of each experimental factors were in the expected directions (Figure 16). The highest levels of utility was associated with the lowest price, and as price increased future purchase probability decreased. Also, relationships were found for the other two experimental factors: i) as the level of bruising increased, future purchase probability decreased; and ii) as the incidence of purchasing an avocado with bruising increased, future purchase probability decreased. The slope of the part-worth function for the price factor (Figure 16A was less steep for the change in price from $1.29 to $1.99 than for the subsequent price increases, suggesting a less negative impact on future purchase probability at lower than higher price levels. For the experimental factor relating to level of bruising, the strongest negative impact on future purchase probability was for the increase from 10% to 25% bruising (Figure 16B). There was relative insensitivity to the increase from 25% bruising to 33% bruising, and then a stronger negative impact when bruising increased from 33% to 50%. For the part-worth function pertaining to the incidence of bruising, there was relatively less impact on future purchase probability as incidence increased (Figure 16C). The negative impact was strongest when the frequency of occurrence changed from 1-in-10 to 1-in-5; lesser when the change in frequency was from 1-in-5 to 3-in-5; and smallest when the change was from 3-in-5 to 5-in-5.

39

(A)

(B)

(C)

Figure 16. Part-worths for a main effects model bassed on the aggregate sample (N=107). 16A) part-worths for the price experimental factor, 16B) part-worths for the level of bruising experimental factor, 16C) part-worths for the incidence of bruising experimental factor.

40

Next, following the procedures outlined earlier, the relative factor importances were determined: Price = 28.8%, Level of Bruising = 36.6% and Incidence of bruising = 34.6%. This suggested that price was of less importance in Australian consumers purchase decisions than the experimental factors relating to internal defects, and that both the level of bruising and the frequency with which such a level of bruising was experienced strongly and negatively impacted future purchase probability. In the aggregate analysis, it was of particular interest to understand if, in fact the relative importances of the three experimental factors differed significantly, and to do so, as outlined in methods section, paired t-tests for differences in the log transformed relative importances were performed. Recall that because the factor importances are bounded by 0 and 1, they do not distribute Normal. To overcome this, a log transformation was applied, and the subsequent t-test therefore tested if the odds ratio between a pair of factor importances was different from 1. Where evidence was found that the odds ratio differed from 1, it could be concluded that the relative importances were also significantly different. The relative importance (RI) of the experimental factor for bruising (36.6%) was not significantly different from the relative importance for incidence of bruising (34.6%) (t = 0.11, 106 d.f., p = 0.91). However, the RI of the experimental factor for bruising (36.6%) was significantly different from the relative importance for price (28.8%) (t = 2.81, 106 d.f., p = 0.006). Further, the RI of the experimental factor for incidence of bruising (34.6%) was significantly different from the relative importance for price (28.8%) (t = 2.48, 106 d.f., p = 0.015). To focus the analysis further in order to determine the maximum level of internal defects at different price points above which future consumer purchase decisions are negatively influenced, the model was used to predict future purchase probability at fixed price points. Specifically, for each price point, future purchase probability was calculated for all possible combinations of levels and incidence of bruising. The results are shown in Figure 17, using colour coding matched to the 6-point response scale for purchase probability.

41

(A) Price=$1.29 Definitely will buy (90-100% chance)

Bruising 1 in 10 1 in 5 3 in 5 5 in 5 Probably will buy (70-89% chance)

10% 0.95 0.87 0.68 0.57 Possibly will buy (50-69% chance)

25% 0.76 0.68 0.49 0.38 Possibly will not buy (30-49% chance)

33% 0.68 0.60 0.41 0.30 Probably will not buy (10-29% chance)

50% 0.58 0.50 0.31 0.20 Definitely will not buy (less than 10% chance)

Incidence

(B) Price=$1.99 Definitely will buy (90-100% chance)

Bruising 1 in 10 1 in 5 3 in 5 5 in 5 Probably will buy (70-89% chance)

10% 0.84 0.79 0.59 0.52 Possibly will buy (50-69% chance)

25% 0.63 0.58 0.39 0.31 Possibly will not buy (30-49% chance)

33% 0.59 0.54 0.35 0.27 Probably will not buy (10-29% chance)

50% 0.45 0.40 0.20 0.13 Definitely will not buy (less than 10% chance)

Incidence

(C) Price=$2.49 Definitely will buy (90-100% chance)

Bruising 1 in 10 1 in 5 3 in 5 5 in 5 Probably will buy (70-89% chance)

10% 0.71 0.62 0.47 0.37 Possibly will buy (50-69% chance)

25% 0.55 0.46 0.31 0.21 Possibly will not buy (30-49% chance)

33% 0.50 0.41 0.26 0.16 Probably will not buy (10-29% chance)

50% 0.41 0.32 0.17 0.07 Definitely will not buy (less than 10% chance)

Incidence

(D) Price=$2.99 Definitely will buy (90-100% chance)

Bruising 1 in 10 1 in 5 3 in 5 5 in 5 Probably will buy (70-89% chance)

10% 0.61 0.54 0.43 0.37 Possibly will buy (50-69% chance)

25% 0.36 0.29 0.18 0.12 Possibly will not buy (30-49% chance)

33% 0.38 0.31 0.20 0.14 Probably will not buy (10-29% chance)

50% 0.31 0.24 0.13 0.07 Definitely will not buy (less than 10% chance)

Incidence

Figure 17. Prediction of future purchase probability at fixed price points. 17A) Purchase probabilities at the $1.29 price point; 17B) Purchase probabilities at the $1.99 price point; 17C) Purchase probabilities at the $2.49 price point; and 17D) Purchase probabilities at the $2.99 price point. The highest level of future purchase probability (‘Definitely will buy’ (90–100% chance)) was only predicted to occur for an avocado costing $1.29 and when previous purchases have been characterized by the lowest levels of bruising and incidence of bruising occurring (1-in-10 frequency). However, it is noted that at this price level the negative impact of increase in incidence from 1-in-10 to 1-in-5 appears to be smaller than the increase in level of bruising from 10% to 25% (Figure 17A). Future purchase probability is predicted to fall in the category ‘Probably will buy’ (70–89%) for three different price points. However, it is only when the price is $1.29 that a 25% level of bruising is tolerated (Figure 17A). For the $1.99 price point, probability is predicted at 89% and 79%, respectively for 10% bruising in combination with incidences 1-in-10 and 1-in-5 (Figure 17B). For the $2.49 price point, bruising and incidence at the lowest experimental levels lead to predicted future purchase probability of 71% (Figure 17C), which is at the very lower end of the ‘Probably will buy’ response category. This suggests that when an avocado costs $2.49, consumers expect a consistent and high quality product. This latter expectation is seen even stronger in Figure 17D, which pertains to the $2.99 price point. Bruising and incidence of bruising at the lowest experimental levels result in low future purchase probabilities. At the highest of the price points included in the study, the strong negative impact of bruising is particularly noticeable for the incidence level 1-in-10.

42

INTERPRETATION AND IMPLICATIONS OF STUDY ON CONSUMER RESPONSES TO

BRUISING

The study has demonstrated that all three experimental factors (i.e., price, level of bruising and incidence of bruising) significantly impact on consumers’ future purchase decisions. The impacts are in the expected directions: increases in price, level of bruising or frequency of bruising occurring lead to lower future purchase probability. The impact of price (relative importance = 28.8%) is significantly lower than the negative impact of level of bruising (relative importance = 36.6%) and frequency of bruising occurring (relative importance = 34.6%). Further, the difference in relative importance between level of bruising and incidence of bruising is not statistically significant. It is predicted that future purchase probability would only be very high (90–100% chance) when avocados are priced at $1.29 and the level of bruising is at 10% and the frequency of occurrence 1-in-10. For fruit priced at $2.99, any presence of bruising even at the lowest occurrence (1-in-10) would lead to low predicted future purchase probability (61%; ‘Possibly will buy’). Overall, the results suggest that to maintain high future purchase probability, price should be kept as low as possible. It is more important, however, to reduce bruising and incidence of bruising in avocado fruit available to Australian consumers. The objective of this part of the study was:

To determine the maximum acceptable level of internal defects (bruising) at different

price points above which future consumer purchasing decisions are negatively

influenced.

If we take “probably will buy”(70% to 89% probability of purchase; mean = 80%) which was the maximum average score in all research which involved tasting of avocados (Figures 6 & 7) as the starting point, we can consider what levels and incidences of bruising will reduce purchase intent below this optimum:

• At a price point of $1.29, consumers would continue to indicate that they would ‘probably buy’ the fruit as long as no more than 25% of the flesh is bruised in no more than 1 in 10 purchases or when no more than 10% of the flesh is bruised in no more than 1 in 5 purchases.

• At a price point of $1.99, consumers would continue to indicate that they would ‘probably buy’ the fruit as long as no more than 10% of the flesh is bruised in no more than 1 in 5 purchases.

• An 80% probability of purchase was not achieved for avocados costing $2.49. The highest probability was 71% (lowest end of the category ‘probably buy’) and this was achieved only when the level and incidence of bruising was at the lowest experimental levels (i.e. 10% tissue damage in 1-in-10 avocados).

• At a price point of $2.99, even with minimum bruising, consumers only indicated that they would ‘possibly buy’ the avocados (61% purchase intention).

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CONCLUSIONS

The study has found that maturity (DM content), ripeness (firmness) and level of bruising in avocados all have a major impact on consumer responses and in particular on purchase intentions. Consumers showed a progressive increase in liking and intent to buy avocados as the DM content increased. Consumers were unsure if they would purchase (~50% chance) an avocado with a DM of 20% when the price was $1.99 (i.e. the average price for avocados). When the DM increased to 38%, consumers indicated they would probably buy (~80% chance) the avocados. Consumer acceptance of the quality of avocados was relatively high at about 90-95%, but declined significantly to 70% if the DM was lower than 22%. Consumers assessed firmness of whole fruit as well as the tasting of the avocado flesh. After handling (squeezing) avocados from the hardest firmness category (~5 kgf firmness) 86% of the consumers indicated that they would leave the avocados to eat/use on a later date. The firm fruit (1.05 kgf firmness), were also judged as needing to be left to eat/use on a later date by 50% of consumers. For both these firmness categories (~5 kgf and 1.05 kgf) it is likely that fewer consumers would actively select them to eat compared with softer avocados. Consumers who tasted avocados indicated that on average the fruit that were about 1.05 kgf firmness were significantly less liked, less likely to be purchased and less acceptable than fruit that were 0.65 kgf or 0.45 kgf. Avocados from these two softer firmness categories were not significantly different from each other according to any of the consumer responses measured. A conjoint study approach was used explore the impact of flesh damage, in this case bruising, on consumer preferences. The study has demonstrated that all three experimental factors (i.e., price, level of bruising and incidence of bruising occurring) significantly impact on consumers’ future purchase decisions. The impacts are in the expected directions: increases in price, level of bruising or frequency of bruising occurring lead to lower future purchase probability. The impact of price (relative importance = 28.8%) was significantly lower than the negative impact of level of bruising (relative importance = 36.6%) and frequency of bruising (relative importance = 34.6%). Further, the difference in relative importance between level of bruising and incidence of bruising was not statistically significant. It is predicted that future purchase probability would only be very high (90–100% chance) when avocados are priced at $1.29 and the level of bruising is at 10% and the frequency of occurrence 1-in-10. For fruit priced at $2.99 any presence of bruising even at the lowest occurrence (1-in-10) lead to low predicted future purchase probability (61%; ‘Possibly will buy’). Overall, the results suggest that to maintain high future purchase probability price should be kept as low as possible. More importantly, however, is to reduce bruising and incidence of in avocado fruit available to Australian consumers.

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RECOMMENDATIONS

Objective 1. To determine the minimum maturity measurement as measured by % Dry

Matter that produces ‘Hass’ avocados which are of acceptable eating quality to

Australian consumers.

There are three options for setting a minimum DM for avocados:

• Minimum of 22% DM to exclude avocados that are of low taste acceptability.

• Maximum of 28% DM to exclude avocados that do not attract optimum consumer responses in terms of purchase intent.

• Minimum between 22% DM and 28% DM to ensure an appropriate competitive advantage in the marketplace.

There first two options are based on the observation of DM thresholds that were associated with marked changes in consumer responses. The third option reflects the approximately linear increase in liking and purchase intent that occurs as DM increases from 22% to 28%. Thus, improvements in DM in this region have the potential to stimulate consumer demand and consequently increase prices or increase volume of sales. However, decisions on where to set a minimum would require additional information to establish the desired competitive positioning of the Australian avocado industry. Objective 2. To determine the level of ripeness (firmness) that is preferred by consumers

at the time of consumption.

In responding to this objective it was necessary to consider consumers’ preferences based on their assessments of whole fruit as well as the taste of the avocado flesh.

• The ripeness (firmness) of avocados that was preferred by consumers was 0.65 kgf or softer (measurement of flesh texture using a penetrometer with an 11 mm diameter probe). This firmness level usually relates to Firmometer value of about 80 and a hand firmness of about 5 (i.e. whole fruit deforms with moderate hand pressure).

Objective 3. To determine the maximum acceptable level of internal defects (bruising) at

different price points above which future consumer purchasing decisions are negatively

influenced.

The levels and incidences of bruising will reduce consumers’ purchase intent below ‘probably buy’ (i.e. 70% to 89% probability of purchase) were:

• At a price point of $1.29, bruising should damage no more than 25% of the flesh and no more than 1 in 10 avocados should exhibit this level of damage. Alternatively, if less of the flesh is damaged (i.e. 10% of the flesh is bruised) then consumers will accept a higher incidence of damaged fruit (i.e. no more than 1 in 5 avocados).

• At a price point of $1.99, bruising should damage no more than 10% of the flesh and no more than 1 in 5 avocados should exhibit this level of damage.

• At a price point of $2.49, the maximum bruise size that would be tolerated remained at 10% of the flesh, but incidence of bruising needed to be much lower at no more than 1 in 10 avocados. Even at this low level and incidence of bruising, the highest probability was 71% (i.e. at the very lowest end of the category ‘probably buy’).

• At a price point of $2.99, even with minimum bruising, consumers only indicated that they would ‘possibly buy’ the avocados (61% purchase intention).

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REFERENCES

Arpaia ML, Boreham D, Hofshi R 2001. Development of a new method for measuring minimum maturity of avocados. Californian. Avocado Society 2001 Yearbook 85: 153-178. Chernick MR 1999. Bootstrap methods. New York, John Wiley and Sons, Inc. Efron B 1979. Bootstrap methods: another look at the jackknife, The Annals of Statistics, 7 (1): 1-26. Efron B 1981. Nonparametric estimates of standard error: the jackknife, the Bootstrap and Other Methods. Biometrika, 68 (3): 589-599. Efron B 1982. The jackknife, the bootstrap and other resampling plans, Regional Conference Series in Applied Mathematics, Stanford, 38. Efron B, Tibshirani RJ 1993. An introduction to the bootstrap, New York: Chapman & Hall. Foley MM, Lancaster BM 2003. Method for determining forced choice consumer preferences by hedonic testing. United States Patent: 6,623,040 Gil JM, Sánchez M 1997. Consumer Preferences for Wine Attributes: A Conjoint Approach. British Food Journal, 99 (1): 3-11. Green PE, Rao VR 1971. Conjoint measurement for quantifying judgmental data. Journal of. Marketing Research, 8: 355-363. Green PE, Srinivasan V 1978. Conjoint analysis in consumer research: issues and outlook. Journal of Consumer Research, 5 (2): 103-123. Hair JFJr, Black WC, Babin BJ, Anderson RE, Tatham RL 2006. Multivariate Analysis, 6th ed. Pearson Education International, Upper Saddle River, NJ. Hofman P, Ledger S. 2001. Reducing avocado defects at retail level – Avocare. Department of Primary Industries, Queensland. 33pp. Johnston J, Requejo-Jackman C, White A, Woolf A 2006. Avocado maturity: a review of harvest indices and the relationship with postharvest quality. Report to Avocados Australia and Horticulture Australia. HortResearch Client Report Number 20621. Luce RD, Tukey JW 1964. Simultaneous conjoint measurement: a new type of fundamental measurement. Journal of Mathematical Psychology, 1: 1-27. Schroeder 1985. California Avocado Society Yearbook, 69: 137-143. White A, Woolf A, Hofman P, Arpaia ML 2005. The international avocado quality manual. The Horticultural and Food Research Institute of New Zealand Ltd, Auckland, New Zealand. 72 pp.

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ACKNOWLEDGEMENTS

We would like to thank the staff at the Redlands Research Station for their assistance and use of the facilities. We would also like to acknowledge TNS for the recruitment of consumers, and Melody Tyrer for welcoming the consumers and providing support during the panels. The support received by Joanna Embry both with the preparation and during the consumer panels was also much appreciated. And finally we would like to extend our thanks to Avocados Australia Ltd for the opportunity to be involved in the project, and for their continued input and interest throughout the development of the questionnaires and other aspects of the project.

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APPENDIX 1. CONJOINT STUDY ON BRUISING: ANALYSIS

OF CONSUMER SEGMENTS

WITHIN-SEGMENT MAIN EFFECTS MODELS

‘High eating frequency’ segment (‘A’)

First, the main effect model for each segment is described in turn. For the ‘high eating frequency segment’ (‘A’, once per week or more often), an aggregate model was estimated based on 39 participants (36.4%). It was highly significant (F9,614 = 73.2, p < 0.0001) with R2 = 0.51. All beta coefficients were significant (p < 0.001) and the signs of part-worths associated with the levels of each experimental factors were in the expected directions (Figure A1). For example, as price increased, part-worths (and by proxy utilities) decreased, and therefore impacted negatively on future purchase probability. Similar expected relationships were found for the other two experimental factors: i) as the level of bruising increased, utility decreased and so did future purchase probability; and ii) as the incidence of purchasing an avocado with bruising increased, future purchase probability decreased. However, as can also be seen from Figure A1, the change in part-worths within a factor was not linear. For the experimental factor pertaining to price, the negative impact on purchase price was lower at lower prices. Figure A1a shows that the slope of the part-worth function changes at $1.99 and becomes steeper. This says that in the ‘high eating frequency’ segment (‘A’), future purchase probability is somewhat less negatively impacted when the price of avocados change from $1.29 to $1.99 than when the price changes from $1.99 to $2.49 and from $2.49 to $2.99. The piece-wise linearity of the part-worth function is very obvious for the experiment factor relating to the level of bruising (Figure A1b). The negative impact of an increase in bruising from 10% to 25% is much stronger than the increases from 25% to 33% and from 33% to 50%. This says that in the ‘high eating frequency’ segment, future purchase probability is more sensitive to lower than higher levels of the internal defect of flesh bruising. For the experimental factor manipulating the non-linearity of impact on utility across the four levels (1-in-10: very infrequent occurrence; 1-in-5: infrequent occurrence; 3-in-5 quite frequent occurrence; 5-in-5 persistent occurrence) was also evident (Figure A1c). The negative impact on purchase probability was greatest when the incidence of occurrence changed from 1-in-10 to 1-in-5; lesser when the change in incidence was from 1-in-5 to 3-in-5, and smallest when the change in incidence was from 3-in-5 to 5-in-5. Following the procedures outlined in the methods, the relative factor importances were determined: Price = 28.9%, Level of Bruising = 35.2% and Incidence of bruising = 35.9%. This suggested that price was of less importance in consumers purchase decisions that the experimental factors relating to internal defects, and that both the level of bruising, as well as the frequency with which such a level of bruising was experienced strongly and negatively impacted future purchase probability in the ‘high eating frequency’ segment.

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Figure A1. Part-worths for the ‘high eating frequency’ segment (‘A’). a) part-worths for the price experimental factor, b) part-worths for the level of bruising experimental factor, c) part-worths for the incidence of bruising experimental factor.

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‘Medium eating frequency’ segment (‘B’)

For the ‘medium eating frequency’ segment (‘B’, about once per fortnight), an aggregate model was estimated based on 41 participants (38.3%). It was highly significant (F9,646 = 50.9, p<0.0001) with R2 = 0.41. All beta coefficients were significant (p<0.02) and the signs of part-worths associated with the levels of each experimental factors were in the expected directions (Figure A2). As was found in the ‘High eating frequency’ segment, the highest levels of utility was associated with the cheapest price, and as price increased future purchase probability decreased. Also as in the previous segment, expected relationships were found for the other two experimental factors: i) as the level of bruising increased, future purchase probability decreased; and ii) as the incidence of purchasing an avocado with bruising increased, future purchase probability decreased. As also found in the previous segment, the change in part-worths within a factor was not linear (Figure A2). Further, the pattern of non-linearity was very similar to that determined in the ‘high eating frequency’ segment. This was particularly the case for the price and incidence of bruising experimental factors, as can be ascertained by a comparison of Figures 3a and 4a, and 3c and 4c, respectively. For the factor pertaining to level of bruising, the strong negative impact on the change from 10% to 25% bruising remained. However, the consumers in this ‘medium eating frequency’ segment were almost insensitive to a change in bruising from 25% to 33% (as can be seen by the near horizontal part-worth function connecting 25% and 33% in Figure A2b). The increase from 33% bruising to 50% bruising was, however, strongly and negatively reacted to. Following the procedures outlined in the methods, the relative factor importances were determined: Price = 28.2%, Level of Bruising = 36.40% and Incidence of bruising = 35.41%. As above, this suggested that price was of less importance in consumers purchase decisions that the experimental factors relating to internal defects, and that both the level of bruising, as well as the frequency with which such a level of bruising was experienced strongly and negatively impacted future purchase probability in the ‘medium eating frequency’ segment.

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Figure A2. Part-worths for the ‘Medium eating frequency’ segment (‘B’). a) part-worths for the price experimental factor, b) part-worths for the level of bruising experimental factor, c) part-worths for the incidence of bruising experimental factor.

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‘Occasional eating frequency’ segment

For the ‘occasional eating frequency ‘segment (‘C’, about once per month), an aggregate model was estimated based on 27 participants (25.2%). It was highly significant (F9,442 = 33.5, p<0.0001) with R2 = 0.40. All beta coefficients were significant (p<0.02) and the signs of part-worths associated with the levels of each experimental factors were in the expected directions (Figure A3). As was found in the previous two segments, the highest levels of utility was associated with the cheapest price, and as price increased future purchase probability decreased. Also as in the previous segments, expected relationships were found for the other two experimental factors: i) as the level of bruising increased, future purchase probability decreased; and ii) as the incidence of purchasing an avocado with bruising increased, future purchase probability decreased. For the ‘occasional eating frequency’ segment, the pattern of the part-worth function was very similar to those established for the previous two segments. Minor deviances included an apparent greater sensitivity to a change in price from $1.99 to $2.49 than the price changes from $1.29 to $1.99 and from $2.49 to $2.99 (Figure 5a). For the factor pertaining to level of bruising there was, as in segment ‘B’ the same relative insensitivity to the increase in bruising from 25% to 33%. The negative impact on utility was much smaller than the changes from 10% to 25% bruising and from 33% to 50% bruising (Figure A3b). In terms of the negative impact on the increase in incidence of bruising, it was clear that the change from a frequency of 1-in-10 occurrence to 1-in-5 occurrence was very influential (Figure A3c). Again following the procedures outlined in the methods, the relative factor importances were determined: Price = 29.5%, Level of Bruising = 38.9% and Incidence of bruising = 31.6%. As for the previous two segments, this suggested that price was of less importance in consumers purchase decisions that the experimental factors relating to internal defects, and that both the level of bruising, as well as the frequency with which such a level of bruising was experienced strongly and negatively impacted future purchase probability in the ‘occasional eating frequency’ segment.

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Figure A3. Part-worths for the ‘Occasional eating frequency’ segment (‘C’). a) part-worths for the price experimental factor, b) part-worths for the level of bruising experimental factor, c) part-worths for the incidence of bruising experimental factor.

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Comparison of relative factor importances across the three eating frequency segments

Recall, that to compare whether there were differences between eating frequency segments in the relative importance given to the experimental factors, bootstrapped 95% confidence intervals for the difference in mean relative importance were calculated. Specifically, the approach required a pair-wise comparison of segments, and the results are presented in Table A1. This shows that all confidence intervals spanned the value zero, and there was therefore no statistical support for the notion the eating frequency segments differed in terms of the relative importance attached to each of the experimental factors. Based on this result, it was decided to focus all further analyses on the aggregate sample. Table A1. Bootstrapped 95% confidence of the difference in relative factor importance for sets of two eating frequency segments.

Pair-wise comparison of

segments

Factor: Price Factor: level of

bruising

Factor: Incidence

of bruising Segment ‘A’ vs Segment ‘B’ [-0.079,0.087] [-0.096, 0.062] [-0.073,0.101] Segment ‘A’ vs Segment ‘C’ [-0.095,0.082] [-0.106, 0.039] [-0.044,0.119] Segment ‘B’ vs Segment ‘C’ [-0.111,0.093] [-0.096, 0.064] [-0.077,0.125]

Note. Segment ‘A’ is the ‘high eating frequency segment’; Segment ‘B’ is the ‘medium eating frequency’ segment; Segment ‘C’ is the ‘Occasional eating frequency’ segment.