Hoja1_Log_LinearTimeMeasured LOG10(N)Identified LOG10(N)Squared differenceParametersParameter valuesStandard Error1.0010.0010.320.10kmax1.520.07Mean Sum of Squared Error0.06282.009.709.660.00LOG10(N0)10.980.18Root Mean Sum of Squared Error0.25063.009.009.000.00R-Square0.98354.008.608.340.07R-Square adjusted0.98115.007.807.680.014D reduction is reached at6.13units of time6.007.007.020.00Inactivation model identified7.006.506.360.02N= N0 * exp(-kmax * t)8.005.905.700.04For identification purposes reformulated as9.004.605.040.19LOG10(N)=LOG10(N0)-kmax*t/LN(10) Least Sum of Squared Error0.44as can be derived fromW.D. Bigelow and J.R. Esty 1920. The thermal death point in relation to typical thermophylic organisms. Journal of Infectious Diseases, 27, 602

0.0010.981.0910.261.1810.201.2710.141.3610.081.4510.021.549.961.639.901.729.841.819.781.909.721.999.662.089.602.179.552.269.492.359.432.449.372.539.312.629.252.719.192.809.132.899.072.989.013.078.953.168.893.258.833.348.773.438.713.528.653.618.603.708.543.798.483.888.423.978.364.068.304.158.244.248.184.338.124.428.064.518.004.607.944.697.884.787.824.877.764.967.705.057.645.147.595.237.535.327.475.417.415.507.355.597.295.687.235.777.175.867.115.957.056.046.996.136.936.226.876.316.816.406.756.496.696.586.636.676.586.766.526.856.466.946.407.036.347.126.287.216.227.306.167.396.107.486.047.575.987.665.927.755.867.845.807.935.748.025.688.115.638.205.578.295.518.385.458.475.398.565.338.655.278.745.218.835.158.925.09

Hoja1_WeibullTimeMeasured LOG10(N)Identified LOG10(N)Squared differenceParametersParameter valuesStandard Error1.0010.0010.020.00Mean Sum of Squared Error0.02952.009.709.610.01delta2.680.38Root Mean Sum of Squared Error0.17193.009.009.100.01p1.410.15R-Square0.99334.008.608.520.01LOG10(N0)10.270.21R-Square adjusted0.99115.007.807.870.004D reduction is reached at7.21units of time6.007.007.170.03Inactivation model identified7.006.506.420.01N/N0= 10**(-((t/delta)**p))8.005.905.620.08For identification purposes reformulated as9.004.604.780.03LOG10(N)=LOG10(N0)-((t/delta)**p)Least Sum of Squared Error0.18as can be derived fromP. Mafart, O. Couvert, S. Gaillard and I. Leguerinel 2002. On calculating sterility in thermal preservation methods: application of the Weibull frequency distribution model. International Journal of Food Microbiology, 72, 107-113

0.0010.271.099.991.189.951.279.921.369.881.459.851.549.811.639.771.729.731.819.691.909.651.999.612.089.572.179.532.269.482.359.442.449.392.539.352.629.302.719.252.809.212.899.162.989.113.079.063.169.013.258.963.348.913.438.863.528.803.618.753.708.703.798.643.888.593.978.534.068.484.158.424.248.374.338.314.428.254.518.194.608.134.698.084.788.024.877.964.967.905.057.845.147.775.237.715.327.655.417.595.507.535.597.465.687.405.777.335.867.275.957.206.047.146.137.076.227.016.316.946.406.876.496.816.586.746.676.676.766.606.856.536.946.467.036.397.126.327.216.257.306.187.396.117.486.047.575.977.665.907.755.827.845.757.935.688.025.618.115.538.205.468.295.388.385.318.475.238.565.168.655.088.745.018.834.938.924.85

Hoja1_Weibull_FixedTimeMeasured LOG10(N)Identified LOG10(N)Squared differenceParametersParameter valuesStandard Error1.0010.0010.300.09Mean Sum of Squared Error0.06882.009.709.660.00delta1.580.62Root Mean Sum of Squared Error0.26233.009.009.000.00p1.020.19R-Square0.98454.008.608.350.06LOG10(N0)10.930.50R-Square adjusted0.97935.007.807.690.014D reduction is reached at6.22units of time6.007.007.020.00Inactivation model identified7.006.506.360.02N/N0= 10**(-((t/delta)**p))8.005.905.690.04For identification purposes reformulated as9.004.605.020.18LOG10(N)=LOG10(N0)-((t/delta)**p)Least Sum of Squared Error0.41as can be derived fromP. Mafart, O. Couvert, S. Gaillard and I. Leguerinel 2002. On calculating sterility in thermal preservation methods: application of the Weibull frequency distribution model. International Journal of Food Microbiology, 72, 107-113

0.0010.931.0910.241.1810.191.2710.131.3610.071.4510.011.549.951.639.901.729.841.819.781.909.721.999.662.089.602.179.552.269.492.359.432.449.372.539.312.629.252.719.192.809.142.899.082.989.023.078.963.168.903.258.843.348.783.438.723.528.663.618.603.708.553.798.493.888.433.978.374.068.314.158.254.248.194.338.134.428.074.518.014.607.954.697.894.787.834.877.774.967.715.057.655.147.595.237.545.327.485.417.425.507.365.597.305.687.245.777.185.867.125.957.066.047.006.136.946.226.886.316.826.406.766.496.706.586.646.676.586.766.526.856.466.946.407.036.347.126.287.216.227.306.167.396.107.486.047.575.987.665.927.755.867.845.807.935.748.025.688.115.628.205.568.295.508.385.448.475.388.565.328.655.268.745.208.835.148.925.08

Hoja1_Geeraerd_Shoulder_TailTimeMeasured LOG10(N)Identified LOG10(N)Squared differenceParametersParameter valuesStandard Error1.0010.009.970.00Sl (Shoulder length)1.870.58Mean Sum of Squared Error0.04742.009.709.710.00kmax1.660.14Root Mean Sum of Squared Error0.21773.009.009.170.03LOG10(N_res)-0.3258842.45R-Square0.99114.008.608.500.01LOG10(N0)10.050.26R-Square adjusted0.98575.007.807.790.00Log10(Nres) is less than the minimal measured value. Model with tailing is unlikely for these data.4D reduction is reached at7.48units of time6.007.007.070.00Inactivation model identified7.006.506.350.02N= (N0- N_res) * exp(-kmax * t) * ( (exp(kmax * Sl)))/(1+(exp(kmax * Sl) - 1) *exp(-kmax*t)))+N_res8.005.905.630.07For identification purposes reformulated as9.004.604.910.10LOG10(N)= LOG10((10LOG10(N0)- 10LOG10(N_res)) * exp(-kmax * t) * ( (exp(kmax * Sl)))/(1+(exp(kmax * Sl) - 1) *exp(-kmax*t)))+10LOG10(N_res))Least Sum of Squared Error0.24as can be derived fromA.H. Geeraerd, C.H. Herremans and J.F. Van Impe 2000. Structural model requirements to describe microbial inactivation during a mild heat treatment. International Journal of Food Microbiology, 59(3), 185-209

0.0010.051.099.961.189.941.279.931.369.911.459.891.549.861.639.841.729.811.819.781.909.751.999.712.089.672.179.632.269.592.359.552.449.502.539.452.629.402.719.352.809.302.899.242.989.193.079.133.169.073.259.013.348.953.438.893.528.833.618.773.708.713.798.653.888.583.978.524.068.464.158.394.248.334.338.274.428.204.518.144.608.084.698.014.787.954.877.884.967.825.057.755.147.695.237.625.327.565.417.495.507.435.597.375.687.305.777.245.867.175.957.116.047.046.136.986.226.916.316.856.406.786.496.726.586.656.676.596.766.526.856.466.946.397.036.337.126.267.216.207.306.137.396.077.486.007.575.947.665.877.755.817.845.747.935.688.025.628.115.558.205.498.295.428.385.368.475.298.565.238.655.168.745.108.835.038.924.97

Hoja1_Geeraerd_ShoulderTimeMeasured LOG10(N)Identified LOG10(N)Squared differenceParametersParameter valuesStandard Error1.0010.009.970.00Sl (Shoulder length)1.870.48Mean Sum of Squared Error0.03952.009.709.710.00kmax1.660.09Root Mean Sum of Squared Error0.19873.009.009.170.03LOG10(N0)10.050.23R-Square0.99114.008.608.500.01R-Square adjusted0.98815.007.807.790.004D reduction is reached at7.48units of time6.007.007.070.00Inactivation model identified7.006.506.350.02N= N0 * exp(-kmax * t) * ( exp(kmax * Sl))/(1+(exp(kmax * Sl) - 1) *exp(-kmax*t)))8.005.905.630.07For identification purposes reformulated as9.004.604.910.10Log10(N) = Log10(N0) - kmax * t / Ln(10) + Log10(Exp(kmax * Sl) / (1 + (Exp(kmax * Sl) - 1) * Exp(-kmax * t)))Least Sum of Squared Error0.24as can be derived fromA.H. Geeraerd, C.H. Herremans and J.F. Van Impe 2000. Structural model requirements to describe microbial inactivation during a mild heat treatment. International Journal of Food Microbiology, 59(3), 185-209

0.0010.051.099.961.189.941.279.931.369.911.459.891.549.861.639.841.729.811.819.781.909.751.999.712.089.672.179.632.269.592.359.552.449.502.539.452.629.402.719.352.809.302.899.242.989.193.079.133.169.073.259.013.348.953.438.893.528.833.618.773.708.713.798.653.888.583.978.524.068.464.158.394.248.334.338.274.428.204.518.144.608.084.698.014.787.954.877.884.967.825.057.755.147.695.237.625.327.565.417.495.507.435.597.375.687.305.777.245.867.175.957.116.047.046.136.986.226.916.316.856.406.786.496.726.586.656.676.596.766.526.856.466.946.397.036.337.126.267.216.207.306.137.396.077.486.007.575.947.665.877.755.817.845.747.935.688.025.628.115.558.205.498.295.428.385.368.475.298.565.238.655.168.745.108.835.038.924.97

Hoja1_BiphasicTimeMeasured LOG10(N)Identified LOG10(N)Squared differenceParametersParameter valuesStandard ErrorPlease be aware that preferably at least 10 observations, as listed in columns A, B, are needed for a valid application of this model.1.0010.0010.320.10f0.0000ERROR:#NUM!Mean Sum of Squared Error0.08792.009.709.660.00kmax13.00ERROR:#NUM!Root Mean Sum of Squared Error0.29653.009.009.000.00kmax21.52ERROR:#NUM!R-Square0.98354.008.608.340.07LOG10(N0)10.98ERROR:#NUM!R-Square adjusted0.97355.007.807.680.014D reduction is reached at6.13units of time6.007.007.020.00Inactivation model identifiedThe parameter estimate for the fraction f is exactly zero. This indicates that the biphasic model is unlikely for these data.7.006.506.360.02log10(N)=log10(N0)+log10(f*exp(-kmax1*t)+(1-f)*exp(-kmax2*t))8.005.905.700.04For identification purposes reformulated as9.004.605.040.19log10(N)=log10(N0)+log10(f*exp(-kmax1*t)+(1-f)*exp(-kmax2*t))Least Sum of Squared Error0.44as can be derived fromCerf O. 1977. Tailing of survival curves of bacterial spores.Journal of Applied Bacteriology, 42, 1-19

0.0010.981.0910.261.1810.201.2710.141.3610.081.4510.021.549.961.639.901.729.841.819.781.909.721.999.662.089.602.179.552.269.492.359.432.449.372.539.312.629.252.719.192.809.132.899.072.989.013.078.953.168.893.258.833.348.773.438.713.528.653.618.603.708.543.798.483.888.423.978.364.068.304.158.244.248.184.338.124.428.064.518.004.607.944.697.884.787.824.877.764.967.705.057.645.147.595.237.535.327.475.417.415.507.355.597.295.687.235.777.175.867.115.957.056.046.996.136.936.226.876.316.816.406.756.496.696.586.636.676.586.766.526.856.466.946.407.036.347.126.287.216.227.306.167.396.107.486.047.575.987.665.927.755.867.845.807.935.748.025.688.115.638.205.578.295.518.385.458.475.398.565.338.655.278.745.218.835.158.925.09

Hoja1tiempopoblacion11029.73948.657.86776.585.994.6

Hoja2

Hoja3