Bozkurt, SeferKeskin, Muharrem2024-09-182024-09-1820181560-85301814-9596https://doi.org/10.17957/IJAB/15.0579https://hdl.handle.net/20.500.12483/9284Simple, accurate, and nondestructive methods of quantifying leaf area are important for many experimental comparisons. The aims of this study were to establish models to estimate the leaf area of cucumber plants grown under greenhouse conditions and evaluate the effects of different irrigation water levels on this estimation. Six irrigation levels based on evaporation from a Class A Pan (I-20:20%, I-40:40%, I-60:60%, I-80:80%, I-100:100% and I-120:120% of) were utilized A total of about 690 leaves from different irrigation levels were collected and relationships among leaf width (W), length (L) and leaf area (LA) were investigated. Estimation models were derived using Multiple Linear Regression (MLR) method and Full Cross Validation was used to validate the models. The Root Mean Square Error of Prediction (RMSEP) and R-2 values were used to compare the models. It was found that mean leaf area values were affected by different irrigation amounts. Mean leaf areas in I-20 and I-40 were significantly lower than the other irrigation treatments. A strong non-linear relationship was found between cucumber W, L and LA (R-2 >= 0.94). Three LA prediction models with W (Model 1), L (Model 2) and W and L (Model 3) were developed for each irrigation levels and for the combined data. RMSEP and R-2 values were 16.3 cm(2) and 0.99 for the model of combined data for all leaves from all different irrigation treatments. In conclusion, for various physiological and morphological studies, model developed in this study can be used as non-destructive technique to estimate cucumber leaf area from leaf size for each irrigation levels and for the combined data in a shorter time with less labor and budget. (C) 2018 Friends Science Publisherseninfo:eu-repo/semantics/closedAccessCucumberDeficit irrigationLeaf area estimationWater stressArticle20487788210.17957/IJAB/15.05792-s2.0-85045633971Q3WOS:000430465400027Q3