Accurate and nondestructive methods to determine individual leaf areas of plants are a useful tool in physiological and agronomic research. Determining the individual leaf area (LA) of rose (Rosa hybrida L.) involves measurements of leaf parameters such as length (L) and width (W), or some combinations of these parameters. Two-year investigation was carried out during 2007 (on thirteen cultivars) and 2008 (on one cultivar) under greenhouse conditions, respectively, to test whether a model could be developed to estimate LA of rose across cultivars. Regression analysis of LA vs. L and W revealed several models that could be used for estimating the area of individual rose leaves. A linear model having L×W as the independent variable provided the most accurate estimate (highest r2, smallest MSE, and the smallest PRESS) of LA in rose. Validation of the model having L×W of leaves measured in the 2008 experiment coming from other cultivars of rose showed that the correlation between calculated and measured rose LA was very high. Therefore, this model can estimate accurately and in large quantities the LA of rose plants in many experimental comparisons without the use of any expensive instruments

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Highlights Mixtures of similar MoA chemicals increased BDNF levels and neurite outgrowth. Mixtures of similar MoA chemicals decreased synapse formation and electrical activity. Synergistic effects on synaptogenesis features was predicted by mathematical modelling. Some of the DNT effects observed in hiPSC-neurons/astrocytes recapitulate ASD features. In vitro assays combined with mathematical modelling enable DNT testing of chemical mixtures.

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