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

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 2001.11a
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• pp.178-180
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• 2001

작물의 엽면적 등 다양한 생육정보를 간편하고 비파괴적으로 추정할 수 있다면 작물의 생리 생태학적 모델에의 적용을 통하여 다양한 작물 연구에 중요한 공헌을 할 수 있다. 본 연구에서는 오이 개개 잎의 형태정보를 이용하여 오이의 개개 엽면적, 생체중 및 건물중 예측하는 것을 목적으로 하였고, 이를 위하여 엽면적은 5가지 모델을 사용하였고, 생체중 및 건물중은 6가지의 모델을 사용하여 분석하였다. 또한 신경회로망은 3 layer의 back propagation method를 사용하여 분석하였다. 각 모델들은 독립변수로는 Robinson ＆ Pharr이 사용한 개개 잎의 폭 및 길이를 사용하였다. 회귀모델에 의한 추정 결과, 모델의 정확성 및 정밀성은 엽면적 > 생체중 > 건물중 순 이었지만, 특히 건물중의 경우는 상대적으로 낮은 상관관계를 가지는 것으로 나타났다. 회귀모델을 사용하여 건물중 추정하는 것에는 한계가 있는 것으로 생각되며, 신경회로망도 이와 유사한 관계를 나타냈지만 다양한 변수 수정을 통하여 상관계수를 증가시킬 수 있을 것이라고 생각된다.

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

• KOREAN JOURNAL OF CROP SCIENCE
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• v.34 no.4
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• pp.364-369
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• 1989

Leaf characteristics of main stem and tiller of IK type maize (IK/ /IRI/B68) were compared with those of Jinjoo Ok hybrid which are not usually tillered. A total of nine leaves from flag leaf to the third or the fourth leaf below ear-bearing node were sampled from each stem or tiller. There was no significant difference in mean leaf length between IK/ /IRI/B68 and Jinjoo Ok. But the mean leaf width of IK/ /IRI/ B68 was about 2 cm narrower than that of Jinjoo Ok. The mean leaf area of the IK/ /IRI/B68 was also smaller than that of Jinjoo Ok due to the narrower leaf width. There were not significant differences in mean leaf characteristics between main stem and tillers of IK/IRI/B68. The longest leaf was the leaf below the ear-bearing node and the widest leaf was the leaf just above the ear-bearing node. Mean length. width and area of leaf on main stem and tillers were similar. Coefficients of variation calculated for individual leaf indicated that the leaves near the ear-bearing node were more uniform than others. The leaf area measured was significantly greater than that estimated by formular, length x width x 0.75. New constant to estimate leaf area of tillering maize was derived as 0.8.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.232-238
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• 2014

We have developed a non-destructive, touch-free method for estimating leaf areas with a structured-light three-dimensional (3D) scanner. When the surfaces of soybean leaves were analyzed with both the 3D scanner and a leaf area meter, the results were linearly related ($R^2=0.90$). The strong correlation ($R^2=0.98$) was calculated between shoot fresh weights and leaf areas when the scanner was employed during growth stages V1 to V4. We also found that leaf areas measured by the scanner could be used to detect changes in growth responses to abiotic stress. Whereas under control conditions the areas increased over time, salt and drought treatments were associated with reductions in those values after 14 d and 12 d, respectively. Based on our findings, we propose that a structured-light 3D scanner can be used to obtain reliable estimates of leaf area and plant biomass.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.90-92
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• 2022

이 논문에서는 합성된 애기장대 데이터셋을 활용하여 딸기의 엽면적을 추정할 수 있는 딥러닝 모델을 제안한다. 제안된 모델에서는 개별 잎 검출을 위하여 합성 데이터셋으로 학습된 Mask R-CNN 의 객체 검출 모델을 사용하였고, 이어 이미지 후처리 작업에 해당되는 모폴로지 연산의 침식 및 팽창, 픽셀 카운터를 통해 엽면적을 추정하였다. 각기 다른 역할을 수행하는 신경망 계층에 어텐션 메커니즘 적용하여 검출 성능의 향상과 검출 시간을 단축하였다. 제안된 모델은 딸기 데이터셋을 사용하지 않는 합성된 데이터셋만으로도 실제 온실에서 획득한 다양한 이미지에서의 딸기 엽면적을 추정하는 데에 우수한 성능을 보여준다.

• Journal of Korean Society of Forest Science
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• v.84 no.2
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• pp.186-197
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• 1995

Site-specific allometric equations relating aboveground tree component biomass and leaf area to tree diameter, basal area, sapwood cross-sectional area and sapwood volume were developed using the destructive harvesting method for Pinus rigida Mill., Larix leptolepis Gordon, and Quercus serrata Thunb. stands in Yangpyeong, Kyonggi Province. There were significantly strong correlations between aboveground tree component biomass or leaf area and diameter at breast height (DBH), basal area, sapwood area and sapwood volume. For a similar diameter tree, the three species had a similar stem wood biomass. However, carbon allocation patterns to stem bark, foliage, branch and total aboveground biomass differed among the three species. Specific leaf area and the ratio of leaf area to sapwood cross-sectional area of the three species were significantly different. Allometric equations seemed To be related to leaf habit or leaf longevity. To elucidate the effect of leaf habit or leaf longevity on allometry and canopy characteristics clearly, more intensive studies are needed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.78-82
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• 2022

Phenology determines the timing of crop development, and the timing of phenological events is strongly influenced by the temperature during the growing season. In process-based model, leaf area is simulated dynamically by coupling of morphology and phenology module. Therefore, the prediction of leaf appearance rate and final leaf number affects the performance of whole crop model. The dataset for the model equation was collected from SPA R chambers with five different temperature treatments. Beta distribution function (proposed by Yan and Hunt (1999)) was used for describing the leaf appearance rate as a function of temperature. The optimum temperature and the critical value were estimated to be 26.0℃ and 35.3℃, respectively. For evaluation of the model, the accumulated number of onion leaves observed in a temperature gradient chamber was compared with model estimates. The model estimate is the result of accumulating the daily increase in the number of onion leaves obtained by inputting the daily mean temperature during the growing season into the temperature model. In this study, the coefficient of determination (R²) and RMSE value of the model were 0.95 and 0.89, respectively.

• The Bimonthly Magazine for Agrochemicals and Plant Protection
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• v.6 no.12
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• pp.77-82
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• 1985

금년 보리파종기에는 유난스럽게도 비가 많이 왔고 비오는 일수가 잦아 가을장마라고도 하였다. 따라서 벼 수확이 늦어졌고 벼를 벤 논은 물론이고 밭에서까지 보리파종작업이 어려웠던 탓으로 예년에는 전국적으로 만파면적이 20$\%$내외 이던 것이 금년에는 70$\%$가 될 것으로 추정하고 있다. 보리가 겨울을 잘나기 위해서는 적파(適播)하여 주간의 잎이 4$\~$5매가 되어야 하는데 늦게 심어 1$\~$2매로 월동하게 되었으니 겨울동안 특별한 관리를 하지 않는 한 수량이 떨어지고 내년도의 출수기와 성숙기가 늦어질 염려가 있다. 그러나 이러한 피해는 겨울철 보리밭 관리의 철저로 어느 정도는 막을 수 있다.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.115-121
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• 2023

The leopard plant has the characteristic of being used for ornamental purposes when there are yellow spots on the leaves, and is widely used as a bed plant for viewing flowers. To set several indicators to predict the growth of crops with ornamental value, and to quantitatively express the relationship between the indicators are necessary. In this study, we determine a model that estimates the leaf area and the number of flower of Farfugium japonicum Kitam. using leaf length and width, and conducting a regression analysis on some regression models. As an indicator for estimating the leaf area and the number of flower, the leaf length and width of F. japonicum were measured and applied to 8 regression models. As a result of regression analysis of 8 models that estimated leaf area and the number of flower, R² values of the linear models were all higher than 0.84 and 0.80. As a result of validation, using the most reliable model among the models for estimating the leaf area and the number of flowering, R² was 0.90 and 0.82, respectively. Using a model that estimates various indicators that can be used for quality evaluation from easy-to-measure morphological factors, the evaluation of ornamental plants will be facilitated.