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.     

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.     

Leaf allometry and prediction of specific leaf area (SLA) in a sugar beet (<Emphasis Type="Italic">Beta vulgaris</Emphasis> L.) cultivar

Sugar beet cv. Rizor was grown for five growing seasons (2002–2006) in field conditions in Thessaly, central Greece. A total of 55 samplings took place during the growing seasons and allometric growth of the leaves was monitored. Highly significant (p<0.001) quadratic relationships were found between individual leaf mass (LM), individual leaf area (LA), aboveground dry biomass (ADB), and leaf area index (LAI). Only the LM-LA relationship (LA = 43.444 LM² − 10.693 LM + 118.34) showed a relatively high r ² (0.63) and thus could be used for prediction of LA. Specific leaf area (SLA) was significantly related with leaf water content (LWC) (SLA = 26 279 LWC² − 44 498 LWC + 18 951, r ² = 0.91, p<0.001) and thus LWC could be a good indirect predictor of SLA in this cultivar.     

Leaf area estimation in a sugar beet cultivar by linear models

An indirect method of leaf area measurement for Rizor sugar beet cultivar was tested. Leaves were sampled during two growing seasons in a Randomised Complete Block Design experiment. For 2002 samplings, leaf area [cm²] was linearly correlated with maximum leaf width [cm] using all leaf samples (r ² = 0.83, p < 0.001) or using the means of the 8 sampling occasions (r ² = 0.97, p < 0.001). Correlations between leaf area and leaf mid vein length [cm] were weaker (r ² = 0.75, p < 0.001 and r ² = 0.93, p < 0. 001, respectively). For 2003 samplings, the area estimated by the equations was highly correlated to the measured leaf area.     

Leaf area prediction model for sugar beet (<Emphasis Type="Italic">Beta vulgaris</Emphasis> L.) cultivars

In two successive years (2003 and 2004), a set of 16 commercial sugar beet cultivars was established in Randomized Complete Block experiments at two sites in central Greece. Cultivar combination was different between years, but not between sites. Leaf sampling took place once during the growing season and leaf area, LA [cm²], leaf midvein length, L [cm] and maximum leaf width, W [cm] were determined using an image analysis system. Leaf parameters were mainly affected by cultivars. Leaf dimensions and their squares (L², W²) did not provide an accurate model for LA predictions. Using L×W as an independent variable, a quadratic model (y = 0.003 x² − 1.3027 x + 296.84, r ² = 0.970, p<0.001, n = 32) provided the most accurate estimation of LA. With compromises in accuracy, the linear relationship between L×W and LA (y = 0.5083 x + 31.928, r ² = 0.948, p<0.001, n = 32) could be used as a prediction model thanks to its simplicity.     

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 .