Allometric models for leaf area estimation across different leaf-age groups of evergreen broadleaved trees in a subtropical forest

The accurate and nondestructive determination of individual leaf area (LA) of plants, by using leaf length (L) and width (W) measurement or combinations of them, is important for many experimental comparisons. Here, we propose reliable and simple regressions for estimating LA across different leaf-age groups of eight common evergreen broadleaved trees in a subtropical forest in Gutianshan Natural Reserve, eastern China. During July 2007, the L, W, and LA of 2,923 leaves (202 to 476 leaves for each species) were measured for model construction and the respective measurements on 1,299 leaves were used for model validation. Mean L, W, LA and leaf shape (L:W ratio) differed significantly between current and older leaves in four out of the eight species. The coefficients of one-dimension LA models were affected by leaf age for most species while those incorporating both leaf dimensions (L and W) were independent of leaf age for all the species. Therefore, the regressions encompassing both L and W (LA = a L W + b), which were independent of leaf age and also allowed reliable LA estimations, were developed. Comparison between observed and predicted LA using these equations in another dataset, conducted for model validation, exhibited a high degree of correlation (R ² = 0.96−0.99). Accordingly, these models can accurately estimate the LA of different age groups for the eight evergreen tree species without using instruments.     

辽东栎（Quercus liaotungensis ）叶特性沿海拔梯度的变化及其环境解释

植物对环境的适应一直是生态学研究的核心问题之一。山地由于海拔剧烈变化造成显著的环境差异,成为研究植物对环境适应性变化的理想对象。为阐明辽东栎(Quercus liaotungensis Koidz.)叶对环境的适应性变化,在北京东灵山地区辽东栎海拔分布范围(1000~1800 m)内研究了叶特性的变化规律及其与地形和土壤养分的关系。回归分析发现：辽东栎气孔密度、气孔长度和叶面积随海拔的升高呈现曲线变化形式。在海拔约1400m处,气孔密度最小而气孔长度和叶面积最大;气孔密度和长度成反比;叶长宽比没有明显变化;叶绿素(a+b)含量和单位干重叶氮、磷和钾含量沿海拔梯度呈上升趋势,同时叶绿素含量和叶氮含量有较弱的正相关。偏相关分析显示：叶绿素含量和坡位有显著的相关关系,叶磷含量与坡度关系显著,但叶养分与土壤养分之间未表现出明显的相关关系;地形和土壤养分与气孔密度、长度和叶面积等形态指标的关系均不显著。方差分析表明上坡位与中、下坡位的叶绿素含量有显著差异,上坡位的叶绿素含量最高。辽东栎大部分叶特性在其海拔分布范围内有显著的变化,并且形态特征和养分特征的变化形式不同,海拔1400 m左右是辽东栎叶形态特征变化最显著的范围。这些叶特征的变化与土壤养分的关系不明显。     

Leaf area estimation by simple measurements and evaluation of leaf area prediction models in Cabernet-Sauvignon grapevine leaves

For two growing seasons (2005 and 2006), leaves of grapevine cv. Cabernet-Sauvignon were collected at three growth stages (bunch closure, veraison, and ripeness) from 10-year-old vines grafted on 1103 Paulsen and SO4 rootstocks and subjected to three watering regimes in a commercial vineyard in central Greece. Leaf shape parameters (leaf area-LA, perimeter-Per, maximum midvein length-L, maximum width-W, and average radial-AR) were determined using an image analysis system. Leaf morphology was affected by sampling time but not by year, rootstock, or irrigation treatment. The rootstock×irrigation×sampling time interaction was significant for all the leaf shape parameters (LA, Per, L, W, and AR) and the means of the interaction were used to establish relationships between them. A highly significant linear function between L and LA could be used as a non-destructive LA prediction model for Cabernet-Sauvignon. Eleven models proposed for the non-destructive LA estimation in various grapevine cultivars were evaluated for their accuracy in predicting LA in this cultivar. For all the models, highly significant linear functions were found between calculated and measured LA. Based on r ² and the mean square deviation (MSD), the model proposed for LA estimation in cv. Cencibel [LA = 0.587(L×W)] was the most appropriate.     

辽东栎(Quercus liaotungensis )叶特性沿海拔梯度的变化及其环境解释

植物对环境的适应一直是生态学研究的核心问题之一。山地由于海拔剧烈变化造成显著的环境差异,成为研究植物对环境适应性变化的理想对象。为阐明辽东栎（Quercus liaotungensis Koidz.）叶对环境的适应性变化,在北京东灵山地区辽东栎海拔分布范围（1000~1800m）内研究了叶特性的变化规律及其与地形和土壤养分的关系。回归分析发现：辽东栎气孔密度、气孔长度和叶面积随海拔的升高呈现曲线变化形式。在海拔约1400m处,气孔密度最小而气孔长度和叶面积最大;气孔密度和长度成反比;叶长宽比没有明显变化;叶绿素（a＋b）含量和单位干重叶氮、磷和钾含量沿海拔梯度呈上升趋势,同时叶绿素含量和叶氮含量有较弱的正相关。偏相关分析显示：叶绿素含量和坡位有显著的相关关系,叶磷含量与坡度关系显著,但叶养分与土壤养分之间未表现出明显的相关关系;地形和土壤养分与气孔密度、长度和叶面积等形态指标的关系均不显著。方差分析表明上坡位与中、下坡位的叶绿素含量有显著差异,上坡位的叶绿素含量最高。辽东栎大部分叶特性在其海拔分布范围内有显著的变化,并且形态特征和养分特征的变化形式不同,海拔1400m左右是辽东栎叶形态特征变化最显著的范围。这些叶特征的变化与土壤养分的关系不明显。     

Assessment of a non-destructive method to estimate the leaf area of <Emphasis Type="Italic">Armoracia rusticana</Emphasis>

The aim of the study was to analyze horseradish growth for developing a mathematical model to estimate the leaf area based on linear measurements of the leaf surface. Leaf area (LA), number, and morphometric characteristics of the leaves including lamina length (L) and width (W) were evaluated on two horseradish accessions (Cor and Mon) throughout a 2 year growing cycle. In both accessions, increased values of LA and leaf number were found by comparing the second with the first-growing season. Leaf development occurs along with variations in size and not in shape during the plant growth. The leaves are elliptical in shape but tend to be wider and bigger in Cor accession and tapered and similar to narrow ellipses in Mon showing different length/width relationship. Consequently, several regression models relating to the LA and L, W, L², and W² individually or in combination were fitted for each accession based on a set of 1000 leaves. The horseradish LA can be predicted based on either length or width alone. However, the regression linear model LA?=?aLW?+?b (LA?=?0.71LW ??0.27 and LA?=?0.76LW ??3.22 for Cor and Mon, respectively) provided the best LA estimation (R²?>?0.95). The validation of this latter model showed high correlation between LA measured and LA predicted in both accessions (R²?=?0.98). Considering the type of foliage of horseradish, the proposed model can be used to estimate the leaf area throughout the entire crop cycle.     

Modeling individual leaf area of rose (<Emphasis Type="Italic">Rosa hybrida</Emphasis> L.) based on leaf length and width measurement

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 r ² , 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.     

Application of linear models for estimation of leaf area in soybean [<Emphasis Type="Italic">Glycine max</Emphasis> (L.) Merr]

Leaf area estimation is an important measurement for comparing plant growth in field and pot experiments. In this study, determination of the leaf area (LA, cm²) in soybean [Glycine max (L.) Merr] involves measurements of leaf parameters such as maximum terminal leaflet length (L, cm), width (W, cm), product of length and width (LW), green leaf dry matter (GLDM) and the total number of green leaflets per plant (TNLP) as independent variables. A two-year study was carried out during 2009 (three cultivars) and 2010 (four cultivars) under field conditions to build a model for estimation of LA across soybean cultivars. Regression analysis of LA vs. L and W revealed several functions that could be used to estimate the area of individual leaflet (LE), trifoliate (T) and total leaf area (TLA). Results showed that the LW-based models were better (highest R ² and smallest RMSE) than models based on L or W and models that used GLDM and TNLP as independent variables. The proposed linear models are: LE = 0.754 + 0.655 LW, (R ² = 0.98), T = −4.869 + 1.923 LW, (R ² = 0.97), and TLA = 6.876 + 1.813 ΣLW (summed product of L and W terminal leaflets per plant), (R ² = 0.99). The validation of the models based on LW and developed on cv. DPX showed that the correlation between calculated and measured LA was strong. Therefore, the proposed models can estimate accurately and massively the LA in soybeans without the use of expensive instrumentation.     

Models for leaf area estimation of three forest species in a short coppice rotation

It was obtained statistical models to estimate the leaf area (LA) based in the length (L) and the width (W) of Bambusa vulgaris, two different eucalypt clones, AEC-144 (spontaneous hybrid of Eucalyptus urophylla) and LW07 (Eucalyptus urophylla x Eucalyptus grandis), and Salix nigra leaves. The trees or clumps were provbrided from a short rotation coppice (SRC) for bioenergy, mainly characterized by the high tree density, in Botucatu, Sao Paulo, Brazil. It was collected, by chance, more than 4000 leaves that represented a quarter of the coppices. The bamboo and AEC-144 clone were, at the time, 22 months old, while the willow and LW07 clone were 18 months old. Young, intermediate and old leaves were mixed and measured. The measured leaves were correlated to obtain the simple linear eqs. (LA in function of L and W) and multiple linear regression (LA in function of L × W), to each species. All the species shown a positive correlation coefficient (r) to L (r = 0.75 to 0.95), W (r = 0.70 to 0.82) e L × W (r = 0.87 to 0.95), significative to p ≤ .05. The multiple linear models, that used L × W, are the most appropriated once it had better adjustments with the determination coefficients (R²) between 0.76 and 0.91 with exception in the case of S. nigra (willow), the R² of the simple linear regression using L was similar to the multiple linear regression, 0.90 and 0.91 respectively, showing that it is possible to estimate the LA in willow just using length.     

Evaluation of a leaf area prediction model proposed for sunflower

Six leaf samplings were conducted in two sunflower (Helianthus annuus L.) hybrids during the 2006 growing season in order to evaluate a simple model proposed for leaf area (LA) estimation. A total of 144 leaves were processed using an image analysis system and LA, maximum leaf width (W) [cm], and midvein length (L) [cm] were measured. Also, LA was estimated using the model proposed by Rouphael et al. (2007). Measured LA was exponentially related with L and W, and the W-LA relationships showed higher r ². Estimated LA was strongly and exponentially related with L. Strong, linear relationships with high r ² between estimated and measured LA confirmed the high predictability of the proposed model.     

Nitrogen fertilization effects on leaf morphology and evaluation of leaf area and leaf area index prediction models in sugar beet

In a two-year experiment (2002–2003), five N application rates [0, 60, 120, 180, and 240 kg(N) ha⁻¹, marked N₀, N₆₀, N₁₂₀, N₁₈₀, and N₂₄₀, respectively] were applied to sugar beet cv. Rizor arranged in a Randomized Complete Block design with six replications. Leaf shape parameters [leaf area (LA), maximum length (L), maximum width (W), average radial (AR), elongation (EL), and shape factor (SF)] were determined using an image analysis system, and leaf area index (LAI) was non-destructively measured every two weeks, from early August till mid-September (four times). Years, samplings, and their interaction had significant effects on the determined parameters. Fertilization at the highest dose (N₂₄₀) increased L and sampling×fertilization interaction had significant effects on LA, L, W, and SF. For this interaction, W was the best-correlated parameter with LA and LAI meaning that W is a good predictor of these parameters. Two proposed models for LA estimation were tested. The model based on both leaf dimensions [LA = 0.5083 (L×W) + 31.928] predicted LA better than that using only W (LA = 21.686 W − 112.88). Instrumentally measured LAI was highly correlated with predicted LAI values derived from a quadratic function [LAI = −0.00001 (LA)² + 0.0327 LA − 2.0413]. Thus, both LA and LAI can be reliably predicted non-destructively by using easily applied functions based on leaf dimensions (L, W) and LA estimations, respectively.     

Leaf shape and its relationship with Leaf Area Index in a sugar beet (<Emphasis Type="Italic">Beta vulgaris</Emphasis> L.) cultivar

Heteroblasty of sugar beet cultivar Rizor was studied under field conditions for three growing seasons (2003, 2005, 2006) in a Randomized Complete Block (RCB) design experiment. Eleven leaf samplings, from early June till the end of October, were conducted each year and leaf shape parameters [leaf area (LA), centroid X or Y (CX or CY), length (L), width (W), average radial (AR), elongation (EL), shape factor (SF)] were determined by an image analysis system. During samplings, Leaf Area Index (LAI) was measured non-destructively. Significant year and sampling effects were found for all traits determined. With the progress of the growing season, leaves became smaller (LA, L, W, and AR were decreased) and rounded. The largest leaves were sampled in 2006 when LAI was highest. LA was strongly correlated with L and W with simple functions (y = 0.1933 x^2.2238, r ² = 0.96, p<0.001, and y = 28.693 x − 192.33, r ² = 0.97, p< 0.001, respectively), which could be used for non-destructive LA determination. Also, LAI was significantly related with LA and leaf dimensions (L, W) suggesting that an easy, non-destructive determination of LAI under field conditions is feasible for sugar beet cv. Rizor. An erratum to this article is available at .     

龙船花两变种叶面积回归方程的建立

以龙船花两变种橙红龙船花Ixora coccinea var. coccinea、邦德胡卡红仙丹草I. coccinea var. bandhuca的成熟叶为材料,利用WinFolia软件测定多项叶形态指标,并对叶面积进行回归分析,分别建立其8种回归方程以及总的适用回归方程。结果表明,龙船花两变种的叶片长×叶水平宽、叶周长、叶垂直长、叶片长、叶水平宽、叶片长×叶片长以及叶水平宽×叶水平宽与叶面积之间的相关系数及复相关系数均呈极显著水平(P＜0.01),可分别用来建立龙船花的叶面积回归方程;叶面积与叶片长×叶水平宽的相关系数及复相关系数最高,基于叶片长×叶水平宽的8种叶面积回归方程更好地估测两种龙船花的叶面积。经检验发现,二次函数、复合函数、幂函数能更准确地估测叶面积;由两种龙船花共同建立的3种总的回归方程中,复合函数与幂函数能更好地模拟估测叶面积。     

Altitudinal variation in stomatal conductance,nitrogen content and leaf anatomy in different plant life forms in New Zealand

Summary This study is part of a series of investigations on the influence of altitude on structure and function of plant leaves. Unlike most other mountain areas, the Southern Alps of New Zealand provide localities where physiologically effective moisture stress occurs neither at high nor at low elevation, but the changes in temperature and radiation with elevation are similar or even steeper than in most other regions. In comparison with results from other mountains, where moisture may impair plant functioning at low elevation, this study allows an estimation of the relative role of water for the expression of various leaf features typically associated with alpine plants. Maximum leaf diffusive conductance (g), leaf nitrogen content (LN), stomatal density (n) and distribution, as well as area (A), thickness (d) and specific area (SLA) of leaves were studied. Three different plant life forms were investigated over their full altitudinal range (m): trees, represented by Nothofagus menziesii (1,200 m), ericaceous dwarf shrubs (1,700 m), and herbaceous plants of the genus Ranunculus (2,500 m). In all three life forms g, LN, and n increased, while SLA and A decreased with elevation. Recent investigations have found similar trends in other mountains from the temperate zone, but the changes are larger in New Zealand than elsewhere. Herbs show the greatest differences, followed by shrubs and then trees.It is concluded that g is dependent upon light climate rather than water supply, whereas SLA and related structural features appear to be controlled by the temperature regime, as they show similar altitudinal changes under different light and moisture gradients. The higher leaf nitrogen content found at high elevations in all three life forms, suggests that metabolic activity of mature leaves is not restricted by low nitrogen supply at high altitude. In general, the leaves of herbaceous plants show more pronounced structural and functional changes with altitude than the leaves of shrubs and trees.     

The roles of genetic drift and natural selection in quantitative trait divergence along an altitudinal gradient in Arabidopsis thaliana

Understanding how natural selection and genetic drift shape biological variation is a central topic in biology, yet our understanding of the agents of natural selection and their target traits is limited. We investigated to what extent selection along an altitudinal gradient or genetic drift contributed to variation in ecologically relevant traits in Arabidopsis thaliana. We collected seeds from 8 to 14 individuals from each of 14 A. thaliana populations originating from sites between 800 and 2700 m above sea level in the Swiss Alps. Seed families were grown with and without vernalization, corresponding to winter-annual and summer-annual life histories, respectively. We analyzed putatively neutral genetic divergence between these populations using 24 simple sequence repeat markers. We measured seven traits related to growth, phenology and leaf morphology that are rarely reported in A. thaliana and performed analyses of altitudinal clines, as well as overall Q_ST-F_ST comparisons and correlation analyses among pair-wise Q_ST, F_ST and altitude of origin differences. Multivariate analyses suggested adaptive differentiation along altitude in the entire suite of traits, particularly when expressed in the summer-annual life history. Of the individual traits, a decrease in rosette leaf number in the vegetative state and an increase in leaf succulence with increasing altitude could be attributed to adaptive divergence. Interestingly, these patterns relate well to common within- and between-species trends of smaller plant size and thicker leaves at high altitude. Our results thus offer exciting possibilities to unravel the underlying mechanisms for these conspicuous trends using the model species A. thaliana.     

A simple model for nondestructive leaf area estimation in bedding plants

Measurement of leaf area is commonly used in many horticultural research experiments, but it is generally destructive, requiring leaves to be removed for measurement. Determining the individual leaf area (LA) of bedding plants like pot marigold (Calendula officinalis L.), dahlia (Dahlia pinnata), sweet William (Dianthus barbatus L.), geranium (Pelargonium × hortorum), petunia (Petunia × hybrida), and pansy (Viola wittrockiana) involves measurements of leaf parameters such as length (L) and width (W) or some combinations of these parameters. Two experiments were carried out during spring 2010 (on two pot marigold, four dahlia, three sweet William, four geranium, three petunia, and three pansy cultivars) and summer 2010 (on one cultivar per species) under greenhouse conditions to test whether a model could be developed to estimate LA of bedding plants across cultivars. Regression analysis of LA versus L and W revealed several models that could be used for estimating the area of individual bedding plants leaves. A linear model having LW as the independent variable provided the most accurate estimate (highest R ², smallest mean square error, and the smallest predicted residual error sum of squares) of LA in all bedding plants. Validation of the model having LW of leaves measured in the summer 2010 experiment coming from other cultivars of bedding plants showed that the correlation between calculated and measured bedding plants leaf areas was very high. Therefore, these allometric models could be considered simple and useful tools in many experimental comparisons without the use of any expensive instruments.     

Variation in resource exploitation along an altitudinal gradient: the willow psyllids (Cacopsylla spp.) on Salix lapponum

Three congeneric species of Salix -fedding psyllid Cacospsylla spp. Occur along an altitudinal gradient (988 1222 m. a.s.l.) in southern Norway. The 27-km transect covered the local altitudinal range of the three species. Each species showed a different characteristic altitudinal distribution: C. propinqua occurred over the entire altitudinal range of the transect C. palmeni was restricted to higher altitude and C brunneipennis occurred manly at lower altitudes. This pattern of local altitudinal distribution mirrored the broader geographical distributions of these psyllids along latitudinal gradients. All three species developed on willow catkins, but also made use of leaves. Species differed in their use of leaves with >10% of sampled individuals of C. brunncipennis or C. Palmeni developing on leaves compared with up to 80% in C. propinqua. The proportion of C. propinqua nymphs developing on catkins increased with altitude and was also related to the temporal and spatial availability of catkins but was not a result of competitive displacement from catkins. Nitrogen concentration of host plants did not affect the proportions of C propinqua on leaves or catkins and was not related to adult size or psyllid density on catkins. Patterns or resource use are discussed in relation to differences in the distribution and abundance of the three species along the transect.     

Adaptive characteristics of grassland community structure and leaf traits along an altitudinal gradient on a subtropical mountain in Chongqing,China

Community structure and leaf traits are important elements of terrestrial ecosystems. Changes of community structure and leaf traits are of particular use in the study of the influence of climate change on terrestrial ecosystems. Patterns of community structure (including species richness, above- and below-ground biomass) and leaf traits (including leaf mass per area (LMA), nitrogen content both on mass and area bases (N _mass and N _area), and foliar δ¹³C) from 19 grassland plots along an altitudinal transect at Hongchiba in Chongqing, China, were analyzed. Species richness along the altitudinal transect had a hump-shaped pattern. Above-ground biomass had a quadratic decrease along the altitudinal gradient whereas below-ground biomass had the opposite pattern. Change of above-ground biomass of various taxonomic groups with altitude was also studied. Poaceae showed strong negative relationships and Asteraceae showed a hump-shaped relationship with increase of altitude. Five common species of the grassland, Trifolium pratense, Geranium wilfordii, Aster tataricus, Leontopodium leontopodioides, and Spiraea prunifolia, were particularly studied for variation of leaf traits along the altitudinal gradient. Averaged for all species, LMA, N _area and foliar δ¹³C had positive correlations with altitude. N _mass did not change significantly as altitude increased. LMA and N _area showed significant positive relationships with foliar δ¹³C. The adaptive features of leaf traits among different species were not consistent. The study highlights specific adaptation patterns in relation to altitude for different plant species, provides further insights into adaptive trends of community structure and leaf traits in a specific ecological region filling a gap in the definition of global patterns, and adds to the understanding of how adaptive patterns of plants may respond to global climate change.     

Leaf area estimation in muskmelon by allometry

This study developed a method for estimating the leaf area (LA) of muskmelon by using allometry. The best linear measure was evaluated first, testing both a leaf length and width (W). Leaf samples were collected from plants grown in containers of different sizes, leaves of four cultivars, at different develpoment stages, and of different leaf sizes. Two constants of a power equation were determined for relating allometrically a linear leaf measure and LA, in a greenhouse crop. W proved to be a better fit than the leaf length. The maximum attainable W and LA were estimated at W_x = 15.4 cm and LA_x = 174.1 cm². The indicators of fit quality showed that the function was properly related to LA and W as: LA/LA_x = A_o × (W/W_Lx)^b; the allometric exponent was b = 1.89, where R ² = 0.9809 (n = 484), the absolute sum of squares, 0.4584, and the standard deviation of residues, 0.03084, based on relative values calculations (LA/LA _x and W/W_Lx). The relationship was not affected by the cultivar, crop age, leaf size or stress treatment in the seedling stage. The empirical value of allometric constant (A₀) was estimated as 0.963.     

Leaf area estimation of sunflower leaves from simple linear measurements

Simple, accurate, and non-destructive methods for determining leaf area (LA) of plants are important for many experimental comparisons. Determining the individual LA of sunflower (Helianthus annuus L.) involves measurements of leaf parameters such as length (L) and width (W), or some combinations of these parameters. Two field experiments were carried out during 2003 and 2004 to compare predictive equations of sunflower LAs using simple linear measurements. Regression analyses of LA vs. L and W revealed several equations that could be used for estimating the area of individual sunflower leaves. A linear equation having W² as the independent variable provided the most accurate estimate (r ² = 0.98, MSE = 985) of sunflower LA. Validation of the equation having W² of leaves measured in the 2004 experiment showed that the correlation between calculated and measured areas was very high.     

Allometric models for non-destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora)

We aimed to evaluate the currently used allometric models, as well as to propose a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W), for estimating the area of leaves of eight field-grown coffee cultivars. For model construction, a total of 1563 leaves were randomly selected from different levels of the tree canopies and encompassed the full spectrum of measurable leaf sizes (0.3–263 cm²) for each genotype. Power models better fit coffee leaf area (LA) than linear models. To validate the model, an independent data set of 388 leaves was used. We demonstrated that the currently used allometric models are biased, underestimating the area of a coffee leaf. We developed a single power model     based on two leaf dimensions [LA = 0.6626 (LW)^1.0116; standard errors: β₀ = 0.0064, β₁ = 0.0019; R² = 0.996] with high precision and accuracy, random dispersion pattern of residuals and also unbiased, irrespective of cultivar and leaf size and shape. Even when the L (but not width) alone was used as the single leaf dimension, the power model developed still predicted with good accuracy the LA but at the expense of some loss of precision, as particularly found for 8% of the leaves sampled with length-to-width ratios below 2.0 or above 3.0.