FOOD 3007 and FOOD 7012 SENSORY EVALUATION MANUAL Associate Professor Richard Mason The University of Queensland and Stephen Nottingham Sensory Evaluation ACKNOWLEDGEMENTS These notes form the basis of a practical workshop presented for personnel at Naresuan University, Phitsanulok, Thailand in July, 2002 We would like to thank Michael O’Mahony for his permission to include copies of the statistical tables from his book “Sensory Evaluation of Food: Statistical Methods and Procedures” and material supplied by the Centre for Food Technology, DPI, Brisbane COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation TABLE OF CONTENTS ACKNOWLEDGEMENTS PROGRAM ERROR! BOOKMARK NOT DEFINED INTRODUCTION THE HUMAN SENSES IN SENSORY EVALUATION .7 THE SENSES - AN INTRODUCTION SENSE OF SIGHT- THE SENSE OF SMELL 13 THE SENSE OF TASTE .15 THE SENSE OF HEARING .19 THE SENSE OF TOUCH .20 SENSORY INTERACTION 21 OPERATIONAL PRINCIPLES OF SENSORY TESTING .23 DESIGN OF A SENSORY TESTING AREA 31 STATISTICAL PRINCIPLES .34 SENSORY EVALUATION METHODS .38 AFFECTIVE TESTS .38 SPECIFIC TEST METHODS 39 PAIRED PREFERENCE TEST .39 RANKING FOR PREFERENCE 41 RATING FOR PREFERENCE 44 SENSORY EVALUATION IN CONSUMER TESTING 46 ANALYTICAL SENSORY TESTS: 53 DIFFERENCE TESTING 53 SIMPLE DIFFERENCE TEST 53 TRIANGLE TEST .53 DUO-TRIO TEST 55 TWO-OUT-OF-FIVE TEST 59 COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation “A” – “NOT A” TEST .59 DIFFERENCE-FROM-CONTROL TEST (DFC) 59 DIRECTIONAL DIFFERENCE TESTS 65 PAIRED COMPARISON TEST 65 RANKING TEST .67 RATING TEST 69 STATISTICS FOR SENSORY: DIFFERENCE TESTING .73 DESCRIPTIVE TESTING 76 STATISTICS FOR SENSORY: DESCRIPTIVE TESTING 81 SELECTION, TRAINING AND MOTIVATION OF A PANEL .86 REPORTING 91 SELECTED BIBLIOGRAPHY 92 JOURNALS 94 STATISTICAL TABLES 95 COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation INTRODUCTION Sensory evaluation - A scientific discipline used to evoke, measure, analyse and interpret reactions to those characteristics of foods and materials as they are perceived by the senses of sight, smell, taste, touch and hearing Sensory evaluation was one of the earliest methods of quality control and it is still widely used in industry However, the level of application depends on the situation (e.g beer and wine tasting to operators sampling of products from production line) Four variables affect sensory evaluation: • • • • The Food The People The Testing Environment Methods Sensory evaluation terminology • • • • • • Sensory evaluation Sensory Analysis Organoleptic Analysis Taste Testing Psychophysics Subjective Evaluation Advantages • • • • • Gives real answer regarding consumer quality Relatively cheap process (depending on how it is done) Rapid Many applications Objective methods are more reliable, accurate and reproducible However, they must be correlated to sensory evaluation to indicate a consumer response Disadvantages • • • • • Time consuming Expensive to run Method selection Analysis Interpretation Industry applications of sensory evaluation • • • Product development Product matching Product improvement COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation • • • • • • • • • • Process change Cost reduction New raw materials selection Quality control Storage stability Product grading / rating Consumer acceptance Consumer preference Panel selection / training Correlation subjective / objective Sensory Standards Aus Standard Year Title AS 2542.0 1995 Sensory analysis of foods - Introduction and list of methods AS 2542.1.1 1984 Sensory analysis of foods - General guide to methodology General requirements AS 2542.1.2 1984 Sensory analysis of foods - General guide to methodology Types and choice of test AS 2542.1.3 1995 Sensory analysis of foods - General guide to methodology Selection of assessors AS 2542.2.1 1982 Sensory analysis of foods - Specific methods - Paired comparison test AS 2542.2.2 1983 Sensory analysis of foods - Specific methods - Triangle test AS 2542.2.3 1988 Sensory analysis of foods - Specific methods - Rating AS 2542.2.4 1988 Sensory analysis of foods - Specific methods - Duo-trio test AS 2542.2.5 1991 Sensory analysis of foods - Specific methods - 'A not A' test AS 2542.2.6 1995 Sensory analysis of foods - Specific methods - Ranking AS 2542.3 1989 Sensory analysis of foods - Glossary of terms COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation THE HUMAN SENSES IN SENSORY EVALUATION THE SENSES - AN INTRODUCTION The sensory properties of foods are related to three major attributes: • • • Appearance - colour, size, shape; Flavour - odour, taste; and Texture - mouth feel, viscosity and hearing These attributes are expressed as a continuum and not as finite properties It is impossible to rate each one individually unless special precautions are taken, e.g blindfolds, nose clips, coloured lights, purees COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation Humans possess about 30 different senses However, the sensory properties of foods are perceived through the senses of: • • • • • Sight; Smell; Taste; Touch; and Hearing Stimuli A stimulus is any chemical or physical activator that causes a response in a receptor, e.g eye is receptor for light, ear is receptor for sound An effective stimulus produces a sensation, the dimensions of which are: • • • • Intensity/strength; Extent/separation; Duration/retention; and Hedonics/like-dislike Receptors Receptors are the stimuli detecting cells of the sense organ, e.g taste buds on tongue, light receptors in retina of eye Perception Perception is the psychological interpretation of sensations determined by comparison with past experiences, e.g the sour taste of lemons is the perception of the sensation received by the receptors (taste buds) from a chemical stimulus (citric acid) COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation SENSE OF SIGHTThe appearance of food Stimuli = visible light Receptor= retina of the eye Perception=sight, vision, appearance The appearance of foods is a major factor governing its acceptability and can be subdivided into three main categories: • Optical properties- colour, gloss and translucency • Physical form-shape and size • Mode of presentation-lighting packaging etc Optical properties Vision Vision is a complex phenomena consisting of several basic components A stimulus, light, from an external source interacts with the object and is brought to focus on the retina of the eye The retina is the receptor of vision and contains two types of cells The rods are responsible for vision in dim light and the cones are responsible for colour vision Light incident on these cells causes a photochemical reaction that generates an electrical impulse which is transmitted to the brain via the optic nerve Colour blindness is caused by loss or lack of colour receptor cells in the cones Approximately 8% of the population have some defect with relation to colour; mostly males COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation Light Visible light is that part of the electromagnetic spectrum which radiates between wavelengths of 380 - 770 nm Different wavelengths produce different colours 380 450 500 575 590 - 450 nm - 475 nm - 575 nm — 590 nm — 770 nm =violet =blue =green =yellow = red [NOTE: All electromagnetic radiations are physically the same However, the optical system of the eye is such that only the visible range of wavelengths is absorbed by the lens.] Light sources Incandescent lights consist of a tungsten filament which is heated in an inert gas The higher the temperature, the more light produced Light from this source tends to be harsh and tends to highlight the red end of the spectrum Fluorescent lights operate by electrical excitation of atoms that produces spectral lines at specific wavelengths which then impinge onto fluorescent materials which convert the incident light into light at a longer wavelength Light produced is softer but can produce colour distortion at particular wavelengths Natural light is too variable for use in evaluating appearance of foods Light - Object interactions Light incident on an object may be: • • • • Absorbed; Reflected; Transmitted; and Refracted The relationship between and within each of these components is responsible for the colour and gloss characteristics of the food The main light/object interactions produced are: Lightness/value; Colour/hue; Chroma/purity; and Gloss Physical form The second class of product appearance is physical form that can be subdivided into three parts: COPYRIGHT 10 R L Mason and S M Nottingham Sensory Evaluation the actual food products may also be used A series of triangle or duo-trio tests may be completed to assess the ability of the potential panellists to detect small differences between stimuli at supra-threshold levels Preferably, potential panellists should respond correctly 100% of the time Matching tests may be used to evaluate the ability of a prospective panellist to distinguish between different sensory stimuli In order to evaluate the ability of the panellists to describe sensory responses, a series of products can be presented and potential panellists asked to describe the sensory impression The products used should be related to those that will be used in the envisaged sensory testing For example, a range of odours may be presented: Chemical name Benzaldehyde Octene-3-ol Phenyl-2 ethyl acetate Diallyl sulfide Camphor Menthol Eugenol Anethol Vanillin Geosmin Beta-ionone Butyric acid Acetic acid Isoamyl acetate Dimethylthiophene Name most commonly associated with the odour Bitter almonds, Mushroom, Floral, Garlic, Camphor, Peppermint, Clove, Aniseed, Vanilla, Musty/mouldy, Violets, raspberries, Rancid butter, Vinegar, Fruit, acid drops, Grilled onions, Panellists are given these samples to assess one at a time and asked to describe the odour using his/her own words A system of marking can be devised e.g points for absolutely correct, points for correct in general terms, points for a vague association, point for a wrong association and points for no response A satisfactory level for selection of panellists needs to be specified in relation to the materials used Similar techniques can be applied for taste and texture The potential panellists may be screened for their ability to rank or rate products for selected attributes using the same technique as the final panel will use All potential panellists are presented with the samples in the same order Panellists are chosen if a satisfactory level is attained which will depend on the intensities of the samples used Also check that they have used most of the scale COPYRIGHT 88 R L Mason and S M Nottingham Sensory Evaluation Training In this phase, it is important that the panellists develop confidence as well as the skills for product assessment Panellists must be taught the correct procedures for evaluating samples and ways to reduce or eliminate sensory adaptation They must also learn to disregard their personal preferences Between 40 and 120h of training are required for a descriptive sensory panel which will depend on the product, the number of attributes as well as the validity and reliability required A trained panel usually consists of 10-20 panellists The initial stage of training involves vocabulary development The entire range of products is presented to the panellists They are instructed to individually assess the sensory differences between the samples and record any differences as descriptive words On completion of this task, the panellists each list the attributes used to describe each sample At this time, it is very important that the panel leader does not lead or judge the descriptive words generated by the panellist although they can ask for clarification The panellists themselves will usually start to move towards a general consensus once the total attribute list has been generated It is then the role of the panel leader to provide reference standards for the attributes that have been previously selected by general panel consensus The references can be used to help the panellists to identify and remember a sensory attribute found in the sample The references may be chemicals, ingredients or products The panellists then assess the samples alongside the references until a consensus is reached regarding the sensory attributes, reference standards and definitions This process should continue until the panellists are all happy and understand the terms used Towards the end of training, a scoresheet is created by the panellists The panellists decide on the order in which the attributes are to be assessed Generally the panel leader decides on the type of scale used, although the panel decides on the verbal anchors to be used Once the panellists have become familiar with the samples, references and definitions, panel evaluation sessions are completed that should be similar to the final testing situation The panellists are presented with coded samples in triplicate and asked to rate them using the scoresheets and attribute scales they have trained with By statistically analysing the data, the panel leader will be able to determine if further training is required or if the evaluation phase can begin Like any instrument, the performance of individual panellists as well as the panel as a whole needs to be monitored to check they are producing reliable results Reliability is checked by completing test replications and the descriptive data obtained is analysed statistically using an analysis of variance Motivation of panellists is one of the most important factors in maintaining an efficient trained sensory panel If panellists are motivated and interested they will perform well For panellists, a sense of completing meaningful work is an important source of motivation When appropriate on completion of a project, feedback should be given to the panel as to the project objectives and outcomes and the contribution of the sensory results Individual panellist feedback is also important They should be made to feel that attendance at sensory evaluation sessions is COPYRIGHT 89 R L Mason and S M Nottingham Sensory Evaluation important This can be reinforced by running sessions strictly and efficiently to keep their time input to a minimum Throughout training as well as during ongoing sensory evaluation sessions, it is important to keep the channels of communications open through panel discussion at the completion of a training session or a sensory testing session Ongoing records of panellists' training and experience are invaluable In some instances training can occupy more time than the actual experimental testing sessions, especially when you first start However, if the job is done correctly right from the start, your trained panel will be one of the most valuable resources in the company Make sure you look after them An aside: Expert panels Panellists who have a great deal of experience in assessing a particular product are often referred to as "Expert tasters" Commodities that utilise expert tasters include the tea, coffee, wine and dairy industries These panels usually include only or highly trained tasters These tasters are particularly sensitive to the nuances of a specific product They also have the ability to carry the characteristics of standard samples in their sensory memory It takes a great deal of practice to develop the skill and requires continued tasting to stay "tuned" They are usually responsible for arranging the tasting conditions and samples themselves, in addition to actually tasting and making a final report This type of panel is most frequently used to assign a quality grade to a finished product, as in butter and cheese grading In the wine and coffee industries one expert may use these skills to blend individual components to produce a final product with the desired characteristics COPYRIGHT 90 R L Mason and S M Nottingham Sensory Evaluation REPORTING As with any other scientific experiment your sensory testing needs to be reported in a clear and concise manner The Australian standards for each test type details what should be included in the report The results obtained should be interpreted and conclusions drawn using all the information gathered in the experiment Recommendations may also need to be included depending on the nature of the work Remember that it is much easier to write the report if you keep a record as you go along! COPYRIGHT 91 R L Mason and S M Nottingham Sensory Evaluation SELECTED BIBLIOGRAPHY American Meat Science Association, “Guidelines for Cookery and Sensory Evaluation of Meat”, AMS, USA, 1978 Amerine, M A, Pangborn, R M and Roessler, E B, “Principles of Sensory Evaluation of Food”, New York: Academic Press, 1965 ASTM, “Manual on Sensory Testing Methods”, STP 434, Am Soc Test Makr., Philadelphia, Pennsylvania, 1968 Aust, L B, Gacula, M C, Beard,S A and Washam, R W “Degree of Difference Test Method in Sensory Evaluation of Heterogeneous Product Types Journal of Food Science, 50: 511 – 513, 1985 Bartoshuk, L, “Separate worlds of taste” Psychology Today 14 (9): 48-57, 1980 Bartoshuk, L M, “The biological basis of food perception and acceptance” Food Quality & Preference 4: 21-32, 1993 Bourne, M C, “Food Texture and Viscosity: Concept and Measurement”, Academic Press Inc., California, 1982 Chi-Tang Ho, Manley, C H, “Flavor Measurement”, Marcel Dekker, Inc 1993 Gacula M C., “Design and analysis of Sensory Optimization”, Food & Nutrition Press 1993 Gacula, M C and Singh, J, “Statistical Methods in Food and Consumer Research, New York: Academic Press, 1984 Jellinek, G, “Sensory Evaluation of Food: Horwood; 1985 Theory and Practice”, Chichester: Ellis Lawless, H T, “Pepper potency and the forgotten flavour sense” Food Technology 43 (11): 52, 57-58, 1989 Lawless, H T & Heymann, H, “Sensory Evaluation of Food: Principles and Practices”, Chapman & Hall, New York, 1998 Lyman, B, “A Psychology of Food”, Van Nostrand Reinhold Co Inc., New York, USA, 1989 Lyon, D H, Francombe, M A, Hasdell, T A and Lawson, K, (editors) “Guidelines for Sensory Analysis in Food Product Development and Quality Control” Chapmann and Hall, London, UK, 1992 McBride, R L, “The Bliss Point Factor”, Sun Books, Australia, 1990 COPYRIGHT 92 R L Mason and S M Nottingham Sensory Evaluation McBride, R L, (editor), “Psychological Basis of Sensory Evaluation”, Elsevier Applied Science, London, UK, 1990 McRae, R, Robinson, R K & Sadler, M J (eds) “Encyclopedia of Food Science, Food Technology and Nutrition”, Volume 6, Academic Press, London, 1993 Meilgaard, M, Civille, G V and Carr, B T, “Sensory Evaluation Techniques: Boca Raton, Fla: CRC Press, 1999 (3rd Edition) Miflora Minoza-Gatchalian, “Sensory Evaluation Methods with Statistical Analysis (for Research Product Development and Quality Control)” 1981 Moskowitz, H R, “New Directions for Product Testing and Sensory Analysis of Foods”, Food & Nutrition Press, Inc 1985 Moskowitz, H, “Applied Sensory Analysis of Food”, Volumes and 2, CRC Press, Florida, USA, 1988 O’Mahoney, M, “Sensory Evaluation of Food: Statistical Methods and Procedures”, New York: Marcel Dekker, Inc, 1986 O’Mahony, M & Ishii, I “Do you have an umami tooth?” Nutrtion Today May/June, 1985 Piggott, J R, “Sensory Analysis of Food”, London: Elsevier Applied Science, 1988 (2nd edition now available) Piggott, J R, “Statistical Procedures in Food Research”, London: Elsevier Applied Science, 1986 Piggott, J R, Paterson, A “Understanding Natural Flavors” Professional 1994 Blackie Academic & Poste, L M, Mackie, D A, Butter, G and Larmond, E, “Laboratory Methods for Sensory Analysis of Food”, Agriculture Canada Publication 1864/E, 1991 Rutledge, K P and Hudson, J M, “Sensory Evaluation: Method for Establishing and Training a Descriptive Flavour Panel, Food Technology 44 (12): 78-84, 1990 Stone, H and Sidel, J L, “Sensory Evaluation Practices”, 2nd edition, New York: Academic Press, 1992 Thomson, D M H, “Food Acceptability”, Elsevier Applied Science, London, UK, 1988 COPYRIGHT 93 R L Mason and S M Nottingham Sensory Evaluation JOURNALS Gacula, M C, “Journal of Sensory Studies” Food & Nutrition Press, Inc MacFie, H J., Meiselman, H L., “Food Quality and Preference” Elsevier Applied Scien COPYRIGHT 94 R L Mason and S M Nottingham STATISTICAL TABLES Table 1: Probability of X or More Correct Judgments in n Trials (one-tailed, p = 1/3)a n\x 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 47 38 39 40 41 42 43 44 45 46 47 48 49 50 868 912 941 961 974 983 988 992 995 997 998 998 999 999 COPYRIGHT 539 649 737 805 857 896 925 946 961 973 981 986 990 993 995 997 998 998 999 999 999 210 320 429 532 623 701 766 819 861 895 921 941 956 967 976 982 987 991 993 995 996 997 998 999 999 999 045 100 173 259 350 441 527 607 678 739 791 834 890 898 921 940 954 965 974 980 985 989 992 994 996 997 998 998 999 999 999 004 018 045 088 145 213 289 368 448 524 596 661 719 769 812 848 879 904 924 941 954 964 972 979 984 988 991 993 995 996 997 998 998 999 999 999 001 007 020 042 077 122 178 241 310 382 453 522 588 648 703 751 794 831 862 888 910 928 943 955 965 972 978 983 987 990 992 994 996 997 997 998 999 999 999 999 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 003 008 020 039 066 104 149 203 263 326 391 457 521 581 638 690 737 778 815 847 874 897 916 932 946 957 965 973 978 963 987 990 992 994 995 996 997 998 998 999 999 999 999 001 003 009 019 035 058 088 126 172 223 279 339 399 460 519 576 630 679 725 765 801 833 861 885 905 922 937 949 959 967 973 979 983 987 990 992 994 995 996 997 998 998 001 004 009 017 031 050 075 108 146 191 240 293 349 406 462 518 572 623 670 714 754 789 821 849 873 895 913 928 941 952 961 968 974 980 984 987 990 992 994 995 001 002 004 008 016 027 043 065 092 125 163 206 254 304 357 411 464 517 568 617 662 705 744 779 810 838 863 885 903 920 933 945 955 963 970 976 980 984 987 001 002 004 008 014 024 038 056 079 107 140 178 220 266 314 364 415 466 516 565 612 656 697 735 769 800 829 854 876 895 912 926 938 949 958 965 972 001 002 004 007 013 021 033 048 068 092 121 154 191 232 276 322 370 419 468 516 562 607 650 689 726 761 791 820 845 867 887 904 919 932 943 001 002 004 007 012 019 028 042 058 079 104 133 166 203 243 285 330 376 422 469 515 560 603 644 683 719 753 783 811 836 859 879 896 001 002 003 006 010 016 025 036 050 068 090 115 144 177 213 252 293 336 381 425 470 515 558 600 639 677 713 745 776 803 829 001 002 003 006 009 014 022 031 043 059 078 100 126 155 187 223 261 301 32 385 428 471 514 556 596 635 672 706 739 001 002 003 055 008 013 019 027 038 051 067 087 109 135 164 196 231 268 307 347 389 430 472 514 554 593 631 001 002 003 005 007 011 016 023 033 044 058 075 095 118 144 173 205 239 275 313 352 392 433 473 513 001 001 002 004 066 010 014 020 028 038 051 066 083 104 127 153 182 213 246 282 318 356 395 001 001 002 004 006 009 012 018 025 033 044 057 073 091 111 135 161 189 220 253 287 001 001 002 003 005 007 011 016 021 029 038 050 063 079 098 119 142 168 196 001 001 002 003 004 007 010 014 019 025 033 043 055 070 086 105 126 001 001 002 003 004 006 008 012 016 022 029 038 048 061 076 001 001 001 002 003 005 007 010 014 019 025 033 042 001 001 002 003 004 006 009 012 017 022 001 001 002 003 004 006 008 011 001 001 002 002 003 005 001 001 001 002 001 R L Mason and S M Nottingham 95 Table 2: Minimum Numbers of Correct Judgments to Establish Significance at Various Probability Levels for the Triangle tests (one tailed, p = 1/3) Probability Levels No of trials (n) 0.05 0.04 0.03 0.02 0.01 0.005 5 5 5 5 5 6 6 6 7 6 6 7 7 7 8 10 7 7 8 11 7 8 10 12 8 8 9 10 13 8 9 10 11 14 9 9 10 10 11 15 9 10 10 10 11 12 16 10 10 10 11 11 12 17 10 10 10 11 11 12 13 18 10 11 11 11 12 12 13 19 11 11 11 12 12 13 14 20 11 11 12 12 13 13 14 21 12 12 12 13 13 14 15 22 12 12 13 13 14 14 15 23 12 13 13 13 14 15 16 24 13 13 13 14 15 15 16 25 13 14 14 14 15 16 17 26 14 14 14 15 15 16 17 27 14 14 15 15 16 17 18 28 15 15 15 16 16 17 18 29 15 15 16 16 17 17 19 30 15 16 16 16 17 18 19 31 16 16 16 17 18 18 20 32 16 16 17 17 18 19 20 33 17 17 17 18 18 19 21 34 17 17 18 18 19 20 21 35 17 18 18 19 19 20 22 36 18 18 18 19 20 20 22 37 18 18 19 19 20 21 22 38 19 19 19 20 21 21 23 39 19 19 20 20 21 22 23 40 19 20 20 21 21 22 24 41 20 20 20 21 22 23 24 42 20 20 21 21 22 23 25 43 20 21 21 22 23 24 25 44 21 21 22 22 23 24 26 45 21 22 22 23 24 24 26 46 22 22 22 23 24 25 27 47 22 22 23 23 24 25 27 48 22 23 23 24 25 26 27 49 23 23 24 24 25 26 28 50 23 24 24 25 26 26 28 60 27 27 28 29 30 31 33 70 31 31 32 33 34 35 37 80 35 35 36 36 38 39 41 90 38 39 40 40 42 43 45 COPYRIGHT 96 0.001 R L Mason and S M Nottingham Table 3: Minimum Numbers of Correct Judgments to Establish Significance at Various Probability Levels for Paired - Comparison and Duo-Trio Tests (one-tailed, p=1/2) Probability levels No of trials (N) 0.05 0.04 0.03 0.02 0.01 0.005 0.001 7 7 7 7 8 8 8 8 9 10 9 9 10 10 10 11 9 10 10 10 11 11 12 10 10 10 10 11 11 12 13 10 11 11 11 12 12 13 14 11 11 11 12 12 13 13 15 12 12 12 12 13 13 14 16 12 12 13 13 14 14 15 17 13 13 13 14 14 15 16 18 13 14 14 14 15 15 16 19 14 14 15 15 15 16 17 20 15 15 15 16 16 17 18 21 15 15 16 16 17 17 18 22 16 16 16 17 17 15 19 23 16 17 17 17 18 19 20 24 17 17 18 18 19 19 20 25 18 15 18 19 19 20 21 26 18 18 19 19 20 20 22 27 19 19 19 20 20 21 22 28 19 20 20 20 21 22 23 29 20 20 21 21 22 22 24 30 20 21 21 22 22 23 24 31 21 21 22 22 23 24 25 32 22 22 22 23 24 24 26 33 22 23 23 23 24 25 26 34 23 23 23 24 25 25 27 35 23 24 24 25 25 26 27 36 24 24 25 25 26 27 28 37 24 25 25 26 26 27 29 38 25 25 26 26 27 28 29 39 26 26 26 27 28 28 30 40 26 27 27 27 28 29 30 41 27 27 27 28 29 30 31 42 27 28 28 29 29 30 32 43 28 28 29 29 30 31 32 44 28 29 29 30 31 31 33 45 29 29 30 30 31 32 34 46 30 30 30 31 32 33 34 47 30 30 31 31 32 33 35 48 31 31 31 32 33 34 36 49 31 32 32 33 34 34 36 50 32 32 33 33 34 35 37 60 37 38 38 39 40 41 43 70 43 43 44 45 46 47 49 80 48 49 49 50 51 52 55 90 54 54 55 56 57 58 61 100 59 60 60 61 63 64 66 Source : E.B Roessler et al Journal of Food Science, 1978, 43, 940-947 COPYRIGHT 97 R L Mason and S M Nottingham Table 4: Minimum Numbers of Agreeing Judgements Necessary to Establish Significance at Various Probability Levels for the Paired – Preference Tests and Difference (two tailed, p=1/2) Probability Levels No of trials (n) 0.05 0.04 0.03 0.02 0.01 0.005 0.001 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 60 70 80 90 100 8 10 10 11 12 12 13 13 14 15 15 16 17 17 18 18 19 20 20 21 21 22 23 23 24 24 25 25 26 27 27 28 28 29 29 30 31 31 32 32 33 39 44 50 55 61 8 10 10 11 12 12 13 14 14 15 16 16 17 17 18 19 19 20 20 21 22 22 23 23 24 25 25 26 26 27 27 28 29 29 30 30 31 31 32 33 33 39 45 50 56 61 9 10 11 11 12 13 13 14 15 15 16 16 17 18 18 19 19 20 21 21 22 22 23 24 24 25 25 26 27 27 28 28 29 30 30 31 31 32 32 33 34 39 45 51 56 62 10 10 11 12 12 13 14 14 15 15 16 17 17 18 19 19 20 20 21 22 22 23 23 24 25 25 26 26 27 28 28 29 29 30 30 31 32 32 33 34 34 40 46 51 57 63 10 11 11 12 13 13 14 15 15 16 17 17 18 19 19 20 20 21 22 22 23 24 24 25 25 26 27 27 28 28 29 30 30 31 31 32 33 33 34 34 35 41 47 52 58 64 10 11 12 12 13 14 14 15 16 16 17 18 18 19 20 20 21 22 22 23 24 24 25 25 26 27 27 28 29 29 30 30 31 32 32 33 33 34 35 35 36 42 48 53 59 65 11 12 13 14 14 15 16 17 17 18 19 19 20 21 21 22 23 23 24 25 25 26 27 27 28 29 29 30 31 31 32 32 33 34 34 35 36 36 37 37 44 50 56 61 67 COPYRIGHT 98 R L Mason and S M Nottingham Table 5a ¨ % Points for the Distribution of F n2\n1 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 40 60 120 161.40 18.51 10.13 7.71 6.61 5.99 5.59 5.32 5.12 4.96 4.84 4.75 4.67 4.60 4.54 4.49 4.45 4.41 4.38 4.35 4.32 4.30 4.28 4.26 4.24 4.22 4.21 4.20 4.18 4.17 4.08 4.00 3.92 3.84 199.50 19.00 9.55 6.94 5.79 5.14 4.74 4.46 4.26 4.10 3.98 3.88 3.80 3.74 3.68 3.63 3.59 3.55 3.52 3.49 3.47 3.44 3.42 3.40 3.38 3.37 3.35 3.34 3.33 3.32 3.23 3.15 3.07 2.99 215.70 19.16 9.28 6.59 5.41 4.76 4.35 4.07 3.86 3.71 3.59 3.49 3.41 3.34 3.29 3.24 3.20 3.16 3.13 3.10 3.07 3.05 3.03 3.01 2.99 2.98 2.96 2.95 2.93 2.92 2.84 2.76 2.68 2.60 224.60 19.25 9.12 6.39 5.19 4.53 4.12 3.84 3.63 3.48 3.36 3.26 3.18 3.11 3.06 3.01 2.96 2.93 2.90 2.87 2.84 2.82 2.80 2.78 2.76 2.74 2.73 2.71 2.70 2.69 2.61 2.52 2.45 2.37 230.20 19.30 9.01 6.26 5.05 4.39 3.97 3.69 3.48 3.33 3.20 3.11 3.02 2.96 2.90 2.85 2.81 2.77 2.74 2.71 2.68 2.66 2.64 2.62 2.60 2.59 2.57 2.56 2.54 2.53 2.45 2.37 2.29 2.21 234.00 19.33 8.94 6.16 4.95 4.28 3.87 3.58 3.37 3.22 3.09 3.00 2.92 2.85 2.79 2.74 2.70 2.66 2.63 2.60 2.57 2.55 2.53 2.51 2.49 2.47 2.46 2.44 2.43 2.42 2.34 2.25 2.17 2.09 238.90 19.37 8.84 6.04 4.82 4.15 3.73 3.44 3.23 3.07 2.95 2.85 2.77 2.70 2.64 2.59 2.55 2.51 2.48 2.45 2.42 2.40 2.38 2.36 2.34 2.32 2.30 2.29 2.28 2.27 2.18 2.10 2.02 1.94 12 243.90 19.41 8.74 5.91 4.68 4.00 3.57 3.28 3.07 2.91 2.79 2.69 2.60 2.53 2.48 2.42 2.38 2.34 2.31 2.28 2.25 2.23 2.20 2.18 2.16 2.15 2.13 2.12 2.40 2.09 2.00 1.92 1.83 1.75 24 249.00 19.45 8.64 5.77 4.53 3.84 3.41 3.12 2.90 2.74 2.61 2.50 2.42 2.35 2.29 2.24 2.19 2.15 2.11 2.08 2.05 2.06 2.00 1.98 1.96 1.95 1.93 1.91 1.90 1.89 1.79 1.70 1.61 1.52 254.30 19.50 8.53 5.63 4.36 3.67 3.23 2.93 2.71 2.54 2.40 2.30 2.21 2.13 2.07 2.01 1.96 1.92 1.88 1.84 1.81 1.78 1.76 1.73 1.71 1.69 1.67 1.65 1.64 1.62 1.51 1.39 1.25 1.00 Source : Table is taken from Table V of Fisher and Yates : 1974 Statistical Tables for Biological, Agricultural and Medical Research published by Longman Group UK Ltd London (previously published by Oliver and Boyd Ltd Edinburgh) and by permission of the authors and publishers COPYRIGHT 99 R L Mason and S M Nottingham Table 5b ¨ % Points for the Distribution of F n2\n1 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 40 60 120 4052 98.49 34.12 21.20 16.46 13.74 12.25 11.26 10.56 10.04 9.65 9.33 9.07 8.86 8.68 8.53 8.40 8.28 8.18 8.10 8.02 7.94 7.88 7.82 7.77 7.72 7.68 7.64 7.60 7.56 7.31 7.08 6.85 6.64 4999 99.00 30.81 18.00 13.27 10.92 9.55 8.65 8.02 7.56 7.20 6.93 6.70 6.51 6.36 6.23 6.11 6.01 5.93 5.85 5.78 5.72 5.66 5.61 5.57 5.53 5.49 5.45 5.42 5.39 5.18 4.98 4.79 4.60 5403 99.17 29.46 16.69 12.06 9.78 8.45 7.59 6.99 6.55 6.22 5.95 5.74 5.56 5.42 5.29 5.18 5.09 5.01 4.94 4.87 4.82 4.76 4.72 4.68 4.64 4.60 4.57 4.54 4.51 4.31 4.13 3.95 3.78 5625 99.25 28.71 15.98 11.39 9.15 7.85 7.01 6.42 5.99 5.67 5.41 5.20 5.03 4.89 4.77 4.67 4.58 4.50 4.43 4.37 4.31 4.26 4.22 4.18 4.14 4.11 4.07 4.04 4.02 3.83 3.65 3.48 3.32 5764 99.30 28.24 15.52 10.97 8.75 7.46 6.63 6.06 5.64 5.32 5.06 4.86 4.69 4.56 4.44 4.34 4.25 4.17 4.10 4.04 3.99 3.94 3.90 3.86 3.82 3.78 3.75 3.73 3.70 3.51 3.34 3.17 3.02 5859 99.33 27.91 15.21 10.67 8.47 7.19 6.37 5.80 5.39 5.07 4.82 4.62 4.46 4.32 4.20 4.10 4.01 3.94 3.87 3.81 3.76 3.71 3.67 3.63 3.59 3.56 3.53 3.50 3.47 3.29 3.12 2.96 2.80 5981 99.36 27.49 14.80 10.29 8.10 6.84 6.03 4.47 5.06 4.74 4.50 4.30 4.14 4.00 3.89 3.79 3.71 3.63 3.56 3.51 3.45 3.41 3.36 3.32 3.29 3.26 3.23 3.20 3.17 2.99 2.82 52.66 2.51 12 6106 99.42 27.05 14.37 9.89 7.72 6.47 5.67 5.11 4.71 4.40 4.16 3.96 3.80 3.67 3.55 3.45 3.37 3.30 3.23 3.17 3.12 3.07 3.03 2.99 2.96 2.93 2.90 2.87 2.84 2.66 2.50 2.34 2.18 24 6234 99.46 26.60 13.93 9.47 7.31 6.07 5.28 4.73 4.33 4.02 3.78 3.59 3.43 3.29 3.18 3.08 3.00 2.92 2.86 2.80 2.75 2.70 2.66 2.62 2.58 2.55 2.52 2.49 2.47 2.29 2.12 1.95 1.79 6366 99.50 26.12 13.46 9.02 6.88 5.65 4.86 4.31 3.91 3.60 3.36 3.16 3.00 2.87 2.75 2.65 2.57 2.49 2.42 2.36 2.31 2.26 2.21 2.17 2.13 2.10 2.06 2.06 2.01 1.80 1.60 1.38 1.00 Source : Table is taken from Table V of Fisher and Yates : 1974 Statistical Tables for Biological, Agricultural and Medical Research published by Longman Group UK Ltd London (previously published by Oliver and Boyd Ltd Edinburgh) and by permission of the authors and publishers COPYRIGHT 100 R L Mason and S M Nottingham Table 6: Critical Value of ta df 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 40 60 120 00 Level of significance for one-tailed test 0.1 0.05 0.025 Level of significance for two-tailed test 0.2 0.1 0.05 3.078 6.314 12.706 1.886 2.92 4.303 1.638 2.353 3.182 1.533 2.132 2.776 1.476 2.015 2.571 1.44 1.943 2.447 1.415 1.895 2.365 1.397 1.86 2.306 1.383 1.833 2.262 1.372 1.812 2.228 1.363 1.796 2.201 1.356 1.782 2.179 1.35 1.771 2.16 1.345 1.761 2.145 1.341 1.753 2.131 1.337 1.746 2.12 1.333 1.74 2.11 1.33 1.734 2.101 1.328 1.729 2.093 1.325 1.725 2.086 1.323 1.721 2.08 1.321 1.717 2.074 1.319 1.714 2.069 1.318 1.711 2.064 1.316 1.708 2.06 1.315 1.706 2.056 1.314 1.703 2.052 1.313 1.701 2.048 1.311 1.699 2.045 1.31 1.697 2.042 1.303 1.684 2.021 1.296 1.671 1.289 1.658 1.98 1.282 1.645 1.96 0.01 0.005 0.0005 0.02 31.821 6.965 4.541 3.747 3.365 3.143 2.998 2.896 2.821 2.764 2.718 2.681 2.63 2.624 2.602 2.583 2.567 2.552 2.539 2.528 2.518 2.508 2.5 2.492 2.485 2.479 2.473 2.467 2.462 2.457 2.423 2.39 2.358 2.326 0.01 63.657 9.925 5.841 4.604 4.032 3.707 3.499 3.355 3.25 3.169 3.106 3.055 3.012 2.977 2.947 2.921 2.898 2.878 2.861 2.845 2.831 2.819 2.807 2.797 2.787 2.779 2.771 2.763 2.756 2.75 2.704 2.66 2.617 2.576 0.001 636.619 31.598 12.941 8.61 6.859 5.959 5.405 5.041 4.781 4.587 4.437 4.318 4.221 4.14 4.073 4.015 3.965 3.922 3.883 3.85 3.819 3.792 3.767 3.745 3.725 3.707 3.69 3.674 3.659 3.646 3.551 3.46 3.373 3.2 a The value listed in the table is the critical value of t for the number of degrees of freedom listed in the left column for a one- or two-tailed test at the significance level indicated at the top of each column If the observed t is greater than or equal to the tables value, reject Ho Source: Table III of Fisher and Yates, Statistical Tables for Biological, Agricultural and Medical Research, published by Longman Group Ltd, London (previously published by Oliver and Boyd Ltd, Edinburgh) and by permission of the authors and publishers COPYRIGHT 101 R L Mason and S M Nottingham Table 7: Critical Values of Chi-Squarea df 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 32 34 36 38 40 44 48 52 56 60 Level of significance for one-tailed test 0.10 0.05 0.025 Level of significance for two-tailed test 0.2 0.1 0.05 1.64 2.71 3.84 3.22 4.6 5.99 4.64 6.25 7.82 5.99 7.78 9.49 7.29 9.24 11.07 8.56 10.64 12.59 9.8 12.02 14.07 11.03 13.36 15.51 12.24 14.68 16.92 13.44 15.99 18.31 14.63 17.28 19.68 15.81 18.55 21.03 16.98 19.81 22.36 18.15 21.06 23.68 19.31 22.31 25 20.46 23.54 26.3 21.62 24.77 27.59 22.76 25.99 28.87 23.9 27.2 30.14 25.04 28.41 31.41 26.17 29.62 32.67 27.3 30.81 33.92 28.43 32.01 35.17 29.55 33.2 36.42 30.68 34.38 37.65 31.8 35.56 38.88 32.91 36.74 40.11 34.03 37.92 41.34 35.14 39.09 42.69 36.25 40.26 43.77 38.47 42.59 46.19 40.68 44.9 48.6 42.88 47.21 51 45.08 49.51 53.38 47.27 51.81 55.76 51.64 56.37 60.48 55.99 60.91 65.17 60.33 65.42 69.83 64.66 69.92 74.47 68.97 74.4 79.08 0.01 0.005 0.0005 0.02 5.41 7.82 9.84 11.67 13.39 15.03 16.62 18.17 19.68 21.16 22.62 24.05 25.47 26.87 28.26 29.63 31 32.35 33.69 35.02 36.34 37.66 38.97 40.27 41.57 42.86 44.14 45.42 46.69 47.96 50.49 53 55.49 57.97 60.44 65.34 70.2 75.02 79.82 84.58 0.01 6.64 9.21 11.34 13.28 15.09 16.81 18.48 20.09 21.67 23.21 24.72 26.22 27.69 29.14 30.58 32 33.41 34.8 36.19 37.57 38.93 40.29 41.64 42.98 44.31 45.64 46.96 48.28 49.59 50.89 53.49 56.06 58.62 61.16 63.69 68.71 73.68 78.62 83.51 88.38 0.001 10.83 13.82 16.27 18.46 20.52 22.46 24.32 26.12 27.88 29.59 31.26 32.91 34.53 36.12 37.7 39.29 40.75 42.31 43.82 45.32 46.8 48.27 49.73 51.18 62.62 54.05 55.48 56.89 58.3 59.7 62.49 65.25 67.99 70.7 73.4 78.75 84.04 89.27 94.46 99.61 a The table lists the critical values of chi square for the degrees of freedom shown at the left for tests corresponding to those significance levels heading each column If the observed value of xobs2 is greater than or equal to the tabled value, reject Ho Source: Table IV of Fisher and Yates, Statistical Tables for Biological, Agricultural and Medical Research, published by Longman Group Ltd, London (previously published by Oliver and Boyd Ltd, Edinburgh) and by permission of the authors and publishers COPYRIGHT 102 R L Mason and S M Nottingham ... line) Four variables affect sensory evaluation: • • • • The Food The People The Testing Environment Methods Sensory evaluation terminology • • • • • • Sensory evaluation Sensory Analysis Organoleptic... 2542.3 1989 Sensory analysis of foods - Glossary of terms COPYRIGHT R L Mason and S M Nottingham Sensory Evaluation THE HUMAN SENSES IN SENSORY EVALUATION THE SENSES - AN INTRODUCTION The sensory. .. .20 SENSORY INTERACTION 21 OPERATIONAL PRINCIPLES OF SENSORY TESTING .23 DESIGN OF A SENSORY TESTING AREA 31 STATISTICAL PRINCIPLES .34 SENSORY EVALUATION