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

• Korean Journal of Poultry Science
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• v.51 no.2
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• pp.57-63
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• 2024

As global warming worsens, it is feared that higher ambient temperatures and relative humidity might result in a more intense heat stress for livestock animals, especially broilers, which lack sweat glands for thermoregulation and have been selectively bred for rapid growth. Therefore, strategic livestock management is needed to mitigate the adverse effects of heat stress on broilers. In Korea's poultry farming systems, tunnel-ventilated broiler houses and pad cooling systems are commonly installed to lower indoor temperatures during the summer. However, caution is advised with pad cooling systems as they can increase the humidity inside the houses, potentially causing further harm. This study aimed to evaluate the effectiveness of pad cooling systems in tunnel-ventilated broiler house by assessing the reduction in indoor temperature using the Temperature-Humidity Index (THI), which accounts for the impact of relative humidity. Temperature and humidity data were collected during the summer (Jun to Sep) from eight farms with tunnel-ventilated broiler house located in different regions of Korea. The farms were divided into two groups based on the use of pad cooling systems is used, and temperature and humidity data, along with THI values, were analyzed two weeks before the birds were marketed. Meta-analysis results showed that at the hottest time of the day, 14:00, farms with pad cooling systems had significantly lower indoor temperatures compared to the control group, but observed an increase in indoor temperatures by 16:00 (p<0.05). There is no significant difference in relative humidity (p>0.05). The THI values decreased in the treatment group with cooling pads compared to the control group starting from 15:00, suggesting a diminished effect (p<0.05). This study indicates the potential for developing optimal operational guidelines for cooling pads to reduce heat stress in broilers during the summer season.