Kinetic Modeling of Slightly Acidic Electrolyzed Water Decay Characteristics in Fresh Cabbage Disinfection Against Human Norovirus

To consistently disinfect fresh vegetables efficiently, the decay of disinfectants such as chlorine, electrolyzed oxidizing water (EOW), ozonated water, and plasma-activated water during the disinfection maintenance stage needs to be understood. The aim of our study was to evaluate the changes in the inactivation kinetics of slightly acidic electrolyzed water (SAEW) against human norovirus (HuNoV), based on the cabbage-to-SAEW ratio. After disinfection of fresh cabbage with disinfected SAEW solution, SAEW samples were collected and analyzed for physicochemical properties such as pH, available chlorine concentrations (ACCs), and oxidation-reduction potential (ORP). SAEW virucidal effects were evaluated. We confirmed the decay of post-disinfection SAEW solution and demonstrated the different patterns of the decay kinetic model for HuNoV GI.6 and GII.4. In addition, the goodness of fit of the tested models based on a lower Akaike information criterion, root-mean-square error (RMSE), and residual sum of squares (RSS) was close to zero. In particular, the change in both the HuNoV GI.6 and GII.4 inactivation exhibited a strong correlation with the changes in the ACC of post-disinfection SAEW. These findings demonstrate that physicochemical parameters of SAEW play a key role in influencing the kinetic behavior of changes in the disinfection efficiency of SAEW during the disinfection process. Therefore, to optimize the efficiency of SAEW, it is necessary to optimize the produce-to-SAEW ratio in future studies.

Non-destructive method for estimating leaf area of Erythroxylum pauferrense (Erythroxylaceae) from linear dimensions of leaf blades

Background and Aims: Determining the leaf area is essential for studies on growth, propagation, and ecophysiology of forest species. Developing quick, practical, and accurate methods is needed to estimate leaf area without destroying leaves. Therefore, this research aimed to obtain an equation from regression models that meaningfully estimate the leaf area of Erythroxylum pauferrense using linear dimensions of its leaf blades.Methods: For this purpose, 1200 leaves were randomly collected from different plants in the Mata do Pau-Ferro, a state park located in Areia city, Paraíba state, Brazil. Equations were fitted from simple linear, linear without intercept, quadratic, cubic, power, and exponential regression models. Next, the best equation was selected by checking the following assumptions: higher determination coefficient (R²) and Willmott's index (d), lower Akaike information criterion (AIC) and root mean square error (RMSE), as well as the BIAS index closest to zero.Key results: Based on the criteria used, all equations fitted using the product of length by width (L.W) can estimate the leaf area of E. pauferrense.Conclusions: The equation ŷ=0.6740*LW from the linear model without intercept significantly estimates the leaf area of E. pauferrense in a quick and practical way (R²=0.9960; d=0.9953; AIC=1231.61; RMSE=0.4255; BIAS=-0.0130).