• Korean Journal of Organic Agriculture
• /
• v.15 no.3
• /
• pp.319-330
• /
• 2007

This study analyzed physical and chemical characteristics of peat soil to use peat soil as the materials fur pot media and investigated seedling quality of horticultural plants in order to use peat soil as the raw materials fur pot media. The summary of the results is as follows; The chemical characteristics of peat soil, which is main ingredient of pot media are as follows; pH was 4.9, EC was less than $2.0ds{\cdot}m^{-1}$, which interferes the growth of the plant and organic ingredient was 33%. When looking into the germination characteristics of plants according to the mixture of pot media, red pepper showed 54.2% speed of germination and 97% germination rate in peat soil single treatment. Therefore the peatsoil was appropriate for the pot media for red pepper. In case of cucumbers, in the 50 : 50 treatment of main ingredient (peat soil) and auxiliary ingredients (vermiculite, peat moss and perlite) they showed 100% speed of germination and 100% germination rate. Therefore 50 : 50 treatment was appropriate fur the pot media for cucumbers. In case of chinese cabbage, peat soil, perlite and peat moss mixture (50 : 25 : 25) treatment showed the highest speed of germination (77.5%), while the germination rate was a little lower (92.15%) than comparative soil. However, it was appropriate for the pot media for chinese cabbage. In case of watermelon, germination was bad because of the influence of EC when the teat soil ingredient is over 80%. However, in the mixture of peat soil and vermiculite (50:50) treatment, they showed 91.6% speed of germination and 100% germination rate. Therefore it was appropriate for the pot media for watermelon. When looking into the growth of the plants according to the mixture of ingredients, peat soil and perlite (50:50) mixture showed excellent seedling quality for cucumbers, peat soil and perlite (50:50) mixture showed excellent seedling quality and it was proven to be appropriate for the pot media for cucumbers. In case of watermelon, peat soil, peat moss and perlite (80 : 10 : 10) mixture showed excellent seedling quality and it was proven to be appropriate for the pot media for watermelon.

• Journal of Bio-Environment Control
• /
• v.31 no.4
• /
• pp.409-415
• /
• 2022

Plant growth and development are also affected by root-zone environment. Therefore, it is important to consider the variables of the root-zone environment when establishing an irrigation strategy. The purpose of this study is to analyze the relationship between the volumetric moisture content (VWC), Bulk EC (ECb), and Pore EC (ECp) used by plant roots using FDR sensors in two types of rockwool media with different water transmission characteristics, using the method above this was used to establish a method for collecting and correcting available root-zone environmental data. For the experiment, two types of rockwool medium (RW1, RW2) with different physical characteristics were used. The moisture content (MC) and ECb were measured using an FDR sensor, ECp was measured after extracting the residual nutrient solution from the medium using a disposable syringe in the center of the medium at a volumetric moisture content (VWC) of 10-100%. Then, ECb and ECp are measured by supplying nutrient solution having different concentration (distilled water, 0.5-5.0) to two types of media (RW1, RW2) in each volume water content range (0 to 100%). The relationship between ECb and ECp in RW1 and RW2 media is best suited for cubic polynomial. The relationship between ECb and ECp according to volume moisture content (VWC) range showed a large error rate in the low volume moisture content (VWC) range of 10-60%. The correlation between the sensor measured value (ECb) and the ECp used by plant roots according to the volumetric water content (VWC) range was the most suitable for the Paraboloid equation in both media (RW1, RW2). The coefficient of determination the calibration equation for RW1 and RW2 media were 0.936, 0.947, respectively.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.4
• /
• pp.427-435
• /
• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.