Application and Research Status of Sorting in Food Research and Development

LIU Songyu; SHAN Bingqi; ZHOU Xiaomiao; CHEN Haohan; PENG Gongfeixue; LIU Yue; SONG Hao; ZHU Baoqing; WANG Xiaonan

doi:10.13386/j.issn1002-0306.2021080051

Volume 43 Issue 16

Aug. 2022

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Science and Technology of Food Industry > 2022 > 43(16): 458-466. > DOI: 10.13386/j.issn1002-0306.2021080051

LIU Songyu, SHAN Bingqi, ZHOU Xiaomiao, et al. Application and Research Status of Sorting in Food Research and Development[J]. Science and Technology of Food Industry, 2022, 43(16): 458−466. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021080051.

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Application and Research Status of Sorting in Food Research and Development

1.
Department of Food Science and Engineering, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
2.
Beijing Industrial Technology Research Institute Co., Ltd., Beijing 101111, China

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Received Date: August 04, 2021
Available Online: June 15, 2022

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Abstract

Abstract

Sensory analysis methods are widely used in the food industry. Due to the limitations of traditional sensory analysis methods such as long training time and high investment, various rapid analysis methods have been developed, one of which is the sorting method. Sorting method requires assessors to categorize products according to the similarity of their sensory characteristics and use multivariate statistical analysis methods to quickly obtain the sensory distribution of products. This paper mainly introduces the experimental design, data analysis, development, application in food research, and advantages and limitations of Sorting. The development trend of sorting is also prospected, aiming to provide a reference for further research and application of the method in the food industry.
- sorting,
- rapid sensory analysis methods,
- applications,
- advantages,
- limitations

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References (59)

References

[1]	MUÑOZ A, CIVILLE G, CARR B. Comprehensive descriptive method[J]. Springer US, 1992: 52-107.
[2]	BERGET I, BECH S, GIACALONE D, et al. Sound quality perception of loudspeakers evaluated by different sensory descriptive methods and preference mapping[J]. Journal of Sensory Studies,2021,36(1):e12620.
[3]	马德秀, 洪梅玲, 冯作山, 等. 促溶工艺对赤霞珠葡萄汁香气成分及感官评价的影响[J]. 食品科技,2019,44(7):101−108. [MA Dexiu, HONG Meiling, FENG Zuoshan, et al. Effects of solubilizing process on aroma components and sensory evaluation of cabernet sauvignon grape juice[J]. Food Science and Technology,2019,44(7):101−108. MA Dexiu, HONG Meiling, FENG Zuoshan, et al. Effects of solubilizing process on aroma components and sensory evaluation of cabernet sauvignon grape juice[J]. Food Science and Technology, 2019, 44(7): 101-108.
[4]	ALCANTARA M D, FREITAS-SÁ D D G C. Metodologias sensoriais descritivas mais rápidas e versáteis uma atualidade na ciência sensorial[J]. Brazilian Journal of Food Technology,2018,21:e2016179.
[5]	陈亦新, 兰义宾, 问亚琴, 等. 自选特性排序剖面法在食品研究与开发中的应用及研究现状[J]. 食品工业科技,2022, 43(13):475-483. CHEN Yixin, LAN Yibin, WEN Yaqin, et al. Application and research status of flash profile in food research and development[J]. Science and Technology of Food Industry,2022, 43(13):475-483.
[6]	LEE S, KWAK H S, KIM S S, et al. Combination of the check-all-that-apply (CATA) method and just-about-right (JAR) scale to evaluate korean traditional rice wine (yakju)[J]. Foods,2021,10(8):1895. doi: 10.3390/foods10081895
[7]	单冰淇, 刘松昱, 王春光, 等. 开放式提问调查在食品研究与开发中的研究现状[J]. 食品工业科技, 2022, 43(12):468−474 SHAN Bingqi, LIU Songyu, WANG Chunguang, et al. Current research status of open-ended questions in food research and development[J]. Science and Technology of Food Industry 2022, 43(12):468−474.
[8]	CHOLLET S, LELIÈVRE M, ABDI H, et al. Sort and beer: everything you wanted to know about the sorting task but did not dare to ask[J]. Food Quality and Preference,2011,22(6):507−20. doi: 10.1016/j.foodqual.2011.02.004
[9]	CARTIER R, RYTZ A, LECOMTE A, et al. Sorting procedure as an alternative to quantitative descriptive analysis to obtain a product sensory map[J]. Food Quality and Preference,2006,17(7-8):562−571. doi: 10.1016/j.foodqual.2006.03.020
[10]	AGUIAR L A, MELO L, DE LACERDA DE OLIVEIRA L. Validation of rapid descriptive sensory methods against conventional descriptive analyses: A systematic review[J]. Critical Reviews in Food Science and Nutrition,2019,59(16):2535−2552. doi: 10.1080/10408398.2018.1459468
[11]	PATRIS B , GUFONI V , CHOLLE S, et al. Impact of training on strategies to realize a beer sorting task: Behavioral and verbal assessments[C]//. In D. Valentin, D. Z. Nguyen, & L. Pelletier (Eds. ), New trends in sensory evaluation of food and non-food products. Ho Chi Minh (Vietnam): Vietnam National University-Ho chi Minh City Publishing House, 2007.
[12]	FLEMING E, ZIEGLER G, HAYES J. Check-All-That-Apply (CATA), sorting, and polarized sensory positioning (PSP) with astringent stimuli[J]. Food Quality and Preference,2015,45:41−49. doi: 10.1016/j.foodqual.2015.05.004
[13]	LELIÈVRE M, CHOLLET S, ABDI H, et al. What is the validity of the sorting task for describing beers? A study using trained and untrained assessors[J]. Food Quality and Preference,2008,19(8):697−703. doi: 10.1016/j.foodqual.2008.05.001
[14]	QANNARI E M, CARIOU V, TEILLET E, et al. SORT-CC: A procedure for the statistical treatment of free sorting data[J]. Food Quality and Preference,2010,21(3):302−308. doi: 10.1016/j.foodqual.2009.01.003
[15]	BUCHER T, COLLINS C, DIEM S, et al. Adolescents’ perception of the healthiness of snacks[J]. Food Quality and Preference,2016,50:94−101. doi: 10.1016/j.foodqual.2016.02.001
[16]	DEEGAN K C, KOIVISTO L, NÄKKILÄ J, et al. Application of a sorting procedure to greenhouse-grown cucumbers and tomatoes[J]. LWT-Food Science and Technology,2010,43(3):393−400. doi: 10.1016/j.lwt.2009.08.014
[17]	CLICERI D, DINNELLA C, DEPEZAY L, et al. Exploring salient dimensions in a free sorting task: A cross-country study within the elderly population[J]. Food Quality and Preference,2017,60:19−30. doi: 10.1016/j.foodqual.2017.03.006
[18]	MIELBY L H, HOPFER H, JENSEN S, et al. Comparison of descriptive analysis, projective mapping and sorting performed on pictures of fruit and vegetable mixes[J]. Food Quality and Preference,2014,35:86−94. doi: 10.1016/j.foodqual.2014.02.006
[19]	PARIZET E, KOEHL V. Application of free sorting tasks to sound quality experiments[J]. Applied Acoustics,2012,73(1):61−65. doi: 10.1016/j.apacoust.2011.07.007
[20]	PIOMBINO P, PITTARI E, GAMBUTI A, et al. Preliminary sensory characterisation of the diverse astringency of single cultivar Italian red wines and correlation of subqualities with chemical composition[J]. Australian Journal of Grape and Wine Research,2020,26(3):233−246. doi: 10.1111/ajgw.12431
[21]	FALAHEE M M, AW. Perceptual variation among drinking waters: The reliability of sorting and ranking data for multidimensional scaling[J]. Food Quality Preference,1997,8(5-6):389−394. doi: 10.1016/S0950-3293(97)00061-X
[22]	FAYE P, BRÉMAUD D, DURAND DAUBIN M, et al. Perceptive free sorting and verbalization tasks with naive subjects: an alternative to descriptive mappings[J]. Food Quality and Preference,2004,15(7-8):781−791. doi: 10.1016/j.foodqual.2004.04.009
[23]	SPENCER M, SAGE E, VELEZ M, et al. Using single free sorting and multivariate exploratory methods to design a new coffee taster's flavor wheel[J]. Journal of Food Science,2016,81(12):2997−3005.
[24]	ABDI H, VALENTIN D, CHOLLET S, et al. Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications[J]. Food Quality and Preference,2007,18(4):627−640. doi: 10.1016/j.foodqual.2006.09.003
[25]	LAHNE J. Sorting backbone analysis: A network-based method of extracting key actionable information from free-sorting task results[J]. Food Quality and Preference,2020,82:e103870. doi: 10.1016/j.foodqual.2020.103870
[26]	CARIOU V, QANNARI E M. Statistical treatment of free sorting data by means of correspondence and cluster analyses[J]. Food Quality and Preference,2018,68:1−11. doi: 10.1016/j.foodqual.2018.01.011
[27]	CADORET M, LÊ S, PAGÈS J. A factorial approach for sorting task data (FAST)[J]. Food Quality and Preference,2009,20(6):410−417. doi: 10.1016/j.foodqual.2009.02.010
[28]	TAKANE Y. IDSORT: An individual differences multidimensional scaling program for sorting data[J]. Behavior Research Methods Instrumentation,1982,14(6):546. doi: 10.3758/BF03203421
[29]	LAWLESS H T. Exploration of fragrance categories and ambiguous odors using multidimensional scaling and cluster analysis[J]. Chemical Senses,1989,14(3):349−360. doi: 10.1093/chemse/14.3.349
[30]	LEBART L, PIRON M, MORINEAU A. Statistique exploratoire multidimensionnelle: Visualisations et inférences en fouille de données[M]. Dunod, 2006.
[31]	PÉTEL C, COURCOUX P, GÉNOVESI N, et al. Free sorting and association task: A variant of the free sorting method applied to study the impact of dried sourdough as an ingredienton the related bread odor[J]. Journal of Food Science,2017,82(4):985−992. doi: 10.1111/1750-3841.13678
[32]	DUBOIS D. Sémantique et cognition: Catégories, prototypes, typicalité[J]. Language,1993,69(1):200. doi: 10.2307/416442
[33]	GUÉNOCHE A. Consensus of partitions: A constructive approach[J]. Advances in Data Analysis and Classification,2011,5(3):215−229. doi: 10.1007/s11634-011-0087-6
[34]	COURCOUX P, FAYE P, QANNARI E M. Determination of the consensus partition and cluster analysis of subjects in a free sorting task experiment[J]. Food Quality and Preference,2014,32:107−112. doi: 10.1016/j.foodqual.2013.05.004
[35]	WILEY D E. Latent partition analysis[J]. Psychometrika,1967,32(2):183−93. doi: 10.1007/BF02289425
[36]	DELARUE J, LAWLOR B, ROGEAUX M. Rapid sensory profiling techniques: Applications in new product development and consumer research[M]. Elsevier, 2014.
[37]	KRUSKAL J B. Nonmetric multidimensional scaling: A numerical method[J]. J Psychometrika,1964,29(2):115−129. doi: 10.1007/BF02289694
[38]	LIM J, LAWLESS H T. Qualitative differences of divalent salts: multidimensional scaling and cluster analysis[J]. Chem Senses,2005,30(9):719−726. doi: 10.1093/chemse/bji064
[39]	ARES G, VARELA P, RADO G, et al. Are consumer profiling techniques equivalent for some product categories? The case of orange-flavoured powdered drinks[J]. International Journal of Food Science & Technology,2011,46(8):1600−1608.
[40]	MOUSSAOUI K A, VARELA P. Exploring consumer product profiling techniques and their linkage to a quantitative descriptive analysis[J]. Food Quality and Preference,2010,21(8):1088−1099. doi: 10.1016/j.foodqual.2010.09.005
[41]	LAWLESS H T, SHENG N, KNOOPS S S C P. Multidimensional scaling of sorting data applied to cheese perception[J]. Food Quality and Preference,1995,6(2):91−98. doi: 10.1016/0950-3293(95)98553-U
[42]	RODRIGUES J F, MANGIA B A, SILVA J G E, et al. Sorting task as a tool to elucidate the sensory patterns of artisanal cheeses[J]. Journal of Sensory Studies,2020,35(3):e12562.
[43]	SAINT-EVE A, PAÇI KORA E, MARTIN N. Impact of the olfactory quality and chemical complexity of the flavouring agent on the texture of low fat stirred yogurts assessed by three different sensory methodologies[J]. Food Quality and Preference,2004,15(7-8):655−668. doi: 10.1016/j.foodqual.2003.09.002
[44]	CRUZ A G, CADENA R S, CASTRO W F, et al. Consumer perception of probiotic yogurt: Performance of check all that apply (CATA), projective mapping, sorting and intensity scale[J]. Food Research International,2013,54(1):601−10. doi: 10.1016/j.foodres.2013.07.056
[45]	DEHLHOLM C, BROCKHOFF P B, MEINERT L, et al. Rapid descriptive sensory methods— comparison of free multiple sorting, partial napping, napping, flash profiling and conventional profiling[J]. Food Quality and Preference,2012,26(2):267−277. doi: 10.1016/j.foodqual.2012.02.012
[46]	TANG C, HEYMANN H. Multidimensional sorting, similarity scaling and free-choice profiling of grape jellies[J]. Journal of Sensory Studies,2007,17:493−509.
[47]	COURCOUX P, QANNARI E M, TAYLOR Y, et al. Taxonomic free sorting[J]. Food Quality and Preference,2012,23(1):30−35. doi: 10.1016/j.foodqual.2011.04.001
[48]	HAMILTON L M, LAHNE J. Assessment of instructions on panelist cognitive framework and free sorting task results: A case study of cold brew coffee[J]. Food Quality and Preference,2020,83:e103889. doi: 10.1016/j.foodqual.2020.103889
[49]	BALLESTER J, ABDI H, LANGLOIS J, et al. The odor of colors: Can wine experts and novices distinguish the odors of white, red, and rosé wines?[J]. Chemosensory Perception,2009,2(4):203−213. doi: 10.1007/s12078-009-9058-0
[50]	BÉCUE-BERTAUT M, LÊ S. Analysis of multilingual labeled sorting tasks: application to a cross-cultural study in wine industry[J]. Journal of Sensory Studies,2011,26(5):299−310. doi: 10.1111/j.1745-459X.2011.00345.x
[51]	BRAND J, KIDD M C, VAN ANTWERPEN L, et al. Sorting in combination with quality scoring: a tool for industry professionals to identify drivers of wine quality rapidly[J]. South African Journal of Enology and Viticulture,2018,39(2):163−175.
[52]	KOENIG L, CARIOU V, SYMONEAUX R, et al. Additive trees for the categorization of a large number of objects, with bootstrapping strategy for stability assessment. Application to the free sorting of wine odor terms[J]. Food Quality and Preference,2021,89:104−137.
[53]	LAHNE J, COLLINS T S, HEYMANN H. Replication improves sorting-task results analyzed by DISTATIS in a consumer study of american bourbon and rye whiskeys[J]. Journal of Food Science,2016,81(5):1263−1271. doi: 10.1111/1750-3841.13301
[54]	LAHNE J, ABDI H, HEYMANN H. Rapid sensory profiles with DISTATIS and barycentric text projection: An example with amari, bitter herbal liqueurs[J]. Food Quality and Preference,2018,66:36−43. doi: 10.1016/j.foodqual.2018.01.003
[55]	KESSINGER J, EARNHART G, HAMILTON L, et al. Exploring perceptions and categorization of virginia hard ciders through the application of sorting tasks[J]. Journal of the American Society of Brewing Chemists,2020,79(2):1−14.
[56]	FERINI J L, MORALES M V, DA SILVA T A, et al. Consumers' perception of different brewed coffee extractions using the sorting technique[J]. Journal of Sensory Studies,2021,36(2):e12633.
[57]	HONORÉ-CHEDOZEAU C, LELIÈVRE-DESMAS M, BALLESTER J, et al. Knowledge representation among assessors through free hierarchical sorting and a semi-directed interview: exploring beaujolais wines[J]. Food Quality and Preference,2017,57:17−31. doi: 10.1016/j.foodqual.2016.11.008
[58]	FAYE P, COURCOUX P, GIBOREAU A, et al. Assessing and taking into account the subjects’ experience and knowledge in consumer studies. Application to the free sorting of wine glasses[J]. Food Quality and Preference,2013,28(1):317−327. doi: 10.1016/j.foodqual.2012.09.001
[59]	SANTOSA M, ABDI H, GUINARD J-X. A modified sorting task to investigate consumer perceptions of extra virgin olive oils[J]. Food Quality and Preference,2010,21(7):881−892. doi: 10.1016/j.foodqual.2010.05.011

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