GA0034 S tudy on the Improvement of Pork Quality for Ex port

Transcription

1 GA0034 S tudy on the Improvement of Pork Quality for Ex port

2 : : : : : : : : : : : - 1 -

3 ..,,,, ),,,, - 2 -

4 2), TBA, VBN,, ph,,. 1),. 1) 90kg 110kg. NIR Spectra 1) 2). 1) 2) 3). 1.,,,, VBN, TBA,,,.,,,,, - 3 -

5 , 3, 6,, (LYD), 2 - (LY), - (DH), LYD,, kg,,,,, 10kg 3. 1) kg, kg. 2) kg 0.44% kg 10%, 9. 3) aroma, flavor.. 90kg 110kg

6 4., Cryo-vac film TBA (mg malonaldehyde/kg meat). 5. NIR Spectra,,. 6. 8% 3: 6: 9=1:2:1,, ( )

7 Summary 1. Title Study on the Improvement of Pork Quality for Export 2. Objective and Significance A. Objective 1) Improve quality of the pork for export Until now, Animal husbandry ln Korea has concentrated only on the productivity increase. But the improved national income has affected to the dietary level of the people to consider the health and over fat by consuming the high calorie food, so after all, favor for the animal food which has low cholesterol and low fat is increasing and also there is the tendency to pursue the good taste than to think it as only the protein and calories source in Japan and advanced western countries which are the biggest pork import market. Now, it is the time to improve the quality of the pork for export and also to adopt it to the domestic pork market not to be too late. 2) Evaluate the quality of the pork by countries Make the index for the domestic produced pork and set the direction for the improvement by comparing the quality of other countries pork such as America, Canada, Taiwan and Japan. 3) Quality comparison of the pork by breeds - 6 -

8 Make the base of the quality improvement by comparing and evaluating the meat quality of the domestic dominated pork breed. 4) Quality evaluation by sending out pork weight Domestic slaughtering weight of the pork is 90kg, which shows big difference from 110kg of the Japan. So we have to set the breeding skill guide by comparison and evaluating the change of the meat quality and taste difference through breeding until 110kg. 5) Evaluation of the sensory characteristics due to the storage and distribution Observe and measure the meat quality change during the storage and distribution period and develop the suitable packaging method. 6) Develop the indirect taste measure method for raw pork Develop the indirect taste measure for raw pork using the near-infrared(nir) spectrometry to give quick and good information of the meat taste to the customers. 7) Device the feed for good taste pork Make new feed formulation which can satisfy the functionality and taste. 3. contents and scope of research and development A. First year - 7 -

9 1) Survey data and collect information a) Survey data about pork import-export countries such as Japan, Taiwan, America, Canada and so on. 2) Quality comparison evaluation between domestic and foreign produced pork. a) Pork comparison test among the Korea produced, Taiwan, Japan, Canada, America produced. - General composition analysis, microorganism, TBA, VBN, meat color, ph, the rate of drip and sensory test 3) Quality compare test by pig breed a) Meat quality evaluation test between low-fat pork and high-fat pork General composition, meat color, ph, the rate of drip, sensory test 4) Pork quality evaluation by sending out weight a) Quality evaluation test between 90kg standard pork, 110kg export pork General composition, meat color, ph, the rate of drip, raw meat sensory test Sensory evaluation 5) Develop the indirect taste measure method using NIR Spectra a) Reveal the different taste composition factor between breed by sending out weight. b) Collect the NIR Spectra data for the taste evaluation by weight, breed, fatty acid rate

10 6) Effect of fat content rate of feed, fatty acid composition to the taste of meat a) Mix usage of Animal fat(tallow, fish oil) and plant oil(safflower, olive, perilla, flaxseed) b) Fat feed level 6%, 8% c) Fatty acid composition rate : omega 3, omega 6, omega 9 omega 3 : omega 6 : omega 9 = 1 : 1 : 1 omega 3 : omega 6 : omega 9 = 1 : 2 : 1 omega 3 : omega 6 : omega 9 = 1 : 3 : 1 B. Second year 1) Quality comparison evaluation between domestic and foreign produced pork a) General composition analysis, TBA, VBN, meat color, ph, meat drip rate, sensory test 2) Quality comparison test among the breeds a) Analysis of low-fat pork and high-fat pork and consider the mid-fat pork meat quality evaluation 3) Sensory characteristics evaluation by storage distribution a) By storage temperature(-1.5, 4, 10 ), by storage term( 3 days, 7 days, 10 days, 14 days), sensory test after cooking storage pork 4) Develop indirect taste measure method using NIR Spectra - 9 -

11 a) Survey the relationship between taste factor and sensory test b) Collect NIR Spectra data to evaluate the taste composition factor by weight, breed, fatty acid rate. 5) Effect of fat content of feed and fatty acid composition to the taste of meat a) Fatty acid feed level is fixed to 8% due to the first year result b) Fatty acid composition omega 3 : omega 6 : omega 9 = 1 : 1.5 : 2 omega 3 : omega 6 : omega 9 = 1 : 2 : 3 omega 3 : omega 6 : omega 9 = 1 : 1 : 1 omega 3 : omega 6 : omega 9 = 1 : 2 : 1 omega 3 : omega 6 : omega 9 = 1 : 3 : 1 C. Third year 1) International market data survey a) Survey the data : demand-supply, price, quarantine, customs of Japan, Taiwan, Denmark. 2) Sensory evaluation according to the storage distribution a) Sensory evaluation by storage-temperature, package material, storage term 3) Develop of indirect taste measure method using NIR Spectra a) Reveal the different taste composition by sending out weight, storage temperature, breed

12 b) Survey the relationship between NIR Spectra and taste related factor c) Review the possibility of quick pork taste distinguish method 4) Optimize analysis to improve pork taste a) Establish the pork taste optimum condition through data statistic analysis Analysis data of domestic & foreign pork Comparison data by pork breed Comparison data by pork weight Storage distribution data Indirect taste measure method data using NIR Spectra Fatty acid content of feed and fatty acid composition rate data 4. Result of the research and application suggestion A. Quality comparison evaluation between domestic and foreign produced pork The loin and ham parts of domestic and foreign countries such as Canada, USA, Taiwan and Japan were collected and analyzed on the item of VBN, TBA, meat color, moisture, crude protein, crude fat, ash content, comparition of fatty acid, sensory evaluation and microorganisms. The results of these experiment was that the Canadian and Japanese pork were identified good in aroma, flavor, tenderness and juiciness respectively. B. Quality compare test by swine breeds The Landrace-Yorkshire-Duroc cross bred(lyd), Landrace-Yorkshire(LY) and Duroc-Hampshire(DH) cross bred were tested in the loin parts of the pork meat. The LYD cross bred were evaluated best among the breeds in all the items of

13 palatability, tenderness, juiciness and taste. These results are to be applicated in the mass production of the pigs which suitable to export purpose and domestic demand. C. Pork quality evaluation by sending out weight 1) The pig weight of 110kg is ideal for the purpose of export. Fatty acid content is the lowest in the level of kg and highest in the level of kg live weight. 2) 3 fatty acid content was 0.44% in the level of kg body weight and became twice than other 2 levels. In the level of kg, the 6 fatty acid content was the lowest as below 10% and 9 fatty acid content was increased as the body weight increased. 3) Aroma factor by live weights were increased as the weight gained and flavor, tenderness and juiciness were high points as the weight were decreased. This result is to be expected to encourage the producers to raise the pigs to the weight of 110kg that is ideal weight to export to Japan and give the opportunity of more stable production and additive production effect to the packer at the same time. D. Sensory characteristics evaluation by storage and distribution Observed and measured the meat quality changes during the storage and distribution period and developed the suitable packaging method Cryo-vac film packaging was most stable as the TBA value was (mg malonaldegyde/kg meat) during the storages. E. Develop indirect taste measure method using NIR Spectra Collected NIR Spectra data to evaluate the taste composition factor by

14 weight, breed and fatty acid rate. The method to evaluate the taste of pork indirectly and non-destructive way were studied and pursued the possibility of the method by the slicing the meat into small portions. F. Effect of fat content rate of feed, fatty acid composition to the taste of meat Fat content level is fixed 8% due to the first year result and fatty acid composition rate of 3: 6: 9=1:2:1 caused the target diet. It is possible to contribute to the pork industry by establishing the omega fatty acid rate which is the best factor to improve the taste of pork because single stomach animal like pig has tendency to just accumulate consumed fatty acid in the body. Using this research result, improve the pork quality of the traditional pork such as Jeju black pig to make export product

15 CONTENTS Chapter 1. Introduction. Introduction 1. Effect of grain source to meat taste 2. Effect of protein source to meat taste 3. Effect of dietary fat source to meat taste 4. Effect of trace mineral to meat taste Chapter 2. Materials and Methods. First year 1. Experimental breeds and fattening design 2. Arrangement of diets composition 3. Sampling method. Second year 1. Feed mixture design 2. Experimental breeds and fattening design. Sensory characteristics evaluation by storage distribution 1. Package and storage. Analysis 1. General composition 2. VBN 3. TBA 4. ph 5. Meat color 6. Meat extracts 7. microorganism 8. Sensory evaluation 9. Statistical analysis. NIR spectrometry

16 1. Material 2. Method Chapter 3. Result and Discussion. Survey on the pork market by countries 1. Introduction 2. Japan 3. Taiwan 4. USA 5. Canada 6. Denmark 7. Chilled meat trade 8. Conclusion. Quality comparison evaluation between domestic and foreign produced pork 1. Domestic 2. Foreign. Quality comparison test among breeds 1. First year 2. Second year. Quality comparison test by marketable pork weight 1. General composition 2. Physical and chemical characteristics 3. Fatty acid 4. Microorganism 5. Sensory evaluation. Sensory characteristics evaluation by storage and distribution 1. Sensory evaluation by temperature 2. Sensory evaluation by package method. Develop indirect taste measure method using NIR Spectra 1. Introduction

17 2. Results and discussion 3. Conclusion. Effect of fat content and fatty acid composition of diet to the taste of pork 1. First year 2. Second year. Summary Reference

18 VBN 3. TBA 4. ph

19 5. NIR NIR Spectra

20

21 1 1. IMF,,.. 498,349 (1997 ). Table , %, 29.1%, 27.4%, 10.8% 9.5% 95.. Table 1. ( ) (t) 262, ,672 93,722 30,918 12,556 19, , (%) (t) 266, , ,519 39,211 34,663 52, , (%) (t) 47, , ,830 53,641 47,402 90, , (%)

22 80% WTO 90kg 110kg. 110kg 90kg.,. 110kg 110kg. 90kg 110kg.. 1..,,, 6: 3 1:1 3:1 ( 1990 ) : 6 :

23 NIR %, 38%, 35%, 14% (Table 2). Table 2. ( 90kg ) : (%) (92.9) (92.3) (90.0) (91.0) (89) 121 (100) 14 (119) 104 (86) 79 (65) 75 (62),. 70 kg 1,350 (C & F ) 25%, L/C,,,,,,,, 2, %..,

24 .. 1kg 4, , 1,799.. ( ),.. Table 2,,. 23%..,, 12.3kg(25% ) 37kg(75%).,,,,,,. 3,..,

25 .,,. 90kg 110kg.,,,....,,.,.,,..,,,,.,., 1), 2), 3)

26 , 4), 5). 11.2% 16.3%, 12, 16, 20%.,. 1. Table 3. Panel Type No. 1. : S 6-2. : T Inten 3. : T 6 Desir 4. : : : 6 Desir 5. 0, 20, 40, 60 Desir 80% triticale 6. 0, 50, 100% E 10 Inten 100% S = selected panel, T = trained panel, E = experienced panel Inten = flavor intensity, Desir = flavor desirability,

27 ,,,,.,. 2. Table 4. Panel Type No Desir 2. - E 6 Inten 9% % 3. E 14 Inten 4. - E 6 Accep lentil 0-40% 20% 5. Accep 31%, 6. (0, 3, 6, 9%) C 7 Desir 7. E 11 Desir (3, 7% ) E = experienced panel and C = consumer panel. Desir = flavor desirability ; Iten = flavor intensity Accep = flavor acceptability. No significant difference...,,,,,

28 . 9% 5%. 5%,, 2. 31%. 3..,, % 33.3%, 26% 19.4%, 11.9% 9.4%, %. EPA(Eicosa- pentaenoic acid), DPA(Docosapentaenoic acid), DHA(Docosahexaenoic acid),..,,,. 10%( ), 20%( ), 30%( )

29 %, 6.2% 18.3%, 8.6% 3.5%, %. 4. Cu 250ppm : , Cu. CuSO4.5H2O 0.05% 0.08%, - 100ppm. Table 5. (Organoleptic Properties) Sensory evaluation aroma flavor juiciness tenderness instron A B C D * : (1991 ) WTO

30 ,.,. 10,,.,,

31 kg, 2 50:50 70kg 110kg Basal Diet NRC Control Diet Formula Table 6, 7. Table 8 6% 3: 6: 9 1:1:1(A ), 1:2:1(B ), 1:3:1(C ) 8% 3: 6: 9 1:1:1(D ), 1:2:1(E ), 1:3:1(F ) Formula Table

32 Table 6. basal diet control diet Ingredients % Basal diet Control diet corn(usa),gr soybean-dehull(k75) wheat-aus, GR W. M. R.(LOC) cane molasses-bp sbom-46%, et all T.C.P limestone-# Y/G-LOC(AV15max) salt-proc(fine) L-lysine-HCl-98% (94)Minemix DL-methionine-50% (94)Vitamix choline-cl(60%) virginiamycin-2% pig crave-extra Table 7. basal diet control diet Composition, % Basal diet Control diet Moisture Crude Protein Crude Fat Crude Fiber Crude Ash Selerium, mg/kg Vitamin E, mg/kg N. Energy, cal/g

33 Table 8. Fatty acids % Flaxseed Perilla Safflower oil Tallow Basal diet Control diet SFA1) PUFA2) PUFA3) MUFA4) ) Saturated fatty acid 2) 4) 3, 6-Polyunsaturated fatty acid, 9-Monounsaturated fatty acid Table 9 A F Table 10, 11. Table 9. Ingredient% Experimental diet1) A B C D E F Basal diet Flaxseed Perilla Safflower Tallow ) A; Fat content 6% 3: 6: 9-UFA = 1 : 1 : 1 B; Fat content 6% 3: 6: 9-UFA = 1 : 2 : 1 C; Fat content 6% 3: 6: 9-UFA = 1 : 3 : 1 D; Fat Content 8% 3: 6: 9-UFA = 1 : 1 : 1 E; Fat Content 8% 3: 6: 9-UFA = 1 : 2 : 1 F; Fat Content 8% 3: 6: 9-UFA = 1 : 3 :

34 Table 10. Experimental diet1) Crude fat content, % A B C D E F Control ) The Same as Table 9 Table 11. Fatty Experimental diet7) acids % A B C D E F C12:0-1) C14: C16: C16: C18: C18: C18: C18: Total SFA2) PUFA3) PUFA4) MUFA5) ) Trace(0.001% ) 2) Saturated fatty acid 3) 5) 3, 6-Polyunsaturated fatty acid, 9-Monounsaturated fatty acid 6) The Same as Table

35 110kg 4 chilling, % (1997) 3 6, 3 polyunsaturated fatty acid(pufa) (8%) basal diet 5 (Flaxseed, Olive oil, Perilla, Safflower oil, Tallow) NRC basal diet Table 12. Basal diet, 4% 15%, ME 3400kcal 8% 3: 6: 9. Table 13. 8% 3: 6: 9 1:1.5:2(A ), 1:2:3(B ), 1:1:1(C ), 1:2:1(D ), 1:3:1(E ) Table 13 (liquid Folch (1957) ) Table 3. 3, Miller (1967) Dean (1969)

36 . Table 12. basal diets Ingredients (%) Corn Wheat mill SBM Animal fat 1.16 Molasses 4.00 Corn carrier 3.00 Limstone 0.35 Defl, phos 31/ Salt 0.30 Cho. chl 60% 0.01 V-M 0.20 L-Lysine 0.14 Lipid source 4.00 Total ME C. Protein Lys 0.73 Ca 0.76 P 0.56 Table 13. Fatty acids(%) Flaxseed Olive oil SFA Perilla Safflower oil Tallow Basal diet Control diet PUFA PUFA MUFA

37 Table 14 A F, Table 15, Vertical feed mixer. Table 14. Experimental Ingredient(%) diet1) Basal Diet Flaxseed Perilla Safflower Olive Tallow oil oil A B C D E F ) A ; Fat content 8% & 3: 6: 9-UFA= 1 : 1.5 : 2 B ; Fat content 8% & 3: 6: 9-UFA = 1 : 2 : 3 C ; Fat content 8% & 3: 6: 9-UFA = 1 : 1 : 1 D ; Fat content 8% & 3: 6: 9-UFA = 1 : 2 : 1 E ; Fat content 8% & 3: 6: 9-UFA = 1 : 3 : 1 F ; (Control) Fat content 8% Table 15. Experimental diet1) Crude fat content (%) A B C D E F 1) The same as table

38 Table 16. Fatty Experimental diet5) acids (%) A B C D E F C12: C14: C15: C16: C16: C18: C18: C18: C18: Total SFA1) PUFA2) PUFA3) MUFA4) ) Saturated fatty acid. 2),3) 3, 6-Polyunsaturated fatty acid. 4) 9-Monounsaturated fatty acid. 5)The same as Table kg - - (Landrace Yorkshire Large White) pen / 6/

39 3. 1. (, ) 40 PE film Cryo-Vac film, Cryo-Vac film film , 4, 10, AOAC (1984) Micro Kjeldahl, ( ) Soxhlet, 105 oven, muffle furnace. 2. VBN (1983) conway. 10g 70 blending 100 volumetric flask conway 0.01N boric acid 1 conway reagent 50 (0.066% methyl red : bromocresol green/etoh = 1:1). vacuum grease Potassium carbonate(k2co3 50g / D.W. 100ml)

40 0.01N sulfuric acid. VBN mg %(mg/100g sample)= (a-b) x f x 0.01 x /S x 100 x 100 S: sample wt. a: sample ml b: blank ml f: H2SO4factor 3. TBA 2g 3.86% perchloric acid 18ml BHT 50 homogenization 2ml TBA (TBA 2.883g in 1L D.W.) 2ml 15-17h. 531nm. TBA (mg of maloaldehyde / 100g of meat) = 9.01 x Abs. 4. ph 10g 100ml homogenizer ph. 5. (Color Difference Meter, Yasuda, 600IU, Japan) Hunter scale L, a, b, E {(89.2-L1)2+(0.921-a1)2+(0.783-b1)2}1/2 (L', a', b' )

41 (%) = A - ( B + C ) A - C 100 A : (g) B : (g) C : (g) 7. 1 CFU/cm2. 1g 9ml homogenization, Pouring method. plate count agar 37 incubator 48, plate count agar 25 incubator 48. anaerobic jar (Gaspak 150, Becton Dickinson Microbiology System, USA) Lamond(1977) (triangle test) (descriptive analysis with scaling test)... (triangle test)

42 . 1 8 slight, moderate, much, extreme 1, 2, 3, (descriptive analysis with scaling),,,, 9 point hedonic scale. 9. SAS program, Duncan' Range Test 5%. 5. NIR 1. NIR ice box. 2. NIR system(model 6500, NIR Systems, Inc, USA) Remote Reflectance

43 module( nm) spectrum. software Near-infrared spectral analysis(nasa, NIR System co. USA). NIR spectrum

44 , %.,,, (29.1%), (27.4%), (10.8%), (9.5%), (9.4%) , %, 34.9% 1. 10,094 ( 33.2%) HACCP(Hazard Analysis Critical Point : ).,,.,,. 69.7%, 33.4% 12.9%. ( )

45 ., (risk factor;, ). (Hornstein, 1961; Thrall, 1971; Waldam, 1968). Ford (1975, 1976), Skelley (1975). Myer (1992) Shackelfold (1990) oleic acid( 9). Sim(1994) 3 6 1: :8 9 3 (Lee, 1994) :10 (Sohn, 1997). Chait (1974) Vessby (1980) 3 3/ 6 (Abeywardena, 1987). 3: 6:

46 Table 18. (1997) ( : t) 1 4,166 11,383-2,687 4,504 2, , ,460-4,762 9,393 24,739 34, ,884 3, , , ,221-1,432 10,491 9,218 19, ,281 10, , , ,748 13,475 23, , ,189 8,565 3,478 1,219 3, , ,483 10,815 31,164 41, ,730 10,328 3,857 2,074 3, , ,648 13,486 20,802 34, ,633 6,557 1,910 1,329 1, ,513 8,673 9,313 17, ,842-53,780 8,018 10,587 1,477 9,047 1,094 12, ,437 10, , , ,084 8,275 7,831 1,264 5,227 1,310 3, ,695 10,952 58,735 69, ,306 7,798 3,939 1,709 4,412 1,256 3, ,461 10,873 36,735 47, ,573 9,822 3,751 2,065 2,426 1,348 2, ,166 13,560 23,912 37, ,025 7,047 5,156 1,448 2,973 1,010 3, ,200 9,617 22,607 32, ,753 7,690 4,071 1,517 3,041 1,048 3, ,150 10,607 20,070 30,677 12,331 34, ,647 88,898 47,932 15,167 38,474 9,477 37,925 2,753 87, , , , % 29.1% 27.4% 10.8% 9.5% 18.2% 100% /kg 4.3% % ( 46%), (93%)

47 % 22%, 20% , ,000 89,000 44% Table 19. (1995) ( : t) 1 4,849 11, ,925 3,447 1, , ,236 8,695 25,629 34, ,595 11, ,881 4,025 1, , ,213 10,104 26,628 36, ,581 14, ,261 5,843 1, , ,579 14,093 26,962 41, ,433 15, ,323 6,286 2, ,, 2, ,601 14,385 34,366 48, ,221 18, ,437 6,211 2, , ,779 14,099 37,209 51, ,320 14, ,304 6,085 1, , ,253 14,098 28,183 42, ,364 15, ,315 6,208 2, , ,745 15,203 43,264 58, ,412 14, ,764 8,785 2, , ,257 18,048 35,110 53, ,287 14, ,632 7,341 3, , ,346 15,349 31,029 46, ,018 16, ,359 4,966 2, , ,629 33,561 47, ,747 17, ,403 5,301 3, , , ,404 11,734 39,546 51, ,830 11, ,697 4,224 1, , ,356 12,662 25,428 38,090 85, , ,301 68,672 25,050 4,480 26,438 2,833 9, , , , , % 23.6% 17.1% 5.6% 2.3% 3.6% 100%

48 Table 20. (1996) ( : t) 1 3,482 8, ,490 1, ,, , ,463 13,252 21, ,361 10, , , ,800 14,281 25, ,524 5, , , ,999 8,749 19, ,891 33,240-32,555 9,108 17, , , ,695 19, , , ,445 14, ,106 9,406 12, , , ,859 19,273 74,754 74, ,373 37, ,381 6,831 19, , ,701-17,420 16, , , ,585 10, ,260 6,64 2, , , ,234 15,609 25,172 40, ,041 4, ,734 2, ,750-1,817 15,835 12,614 28, ,096 7, ,305 2, , ,467 14,737 28, ,285 16, ,950 3, , ,499-2,322 15,406 26,350 41, ,208 12, ,634 1, , , ,064 11,863 19,537 31, ,392 24,181-1,959 5,366 1, ,121 1, ,230 11,605 31,948 43,553 80, , ,646 76,961 64,558 7,232 31,979 4,334 30, , , , , % 18.2% 21.7% 6.0% 5.3% 8.0% 100% , , , ,

49 (25%) 95 30,918, 96 39,211, 97 53, , 2 ( 96 ) 80%.,,,,,,, ,672, ,710, , , 7-8, %, 330%, 97 62% Table 1 9.5%, 20% 9,477,, HACCP , 6,

50 9, ,,,. 4,.. 2.,,, Table 21. IJ 24.09%. SJ,

51 Table 21. (%) (%) (%) (%) DD SJ DS IJ Table 22 VBN, TBA, IJ. ph IJ. Table 22. (0 ) VBN TBA ph (mg%) (mg/kg meat) ( E) DD SJ DS IJ Table

52 . DD SJ. Table 23 DD SJ DS IJ % % ,,,,. SJ DD, SJ, SJ SJ. Table 24. DD 921) SJ DS IJ ) 10 scale, panel(n=17)

53 2.,,,,,... 70%.,, 75% drip.. Table 25. (%) (%) (%) (%) VBN TBA. ph drip

54 Table 26. (0 ) VBN TBA drip ph (mg%) (mg/kg meat) ( E) (%) , 6. Table 27. % % Table 28,,

55 Table 28. (CFU/cm2) (CFU/cm2) (CFU/cm2) Table 29.. Table , -,

56 . Table 30. DH, LY, LYD LYD DH. LYD %.. Table 30. (%) (%) (%) (%) LY LYD DH Table 31. VBN, ph TBA LY. LY LYD DH. Drip LYD DH LYD 20% Drip. Table 31. (0 ) LY LYD DH VBN TBA drip ph (mg%) (mg/kg meat) ( E) (%) LYD, 6,

57 . Table 32. % % DH LY LYD LYD 2 10 LY DH LYD 1/10. Table 33. (CFU/cm2) (CFU/cm2) (CFU/cm2) LY DH LYD Table LYD 2 LY DH aroma,,. aroma LY DH LYD

58 Table 34. LY DH LYD (LYD) - 1 (LY), - 1 (DH) Table 35. LYD 71.46%, LY 70.24%, (P>0.05). LY 23.41%, DH 22.57%. LY 5.21%, LYD 4.08%. (P>0.05)., LYD, LY DH. Table 35. LY LYD DH (%) (%) (%) (%)

59 . Table 36. ph (P 0.05), LYD ph. (Drip) LYD,. TBA LY, (P 0.01). DH, LYD TBA DH, LYD ph LY. LYD, DH 3, LYD. LY. (P=0.051). Table 36. LY LYD DH ph* b a a Drip(%) TBA** b a a L Color a b *: P 0.05, **: P 0.01 a,b Means SD with the same row within no common superscripts differ significantly.. Table LY, DH, LY, DH. 3 LYD

60 . Table 37. (CFU/ ) (CFU/ ) (CFU/ ) LY LYD DH Table 38. LY-DH, (Slight).., DH-LY, LY-LYD LYD, LYD-DH. Table 38. Combination Degree of Difference1) Acceptibility DH-LY 1.3 3:3 LY-LYD 0.9 1:4 LYD-DH 1.0 2:2 1) Slight = 1, Moderate = 2, Much = 3, Extreme = 4 Table 39. Table 39. 1) LY LYD DH ) 0 = none, 5 = moderate, 10 = extreme

61 LY LYD DH.,, 3 (LYD) 2 1,,,,, (P>0.05). LYD, LYD Table kg 73.94% , kg 71% kg kg.. Table 40. (%) (%) (%) (%) Table 41. VBN. TBA, ph, drip kg 11.17% 45-78%

62 Table 41. (0 ) VBN TBA drip ph (mg%) (mg/kg meat) ( E) (%) Table kg (46.6%). Table 42. % % kg 0.44% kg 10%, Table

63 Table (CFU/cm2) (CFU/cm2) (CFU/cm2) Table 44. Triangle test , kg kg acceptability kg. Table 44. ( Triangle test) Degree of difference Acceptability : N.S1) : ) 9 : : N.S 1) Not Significant 2) slight;1, moderate;2, much;3, extreme;4 Descriptive analysis Table 45. aroma flavor

64 Table 45. (Descriptive analysis with scaling) ) ) 10 scale, panel(n=12) mean 5. (-1.5, 4, 10 ),. 1.. Table 46. VBN 14 VBN. TBA 4. ph ph

65 Table 46. VBN (mg%) TBA (mg/kg ph meat) L a b a 5.48dm abm bcl bc dm bl bcn d cb cn al abc ab abc cn en a al al bn cn cm c bc d dl a al elm 5.70cm bm b ab cm a em b a al a 5.74bl b abm m bm b al cm ab bc cn al m dl bn abl a bl dn abc bm bm bc m lm al am abcl a,b,c,d,e, (P<0.05). l,m,n, (P<0.05).. Table

66 Table 47. % % Table ( ) (CFU/cm2) (CFU/cm2) Table 49. 1,,

67 . 3, Table VBN Fig. 1 VBN. VBN. 10 > 4 > -1.5 VBN, 20 Cryo-Vac film PE film VBN 23 Cryo-Vac film VBN. VBN 5-10 mg%, -1.5 PE film mg% 10mg% Cryo-Vac

68 film mg%. 4 PE film 3, Cryo-Vac film mg% mg%(PE film) 10.39mg%(Cryo-Vac film) 10mg% Cryo-Vac film 16 10mg% mg%. Figure 1. VBN. TBA Fig. 2 TBA. PE TBA

69 Cryo-Vac film TBA (mg malonaldehyde/kg meat). Cryo-Vac film TBA., PE film 10 TBA TBA 0.2(mg malonaldehyde/kg meat) (mg malonaldehyde/kg meat), (mg malonaldehyde/kg meat) 0.2(mg malonaldehyde/kg meat). Figure 2. TBA. ph Table 50 ph

70 . ph ,, -1.5 PE film , Cryo-Vac film , 4 PE film , Cryo-Vac film PE film Cryo-Vac film ph. Table 50. ph ( ) PE Cryo-Vac PE Cryo-Vac PE Cryo-Vac Table 51, 52, 53, 54 (L value), (a value), ( b value), Total color difference ( E) PE film, Total color difference( E)., -1.5 PE film 6,, Total color difference( E) , 7.99, Cryo-Vac film

71 , , Total color difference( E) 3. 4 PE film 9, 16. Total color difference( E). Cryo-Vac film 16, Total color difference( E). Table 51. L PE -1.5 Cryo-Vac PE 4 PE 10 ( ) Cryo-Vac Cryo-Vac PE film , Total color difference Cryo-Vac film

72 8.81. Total color difference. Table 52. a PE -1.5 Cryo-Vac PE 4 PE 10 ( ) Cryo-Vac Cryo-Vac Table 53. b PE -1.5 Cryo-Vac PE 4 PE 10 ( ) Cryo-Vac Cryo-Vac Table 54. E

73 -1.5 PE Cryo-Vac PE Cryo-Vac PE Cryo-Vac ( ) Table 55. Table 55. ( :%) ( ) PE Cryo-Vac PE Cryo-Vac PE Cryo-Vac PE film % 15.50% %. Cryo-Vac film PE film, Cryo-Vac film, 10 PE film %, 6.33%,

74 7.70%, 7.13%. Cryo-Vac film %.. 1) Fig. 3. Figure < 4 < 10, Cryo-Vac film

75 PE film (CFU/ ), (CFU/ ). 4 PE film 20, Cryo-Vac film (CFU/ ) (CFU/ ). 2) Fig. 4. Figure < 4 < 10,

76 Cryo-Vac film PE film. 10 PE film (CFU/ ), Cryo-Vac film 9. 4 PE film 9, Cryo-Vac film (CFU/ ) , Table 56, 57. 1,, (p<0.05), Cryo-Vac film, PE film., (p<0.01), PE film Cryo-Vac film 4 PE film. 3 (p=0.015), 10 Cryo-Vac film., PE film 10 Cryo-Vac film. 6 (p<0.05), 10 PE film, -1.5 Cryo-Vac film. (p<0.01), -1.5 Cryo-Vac film. 9 (p<0.01). 4 Cryo-Vac film 10 PE film

77 , 10 PE film.. Table 56. ( )1) PE Cryo-Vac PE 10 Cryo-Vac PE Cryo-Vac ( ) ab bc a bc b b a a a abc a c c b b b ab c a ab c b ab a a ab a bc c b a a a a b abc a a a a b abc a a ab b ab ab ) n=11, (p<0.05)

78 Table 57. ( )1) PE Cryo-Vac PE Cryo-Vac PE 10 Cryo-Vac ( ) a ab b ab a a a a a c b bc a bc b abc b bc b c a ab ab bc ) n=11, (p<0.01)

79 6. NIR spectra Norris(1962, 1964),, NIR spectrophotometer (NIRS : ) Norris (Bengera Norris ; 1968a, 1968b, Butler Norris ; 1960) (U.S.D.A.) Norris. NIR Europe,,, juice. North America.,,,, grains,,,,,,, fast food USSR, Asia.,,,,,,. New zealand, (Williams Norris, 1987) NIR.,

80 O-H, N-H, C-H ( Chemometrics ) (Combination band : m) 1 (1st Overtone : m) 2 (2nd Overtone : m). (UV-VIS).,,. NIR region visible mid IR nm nm. NIR C-H, O-H, N-H S-H. NIR. (C-H), (O-H) (N-H, S-H) (Robertson, 1989). Giese(1993) NIR on-line. NIR m (electromagnetic),, Polesello Giangiacomo (1985) 1.94 m methanol. NIR reflectance 80% Anon.(1973). Norris (1976) NIR 2 equation Table.. Y = K0+K1{d2(log 1/R R.nm1)}/(d.nm12) K9{d2(log 1/R R.nm9)}/(d.nm92) Rxj= nm K0j K9j= coefficients

81 . NIR NIR system Hildrum (1994) NIR (NIR) nm (NIT) nm. NIR hardness tenderness (multiple correlation coefficient ; R) NIR. (1981) m R , R Kruggel (1981) Martens (1981) NIR,, R , , , NIR. Beck (1991) NIR bull heifer (Intramuscular fat ; IMF) (L-value). R 0.99, (SEP) 0.28, R 0.90, (SEP) 0.9. minolta value R 0.93, 1.0, NIR, (marbling). Conway(1984). deuterium oxide dilution (r = 0.94), skinfold(r = 0.90), ultrasound(r = 0.89) NIR r = 0.91, band 930nm NIR

82 . Stwatland Dattson(1984) optical 650nm ATP. Nagao (1985),, NIR 1208nm, 1230nm, 1726nm 1738nm, r = 0.990, (SEC) 0.88%, r = 0.994, SEC 1.10%, r = 0.976, SEC 1.78%. NIR cut-meat. Mitsumoto (1991) spectra nm fiber spectra nm ph,,,, hydroxyproline,, NIR spectra 2 mode R = , R = , R = , R = R = spectra R = 0.946, fiber R = Lanza(1983),, NIR R paste. Ben-Gera Norris(1986) NIR ( nm) mode. Anderson (1993) NIR, MQM(Meat Quality Marbling) pistol, R 0.80, 0.2% nm, R 0.93, NIR NIR. (1990)

83 capsaicin capsanthin, capsaicin capsanthin SEP NIR 1.76%, 0.43% (, 1991). NIR (1994) NIR (1994) NIR. Ryu (1994) flour extrudate NIR R SEP 0.84% 0.307% extrudate,. (1994) NIR. 2.. NIR. Fig. 5 NIR nm. 1100nm visible NIR. Fig nm, 1100nm, 1200nm, 1400nm, 1740nm 1910nm peak O-H band

84 Figure 5. Raw spectra of pork using reflectance mode by NIR at 400nm nm(n=80)

85 Figure 6. Second derivative spectra of pork using reflectance mode by NIR at 400nm nm(n=80) Table 58. Wavelengths selected and statistical summary of fat content of pork using reflectance mode by NIR Wavelengths(nm) R SEC(%)1) / /2160/ /2160/1876/ ) SEC ; Standard error of the calibration(n=80)

86 NIR calibration Table nm, 2160nm, 1876nm 2304nm 4 (R) (SEC) 0.607%. Fat content = X X X X4 (X1-X4: 1212nm, 2160nm, 1876nm 2304nm ). 2 calibration scatter diagram Fig. 7. Calibration 1.0% %. Figure 7. Scatter diagram for estimation of fat content of pork using reflectance mode by NIR at 400nm nm(n=80)

87 Table 59 calibration equation NIR 1.721%. 5.5% 0.5% 78%. Table Comparison of fat content between chemical with NIR analysis of pork samples for calibration equation Sample name C. A. % NIR % Difference S S S LYD LYD LYD DH DH DH C C

88 Table (Continue) Sample name C. A. % NIR % Difference C C C Average

89 Table 60 NIR 2096nm, 596nm, 952nm 2184nm 4 (R) (SEC) 0.737%. Table 60. Wavelengths selected and statistical summary of protein content of pork using reflectance mode by NIR Wavelengths(nm) R SEC(%)1) / /596/ /596/952/ ) SEC ; Standard error of the calibration(n=80) Protein content = X X X X4 (X1-X4: 2096nm, 596nm, 952nm 2184nm ). NIR calibration equation (R) ,9045 NIR. Fig. 8 calibration scatter diagram. Table 61 calibration equation NIR 2.407%. 90% 1% 10% 1%

90 Figure 8. Scatter diagram for estimation of protein content of pork using reflectance mode by NIR at 400nm nm(n=80)

91 Table Comparison of protein content between chemical with NIR analysis of pork samples for calibration equation Sample name C. A. % NIR % Difference S S S LYD LYD LYD DH DH DH C C

92 Table (Continue) Sample name C. A. % NIR % Difference C C C Average