Luận án Xác định độ tuổi thu hoạch và ứng dụng kỹ thuật chân không trong bảo quản và chế biến cà chua bi đen (Solanum lycopersicum cv. OG)

Nội dung text: Luận án Xác định độ tuổi thu hoạch và ứng dụng kỹ thuật chân không trong bảo quản và chế biến cà chua bi đen (Solanum lycopersicum cv. OG)

1. Parameter Estimate Standard Error Lower Upper k 0,540248 0,00883403 0,522089 0,558407 Analysis of Variance Source Sum of Squares Df Mean Square Model 6,88568 1 6,88568 Residual 0,0161248 26 0,000620186 Total 6,9018 27 Total (Corr.) 2,00365 26 R-Squared = 99,1952 percent b) Chất khô Nonlinear Regression - SDC50 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,244432 0,00223436 0,23984 0,249025 Analysis of Variance Source Sum of Squares Df Mean Square Model 12,1805 1 12,1805 Residual 0,00457805 26 0,000176079 Total 12,1851 27 Total (Corr.) 1,03612 26 R-Squared = 99,5582 percent Nonlinear Regression - S505005 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,338948 0,00414427 0,330429 0,347466 Analysis of Variance Source Sum of Squares Df Mean Square Model 9,83346 1 9,83346 Residual 0,00943798 26 0,000362999 Total 9,8429 27 Total (Corr.) 1,49845 26 R-Squared = 99,3702 percent Nonlinear Regression - S5050010 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,399685 0,00567839 0,388013 0,411357 Analysis of Variance Source Sum of Squares Df Mean Square Model 8,63683 1 8,63683 Residual 0,0129696 26 0,000498832 Total 8,6498 27 Total (Corr.) 1,65767 26 R-Squared = 99,2176 percent Nonlinear Regression - S5050015 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,486832 0,00591004 0,474684 0,498981 Analysis of Variance Source Sum of Squares Df Mean Square pl-78
2. Nonlinear Regression - S5070010 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,674907 0,0161032 0,641806 0,708007 Analysis of Variance Source Sum of Squares Df Mean Square Model 6,30694 1 6,30694 Residual 0,0303615 26 0,00116775 Total 6,3373 27 Total (Corr.) 2,72927 26 R-Squared = 98,8876 percent Nonlinear Regression - S5070015 Function to be estimated: exp(-k*t) Initial parameter estimates: Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,834267 0,0215811 0,789906 0,878628 Analysis of Variance Source Sum of Squares Df Mean Square Model 5,40518 1 5,40518 Residual 0,0303187 26 0,0011661 Total 5,4355 27 Total (Corr.) 2,8408 26 R-Squared = 98,9327 percent Nonlinear Regression - SDC60 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,237237 0,00297167 0,231129 0,243346 Analysis of Variance Source Sum of Squares Df Mean Square Model 12,2892 1 12,2892 Residual 0,00843119 26 0,000324277 Total 12,2976 27 Total (Corr.) 0,955007 26 R-Squared = 99,1172 percent Nonlinear Regression - S605005 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,361972 0,0040353 0,353677 0,370266 Analysis of Variance Source Sum of Squares Df Mean Square Model 9,38406 1 9,38406 Residual 0,00793515 26 0,000305198 Total 9,392 27 Total (Corr.) 1,58347 26 R-Squared = 99,4989 percent Nonlinear Regression - S6050010 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% pl-80
3. Model 6,11798 1 6,11798 Residual 0,0323208 26 0,00124311 Total 6,1503 27 Total (Corr.) 2,70132 26 R-Squared = 98,8035 percent Nonlinear Regression - S607005 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,484829 0,0074647 0,469485 0,500173 Analysis of Variance Source Sum of Squares Df Mean Square Model 7,78497 1 7,78497 Residual 0,0148308 26 0,000570414 Total 7,7998 27 Total (Corr.) 2,15996 26 R-Squared = 99,3134 percent Nonlinear Regression - S6070010 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,631682 0,0150219 0,600804 0,66256 Analysis of Variance Source Sum of Squares Df Mean Square Model 6,53383 1 6,53383 Residual 0,0314729 26 0,0012105 Total 6,5653 27 Total (Corr.) 2,62841 26 R-Squared = 98,8026 percent Nonlinear Regression - S6070015 Function to be estimated: exp(-k*t) Initial parameter estimates: Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,73392 0,0194617 0,693916 0,773924 Analysis of Variance Source Sum of Squares Df Mean Square Model 5,89039 1 5,89039 Residual 0,0353065 26 0,00135794 Total 5,9257 27 Total (Corr.) 2,78407 26 R-Squared = 98,7318 percent Nonlinear Regression - SDC70 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,212558 0,00224313 0,207947 0,217168 Analysis of Variance Source Sum of Squares Df Mean Square Model 13,1633 1 13,1633 Residual 0,00552423 26 0,00021247 Total 13,1688 27 Total (Corr.) 0,846667 26 pl-82
4. Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,487049 0,00642524 0,473841 0,500256 Analysis of Variance Source Sum of Squares Df Mean Square Model 7,73453 1 7,73453 Residual 0,0108744 26 0,000418246 Total 7,7454 27 Total (Corr.) 2,14207 26 R-Squared = 99,4923 percent Nonlinear Regression - S7060015 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,573461 0,00793739 0,557145 0,589776 Analysis of Variance Source Sum of Squares Df Mean Square Model 6,83596 1 6,83596 Residual 0,0112411 26 0,000432352 Total 6,8472 27 Total (Corr.) 2,3167 26 R-Squared = 99,5148 percent Nonlinear Regression - S707005 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,414908 0,00391943 0,406852 0,422965 Analysis of Variance Source Sum of Squares Df Mean Square Model 8,59467 1 8,59467 Residual 0,00572743 26 0,000220286 Total 8,6004 27 Total (Corr.) 1,83039 26 R-Squared = 99,6871 percent Nonlinear Regression - S7070010 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,539224 0,00717035 0,524485 0,553963 Analysis of Variance Source Sum of Squares Df Mean Square Model 7,23213 1 7,23213 Residual 0,0106674 26 0,000410286 Total 7,2428 27 Total (Corr.) 2,31052 26 R-Squared = 99,5383 percent Nonlinear Regression - S7070015 Function to be estimated: exp(-k*t) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper pl-84
5. AB -0,000015 AC -0,000625 BB -0,0000940585 BC -0,0003875 CC -0,0243155 Optimize Desirability Optimum value = 0,996979 Factor Low High Optimum Nong do saccharose 51,591 68,409 59,3775 Do chan khong 515,91 684,09 627,216 Thoi gian 6,63641 13,3636 11,6062 Response Optimum Luong am mat di 28,6021 Luong chat ran tang 2,94332 So sánh ANOVA Table for Anthocyanin mat by Mau Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 0,0522667 1 0,0522667 8,62 0,0426 Within groups 0,0242667 4 0,00606667 Total (Corr.) 0,0765333 5 Multiple Range Tests for Anthocyanin mat by Mau Method: 95,0 percent LSD Mau Count Mean Homogeneous Groups Doi chung 3 9,79 X Toi uu 3 14,01 X ANOVA Table for Lycopene mat by Mau Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 0,00375 1 0,00375 5,77 0,0742 Within groups 0,0026 4 0,00065 Total (Corr.) 0,00635 5 Multiple Range Tests for Lycopene mat by Mau Method: 95,0 percent LSD Mau Count Mean Homogeneous Groups Toi uu 3 1,04 X Doi chung 3 1,09 X ANOVA Table for Vitamin C mat by Mau Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 189,506 1 189,506 210,97 0,0001 Within groups 3,593 4 0,89825 Total (Corr.) 193,099 5 Multiple Range Tests for Vitamin C mat by Mau Method: 95,0 percent LSD Mau Count Mean Homogeneous Groups Doi chung 3 25,01 X Toi uu 3 36,25 X ANOVA Table for Phenolic mat by Mau Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 73,2901 1 73,2901 533,21 0,0000 Within groups 0,5498 4 0,13745 Total (Corr.) 73,84 5 Multiple Range Tests for Phenolic mat by Mau Method: 95,0 percent LSD Mau Count Mean Homogeneous Groups Doi chung 3 15,85 X Toi uu 3 22,84 X ANOVA Table for Anthocyanin say by Mau Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 5,7624 1 5,7624 45,00 0,0026 pl-86
6. MAE 0,00785515 MAPE 5,11983 ME -0,00121983 MPE -3,29732 Nonlinear Regression - MR50 Function to be estimated: exp(-k*t50) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,133357 0,00245955 0,128382 0,138332 Analysis of Variance Source Sum of Squares Df Mean Square Model 25,3718 1 25,3718 Residual 0,133782 119 0,00112422 Total 25,5056 120 Total (Corr.) 9,94255 119 R-Squared = 98,6544 percent Residual Analysis Estimation Validation n 120 MSE 0,00114344 MAE 0,0293929 MAPE 23,5826 ME -0,00192073 MPE -18,6648 Nonlinear Regression - MR60 Function to be estimated: exp(-k*t60) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,196619 0,00574414 0,184736 0,208501 Analysis of Variance Source Sum of Squares Df Mean Square Model 17,6676 1 17,6676 Residual 0,12497 71 0,00176015 Total 17,7926 72 Total (Corr.) 6,18436 71 R-Squared = 97,9793 percent Residual Analysis Estimation Validation n 72 MSE 0,00181116 MAE 0,0365359 MAPE 27,1551 ME -0,00143566 MPE -21,0183 Nonlinear Regression - MR70 Function to be estimated: exp(-k*t70) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,29111 0,00759476 0,275009 0,30721 Analysis of Variance Source Sum of Squares Df Mean Square Model 12,1907 1 12,1907 Residual 0,0479386 50 0,000958771 Total 12,2386 51 Total (Corr.) 4,27873 50 R-Squared = 98,8796 percent pl-88
7. n 1,26063 0,0283394 1,2017 1,31957 Analysis of Variance Source Sum of Squares Df Mean Square Model 14,7706 2 7,38529 Residual 0,0220228 67 0,000328699 Total 14,7926 69 Total (Corr.) 5,06314 68 R-Squared = 99,565 percent Residual Analysis Estimation Validation n 69 MSE 0,000349569 MAE 0,0153333 MAPE 9,79577 ME -0,00510025 MPE -7,07715 Nonlinear Regression - MR70 Function to be estimated: exp(-k*(t70^n)) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,235893 0,0120559 0,210036 0,261751 n 1,15699 0,0360182 1,07974 1,23424 Analysis of Variance Source Sum of Squares Df Mean Square Model 9,21942 2 4,60971 Residual 0,0191838 46 0,000417039 Total 9,23861 48 Total (Corr.) 3,11227 47 R-Squared = 99,3836 percent Residual Analysis Estimation Validation n 48 MSE 0,000456758 MAE 0,0174042 MAPE 12,8782 ME -0,00470307 MPE -9,23968 Page điều chỉnh Nonlinear Regression - MR40 Function to be estimated: exp(-((k*t40)^n)) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper k 0,0889021 0,000410413 0,0880836 0,0897207 n 1,02549 0,00783745 1,00986 1,04112 Analysis of Variance Source Sum of Squares Df Mean Square Model 35,4115 2 17,7057 Residual 0,0228472 214 0,000106762 Total 35,4343 216 Total (Corr.) 15,0718 215 R-Squared = 99,8484 percent Residual Analysis Estimation Validation n 216 MSE 0,000108796 MAE 0,00746364 MAPE 3,95415 ME -0,00105237 pl-90
8. R-Squared = 98,4393 percent Residual Analysis Estimation Validation n 72 MSE 0,00146246 MAE 0,032084 MAPE 23,2559 ME -0,00710495 MPE -18,3659 Nonlinear Regression - MR70 Function to be estimated: a*exp(-k*t70) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper a 1,03008 0,0210555 0,985197 1,07495 k 0,3003 0,00999381 0,278999 0,321602 Analysis of Variance Source Sum of Squares Df Mean Square Model 12,1966 2 6,09832 Residual 0,0419673 49 0,000856476 Total 12,2386 51 Total (Corr.) 4,27873 50 R-Squared = 99,0192 percent Residual Analysis Estimation Validation n 17 MSE 0,000932607 MAE 0,0247211 MAPE 20,5509 ME -0,0056889 MPE -16,2301 Logarit Nonlinear Regression - MR40 Function to be estimated: a*exp(-k*t40)+c Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper a 1,01294 0,00462777 1,00371 1,02217 k 0,085476 0,00118556 0,0831108 0,0878411 c -0,0168593 0,00436611 -0,0255695 -0,00814915 Analysis of Variance Source Sum of Squares Df Mean Square Model 35,4132 3 11,8044 Residual 0,0211234 213 0,0000991707 Total 35,4343 216 Total (Corr.) 15,0718 215 R-Squared = 99,8598 percent Residual Analysis Estimation Validation n 216 MSE 0,000102045 MAE 0,0076424 MAPE 5,20761 ME -1,12053E-7 MPE 0,417442 Nonlinear Regression - MR50 Function to be estimated: a*exp(-k*t50)+c Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval pl-92
9. MSE 0,0000517153 MAE 0,00489798 MAPE 2,4449 ME -4,13607E-8 MPE 0,271354 Hai tham số Nonlinear Regression - MR40 Function to be estimated: a*exp(-k0*t40)+b*exp(-k1*t40) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper a 0,502164 0,00463784 0,492909 0,511419 k0 0,0897583 0,00122546 0,0873129 0,0922037 b 0,502166 9,28401E-8 0,502166 0,502166 k1 0,0896222 0,000104842 0,089413 0,0898314 Analysis of Variance Source Sum of Squares Df Mean Square Model 35,4083 4 8,85208 Residual 0,025994 212 0,000122613 Total 35,4343 216 Total (Corr.) 15,0718 215 R-Squared = 99,8275 percent Residual Analysis Estimation Validation n 216 MSE 0,00012742 MAE 0,00773585 MAPE 4,86199 ME -0,0014015 MPE -3,01699 Nonlinear Regression - MR50 Dependent variable: MR50 Function to be estimated: a*exp(-ko*t50)+b*exp(-k1*t50) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper a 0,52833 0,0148925 0,498126 0,558533 ko 0,140992 0,0060734 0,128674 0,153309 b 0,52833 -1,#IND -1,#IND -1,#IND k1 0,140992 -1,#IND -1,#IND -1,#IND Analysis of Variance Source Sum of Squares Df Mean Square Model 25,412 4 6,353 Residual 0,0935703 116 0,00080664 Total 25,5056 120 Total (Corr.) 9,94255 119 R-Squared = 99,0589 percent Residual Analysis Estimation Validation n 120 MSE 0,000866392 MAE 0,0251133 MAPE 19,7293 ME -0,0061891 MPE -15,4534 Nonlinear Regression - MR60 Function to be estimated: a*exp(-ko*t60)+b*exp(-k1*t60) Estimation Results Asymptotic 95,0% pl-94
10. Residual Analysis Estimation Validation n 216 MSE 0,000156078 MAE 0,00978079 MAPE 6,68939 ME -0,00177381 MPE -4,9749 Nonlinear Regression - MR60 Function to be estimated: a*exp(-k*t60)+(1-a)*exp(-k*a*t60) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper a 0,998497 1474,05 -3056,0 3058,0 k 0,196401 2,09183 -4,14179 4,53459 Analysis of Variance Source Sum of Squares Df Mean Square Model 17,6676 2 8,83381 Residual 0,12498 70 0,00178543 Total 17,7926 72 Total (Corr.) 6,18436 71 R-Squared = 97,9791 percent Residual Analysis Estimation Validation n 24 MSE 0,00189364 MAE 0,0365251 MAPE 27,2663 ME -0,00175129 MPE -21,1958 Nonlinear Regression - MR70 Function to be estimated: a*exp(-k*t70)+(1-a)*exp(-k*a*t70) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper a 0,9747 37,0928 -78,0869 80,0363 k 0,291408 0,632802 -1,05738 1,6402 Analysis of Variance Source Sum of Squares Df Mean Square Model 12,1907 2 6,09533 Residual 0,0479425 49 0,000978419 Total 12,2386 51 Total (Corr.) 4,27873 50 R-Squared = 98,8795 percent Residual Analysis Estimation Validation n 51 MSE 0,00106539 MAE 0,0260443 MAPE 22,4619 ME -0,00252017 MPE -17,6148 Henderson và Pabis điều chỉnh Nonlinear Regression - MR40 Function to be estimated: a*exp(-k*t40)+(1-a)*exp(-k*b*t40) Estimation Results Asymptotic 95,0% Asymptotic Confidence Interval Parameter Estimate Standard Error Lower Upper a 1,15761 0,918442 -0,674639 2,98985 pl-96
11. ME 0,000356381 MPE 1,59326 D.3.3.2 Các chỉ tiêu vật lý Analysis of Variance for aw - Type III Sums of Squares Source Sum of Squares Df Mean Square F-Ratio P-Value MAIN EFFECTS A:Nhiet do say 0,000191407 3 0,0000638025 0,73 0,5400 B:Do am dung 0,264306 3 0,0881019 1012,19 0,0000 INTERACTIONS AB 0,000700237 9 0,0000778042 0,89 0,5416 RESIDUAL 0,00278532 32 0,0000870412 TOTAL (CORRECTED) 0,267983 47 Multiple Range Tests for aw by Nhiet do say Method: 95,0 percent LSD Nhiet do say Count LS Mean LS Sigma Homogeneous Groups 50 12 0,60575 0,00269322 X 60 12 0,606225 0,00269322 X 40 12 0,607925 0,00269322 X 70 12 0,61085 0,00269322 X Multiple Range Tests for aw by Do am dung Method: 95,0 percent LSD Do am dung Count LS Mean LS Sigma Homogeneous Groups 20 12 0,50345 0,00269322 X 25 12 0,578675 0,00269322 X 30 12 0,647475 0,00269322 X 35 12 0,70115 0,00269322 X ANOVA Table for aw by Nhiet do say Do am dung Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 0,265197 15 0,0176798 203,12 0,0000 Within groups 0,00278532 32 0,0000870413 Total (Corr.) 0,267983 47 Multiple Range Tests for aw by Nhiet do say Do am dung Method: 95,0 percent LSD Level Count Mean Homogeneous Groups 50-20 3 0,4961 X 40-20 3 0,5048 X 70-20 3 0,5057 X 60-20 3 0,5072 X 60-25 3 0,5744 X 40-25 3 0,5758 X 50-25 3 0,5797 X 70-25 3 0,5848 X 70-30 3 0,6446 X 60-30 3 0,6451 X 40-30 3 0,6473 X 50-30 3 0,6529 X 50-35 3 0,6943 X 60-35 3 0,6982 X 40-35 3 0,7038 X 70-35 3 0,7083 X ANOVA Table for L by Nhiet do say Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 14,649 3 4,883 23,50 0,0003 Within groups 1,66207 8 0,207758 Total (Corr.) 16,3111 11 Multiple Range Tests for L by Nhiet do say Method: 95,0 percent LSD Nhiet do say Count Mean Homogeneous Groups 40 3 20,5633 X 50 3 22,0433 X 70 3 23,1333 X 60 3 23,3533 X pl-98
12. ANOVA Table for IC50 by Nhiet do say Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 0,029192 3 0,00973067 10,40 0,0039 Within groups 0,00748867 8 0,000936083 Total (Corr.) 0,0366807 11 Multiple Range Tests for IC50 by Nhiet do say Method: 95,0 percent LSD Nhiet do say Count Mean Homogeneous Groups 70 3 0,581667 X 60 3 0,595667 XX 50 3 0,644333 X 40 3 0,707667 X D.3.3.4 Tính chất cảm quan của sản phẩm ANOVA Table for Mau sac by Nhiet do say Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 13,8 3 4,6 22,80 0,0000 Within groups 23,4 116 0,201724 Total (Corr.) 37,2 119 Multiple Range Tests for Mau sac by Nhiet do say Method: 95,0 percent LSD Nhiet do say Count Mean Homogeneous Groups 40 30 3,8 X 50 30 4,2 X 60 30 4,5 X 70 30 4,7 X ANOVA Table for Mui ca chua by Nhiet do say Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 6,0 3 2,0 7,44 0,0001 Within groups 31,2 116 0,268966 Total (Corr.) 37,2 119 Multiple Range Tests for Mui ca chua by Nhiet do say Method: 95,0 percent LSD Nhiet do say Count Mean Homogeneous Groups 40 30 3,9 X 50 30 4,1 XX 70 30 4,3 XX 60 30 4,5 X ANOVA Table for Mui la by Nhiet do say Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 0,825 3 0,275 4,25 0,0069 Within groups 7,5 116 0,0646552 Total (Corr.) 8,325 119 Multiple Range Tests for Mui la by Nhiet do say Method: 95,0 percent LSD Nhiet do say Count Mean Homogeneous Groups 40 30 4,8 X 50 30 4,9 XX 60 30 5,0 X 70 30 5,0 X ANOVA Table for Cau truc by Nhiet do say Source Sum of Squares Df Mean Square F-Ratio P-Value Between groups 14,625 3 4,875 21,18 0,0000 Within groups 26,7 116 0,230172 Total (Corr.) 41,325 119 Multiple Range Tests for Cau truc by Nhiet do say Method: 95,0 percent LSD Nhiet do say Count Mean Homogeneous Groups 40 30 3,7 X 70 30 4,0 X 50 30 4,4 X 60 30 4,6 X pl-100