Non-destructive leaf area estimation in Myrtus communis plants

Non-destructive leaf area estimation in Myrtus communis plants G. Gugliuzza, G. Fascella, M.M. Mammano and M. Militello Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Unità di ricerca per il recupero e la valorizzazione delle specie floricole mediterranee (CRA SFM), Bagheria (Palermo), Italy. Abstract Leaf area (LA) is an important biometrical parameter recorded for evaluating plant growth in field and greenhouse experiments. In the present study a LA estimation model was developed for myrtle (Myrtus communis L.) pot plants under different water regimes, using linear measurements of leaf length (L) and width (W). The aim of the work was to establish if a non-destructive LA model could be used to estimate plant leaf area and, if this model could be used as predictor of plant suboptimal water availability condition. A different approach from those reported in literature was used. The total aerial part (all leaves) of two-year old potted plants of myrtle, were used to develop the model. LA and leaf dimensions were measured with an area meter. Frequency distributions of leaf dimensions were created through the L/W ratio. Frequency distributions provided evidence of leaf-shape polymorphism that greatly influenced the power of the model. Regression analyses of LA versus L and W showed several models that could be used for estimating the area of individual myrtle leaves, with significant differences among the models. A quadratic model having L as the independent variables (y=aL2+bL+c) provided the most accurate estimate (R2=0.92) of leaf area. Validation of the model was performed with the LA data measured using plants grown under different water regimes to evaluate the possibility of using the model to evaluate different treatment effects. Results showed that the correlation between measured and predicted areas was high (R2=0.92±0.1) in every case. The quadratic model developed in this study did not show evidence of the effect of different water regime treatments on total plant leaf area. Keywords: allometric model, regression curve, myrtle INTRODUCTION Many authors report the importance of plant leaf area (LA) as a key variable for most agronomic and physiological studies involving light interception, transpiration, photosynthetic efficiency, plant growth and responses to fertilizers and irrigation (Kumar, 2009; Rouphael et al., 2010). The close relation between LA, plant growth and productivity make this parameter a fundamental component of crop growth models when it is not possible to proceed with a destructive sampling. A large number of methods, either destructive or not, have been developed to measure or estimate plant leaf area. The most common approach is to develop ratios and regression estimators by using simple measured leaf parameters such as length (L) and width (W). This method does not require leaves to be detached, permitting a continuous monitoring during the plants growth period, reducing the variability associated with destructive sampling procedures (Kumar, 2009). Non-destructive methods, based on linear measurements, are quicker and easier than destructive ones to execute, and are characterized by high precision and accuracy as demonstrated for crops, like chestnut (Serdar and Demirsoy, 2006), faba bean (Peksen, 2007), saffron (Kumar, 2009), red pepper (De Swart et al., 2004), Euphorbia × lomi (Fascella et al., 2009) and sunflower (Rouphael et al., 2007). In some plant species, the presence of abiotic stress can induce morphological variations in leaves (Akinci and Losel, 2012). Many authors reported the effects of different kinds of stress on leaf morphology of several species, both spontaneous and cultivated (Fini Acta Hortic. 1104. ISHS 2015. DOI 10.17660/ActaHortic.2015.1104.14 XXIX IHC – Proc. Int. Symp. on Ornamental Horticulture in the Global Greenhouse Ed.: R.A. Criley 89 and Ferrini, 2010). Moreover, a relation between leaf morphology of Myrtus communis L. (myrtle) and solar radiation was evidenced by other authors (Mendes et al., 2001; Tattini et al., 2006). M. communis is an evergreen sclerophyll shrub that grows naturally in the Mediterranean basin, but also extends to eastern Iran and Afghanistan. It occurs in woodlands, maquis and garrigues, but also in coastal areas where drought stress and high solar radiation are very frequent. The aim of this study was to develop a model that could be able to predict LA of myrtle plants from single parameters (L and/or W) and, if this model could be used as predictor of plant sub-optimal water availability condition. MATERIALS AND METHODS The experiment was conducted at the experimental farm of the Agricultural Research Council, Research Unit for Mediterranean Flower Species of Palermo (38°5’N, -13°30’E, 23 m a.s.l.), Italy, during the 2012 growing season. Local myrtle genotypes, from spontaneous Sicilian maquis, were used to develop the leaf area prediction model. For model validation two-year-old myrtle plants grown outdoors were used. Plants were grown in plastic pots containing 3 L of peat and perlite (2:1, v/v), in single rows, at a plant density of 5 plants m-2. Plants were daily irrigated with a drip-irrigation system by using two different water volumes: “T1” plants received 100% of the daily evapo-transpiration (ETe), “T2” plants received 66% of ETe. Evapo-traspiration was estimated by a gravimetric method. All plant leaves were collected in June (end of the blooming time) from six plants per treatment. Leaf length was measured from the lamina tip to the point of intersection of the lamina and stem, while leaf width was measured as the maximum perpendicular dimension of the length. LA and leaf dimensions were measured using a leaf area meter (“WinDIAS 3” Image Analysis System for Leaves, DELTA-T Devices Ltd., Cambridge, England) calibrated to 0.01 cm2. For model design, a double approach was carried out. A first series of model was designed (with an upper-case letter followed by lower-case m, e.g., Am) on a sample of mature leaves, from the middle part of the stem, with a L/W ratio between 1.8 and 2.0. A second series of model was designed (upper-case letter followed by lower-case t, e.g., At) with total plant leaves. A sample of 216 healthy leaves were analyzed for building of the first model series, while for the construction of second model series, 3215 healthy leaves were analyzed. For both model building, LA was regressed with L, W, L2, W2, and the product L×W and 2 2 L ×W . Model equation (coefficients (b) and constants (a)) and mean square error (MSE), means area and coefficient of determination (R2) were also reported. Model validation was performed with the LA data measured in plants irrigated with different water regimes. A sample of 200 leaves was made by random selection from the total leaf area of six plants per treatment. The LA of individual leaves was predicted using the best model selected, and was compared with the measured LA. RESULTS AND DISCUSSION Regression analyses of LA versus L and W revealed several models that could be used for estimating the area of individual myrtle leaves (Tables 1 and 2). The regression estimation model, developed on a sample of mature leaves, resulted in many equations having a coefficient of determination (R2) over 0.9 (Table 1). Amongst the single parameter equations based on leaf length, the quadratic equation indicated as “Bm” was selected (Figure 1) for achieving the same estimated mean area as compared to that measured (2.744 vs. 2.744 cm2), and for the high coefficient of determination (R2=0.92). This model can also easily be used in physiological and agronomic studies. 90 Table 1. Regression estimation model of leaf area on mature leaves of Myrtus communis. Statistical population: 216 units. Coefficient of determination (R2) and mean square errors (MSE). Measured mean area: 2.744 (cm2). Model Am Bm Cm Gm Hm Im Lm Mm Nm Parameter Equation model Length y=2.1489x-2.5454 Length y=0.3745x2+0.1578x-0.029 Length y=0.4828x1.8759 Length×width y=0.5118x+0.1425 Length×width y=-0.0008x2+0.5227x+0.1124 Length×width y=0.5907x0.9435 2 2 Length ×width y=0.035x+1.6432 Length2×width2 y=-0.0001x2+0.0571x+1.2417 Length2×width2 y=0.5907x0.4718 Mean area 2.744 2.744 2.725 2.744 2.744 2.725 2.743 2.827 2.725 MSE 0.0192 0.0174 0.0173 0.0167 0.0167 0.0166 0.0246 0.0213 0.0166 R2 0.897 0.916 0.928 0.921 0.921 0.931 0.850 0.909 0.931 Table 2. Regression estimating model of leaf area on total plant leaves in Myrtus communis. Statistical population: 742 units. Coefficient of determination (R2) and mean square errors (MSE). Measured mean area: 2.818 (cm2). Model At Bt Ct Dt Et Ft Gt Ht It Lt Mt Nt Parameter Length Length Length Width Width Width Length×width Length×width Length×width Length2×width2 Length2×width2 Lengtht2×width2 Equation model y=0.4338x+1.2944 y=-0.0341x2+0.6874x+0.9129 y=1.5265x0.5057 y=0.3022x+0.9284 y=-0.0261x2+0.4963x+0.6365 y=1.0698x0.5055 y=0.5153x+0.3808 y=-0.0027x2+0.5497x+0.2955 y=0.729x0.8708 y=0.0376x+1.7538 y=-0.0002x2+0.0605x+1.4003 y=0.729x0.4354 Mean area 2.386 2.414 2.417 1.466 1.431 1.418 2.818 2.819 2.783 2.817 2.749 2.783 MSE 0.0294 0.0280 0.0523 0.0944 0.0958 0.0965 0.0261 0.0261 0.0260 0.0323 0.0292 0.0260 R2 0.895 0.920 0.921 0.670 0.693 0.695 0.862 0.862 0.881 0.786 0.840 0.881 Figure 1. Regression model validation. On left side, Bm model based on leaf length (L) of mature leaves, on the basis of L/W ratio. On right side, Bt model based on leaf L using total plant leaves. Generally regression estimation models developed on all plant leaves are less accurate with respect to the previous model based on mature leave (Table 2), due to the leaf-shape polymorphism noted. A frequency distribution of the leaf dimensions of L/W ratio showed 91 that young leaves are more circular (L/W=1.4) than adult leaves, which were more stretched (L/W>1.8) (Figure 2). Models based on both dimensional parameters, L and W, had a lower coefficient of determination as compared with models with only L, but the mean areas estimated were closer to those measured (Figure 1). Amongst the single parameter equations based on leaf length, the quadratic equation indicated as “Bt” was selected for achieving a high coefficient of determination (R2) for the estimated mean leaf area and low MSE value (Table 2). Regression models evidenced as the equations based on L and W are more accurate, in terms of mean areas estimation, than equations based on one parameter because the sample of measured leaves included leaves with different L and same W (Figure 3). Figure 2. Frequency distribution of L/W ratio of myrtle leaves. On the left side: distribution using plants cultivated under optimal water availability. On the right side: distribution using plants under water stress. Figure 3. Regression model validation on total plant leaves. Square symbols represent model Bt using L/W ratio. Circle symbols represent model Gt using leaf L. These results are in agreement with those reported by De Swart et al. (2004) using red pepper. The analysis of leaf shape distribution (different L/W ratios in total plant leaves) possibly reveals the presence of new leaves emerging. This possibility is linked to the presence of different elongations of leaf lamina with the same W. In addition, a close relation is known between drought stress and leaf emergence during the growth period (Xu et al., 2009). The application of the regression model on plants 92 subjected to different irrigation regimes, was not able to evidence the presence of stress conditions during the growth period (Figure 4), as reported on other species (Blanco and Folegatti, 2005). In contrast, a significant difference was recorded in the frequency distribution of L/W ratio between well watered and stressed plants, confirming the possibility to use this method to evaluate the presence of drought stress. Figure 4. Regression model estimation used for evaluating the effect of water stress on potted plants of Myrtus. Square symbols represent model Gt, circle symbols represent model Bt using total plant leaves; rhombus symbols represent model Bm using mature leaves. CONCLUSIONS Myrtle plants generally show leaf shape polymorphism. The model developed using mature leaves (indicated as Bm), showed that the correlation between measured and predicted areas was high. The models using the single parameter L (Equations Bt and Bm) were more acceptable for estimating LA, due to their low R2 and MSE values. Equation G based on L and W measurements, could also estimate LA accurately, but doubled the time required for leaf measurement. The quadratic model developed in this study did not detect evidence of the effect of different water availability, but the study of frequency distribution of L/W ratio can be used to evaluate the presence of drought stress during the growth period. ACKNOWLEDGEMENTS The present work was supported by the Italian Ministry of Education, University and Research with the project PON “Sustainable production of pot plant in Mediterranean Environment” - National Operational Programme “Research and Competitiveness” 20072013 PON “R & C”. 93 Literature cited Akinci, S., and Losel, D.M. (2012). Plant water-stress response mechanisms. In Plant Water-Stress Response Mechanisms, Water Stress, P.I.M.M. Rahman, ed. (InTech), p.15–42. Blanco, F.F., and Folegatti, M.V. (2005). Estimation of leaf area for greenhouse cucumber by linear measurements under salinity and grafting. Sci. Agric. 62, 305–309 http://dx.doi.org/10.1590/S0103-90162005000400001. De Swart, E., Groenwold, R., Kanne, H.J., Stam, P., Marcelis, L.F.M., and Voorrips, R.E. (2004). Non-destructive estimation of leaf area for different plant ages and accessions of Capsicum annuum L. J. Hortic. Sci. Biotechnol. 79, 764–770. Fascella, G., Maggiore, P., Zizzo, G.V., Colla, G., and Rouphael, Y. (2009). A simple and low-cost method for leaf area measurement in Euphorbia × lomi Thai hybrids. Advances in Horticultural Science 23, 57–60. Fini, A., and Ferrini, F. (2010). Growth, leaf gas exchange and leaf anatomy of three ornamental shrubs grown under different light intensities. Europ. J. Hortic. Sci. 75, 111–117. Kumar, R. (2009). Calibration and validation of regression model for non-destructive leaf area estimation of saffron (Crocus sativus L.). Sci. Hortic. (Amsterdam) 122, 142–145 http://dx.doi.org/10.1016/j.scienta. 2009.03.019. Mendes, M.M., Gazarini, L.C., and Rodrigues, M.L. (2001). Acclimation of Myrtus communis to contrasting Mediterranean light environments - effects on structure and chemical composition of foliage and plant water relations. Environ. Exp. Bot. 45, 165–178 http://dx.doi.org/10.1016/S0098-8472(01)00073-9. PubMed Peksen, E. (2007). Non-destructive leaf area estimation model for faba bean (Vicia faba L.). Sci. Hortic. (Amsterdam) 113, 322–328 http://dx.doi.org/10.1016/j.scienta.2007.04.003. Rouphael, Y., Colla, G., Fanasca, S., and Karam, F. (2007). Leaf area estimation of sunflower leaves from simple linear measurements. Photosynthetica 45, 306–308 http://dx.doi.org/10.1007/s11099-007-0051-z. Rouphael, Y., Mouneimne, A.H., Ismail, A., Mendoza-De Gyves, E., Rivera, C.M., and Colla, G. (2010). Modeling individual leaf area of rose (Rosa hybrida L.) based on leaf length and width measurement. Photosynthetica 48, 9– 15 http://dx.doi.org/10.1007/s11099-010-0003-x. Serdar, U., and Demirsoy, H. (2006). Non-destructive leaf area estimation in chestnut. Sci. Hortic. (Amsterdam) 108, 227–230 http://dx.doi.org/10.1016/j.scienta.2006.01.025. Tattini, M., Remorini, D., Pinelli, P., Agati, G., Saracini, E., Traversi, M.L., and Massai, R. (2006). Morpho-anatomical, physiological and biochemical adjustments in response to root zone salinity stress and high solar radiation in two Mediterranean evergreen shrubs, Myrtus communis and Pistacia lentiscus. New Phytol. 170, 779–794 http://dx.doi.org/10.1111/j.1469-8137.2006.01723.x. PubMed Xu, F., Guo, W., Xu, W., Wei, Y., and Wang, R. (2009). Leaf morphology correlates with water and light availability: what consequences for simple and compound leaves? Prog. Nat. Sci. 19, 1789–1798 http://dx.doi.org/10.1016/ j.pnsc.2009.10.001. 94