Fuzzy approach for classification of pork into quality grades: coping with unclassifiable samples
•Fuzzy solution is better than traditional method to classify pork into quality grades.•The fuzzy logic are able to handle infeasible samples in classification.•The fuzzy logic enables the industry to meet specific market requirements.•It was possible to detect the contribution of pH in infeasible s...
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Published in | Computers and electronics in agriculture Vol. 150; pp. 455 - 464 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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Amsterdam
Elsevier B.V
01.07.2018
Elsevier BV |
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Abstract | •Fuzzy solution is better than traditional method to classify pork into quality grades.•The fuzzy logic are able to handle infeasible samples in classification.•The fuzzy logic enables the industry to meet specific market requirements.•It was possible to detect the contribution of pH in infeasible samples composition.
Meat classification methods are commonly based on quality parameters standardized by numeric ranges. However, some animal samples from different production chains do not match the current grades proposed. These unclassifiable samples are not capable to fit into a standard created by crisp range of values due to being infeasible toward its definition. An alternative to handle this kind of sample classification is the fuzzy logic, which could deal with uncertainty and ambiguity degree like human reasoning. In this work, we compare the traditional classification method and fuzzy approaches with the objective to handle the infeasible samples. This was compared to traditional pork standards using eleven real-life datasets with a total of 1798 samples described by pH, water holding capacity and/or L∗ value. The results demonstrated that traditional classification could not predict the unclassifiable samples. On the other hand, the fuzzy approaches improve significantly the number of classified samples. Performance of the fuzzy approaches were compared with several machine learning algorithms, but no significant statistical difference was observed. Finally, a real-life study case was explored, highlighting some advantages and further achievements of the fuzzy modeling. |
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AbstractList | Meat classification methods are commonly based on quality parameters standardized by numeric ranges. However, some animal samples from different production chains do not match the current grades proposed. These unclassifiable samples are not capable to fit into a standard created by crisp range of values due to being infeasible toward its definition. An alternative to handle this kind of sample classification is the fuzzy logic, which could deal with uncertainty and ambiguity degree like human reasoning. In this work, we compare the traditional classification method and fuzzy approaches with the objective to handle the infeasible samples. This was compared to traditional pork standards using eleven real-life datasets with a total of 1798 samples described by pH, water holding capacity and/or L∗ value. The results demonstrated that traditional classification could not predict the unclassifiable samples. On the other hand, the fuzzy approaches improve significantly the number of classified samples. Performance of the fuzzy approaches were compared with several machine learning algorithms, but no significant statistical difference was observed. Finally, a real-life study case was explored, highlighting some advantages and further achievements of the fuzzy modeling. •Fuzzy solution is better than traditional method to classify pork into quality grades.•The fuzzy logic are able to handle infeasible samples in classification.•The fuzzy logic enables the industry to meet specific market requirements.•It was possible to detect the contribution of pH in infeasible samples composition. Meat classification methods are commonly based on quality parameters standardized by numeric ranges. However, some animal samples from different production chains do not match the current grades proposed. These unclassifiable samples are not capable to fit into a standard created by crisp range of values due to being infeasible toward its definition. An alternative to handle this kind of sample classification is the fuzzy logic, which could deal with uncertainty and ambiguity degree like human reasoning. In this work, we compare the traditional classification method and fuzzy approaches with the objective to handle the infeasible samples. This was compared to traditional pork standards using eleven real-life datasets with a total of 1798 samples described by pH, water holding capacity and/or L∗ value. The results demonstrated that traditional classification could not predict the unclassifiable samples. On the other hand, the fuzzy approaches improve significantly the number of classified samples. Performance of the fuzzy approaches were compared with several machine learning algorithms, but no significant statistical difference was observed. Finally, a real-life study case was explored, highlighting some advantages and further achievements of the fuzzy modeling. |
Author | Fuzyi, Estefânia Mayumi Andreo, Nayara Barbon Jr, Sylvio Peres, Louise Manha Barbon, Ana Paula A.C. Barbin, Douglas Fernandes Bridi, Ana Maria Maeda Saito, Priscila Tiemi |
Author_xml | – sequence: 1 givenname: Louise Manha surname: Peres fullname: Peres, Louise Manha organization: Department of Animal Science, Londrina State University (UEL), Londrina 86057-970, Brazil – sequence: 2 givenname: Sylvio surname: Barbon Jr fullname: Barbon Jr, Sylvio email: barbon@uel.br organization: Department of Computer Science, Londrina State University (UEL), Londrina 86057-970, Brazil – sequence: 3 givenname: Estefânia Mayumi surname: Fuzyi fullname: Fuzyi, Estefânia Mayumi email: emfuzyi@ppgia.pucpr.br organization: Department of Inf., Pontifícia Univ. Católica do Paraná (PUCPR), Curitiba 80215-901, Brazil – sequence: 4 givenname: Ana Paula A.C. surname: Barbon fullname: Barbon, Ana Paula A.C. organization: Department of Animal Science, Londrina State University (UEL), Londrina 86057-970, Brazil – sequence: 5 givenname: Douglas Fernandes surname: Barbin fullname: Barbin, Douglas Fernandes email: dfbarbin@unicamp.br organization: Department of Food Engineering, Campinas State University (UNICAMP), Campinas 13083-862, Brazil – sequence: 6 givenname: Priscila Tiemi orcidid: 0000-0002-4988-0702 surname: Maeda Saito fullname: Maeda Saito, Priscila Tiemi email: psaito@utfpr.edu.br organization: Department of Computing, Fed. Univ. of Tecn. - Parana (UTFPR), Cornélio Procópio 86300-000, Brazil – sequence: 7 givenname: Nayara surname: Andreo fullname: Andreo, Nayara organization: Department of Animal Science, Londrina State University (UEL), Londrina 86057-970, Brazil – sequence: 8 givenname: Ana Maria surname: Bridi fullname: Bridi, Ana Maria email: ambridi@uel.br organization: Department of Animal Science, Londrina State University (UEL), Londrina 86057-970, Brazil |
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Cites_doi | 10.23986/afsci.8577 10.1016/j.foodchem.2009.08.034 10.1109/IMIS.2016.83 10.1016/j.compag.2016.06.028 10.1016/S0065-2628(08)60141-X 10.17221/2520-CJAS 10.1023/A:1014793820388 10.1016/j.meatsci.2011.07.011 10.1016/0309-1740(93)90078-V 10.17268/sci.agropecu.2015.02.02 10.1016/0309-1740(87)90051-9 10.1016/j.fss.2015.09.001 10.18637/jss.v065.i06 10.1016/0309-1740(94)90109-0 10.22256/pubvet.v8n2.1659 10.1109/LSP.2010.2077278 10.1016/j.sbspro.2014.02.498 10.1016/j.meatsci.2005.04.022 10.1111/asj.12385 10.1016/S0165-0114(02)00246-4 10.1002/col.5080150406 10.1109/TKDE.2008.239 10.1590/S1516-35982005000300040 10.1016/S0309-1740(96)00116-7 10.1016/j.meatsci.2009.09.017 10.5713/ajas.2000.77 10.1023/A:1010933404324 10.1214/15-AOS1321 10.1590/1413-81232015208.19472014 10.1016/j.jag.2009.06.002 |
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References | Coutinho, Rizol, Nascimento, Medeiros (b0065) 2015; 20 Peres, L.M., de Oliveira, E.R., de Lucio; et al, C.L., 2011. Análise comparativa de metodologias de determinaç Bauer, A., Petzet, A., Schwagele, F., Scheier, R., Schmidt, H., August 2013. Towards an online assessment of meat quality in pork. In: 59th International Congress of Meat Science and Technology. Hamm (b0105) 1960; 10 Faucitano, Ielo, Ster, Fiego, Methot, Saucier (b0090) 2010; 84 oes. IST-Rio, Rio de Janeiro Brasil. Joo, Kauffman, Warner, Borggaard, Stevenson-Barry, Rhee, Park, Kim (b0130) 2000; 13 Silva Sobrinho, Purchas, Kadim, Yamamoto (b0205) 2005; 34 Barbin, Elmasry, Sun, Allen (b0015) 2012; 90 Breiman (b0045) 2001; 45 We¸glarz (b0250) 2010; 55 Chen, Li (b0055) 2010; 17 Sharma, Jain (b0195) 2013; 2 Tomovic, Zlender, Jokanović, Tomovic, Sojic, Skaljac, Tasic, Ikonic, Soso, Hromis (b0215) 2014; 23 Jensen, Shen (b0125) 2008; vol. 8 ao de lógica nebulosa para previs Campos, Gomide, Bruno Andreatta Scottá, Soares (b0050) 2014; 8 Shaw (b0200) 2013; vol. 457 Adzitey, Nurul (b0010) 2011; 18 Warriss, Brown (b0245) 1987; 20 Goldschmidt, R.R., 2010. Uma introduç ao à inteligência computacional: fundamentos, ferramentas e aplicaç Sunita, Deo, A., 2012. Fuzzy logic systems design for engineering and applications. In: First International Conference On Advances In Computer, Electronics And Electrical Engineering - CEEE, pp. 34–40. Müller (b0170) 2015 Scornet, Biau, Vert (b0190) 2015; 43 CIE (b0060) 1978 ao do risco de escorregamentos de taludes em solo residual. Lodwick (b0145) 2002; 8 Riza, L.S., Bergmeir, C.N., Herrera, F., Benítez Sánchez, J.M., 2015. frbs: Fuzzy rule-based systems for classification and regression in r. American Statistical Association. Beringues, J.C., 1999. Sorption Isotherms and Water Diffusitivity in Muscles of Pork Ham at Different NaCl Contents. Universitat Politècnica de Catalunya. (accessed: 2015-12-26). He, Garcia (b0110) 2009; 21 Ma, Y., Liang, S., Chen, X., Jia, C., 2016. The approach to detect abnormal access behavior based on naive bayes algorithm. In: 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), 2016. IEEE, pp. 313–315. Kauffman, Sybesma, Smulders, Eikelenboom, Engel, Van Laack, Hoving-Bolink, Sterrenburg, Nordheim, Walstra (b0135) 1993; 34 Moore, Lodwick (b0165) 2003; 135 Sabow, Sazili, Zulkifli, Goh, Kadir, Adeyemi (b0185) 2015; 86 Wilhelm, Maganhini, Hernández-Blazquez, Ida, Shimokomaki (b0255) 2010; 119 Fletcher (b0095) 1999; 78 da Silva, M.A., 2008. Aplicaç Kavzoglu, Colkesen (b0140) 2009; 11 Bezděk (b0035) 2014; 124 Vásquez-Villalobos, Vásquez Angulo, Méndez Reyna (b0230) 2015; 6 Faucitano, L., 2000. Efeitos do manuseio pré-abate sobre o bem-estar e sua influência sobre a qualidade de carne. In: i conferência virtual internacional sobre qualidade de carne suína, vol. 16. Wang (b0235) 2005; vol. 177 ao da capacidade de retenç Huff-Lonergan, Lonergan (b0120) 2005; 71 USA, P., 2003. Meat Quality: Understanding Industry Measurements and Guidelines ao de água. In: XXI Congresso Brasileiro de Zootecnia. Dutson, T., 1983. The measurement of ph in muscle and its importance to meat quality. In: Proceedings Annual Reciprocal Meat Conference. Manikandan, P., Ramyachitra, D., 2014. Naïve bayes classification technique for analysis of ecoli imbalance dataset. Int. J. Comput. Intell. Inform., July âAS Septembe 4. Barbon, Jr., Mantovani, Fuzyi, Peres, Bridi (b0020) 2016; 127 Medeiros, Araújo, Vianna, Moraes (b0160) 2014; 38 Warner, Kauffman, Greaser (b0240) 1997; 45 Hüllermeier (b0115) 2015; 281 Adorni, Bianchi, Cagnoni (b0005) 2001 Van Laack, Kauffman, Sybesma, Smulders, Eikelenmboom, Pinheiro (b0225) 1994; 38 Demšar (b0075) 2006; 7 Billmeyer, Hammond (b0040) 1990; 15 Bezděk (10.1016/j.compag.2018.05.009_b0035) 2014; 124 Tomovic (10.1016/j.compag.2018.05.009_b0215) 2014; 23 Warriss (10.1016/j.compag.2018.05.009_b0245) 1987; 20 Sharma (10.1016/j.compag.2018.05.009_b0195) 2013; 2 Wilhelm (10.1016/j.compag.2018.05.009_b0255) 2010; 119 Coutinho (10.1016/j.compag.2018.05.009_b0065) 2015; 20 10.1016/j.compag.2018.05.009_b0080 Wang (10.1016/j.compag.2018.05.009_b0235) 2005; vol. 177 Breiman (10.1016/j.compag.2018.05.009_b0045) 2001; 45 Chen (10.1016/j.compag.2018.05.009_b0055) 2010; 17 10.1016/j.compag.2018.05.009_b0155 10.1016/j.compag.2018.05.009_b0030 Billmeyer (10.1016/j.compag.2018.05.009_b0040) 1990; 15 Silva Sobrinho (10.1016/j.compag.2018.05.009_b0205) 2005; 34 Warner (10.1016/j.compag.2018.05.009_b0240) 1997; 45 Vásquez-Villalobos (10.1016/j.compag.2018.05.009_b0230) 2015; 6 Demšar (10.1016/j.compag.2018.05.009_b0075) 2006; 7 Fletcher (10.1016/j.compag.2018.05.009_b0095) 1999; 78 Jensen (10.1016/j.compag.2018.05.009_b0125) 2008; vol. 8 Van Laack (10.1016/j.compag.2018.05.009_b0225) 1994; 38 10.1016/j.compag.2018.05.009_b0150 Adorni (10.1016/j.compag.2018.05.009_b0005) 2001 10.1016/j.compag.2018.05.009_b0070 10.1016/j.compag.2018.05.009_b0025 10.1016/j.compag.2018.05.009_b0100 Joo (10.1016/j.compag.2018.05.009_b0130) 2000; 13 Barbon (10.1016/j.compag.2018.05.009_b0020) 2016; 127 Moore (10.1016/j.compag.2018.05.009_b0165) 2003; 135 10.1016/j.compag.2018.05.009_b0220 Lodwick (10.1016/j.compag.2018.05.009_b0145) 2002; 8 He (10.1016/j.compag.2018.05.009_b0110) 2009; 21 Medeiros (10.1016/j.compag.2018.05.009_b0160) 2014; 38 10.1016/j.compag.2018.05.009_b0180 Shaw (10.1016/j.compag.2018.05.009_b0200) 2013; vol. 457 Faucitano (10.1016/j.compag.2018.05.009_b0090) 2010; 84 Barbin (10.1016/j.compag.2018.05.009_b0015) 2012; 90 Scornet (10.1016/j.compag.2018.05.009_b0190) 2015; 43 10.1016/j.compag.2018.05.009_b0210 10.1016/j.compag.2018.05.009_b0175 CIE (10.1016/j.compag.2018.05.009_b0060) 1978 We¸glarz (10.1016/j.compag.2018.05.009_b0250) 2010; 55 Kavzoglu (10.1016/j.compag.2018.05.009_b0140) 2009; 11 Campos (10.1016/j.compag.2018.05.009_b0050) 2014; 8 Sabow (10.1016/j.compag.2018.05.009_b0185) 2015; 86 Kauffman (10.1016/j.compag.2018.05.009_b0135) 1993; 34 Müller (10.1016/j.compag.2018.05.009_b0170) 2015 Adzitey (10.1016/j.compag.2018.05.009_b0010) 2011; 18 10.1016/j.compag.2018.05.009_b0085 Hüllermeier (10.1016/j.compag.2018.05.009_b0115) 2015; 281 Huff-Lonergan (10.1016/j.compag.2018.05.009_b0120) 2005; 71 Hamm (10.1016/j.compag.2018.05.009_b0105) 1960; 10 |
References_xml | – volume: vol. 8 year: 2008 ident: b0125 publication-title: Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches contributor: fullname: Shen – volume: 18 start-page: 11 year: 2011 end-page: 20 ident: b0010 article-title: Pale soft exudative (pse) and dark firm dry (dfd) meats: causes and measures to reduce these incidences-a mini review publication-title: Int. Food Res. J. contributor: fullname: Nurul – year: 1978 ident: b0060 article-title: Recommendations on Uniform Color Spaces, Color Difference Equations, and Psychometric Terms contributor: fullname: CIE – volume: 17 start-page: 933 year: 2010 end-page: 936 ident: b0055 article-title: Tone reservation using near-optimal peak reduction tone set selection algorithm for paper reduction in of dm systems publication-title: IEEE Sig. Process. Lett. contributor: fullname: Li – volume: 45 start-page: 5 year: 2001 end-page: 32 ident: b0045 article-title: Random forests publication-title: Mach. Learn. contributor: fullname: Breiman – volume: 43 start-page: 1716 year: 2015 end-page: 1741 ident: b0190 article-title: Consistency of random forests publication-title: Ann. Statist. contributor: fullname: Vert – volume: vol. 457 year: 2013 ident: b0200 publication-title: Fuzzy Control of Industrial Systems: Theory and Applications contributor: fullname: Shaw – volume: 281 start-page: 292 year: 2015 end-page: 299 ident: b0115 article-title: Does machine learning need fuzzy logic? publication-title: Fuzzy Sets Syst. contributor: fullname: Hüllermeier – volume: 13 start-page: 77 year: 2000 end-page: 85 ident: b0130 article-title: Objectively predicting ultimate quality of post-rigor pork musculature publication-title: Asian-Austral. J. Anim. Sci. contributor: fullname: Kim – volume: 21 start-page: 1263 year: 2009 end-page: 1284 ident: b0110 article-title: Learning from imbalanced data publication-title: IEEE Trans. Knowl. Data Eng. contributor: fullname: Garcia – volume: 55 start-page: 548 year: 2010 end-page: 556 ident: b0250 article-title: Meat quality defined based on ph and colour depending on cattle category and slaughter season publication-title: Czech J. Anim. Sci. contributor: fullname: We¸glarz – volume: 10 start-page: 355 year: 1960 end-page: 463 ident: b0105 article-title: Biochemistry of meat hydration publication-title: Adv. Food Res. contributor: fullname: Hamm – volume: 90 start-page: 259 year: 2012 end-page: 268 ident: b0015 article-title: Near-infrared hyperspectral imaging for grading and classification of pork publication-title: Meat Sci. contributor: fullname: Allen – volume: 38 start-page: 104 year: 2014 end-page: 118 ident: b0160 article-title: Modelo de suporte à decis publication-title: Saúde debate contributor: fullname: Moraes – volume: 6 start-page: 99 year: 2015 end-page: 109 ident: b0230 article-title: Nuevo método para determinar vida útil sensorial utilizando lógica difusa: caso corazones de alcachofa (cynara scolymus l.) marinadas en conserva publication-title: Sci. Agropec. contributor: fullname: Méndez Reyna – volume: 71 start-page: 194 year: 2005 end-page: 204 ident: b0120 article-title: Mechanisms of water-holding capacity of meat: the role of postmortem biochemical and structural changes publication-title: Meat Sci. contributor: fullname: Lonergan – volume: 2 start-page: 1925 year: 2013 end-page: 1931 ident: b0195 article-title: Weka approach for comparative study of classification algorithm publication-title: Int. J. Adv. Res. Comp. Commun. Eng. contributor: fullname: Jain – volume: 45 start-page: 339 year: 1997 end-page: 352 ident: b0240 article-title: Muscle protein changes post mortem in relation to pork quality traits publication-title: Meat Sci. contributor: fullname: Greaser – volume: 20 start-page: 2585 year: 2015 end-page: 2590 ident: b0065 article-title: Fuzzy model approach for estimating time of hospitalization due to cardiovascular diseases publication-title: Ciência & saúde coletiva contributor: fullname: Medeiros – volume: 135 start-page: 5 year: 2003 end-page: 9 ident: b0165 article-title: Interfaces between fuzzy set theory and interval analysis and fuzzy set theory publication-title: Fuzzy Sets Syst. contributor: fullname: Lodwick – volume: 38 start-page: 193 year: 1994 end-page: 201 ident: b0225 article-title: Is colour brightness (l-value) a reliable indicator of water-holding capacity in porcine muscle? publication-title: Meat Sci. contributor: fullname: Pinheiro – volume: 20 start-page: 65 year: 1987 end-page: 74 ident: b0245 article-title: The relationship between initial ph, reflectance and exudation in pig muscle publication-title: Meat Sci. contributor: fullname: Brown – volume: 8 year: 2014 ident: b0050 article-title: Impactos da seleção genética na qualidade da carne suína publication-title: PUBVET contributor: fullname: Soares – volume: 78 start-page: 1323 year: 1999 end-page: 1327 ident: b0095 article-title: Broiler breast meat color variation, ph and texture publication-title: Reason. Nam. Syst. contributor: fullname: Fletcher – year: 2015 ident: b0170 article-title: Computing and Philosophy: Selected Papers from Synthese Library contributor: fullname: Müller – volume: 23 start-page: 9 year: 2014 end-page: 18 ident: b0215 article-title: Technological quality and composition of the m. semimembranosus and m. longissimus dorsi from large white and landrace pigs publication-title: Agricult. Food Sci. contributor: fullname: Hromis – volume: 119 start-page: 1201 year: 2010 end-page: 1204 ident: b0255 article-title: Protease activity and the ultrastructure of broiler chicken PSE (pale, soft, exudative) meat publication-title: Food Chem. contributor: fullname: Shimokomaki – volume: 127 start-page: 368 year: 2016 end-page: 375 ident: b0020 article-title: Storage time prediction of pork by computational intelligence publication-title: Comp. Electron. Agricult. contributor: fullname: Bridi – start-page: 259 year: 2001 end-page: 264 ident: b0005 article-title: Learning fuzzy decision trees for ham quality control publication-title: Trans. QCAV2001 contributor: fullname: Cagnoni – volume: 86 start-page: 981 year: 2015 end-page: 991 ident: b0185 article-title: Physico-chemical characteristics of longissimus lumborum muscle in goats subjected to halal slaughter and anesthesia (halothane) pre-slaughter publication-title: Anim. Sci. J. contributor: fullname: Adeyemi – volume: 34 start-page: 283 year: 1993 end-page: 300 ident: b0135 article-title: The effectiveness of examining early post-mortem musculature to predict ultimate pork quality publication-title: Meat Sci. contributor: fullname: Walstra – volume: 34 start-page: 1070 year: 2005 end-page: 1078 ident: b0205 article-title: Meat quality in lambs of different genotypes and ages at slaughter publication-title: Revista Brasileira de Zootecnia contributor: fullname: Yamamoto – volume: 7 start-page: 1 year: 2006 end-page: 30 ident: b0075 article-title: Statistical comparisons of classifiers over multiple data sets publication-title: J. Mach. Learn. Res. contributor: fullname: Demšar – volume: 11 start-page: 352 year: 2009 end-page: 359 ident: b0140 article-title: A kernel functions analysis for support vector machines for land cover classification publication-title: Int. J. Appl. Earth Observ. Geoinf. contributor: fullname: Colkesen – volume: 15 start-page: 206 year: 1990 end-page: 209 ident: b0040 article-title: Astm standards on color-difference measurements publication-title: Color Res. Appl. contributor: fullname: Hammond – volume: 84 start-page: 466 year: 2010 end-page: 469 ident: b0090 article-title: Shelf life of pork from five different quality classes publication-title: Meat Sci. contributor: fullname: Saucier – volume: 8 start-page: 93 year: 2002 end-page: 95 ident: b0145 article-title: Reliable computing: special issue on the linkages between interval mathematics and fuzzy set theory publication-title: Reliab. Comput. contributor: fullname: Lodwick – volume: 124 start-page: 371 year: 2014 end-page: 380 ident: b0035 article-title: Using fuzzy logic in business publication-title: Proc. - Soc. Behav. Sci. contributor: fullname: Bezděk – volume: vol. 177 year: 2005 ident: b0235 publication-title: Support Vector Machines: Theory and Applications contributor: fullname: Wang – year: 2015 ident: 10.1016/j.compag.2018.05.009_b0170 contributor: fullname: Müller – volume: 23 start-page: 9 issue: 1 year: 2014 ident: 10.1016/j.compag.2018.05.009_b0215 article-title: Technological quality and composition of the m. semimembranosus and m. longissimus dorsi from large white and landrace pigs publication-title: Agricult. Food Sci. doi: 10.23986/afsci.8577 contributor: fullname: Tomovic – volume: 119 start-page: 1201 issue: 3 year: 2010 ident: 10.1016/j.compag.2018.05.009_b0255 article-title: Protease activity and the ultrastructure of broiler chicken PSE (pale, soft, exudative) meat publication-title: Food Chem. doi: 10.1016/j.foodchem.2009.08.034 contributor: fullname: Wilhelm – ident: 10.1016/j.compag.2018.05.009_b0150 doi: 10.1109/IMIS.2016.83 – volume: 127 start-page: 368 year: 2016 ident: 10.1016/j.compag.2018.05.009_b0020 article-title: Storage time prediction of pork by computational intelligence publication-title: Comp. Electron. Agricult. doi: 10.1016/j.compag.2016.06.028 contributor: fullname: Barbon – volume: 10 start-page: 355 year: 1960 ident: 10.1016/j.compag.2018.05.009_b0105 article-title: Biochemistry of meat hydration publication-title: Adv. Food Res. doi: 10.1016/S0065-2628(08)60141-X contributor: fullname: Hamm – volume: 55 start-page: 548 issue: 12 year: 2010 ident: 10.1016/j.compag.2018.05.009_b0250 article-title: Meat quality defined based on ph and colour depending on cattle category and slaughter season publication-title: Czech J. Anim. Sci. doi: 10.17221/2520-CJAS contributor: fullname: We¸glarz – ident: 10.1016/j.compag.2018.05.009_b0100 – ident: 10.1016/j.compag.2018.05.009_b0175 – ident: 10.1016/j.compag.2018.05.009_b0085 – ident: 10.1016/j.compag.2018.05.009_b0030 – volume: 8 start-page: 93 issue: 1 year: 2002 ident: 10.1016/j.compag.2018.05.009_b0145 article-title: Reliable computing: special issue on the linkages between interval mathematics and fuzzy set theory publication-title: Reliab. Comput. doi: 10.1023/A:1014793820388 contributor: fullname: Lodwick – volume: 18 start-page: 11 issue: 1 year: 2011 ident: 10.1016/j.compag.2018.05.009_b0010 article-title: Pale soft exudative (pse) and dark firm dry (dfd) meats: causes and measures to reduce these incidences-a mini review publication-title: Int. Food Res. J. contributor: fullname: Adzitey – volume: 90 start-page: 259 issue: 1 year: 2012 ident: 10.1016/j.compag.2018.05.009_b0015 article-title: Near-infrared hyperspectral imaging for grading and classification of pork publication-title: Meat Sci. doi: 10.1016/j.meatsci.2011.07.011 contributor: fullname: Barbin – volume: 34 start-page: 283 issue: 3 year: 1993 ident: 10.1016/j.compag.2018.05.009_b0135 article-title: The effectiveness of examining early post-mortem musculature to predict ultimate pork quality publication-title: Meat Sci. doi: 10.1016/0309-1740(93)90078-V contributor: fullname: Kauffman – volume: 6 start-page: 99 issue: 2 year: 2015 ident: 10.1016/j.compag.2018.05.009_b0230 article-title: Nuevo método para determinar vida útil sensorial utilizando lógica difusa: caso corazones de alcachofa (cynara scolymus l.) marinadas en conserva publication-title: Sci. Agropec. doi: 10.17268/sci.agropecu.2015.02.02 contributor: fullname: Vásquez-Villalobos – volume: 20 start-page: 65 year: 1987 ident: 10.1016/j.compag.2018.05.009_b0245 article-title: The relationship between initial ph, reflectance and exudation in pig muscle publication-title: Meat Sci. doi: 10.1016/0309-1740(87)90051-9 contributor: fullname: Warriss – volume: 281 start-page: 292 year: 2015 ident: 10.1016/j.compag.2018.05.009_b0115 article-title: Does machine learning need fuzzy logic? publication-title: Fuzzy Sets Syst. doi: 10.1016/j.fss.2015.09.001 contributor: fullname: Hüllermeier – ident: 10.1016/j.compag.2018.05.009_b0210 – ident: 10.1016/j.compag.2018.05.009_b0180 doi: 10.18637/jss.v065.i06 – start-page: 259 year: 2001 ident: 10.1016/j.compag.2018.05.009_b0005 article-title: Learning fuzzy decision trees for ham quality control publication-title: Trans. QCAV2001 contributor: fullname: Adorni – ident: 10.1016/j.compag.2018.05.009_b0220 – volume: 38 start-page: 193 year: 1994 ident: 10.1016/j.compag.2018.05.009_b0225 article-title: Is colour brightness (l-value) a reliable indicator of water-holding capacity in porcine muscle? publication-title: Meat Sci. doi: 10.1016/0309-1740(94)90109-0 contributor: fullname: Van Laack – volume: 8 issue: 2 year: 2014 ident: 10.1016/j.compag.2018.05.009_b0050 article-title: Impactos da seleção genética na qualidade da carne suína publication-title: PUBVET doi: 10.22256/pubvet.v8n2.1659 contributor: fullname: Campos – volume: 17 start-page: 933 issue: 11 year: 2010 ident: 10.1016/j.compag.2018.05.009_b0055 article-title: Tone reservation using near-optimal peak reduction tone set selection algorithm for paper reduction in of dm systems publication-title: IEEE Sig. Process. Lett. doi: 10.1109/LSP.2010.2077278 contributor: fullname: Chen – volume: 124 start-page: 371 year: 2014 ident: 10.1016/j.compag.2018.05.009_b0035 article-title: Using fuzzy logic in business publication-title: Proc. - Soc. Behav. Sci. doi: 10.1016/j.sbspro.2014.02.498 contributor: fullname: Bezděk – volume: 71 start-page: 194 issue: 1 year: 2005 ident: 10.1016/j.compag.2018.05.009_b0120 article-title: Mechanisms of water-holding capacity of meat: the role of postmortem biochemical and structural changes publication-title: Meat Sci. doi: 10.1016/j.meatsci.2005.04.022 contributor: fullname: Huff-Lonergan – ident: 10.1016/j.compag.2018.05.009_b0070 – volume: 2 start-page: 1925 issue: 4 year: 2013 ident: 10.1016/j.compag.2018.05.009_b0195 article-title: Weka approach for comparative study of classification algorithm publication-title: Int. J. Adv. Res. Comp. Commun. Eng. contributor: fullname: Sharma – volume: 86 start-page: 981 issue: 12 year: 2015 ident: 10.1016/j.compag.2018.05.009_b0185 article-title: Physico-chemical characteristics of longissimus lumborum muscle in goats subjected to halal slaughter and anesthesia (halothane) pre-slaughter publication-title: Anim. Sci. J. doi: 10.1111/asj.12385 contributor: fullname: Sabow – volume: 135 start-page: 5 issue: 1 year: 2003 ident: 10.1016/j.compag.2018.05.009_b0165 article-title: Interfaces between fuzzy set theory and interval analysis and fuzzy set theory publication-title: Fuzzy Sets Syst. doi: 10.1016/S0165-0114(02)00246-4 contributor: fullname: Moore – volume: 15 start-page: 206 issue: 4 year: 1990 ident: 10.1016/j.compag.2018.05.009_b0040 article-title: Astm standards on color-difference measurements publication-title: Color Res. Appl. doi: 10.1002/col.5080150406 contributor: fullname: Billmeyer – volume: 21 start-page: 1263 issue: 9 year: 2009 ident: 10.1016/j.compag.2018.05.009_b0110 article-title: Learning from imbalanced data publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2008.239 contributor: fullname: He – volume: 78 start-page: 1323 year: 1999 ident: 10.1016/j.compag.2018.05.009_b0095 article-title: Broiler breast meat color variation, ph and texture publication-title: Reason. Nam. Syst. contributor: fullname: Fletcher – volume: 34 start-page: 1070 issue: 3 year: 2005 ident: 10.1016/j.compag.2018.05.009_b0205 article-title: Meat quality in lambs of different genotypes and ages at slaughter publication-title: Revista Brasileira de Zootecnia doi: 10.1590/S1516-35982005000300040 contributor: fullname: Silva Sobrinho – volume: 45 start-page: 339 issue: 3 year: 1997 ident: 10.1016/j.compag.2018.05.009_b0240 article-title: Muscle protein changes post mortem in relation to pork quality traits publication-title: Meat Sci. doi: 10.1016/S0309-1740(96)00116-7 contributor: fullname: Warner – volume: 84 start-page: 466 issue: 3 year: 2010 ident: 10.1016/j.compag.2018.05.009_b0090 article-title: Shelf life of pork from five different quality classes publication-title: Meat Sci. doi: 10.1016/j.meatsci.2009.09.017 contributor: fullname: Faucitano – volume: vol. 457 year: 2013 ident: 10.1016/j.compag.2018.05.009_b0200 contributor: fullname: Shaw – year: 1978 ident: 10.1016/j.compag.2018.05.009_b0060 contributor: fullname: CIE – volume: vol. 8 year: 2008 ident: 10.1016/j.compag.2018.05.009_b0125 contributor: fullname: Jensen – volume: vol. 177 year: 2005 ident: 10.1016/j.compag.2018.05.009_b0235 contributor: fullname: Wang – volume: 7 start-page: 1 year: 2006 ident: 10.1016/j.compag.2018.05.009_b0075 article-title: Statistical comparisons of classifiers over multiple data sets publication-title: J. Mach. Learn. Res. contributor: fullname: Demšar – volume: 13 start-page: 77 issue: 1 year: 2000 ident: 10.1016/j.compag.2018.05.009_b0130 article-title: Objectively predicting ultimate quality of post-rigor pork musculature publication-title: Asian-Austral. J. Anim. Sci. doi: 10.5713/ajas.2000.77 contributor: fullname: Joo – ident: 10.1016/j.compag.2018.05.009_b0155 – volume: 45 start-page: 5 issue: 1 year: 2001 ident: 10.1016/j.compag.2018.05.009_b0045 article-title: Random forests publication-title: Mach. Learn. doi: 10.1023/A:1010933404324 contributor: fullname: Breiman – volume: 38 start-page: 104 issue: 100 year: 2014 ident: 10.1016/j.compag.2018.05.009_b0160 article-title: Modelo de suporte à decisao aplicado à identificaçao de indivíduos nao aderentes ao tratamento anti-hipertensivo publication-title: Saúde debate contributor: fullname: Medeiros – volume: 43 start-page: 1716 issue: 4 year: 2015 ident: 10.1016/j.compag.2018.05.009_b0190 article-title: Consistency of random forests publication-title: Ann. Statist. doi: 10.1214/15-AOS1321 contributor: fullname: Scornet – ident: 10.1016/j.compag.2018.05.009_b0025 – volume: 20 start-page: 2585 issue: 8 year: 2015 ident: 10.1016/j.compag.2018.05.009_b0065 article-title: Fuzzy model approach for estimating time of hospitalization due to cardiovascular diseases publication-title: Ciência & saúde coletiva doi: 10.1590/1413-81232015208.19472014 contributor: fullname: Coutinho – ident: 10.1016/j.compag.2018.05.009_b0080 – volume: 11 start-page: 352 issue: 5 year: 2009 ident: 10.1016/j.compag.2018.05.009_b0140 article-title: A kernel functions analysis for support vector machines for land cover classification publication-title: Int. J. Appl. Earth Observ. Geoinf. doi: 10.1016/j.jag.2009.06.002 contributor: fullname: Kavzoglu |
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Snippet | •Fuzzy solution is better than traditional method to classify pork into quality grades.•The fuzzy logic are able to handle infeasible samples in... Meat classification methods are commonly based on quality parameters standardized by numeric ranges. However, some animal samples from different production... |
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SubjectTerms | Classical logic Classification Computational intelligence Computational mathematics Fuzzy Logic Machine learning Mathematical models Meat Pattern recognition Pork Quality Sampling methods Statistical analysis Statistical methods |
Title | Fuzzy approach for classification of pork into quality grades: coping with unclassifiable samples |
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