{"text_format":"3","workbook":"xls","n_sheets":8,"sheets":["Preliminary exp","bioactive ing","Design","TPC","TFC","DPPH","ABTS","FRAP"],"not_rendered":{"images":20,"external_links":1,"defined_names":2},"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"Preliminary exp","index":0,"n_rows":35,"n_cols":13,"rows_kept":35,"merged":[[0,0,0,12],[10,0,13,0],[15,0,18,0],[20,0,23,0]],"flags":["formulas_cached_only"]}
["Ultrasound-aided extraction of bioactive ingredients from Vitis vinifera seeds using optimized conditions of Central Composite Design of RSM, ANFIS modeling, and Machine Learning algorithm\nSelvaraj Kunjiappan1*, Lokesh Kumar Ramasamy2, Suthendran Kannan3, Parasuraman Pavadai4, Panneerselvam Theivendren5, Ponnusamy Palanisamy6*"]
["Supplementary file S1 Dataset:  Preliminary studies and RSM outputs"]
[]
["Particle size","x1",0.5,1,0.155396,1.3446,0.75,{"$nulls":4},"y1","TPC"]
["Solvent conc.","x2",60,70,53.1079,76.8921,65,{"$nulls":4},"y2","TFC"]
["Time","x3",18,28,11.1079,34.8921,23,{"$nulls":4},"y3","DPPH"]
["Temp","x4",35,45,28.1079,51.8921,40,{"$nulls":4},"y4","ABTS"]
["Ultrasound intensity","x5",65,75,58.1079,81.8921,70,{"$nulls":4},"y5","FRAP"]
[]
[null,"Ethanol","Methanol","Chloroform","Pet.ether","Ethyl acetate","Diethyl ether","Acetone","n-hexane"]
["TPC",546.23,556.72,470.34,524.93,516.68,525.35,504.23,470.64]
[null,541.28,543.56,478.34,522.82,520.21,530.36,506.23,471.46]
[null,542.56,545.28,475.49,522.94,518.13,529.34,502.15,474.58]
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[]
["TFC",348.36,357.48,302.4,337.51,317.19,338.23,307.23,305.21]
[null,351.26,353.32,300.33,336.32,324.36,340.42,308.08,303.12]
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[]
["DPPH",64.27,65.23,53.45,59.18,55.37,60.32,51.34,52.64]
[null,66.35,67.49,52.12,57.65,56.34,60.04,52.32,50.53]
[null,65.41,69.12,54.45,58.45,55.56,58.23,53.47,51.52]
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[]
[]
[null,"solvents (70%)","TPC","TFC","DPPH"]
[null,"Ethanol",543.36,348.64,65.34]
[null,"Methanol",548.52,354.28,67.28]
[null,"Chloroform",474.72,301.43,53.34]
[null,"Petroleum ether",523.56,335.72,58.43]
[null,"Ethyl acetate",518.34,321.26,55.76]
[null,"Diethyl ether",528.35,338.39,59.53]
[null,"Acetone",504.2,307.32,52.38]
[null,"n-hexane",472.23,303.85,51.56]

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[14,0.5,60,28,45,65,660.12,422.6,63.45,59.93,55.52,629.26,401.58,66.5018,62.4334,57.4315,631.0909,393.1082,74.6341,68.0186,63.6557,660,423,63.5,59.9,55.6]
[15,1,70,18,35,75,414.56,299.39,52.02,48.93,43.78,408.63,284.88,55.7823,51.6174,47.2766,417.9316,301.0248,61.5467,57.9771,53.3769,415,299,52,48.9,43.8]
[16,1,60,28,35,75,398.76,286.48,51.72,46.67,41.37,420.15,291.17,56.3909,52.7922,47.5628,643.5346,411.6351,76.8394,71.119,66.3026,399,286,51.7,46.7,41.4]
[17,0.5,70,28,35,65,656.45,412.92,77.54,73.85,68.67,619.4,400.83,75.9034,72.016,67.1724,572.6794,346.9023,66.0459,62.8244,57.7028,656,413,77.5,73.9,68.7]
[18,0.75,65,23,51.8921,70,556.34,366.45,69.6,65.73,61.32,553.18,366.19,69.8901,65.5421,60.5589,572.6794,346.9023,66.0459,62.8244,57.7028,556,366,69.6,65.7,56.1]
[19,0.75,65,23,40,70,482.67,325.67,72.74,68.63,63.65,483.67,324.5,72.2783,67.2176,62.8535,643.5346,411.6351,76.8394,71.119,66.3026,484,325,72.5,67.5,63.1]
[20,0.75,65,34.8921,40,70,536.32,367.34,69.43,65.91,61.27,559.71,360,66.6376,63.0916,58.0642,631.0909,393.1082,74.6341,68.0186,63.6557,536,367,69.4,65.9,61.3]
[21,1,60,18,45,75,404.45,278.31,56.71,51.76,46.64,447.98,309.3,62.2043,58.1401,53.0184,643.5346,411.6351,76.8394,71.119,66.3026,404,278,56.7,51.8,46.6]
[22,1,60,28,45,65,395.67,264.37,53.56,47.62,42.27,403.45,277.84,54.119,49.77,44.7156,572.6794,346.9023,66.0459,62.8244,57.7028,396,264,53.6,47.7,42.3]
[23,0.75,65,23,40,70,481.36,326.54,74.75,70.74,64.18,483.67,324.5,72.2783,67.2176,62.8535,631.0909,393.1082,74.6341,68.0186,63.6557,484,325,72.5,67.5,63.1]
[24,0.5,70,28,45,65,654.34,432.64,78.56,74.74,70.46,626.1,412.88,72.9875,69.2702,64.9614,643.5346,411.6351,76.8394,71.119,66.3026,654,433,78.6,74.7,70.5]
[25,1,70,28,35,65,422.53,293.08,58.93,53.41,48.45,419.15,276.39,57.4707,52.175,47.5415,417.9316,301.0248,61.5467,57.9771,53.3769,423,293,58.9,53.4,48.4]
[26,0.75,65,23,40,81.8921,602.37,399.45,73.72,69.86,65.78,573.3,379.18,69.715,65.0983,60.8989,572.6794,346.9023,66.0459,62.8244,57.7028,602,399,73.7,69.9,65.8]
[27,0.75,65,11.1079,40,70,574.32,348.52,68.56,65.82,60.43,544.66,349.29,68.6027,64.8763,60.0365,631.0909,393.1082,74.6341,68.0186,63.6557,574,349,68.6,65.8,60.4]
[28,0.75,65,23,40,70,484.65,324.07,71.85,64.74,59.78,483.67,324.5,72.2783,67.2176,62.8535,631.0909,393.1082,74.6341,68.0186,63.6557,484,325,72.5,67.5,63.1]
[29,0.5,70,18,35,75,562.12,371.74,73.54,67.84,63.28,575.57,376.85,70.9012,66.4411,61.6703,631.0909,393.1082,74.6341,68.0186,63.6557,562,372,73.5,67.8,63.3]
[30,0.75,65,23,40,70,485.34,325.94,69.93,65.34,62.54,483.67,324.5,72.2783,67.2176,62.8535,572.6794,346.9023,66.0459,62.8244,57.7028,484,325,72.5,67.5,63.1]
[31,0.5,60,28,35,75,660.12,418.6,79.45,74.93,70.52,624.86,406.96,76.26,71.9907,67.2137,631.0909,393.1082,74.6341,68.0186,63.6557,660,419,79.4,74.9,70.5]
[32,0.5,70,18,45,65,641.32,401.83,75.34,73.32,68.56,627.62,405.62,76.03,72.9339,68.3681,643.5346,411.6351,76.8394,71.119,66.3026,641,402,75.3,73.3,68.6]
[33,0.5,70,28,35,75,633.35,401.162,72.23,70.89,66.28,616.9,406.52,77.16,74.0374,69.1936,631.0909,393.1082,74.6341,68.0186,63.6557,633,401,72.2,70.9,66.3]
[34,1,70,28,45,65,421.65,274.92,55.63,51.62,47.31,437.91,299.48,60.36,55.5055,51.1317,631.0909,393.1082,74.6341,68.0186,63.6557,422,275,55.6,51.6,47.3]
[35,0.5,60,18,35,65,636.45,392.43,74.98,67.56,63.45,660.13,403.42,78.5,72.9217,67.963,643.5346,411.6351,76.8394,71.119,66.3026,636,392,75,67.6,63.5]
[36,0.75,53.1079,23,40,70,586.05,348.65,64.76,61.43,56.34,540.82,345.43,62.22,57.8826,52.8674,572.6794,346.9023,66.0459,62.8244,57.7028,586,349,64.8,61.4,56.3]
[37,1,70,18,35,65,418.9,268.06,53.78,48.04,44.36,427.11,291.69,58.33,53.7638,50.0133,643.5346,411.6351,76.8394,71.119,66.3026,419,268,53.8,48,44.4]
[38,0.75,65,23,40,70,485.76,323.54,75.89,70.05,66.88,483.67,324.5,72.28,67.2176,62.8535,643.5346,411.6351,76.8394,71.119,66.3026,484,325,72.5,67.5,63.1]
[39,0.5,70,28,45,75,645.34,404.72,77.84,69.42,65.24,666.48,431.18,80.95,76.4179,72.4288,631.0909,393.1082,74.6341,68.0186,63.6557,645,405,77.8,69.4,65.2]
[40,1,70,28,35,75,423.76,278.43,55.58,51.56,46.65,449.81,301.07,57.05,53.74,48.429,417.9316,301.0248,61.5467,57.9771,53.3769,424,278,55.6,51.6,46.7]
[41,0.75,65,23,40,70,483.72,324.65,72.86,66.83,62.41,483.67,324.5,72.28,67.22,62.8535,417.9316,301.0248,61.5467,57.9771,53.3769,484,325,72.5,67.5,63.1]
[42,0.5,60,18,45,75,638.34,401.61,76.45,69.49,65.56,630.09,391.51,75.03,68.95,64.1643,572.6794,346.9023,66.0459,62.8244,57.7028,638,402,76.4,69.5,65.6]
[43,1.3446,65,23,40,70,360.76,243.17,50.51,45.76,41.07,286.35,221.78,46.18,41.73,36.4822,643.5346,411.6351,76.8394,71.119,66.3026,361,243,50.5,45.8,41.1]
[44,0.75,65,23,40,58.1079,534.63,345.92,66.76,62.56,58.26,557.44,359.62,68.01,63.56,59.5416,643.5346,411.6351,76.8394,71.119,66.3026,535,346,66.8,62.6,58.3]
[45,0.75,65,23,40,70,485.65,325.73,71.03,68.45,64.07,483.67,324.5,72.28,67.22,62.8535,572.6794,346.9023,66.0459,62.8244,57.7028,484,325,72.5,67.5,63.1]
[46,0.75,65,23,40,70,484.38,324.23,70.98,65.43,61.68,483.67,324.5,72.28,67.22,62.8535,417.9316,301.0248,61.5467,57.9771,53.3769,484,325,72.5,67.5,63.1]
[47,1,60,28,35,65,396.06,256.34,54.76,50.56,45.56,522.2,334.46,67.52,62.47,57.3348,631.0909,393.1082,74.6341,68.0186,63.6557,396,256,54.8,50.6,45.6]
[48,1,60,18,35,75,380.76,268.04,52.56,47.58,43.34,497.88,332.57,65.7,60.41,55.7677,417.9316,301.0248,61.5467,57.9771,53.3769,381,268,52.6,47.6,43.3]
[49,0.5,60,28,45,75,642.82,402.63,73.67,69.67,65.34,650.8,415.85,74.23,69.04,64.9726,643.5346,411.6351,76.8394,71.119,66.3026,643,403,73.7,69.7,65.3]
[50,0.5,60,28,35,65,636.42,393.95,74.76,68.72,63.34,646.2,405.29,75.24,70.51,65.1188,631.0909,393.1082,74.6341,68.0186,63.6557,636,394,74.8,68.7,63.3]
[]
["Verificationn experiments"]
[51,0.25,65,23,40,70,667.67,445.65,78.95,75.65,70.04,695.15,441.62,82.41,77.2256,72.3434,666.868599999999,449.6304,79.5741999999999,75.6553999999999,70.2825999999999,717,471,85.6,81.3,75.7]
[52,0.155,62.5,23,40,70,672.45,454.65,81.89,77.85,71.52,752.64,469.42,82.22,76.72,71.52,669.693799999999,455.1127,81.1799000000001,76.9274,71.1410000000001,632,426,76.5,72.8,67.3]
[53,0.155,67.5,23,40,70,670.13,448.76,79.05,76.45,70.43,732.76,467.24,83.24,78.544,73.5081,668.339999999999,451.3952,79.5148000000001,76.1020999999999,70.4899,634,427,76.8,73.3,67.8]
[54,0.155,65,23,40,67.5,658.65,463.34,80.34,73.78,70.37,751.71,472.56,82.26,77.4991,72.2171,662.4408,458.401899999999,80.1078,74.7083999999999,70.4172999999999,635,427,76.7,73.1,67.6]
[55,0.155,65,23,40,72.5,659.67,462.34,81.32,74.71,70.24,735.34,465.39,83.61,78.0947,73.176,663.284799999998,458.121899999999,80.8525999999999,75.3916,70.3932999999999,632,426,76.7,73,67.5]

{"sheet":"TPC","index":3,"n_rows":78,"n_cols":7,"rows_kept":78,"flags":["formulas_cached_only"]}
["ANOVA for Quadratic model"]
[]
["Response 1: TPC"]
[]
["Source","Sum of Squares","df","Mean Square","F-value","p-value"]
["Model",{"v":439900,"d":"4.40E+05"},20,21993.66,18.49,"< 0.0001","significant"]
["A-Particle size",{"v":395800,"d":"3.96E+05"},1,{"v":395800,"d":"3.96E+05"},332.8,"< 0.0001"]
["B-Methanol conc.",270.07,1,270.07,0.2271,0.6373]
["C-Time",440.06,1,440.06,0.37,0.5477]
["D-Temp",6447.81,1,6447.81,5.42,0.0271]
["E-ultrasound intensity",489.66,1,489.66,0.4118,0.5261]
["AB",2830.15,1,2830.15,2.38,0.1337]
["AC",222.29,1,222.29,0.1869,0.6687]
["AD",290.77,1,290.77,0.2445,0.6247]
["AE",2198.84,1,2198.84,1.85,0.1844]
["BC",545,1,545,0.4583,0.5038]
["BD",1117.46,1,1117.46,0.9397,0.3404]
["BE",710.46,1,710.46,0.5974,0.4458]
["CD",33.74,1,33.74,0.0284,0.8674]
["CE",3002.74,1,3002.74,2.53,0.1229]
["DE",3677.82,1,3677.82,3.09,0.0892]
["A²",1430.88,1,1430.88,1.2,0.2817]
["B²",6893.43,1,6893.43,5.8,0.0226]
["C²",8144.72,1,8144.72,6.85,0.0139]
["D²",2849.08,1,2849.08,2.4,0.1325]
["E²",11581.28,1,11581.28,9.74,0.0041]
["Residual",34486.8,29,1189.2]
["Lack of Fit",34470.09,22,1566.82,656.48,"< 0.0001","significant"]
["Pure Error",16.71,7,2.39]
["Cor Total",{"v":474400,"d":"4.74E+05"},49]
[]
["Factor coding is Coded."]
["Sum of squares is Type III - Partial"]
[]
["The Model F-value of 18.49 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise."]
[]
["P-values less than 0.0500 indicate model terms are significant. In this case A, D, B², C², E² are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model."]
[]
["The Lack of Fit F-value of 656.48 implies the Lack of Fit is significant. There is only a 0.01% chance that a Lack of Fit F-value this large could occur due to noise. Significant lack of fit is bad -- we want the model to fit."]
[]
["Fit Statistics"]
[]
["Std. Dev.",34.48,null,"R²",0.9273]
["Mean",526.91,null,"Adjusted R²",0.8772]
["C.V. %",6.54,null,"Predicted R²",0.693]
[{"$nulls":3},"Adeq Precision",20.3457]
[]
["The Predicted R² of 0.6930 is in reasonable agreement with the Adjusted R² of 0.8772; i.e. the difference is less than 0.2."]
[]
["Adeq Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 20.346 indicates an adequate signal. This model can be used to navigate the design space."]
[]
[]
["Final Equation in Terms of Coded Factors"]
[]
["TPC","="]
[483.67]
[-95.59,"A"]
[2.5,"B"]
[3.19,"C"]
[12.2,"D"]
[3.36,"E"]
[9.4,"AB"]
[-2.64,"AC"]
[3.01,"AD"]
[8.29,"AE"]
[4.13,"BC"]
[5.91,"BD"]
[4.71,"BE"]
[-1.03,"CD"]
[9.69,"CE"]
[10.72,"DE"]
[5.07,"A²"]
[11.14,"B²"]
[12.11,"C²"]
[7.16,"D²"]
[14.44,"E²"]
[]
["The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. By default, the high levels of the factors are coded as +1 and the low levels are coded as -1. The coded equation is useful for identifying the relative impact of the factors by comparing the factor coefficients."]

{"sheet":"TFC","index":4,"n_rows":78,"n_cols":7,"rows_kept":78,"flags":["formulas_cached_only"]}
["ANOVA for Quadratic model"]
[]
["Response 2: TFC"]
[]
["Source","Sum of Squares","df","Mean Square","F-value","p-value"]
["Model",{"v":129800,"d":"1.30E+05"},20,6491.91,19.96,"< 0.0001","significant"]
["A-Particle size",{"v":115600,"d":"1.16E+05"},1,{"v":115600,"d":"1.16E+05"},355.45,"< 0.0001"]
["B-Methanol conc.",679.09,1,679.09,2.09,0.1592]
["C-Time",221.21,1,221.21,0.6801,0.4163]
["D-Temp",2763.7,1,2763.7,8.5,0.0068]
["E-ultrasound intensity",737.91,1,737.91,2.27,0.1428]
["AB",213.72,1,213.72,0.657,0.4242]
["AC",1015,1,1015,3.12,0.0878]
["AD",243.55,1,243.55,0.7488,0.394]
["AE",720.84,1,720.84,2.22,0.1474]
["BC",57.46,1,57.46,0.1767,0.6774]
["BD",496.9,1,496.9,1.53,0.2264]
["BE",32.37,1,32.37,0.0995,0.7547]
["CD",0.0021,1,0.0021,{"v":6.395e-06,"d":"6.40E-06"},0.998]
["CE",1006.91,1,1006.91,3.1,0.0891]
["DE",317.76,1,317.76,0.9769,0.3311]
["A²",660.42,1,660.42,2.03,0.1649]
["B²",1594.97,1,1594.97,4.9,0.0348]
["C²",1575.56,1,1575.56,4.84,0.0359]
["D²",894.54,1,894.54,2.75,0.108]
["E²",3497.2,1,3497.2,10.75,0.0027]
["Residual",9432.79,29,325.27]
["Lack of Fit",9424.85,22,428.4,378.08,"< 0.0001","significant"]
["Pure Error",7.93,7,1.13]
["Cor Total",{"v":139300,"d":"1.39E+05"},49]
[]
["Factor coding is Coded."]
["Sum of squares is Type III - Partial"]
[]
["The Model F-value of 19.96 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise."]
[]
["P-values less than 0.0500 indicate model terms are significant. In this case A, D, B², C², E² are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model."]
[]
["The Lack of Fit F-value of 378.08 implies the Lack of Fit is significant. There is only a 0.01% chance that a Lack of Fit F-value this large could occur due to noise. Significant lack of fit is bad -- we want the model to fit."]
[]
["Fit Statistics"]
[]
["Std. Dev.",18.04,null,"R²",0.9323]
["Mean",347.09,null,"Adjusted R²",0.8856]
["C.V. %",5.2,null,"Predicted R²",0.7567]
[{"$nulls":3},"Adeq Precision",21.0265]
[]
["The Predicted R² of 0.7567 is in reasonable agreement with the Adjusted R² of 0.8856; i.e. the difference is less than 0.2."]
[]
["Adeq Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 21.027 indicates an adequate signal. This model can be used to navigate the design space."]
[]
[]
["Final Equation in Terms of Coded Factors"]
[]
["TFC","="]
[324.5]
[-51.66,"A"]
[3.96,"B"]
[2.26,"C"]
[7.99,"D"]
[4.13,"E"]
[2.58,"AB"]
[-5.63,"AC"]
[2.76,"AD"]
[4.75,"AE"]
[1.34,"BC"]
[3.94,"BD"]
[1.01,"BE"]
[0.0081,"CD"]
[5.61,"CE"]
[3.15,"DE"]
[3.45,"A²"]
[5.36,"B²"]
[5.32,"C²"]
[4.01,"D²"]
[7.93,"E²"]
[]
["The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. By default, the high levels of the factors are coded as +1 and the low levels are coded as -1. The coded equation is useful for identifying the relative impact of the factors by comparing the factor coefficients."]

{"sheet":"DPPH","index":5,"n_rows":77,"n_cols":7,"rows_kept":77,"flags":["formulas_cached_only"]}
["ANOVA for Quadratic model"]
[]
["Response 3: DPPH"]
[]
["Source","Sum of Squares","df","Mean Square","F-value","p-value"]
["Model",3314.9,20,165.74,13.73,"< 0.0001","significant"]
["A-Particle size",2645.01,1,2645.01,219.12,"< 0.0001"]
["B-Methanol conc.",33.29,1,33.29,2.76,0.1076]
["C-Time",7.45,1,7.45,0.617,0.4385]
["D-Temp",49.66,1,49.66,4.11,0.0518]
["E-ultrasound intensity",5.49,1,5.49,0.455,0.5053]
["AB",0.1164,1,0.1164,0.0096,0.9224]
["AC",3.06,1,3.06,0.2532,0.6186]
["AD",67.48,1,67.48,5.59,0.025]
["AE",5.64,1,5.64,0.4669,0.4998]
["BC",26.44,1,26.44,2.19,0.1496]
["BD",67.77,1,67.77,5.61,0.0247]
["BE",0.1093,1,0.1093,0.0091,0.9249]
["CD",23.38,1,23.38,1.94,0.1746]
["CE",69.24,1,69.24,5.74,0.0233]
["DE",90.01,1,90.01,7.46,0.0106]
["A²",105.14,1,105.14,8.71,0.0062]
["B²",110.2,1,110.2,9.13,0.0052]
["C²",37.65,1,37.65,3.12,0.0879]
["D²",42.31,1,42.31,3.51,0.0713]
["E²",20.21,1,20.21,1.67,0.2059]
["Residual",350.06,29,12.07]
["Lack of Fit",321.82,22,14.63,3.63,0.0431,"significant"]
["Pure Error",28.24,7,4.03]
["Cor Total",3664.96,49]
[]
["Factor coding is Coded."]
["Sum of squares is Type III - Partial"]
[]
["The Model F-value of 13.73 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise."]
[]
["P-values less than 0.0500 indicate model terms are significant. In this case A, AD, BD, CE, DE, A², B² are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model."]
[]
["The Lack of Fit F-value of 3.63 implies the Lack of Fit is significant. There is only a 4.31% chance that a Lack of Fit F-value this large could occur due to noise. Significant lack of fit is bad -- we want the model to fit."]
[]
["Fit Statistics"]
[]
["Std. Dev.",3.47,null,"R²",0.9045]
["Mean",67.88,null,"Adjusted R²",0.8386]
["C.V. %",5.12,null,"Predicted R²",0.6661]
[{"$nulls":3},"Adeq Precision",16.5091]
[]
["The Predicted R² of 0.6661 is in reasonable agreement with the Adjusted R² of 0.8386; i.e. the difference is less than 0.2."]
[]
["Adeq Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 16.509 indicates an adequate signal. This model can be used to navigate the design space."]
[]
["Final Equation in Terms of Coded Factors"]
[]
["DPPH","="]
[72.28]
[-7.81,"A"]
[0.8766,"B"]
[-0.4147,"C"]
[1.07,"D"]
[0.3561,"E"]
[-0.0603,"AB"]
[-0.3091,"AC"]
[1.45,"AD"]
[-0.4197,"AE"]
[0.9091,"BC"]
[1.46,"BD"]
[0.0584,"BE"]
[-0.8547,"CD"]
[1.47,"CE"]
[1.68,"DE"]
[-1.38,"A²"]
[-1.41,"B²"]
[-0.8231,"C²"]
[-0.8726,"D²"]
[-0.603,"E²"]
[]
["The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. By default, the high levels of the factors are coded as +1 and the low levels are coded as -1. The coded equation is useful for identifying the relative impact of the factors by comparing the factor coefficients."]

{"sheet":"ABTS","index":6,"n_rows":77,"n_cols":7,"rows_kept":77,"flags":["formulas_cached_only"]}
["ANOVA for Quadratic model"]
[]
["Response 4: ABTS"]
[]
["Source","Sum of Squares","df","Mean Square","F-value","p-value"]
["Model",3196.49,20,159.82,9.97,"< 0.0001","significant"]
["A-Particle size",2543.85,1,2543.85,158.7,"< 0.0001"]
["B-Methanol conc.",58.62,1,58.62,3.66,0.0658]
["C-Time",6.13,1,6.13,0.3825,0.5411]
["D-Temp",61.36,1,61.36,3.83,0.0601]
["E-ultrasound intensity",4.51,1,4.51,0.2812,0.6]
["AB",2.43,1,2.43,0.1513,0.7001]
["AC",10.66,1,10.66,0.6651,0.4214]
["AD",73.84,1,73.84,4.61,0.0403]
["AE",0.4209,1,0.4209,0.0263,0.8724]
["BC",19.58,1,19.58,1.22,0.2782]
["BD",56.9,1,56.9,3.55,0.0696]
["BE",0.5913,1,0.5913,0.0369,0.849]
["CD",38.43,1,38.43,2.4,0.1324]
["CE",94.57,1,94.57,5.9,0.0216]
["DE",52.56,1,52.56,3.28,0.0806]
["A²",98.26,1,98.26,6.13,0.0194]
["B²",74.67,1,74.67,4.66,0.0393]
["C²",18.14,1,18.14,1.13,0.2961]
["D²",35.28,1,35.28,2.2,0.1487]
["E²",14.48,1,14.48,0.9032,0.3498]
["Residual",464.86,29,16.03]
["Lack of Fit",428.67,22,19.48,3.77,0.039,"significant"]
["Pure Error",36.19,7,5.17]
["Cor Total",3661.35,49]
[]
["Factor coding is Coded."]
["Sum of squares is Type III - Partial"]
[]
["The Model F-value of 9.97 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise."]
[]
["P-values less than 0.0500 indicate model terms are significant. In this case A, AD, CE, A², B² are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model."]
[]
["The Lack of Fit F-value of 3.77 implies the Lack of Fit is significant. There is only a 3.90% chance that a Lack of Fit F-value this large could occur due to noise. Significant lack of fit is bad -- we want the model to fit."]
[]
["Fit Statistics"]
[]
["Std. Dev.",4,null,"R²",0.873]
["Mean",63.43,null,"Adjusted R²",0.7855]
["C.V. %",6.31,null,"Predicted R²",0.5611]
[{"$nulls":3},"Adeq Precision",14.0496]
[]
["The Predicted R² of 0.5611 is not as close to the Adjusted R² of 0.7855 as one might normally expect; i.e. the difference is more than 0.2. This may indicate a large block effect or a possible problem with your model and/or data. Things to consider are model reduction, response transformation, outliers, etc. All empirical models should be tested by doing confirmation runs."]
[]
["Adeq Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 14.050 indicates an adequate signal. This model can be used to navigate the design space."]
[]
["Final Equation in Terms of Coded Factors"]
[]
["ABTS","="]
[67.22]
[-7.66,"A"]
[1.16,"B"]
[-0.3762,"C"]
[1.19,"D"]
[0.3226,"E"]
[-0.2753,"AB"]
[-0.5772,"AC"]
[1.52,"AD"]
[-0.1147,"AE"]
[0.7822,"BC"]
[1.33,"BD"]
[0.1359,"BE"]
[-1.1,"CD"]
[1.72,"CE"]
[1.28,"DE"]
[-1.33,"A²"]
[-1.16,"B²"]
[-0.5714,"C²"]
[-0.7968,"D²"]
[-0.5104,"E²"]
[]
["The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. By default, the high levels of the factors are coded as +1 and the low levels are coded as -1. The coded equation is useful for identifying the relative impact of the factors by comparing the factor coefficients."]

{"sheet":"FRAP","index":7,"n_rows":77,"n_cols":7,"rows_kept":77,"flags":["formulas_cached_only"]}
["ANOVA for Quadratic model"]
[]
["Response 5: FRAP"]
[]
["Source","Sum of Squares","df","Mean Square","F-value","p-value"]
["Model",3282.89,20,164.14,10.64,"< 0.0001","significant"]
["A-Particle size",2564.2,1,2564.2,166.17,"< 0.0001"]
["B-Methanol conc.",76.61,1,76.61,4.96,0.0338]
["C-Time",7.49,1,7.49,0.4854,0.4915]
["D-Temp",67.35,1,67.35,4.36,0.0456]
["E-ultrasound intensity",3.5,1,3.5,0.2269,0.6374]
["AB",2.48,1,2.48,0.1608,0.6914]
["AC",14.62,1,14.62,0.9475,0.3384]
["AD",67.31,1,67.31,4.36,0.0456]
["AE",2.57,1,2.57,0.1666,0.6862]
["BC",18.93,1,18.93,1.23,0.2772]
["BD",59.98,1,59.98,3.89,0.0583]
["BE",0.0109,1,0.0109,0.0007,0.979]
["CD",26.48,1,26.48,1.72,0.2005]
["CE",106.32,1,106.32,6.89,0.0137]
["DE",59.32,1,59.32,3.84,0.0596]
["A²",120.83,1,120.83,7.83,0.009]
["B²",80.57,1,80.57,5.22,0.0298]
["C²",25.1,1,25.1,1.63,0.2123]
["D²",48.08,1,48.08,3.12,0.0881]
["E²",12.03,1,12.03,0.7794,0.3846]
["Residual",447.5,29,15.43]
["Lack of Fit",416.99,22,18.95,4.35,0.0264,"significant"]
["Pure Error",30.51,7,4.36]
["Cor Total",3730.39,49]
[]
["Factor coding is Coded."]
["Sum of squares is Type III - Partial"]
[]
["The Model F-value of 10.64 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise."]
[]
["P-values less than 0.0500 indicate model terms are significant. In this case A, B, D, AD, CE, A², B² are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model."]
[]
["The Lack of Fit F-value of 4.35 implies the Lack of Fit is significant. There is only a 2.64% chance that a Lack of Fit F-value this large could occur due to noise. Significant lack of fit is bad -- we want the model to fit."]
[]
["Fit Statistics"]
[]
["Std. Dev.",3.93,null,"R²",0.88]
["Mean",58.74,null,"Adjusted R²",0.7973]
["C.V. %",6.69,null,"Predicted R²",0.5789]
[{"$nulls":3},"Adeq Precision",14.3767]
[]
["The Predicted R² of 0.5789 is not as close to the Adjusted R² of 0.7973 as one might normally expect; i.e. the difference is more than 0.2. This may indicate a large block effect or a possible problem with your model and/or data. Things to consider are model reduction, response transformation, outliers, etc. All empirical models should be tested by doing confirmation runs."]
[]
["Adeq Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 14.377 indicates an adequate signal. This model can be used to navigate the design space."]
[]
["Final Equation in Terms of Coded Factors"]
[]
["FRAP","="]
[62.85]
[-7.69,"A"]
[1.33,"B"]
[-0.4159,"C"]
[1.25,"D"]
[0.2843,"E"]
[-0.2784,"AB"]
[-0.6759,"AC"]
[1.45,"AD"]
[-0.2834,"AE"]
[0.7691,"BC"]
[1.37,"BD"]
[-0.0184,"BE"]
[-0.9097,"CD"]
[1.82,"CE"]
[1.36,"DE"]
[-1.47,"A²"]
[-1.2,"B²"]
[-0.672,"C²"]
[-0.9301,"D²"]
[-0.4652,"E²"]
[]
["The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. By default, the high levels of the factors are coded as +1 and the low levels are coded as -1. The coded equation is useful for identifying the relative impact of the factors by comparing the factor coefficients."]