Prediction of Leaf Area, Fresh and Dry Weight in Stinging Nettle (Urtica dioica) by Linear Regression Models

Abstract

Leaf area, fresh and dry weight measurements are necessary in several agronomical and physiological researches. Although stinging nettle (Urtica dioica) has a long history of use as a medicine, food source and a source of fibre, the trichomes of leaves and stems of plant when touched, will inject a mixture of chemical compounds cause a painful sting. Therefore accurate, non-destructive and safer method to determine leaf area (LA) and fresh (FW) and dry weight (DW) could be a useful tool in researches. In the present study prediction of LA, FW and DW in stinging nettle involved leaf dimensions including measurements of leaf length and width. Plant Samples were selected from around of Rudbar city. It located in northern part of Iran warm Mediterranean climate. Twenty regression models for estimation of leaf area and totally twenty-six models for estimation of leaf fresh and dry weight using different independent variables were tested. Considering all of criteria of selection model in validation including differences between regression coefficient and constant from 1 and 0 respectively, low value for RMSE and CV and high value for R2 adjusted, the best models were identified, for LA prediction were based on L×W and (L+W)2 with equations of LA= -1.21+ 0.36 (L×W) and LA= -1.21+0.08 (L+W)2 for prediction of FW and DW, L×W and (L+W)2 based models provided the most accurate estimate. The suggested linear models are FW= -0.018 + 0.008 (L×W) and DW= -0.014 + 0.0006 (L+W)2. The validation analysis revealed that leaf area, fresh and dry weight of stinging nettle could be determined quickly, accurately and non-destructively by using established models in present study.