• Journal of Ecology and Environment
• /
• v.32 no.1
• /
• pp.61-65
• /
• 2009

We compared two nondestructive methods for leaf area estimation using leaves of 16 common plant species classified into six types depending on leaf shape. Relatively good linear relationships between actual leaf area (LA) and leaf length (L), width (W), or the product of length and width (LW) were found for ordinary leaves with lanceolate, oblanceolate, linear and sagitttate shapes with entire margins, serrate margins, mixed margins with a entire form and shallow lobes, and ordinary incised margins. LA was better correlated with LW than L or W, with $R^2$ > 0.91. However, for deeply incised lobes, LA estimation using LW showed low correlation coefficient values, indicating low accuracy. On the other hand, a method using photographic paper showed a good correlation between estimates of area based on the mass of a cut-out leaf image on a photographic sheet (PW) and actual leaf area for all types of leaf shape. Thus, the PW method for LA estimation can be applied to all shapes of leaf with high accuracy. The PW method takes a little more time and has a higher cost than leaf estimation methods using LW based on leaf dimensions. These results indicate that researchers should choose their nondestructive LA estimation method according to their research goals.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.39 no.6
• /
• pp.602-606
• /
• 1994

The study was conducted to investigate the relationships between the value of fresh leaf lengh ${\times}$ width and actual fresh or cured leaf area, Cured leaf weight of cutter and leaf in Burley tobacco plants. In all tested varieties, Actual fresh leaf area or cured leaf area, cured leaf weight was high significantly correlated with the value of fresh leaf length ${\times}$ width. The linear regression equation between them could be exploited for rapid and easy estimation of either fresh or cured leaf area, cured leaf weight. Highly significant correlation between fresh leaf area and cured leaf area or cured leaf weight was confirmed and a linear regression equation was also obtained for easy estimation of cured leaf area or cured leaf weight.

• Journal of Bio-Environment Control
• /
• v.31 no.2
• /
• pp.98-103
• /
• 2022

Non-destructive estimation of leaf area is a more efficient and convenient method than leaf excision. Thus, several models predicting leaf area have been developed for various horticultural crops. However, there are limited studies on estimating the leaf area of strawberry plants. In this study, we predicted the leaf areas via nonlinear regression analysis using the leaf lengths and widths of three-compound leaves in five domestic strawberry cultivars ('Arihyang', 'Jukhyang', 'Keumsil', 'Maehyang', and 'Seollhyang'). The coefficient of determination (R²) between the actual and estimated leaf areas varied from 0.923 to 0.973. The R² value varied for each cultivar; thus, leaf area estimation models must be developed for each cultivar. The leaf areas of the three cultivars 'Jukhyang', 'Seolhyang', and 'Maehyang' could be non-destructively predicted using the model developed in this study, as they had R² values over 0.96. The cultivars 'Arihyang' and 'Geumsil' had slightly low R² values, 0.938 and 0.923, respectively. The leaf area estimation model for each cultivar was coded in Python and is provided in this manuscript. The estimation models developed in this study could be used extensively in other strawberry-related studies.

• Journal of Bio-Environment Control
• /
• v.31 no.4
• /
• pp.325-331
• /
• 2022

One of the most important factors in predicting tomato growth and yield is the leaf area. Estimating leaf area accurately is the beginning of an effective tomato plant growth assessment model. To this end, this study was conducted to identify the most effective model for estimating plant leaf area through the measurement of tomato plant leaves. Leaf area (LA), leaf length (L), leaf width (W), and lamina length (La) were measured for all leaves of 5 plants at two-week intervals. The correlation between LA and tomato-leaf-independent variables showed a strong positive relationship with the formulas La × W, L × W, La + W, and L + W. For LA estimation, a linear model using the formula LA = a + b (La² + W²) gave the most accurate estimation (R² = 0.867, RMSE = 88.76). After examining the positions of upper, middle, and lower leaves from September to December, the coefficient of determination (R²) values for each model were 0.878, 0.726, and 0.794 respectively. The most accurate estimation came from the model that used the upper leaves of the plants. The high accuracy of the upper-leaf-based model is judged by the 50% defoliation performed by farmers after October.

• Journal of Plant Biology
• /
• v.16 no.1_2
• /
• pp.1-5
• /
• 1973

Six young trees of Alnus tinctoria grown in isolation, each having different growing stage, were selected and the surface area of their roots, stems and leaves was determined. Each of the roots of more than 0.2mm in diameter and stems was cut at intervals of 10cm and their surface area was calculated with 2$\pi$rl from the average diameter (2r) of both sections (upper and lower) by making cylindrical estimation of the cut pieces. The leaf area measured was only one side area, and the volume of cut piece and amount of dry matter of each organ were also measured. The percentage to the surface area of the whole plant body by each organ was 4-12% in root, 7-9% in stem and 69-89% in leaf, respectively. There was relatively a little individual difference. However, the surface area ratios of root and stem showed a slightly increasing tendency while that of leaf decreasing according to the growing stage. The ratio of sum leaf area index (LAIi) was 2.3-4.0$m^2$/$m^2$-and that of the surface area index(SaIi) was 0.16-0.33$m^2$/$m^2$, respectively. It has been known that the stem surface area(SAI) to the leaf area index(LAI) is within the range of 31-53%, but the SAIi is within the range of 8-11% of the LAIi.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.805-809
• /
• 2008

Measurement of leaf area index (LAI) is useful for understanding rice growth, water use, and canopy light interception. The top nitrogen content(TNC) per unit area is an important quantitative index of the condition of nitrogen nutrition in rice production. The rapid and simple method of estimation of TNC, with the use of the existing nondestructive analyzing instruments chlorophyll meter SPAD-502 and plant canopy analyzer (PCA) LAI-2000, was scrutinized. Destructive measurement is time consuming and labor intensive. Our objective was to evaluate sampling procedures using the Li-Cor LI-1800, LAI 2000 plant canopy analyzer (PCA) for nondestructive estimation of rice LAI, and SPAD-502 on the Northern Plains of Cheongju. The LAI estimated by PCA tended to underestimate the LAI determined by actual measurement by about 20%. The estimation of LAI by PCA was judged to have a sufficient accuracy as a practical technique. A high positive correlation was obtained between the values of the SPAD reading and LAI. NDVI and LAI also showed a very high correlation. The values of the SPAD reading and LAI, and NDVI gave a high positive correlation. These results indicated that the method described in this study was effective as a simple and rapid method for the estimation of rice growth.

• Journal of Korean Society of Forest Science
• /
• v.70 no.1
• /
• pp.103-108
• /
• 1985

This paper is concerned with estimating equations of leaf area(A) obtained from linear measurements - leaf length(L) and leaf width(W) - on the leaves of 13 species composing a natural mixed stand in Mt. Jiri. This method is known to be rapid and non-destructive in estimating leaf area. The equation of A=bLW is frequently used in rough and rapid estimation. Each species in this study has its own coefficient b according to its geometrical leaf shape. The range of coefficients of 13 species was 0.579 to 0.717. This means that the relationship A=2/3LW is suitable to most broad leaf species in a natural mixed stand in Mt. Jiri. When more precise estimation of leaf area is needed, full regression equation is used. In this study, the form of ${\log}A=b_0+b_1{\log}LW$ was the most precise estimation equation in 8 species. In addition to this, the form of $A=b_0+b_1LW$ and $A=b_0+b_1L^2+b_2W^2$ were founded to be suitable for estimation of leaf area. In comparision of these two forms, the determination coefficient were about the same, but the F-value of the former was greater than that of the latter. Therefore, the use of the former seems to be more reliable and practical.

• Journal of Forest and Environmental Science
• /
• v.30 no.4
• /
• pp.351-361
• /
• 2014

Leaf area ($A_0$) and leaf biomass ($M_0$) estimation are significant prerequisites to studying tree physiological processes and modeling in the forest ecosystem. The objective of this study was to develop allometric models for estimating $A_0$ and $M_0$ of Swietenia mahagoni L. from different tree parameters such as DBH and tree height of mahogany plantations in the northeastern region of Bangladesh. A total of 850 healthy and well formed trees were selected randomly for sampling in the five study sites. Then, twenty two models were developed based on different statistical criteria that propose reliable and accurate models for estimating the $A_0$ and $M_0$ using non-destructive measurements. The results exposed that model iv and xv were selected on a single predictor of DBH and showed more statistically accuracy than other models. The selected models were also validated with an additional test data set on the basis of linear regression and t-test for mean difference between observed and predicted values. After that, a comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and underestimates $A_0$ and $M_0$ for larger trees. As a result, it showed that the bias-corrected logarithmic model iv and xv can be used to help quantify forest structure and functions, particularly valuable in future research for estimating $A_0$ and $M_0$ of S. mahagoni in this region.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.49 no.6
• /
• pp.463-467
• /
• 2004

This study was carried out to estimate of leaf area index (LAI) rapidly using plant canopy analyzer, comparing with specific leaf area (SLA) and leaf area ratio (LAR) in rice from 2001 to 2002 at Honam Agricultural Research Institute in Iksan Korea. The relationship between LAI values taken by plant canopy analyzer and by leaf area meter showed high correlation at each growth stages of rice. LAIs obtained by plant canopy analyzer were highly correlated with that by leaf area meter which were the highest in Dongjinbyeo and the lowest in Hapcheon1. Specific leaf area (SLA) of all rice cultivars were tend to decrease remarkably with the progress of growth stage. It was found that the SLA of Dasanbyeo was the highest and that of Hapcheon1 was the lowest among rice cultivars tested. Leaf area ratios (LARs) was also decreased with the progress of growth stage.

• Journal of Sericultural and Entomological Science
• /
• v.9
• /
• pp.15-19
• /
• 1969

Experiments were carried out to make clear the relationships among some morphological characters of four-varieties of mulberry trees. Simple correlation coefficients and particial correlation coefficients were calcultated among the characters, namely branch length, branch diameter, leaf number per branch, leaf area per branch, node number per branch, total branch wt. branch weight except leaves and leaf weight per branch of the mulberry trees. The results obtained are summarized as follows: 1. Variances of the characters and covariances between the each characters are shown in table 1, and simple correlation coefficients among various characters are shown in table 2. It was observed that there were close relationships between yield (leaf weight) and branch length, branch diameter, leaf number per branch, leaf are per branch, node number per branch, total branch weight and branch weight except leaves, respectively. 2. Partial correlation coefficients among some characters are shown in table 3. From this table, it was also observed that leaf yield of mulberry trees and leaf area are more closely related more than leaf yield and the other characters of mulberry trees in four different varieties. From the experimental studies, it was recognized that the four characters, namely branch length, branch diameter, leaf number and leaf area, should be very useful characters in the estimation of mulberry leaf yield as they could be measured. or counted easily before harvest of mulberry leaves, and are affected more in mulberry 1eaf yields than the other characters.