• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.346-358
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• 2023

Due to the acceleration of climate change or global warming, it is important to predict rice productivity in the future and investigate physiological changes in rice plants. The research aimed to explore how rice adapts to climate change by examining the response of nitrogen absorption and nitrogen use efficiency in rice under elevated levels of carbon dioxide and temperature, utilizing the SPAR system for analysis. The temperature increased by +4.7 ℃ in comparison to the period from 2001 to 2010, while the carbon dioxide concentration was held steady at 800 ppm, aligning with South Korea's late 21st-century RCP8.5 scenario. Nitrogen was applied as fertilizer at rates of 0, 9, and 18 kg 10a^-1, respectively. Under conditions of climate change, there was an 81% increase in the number of panicles compared to the present situation. However, grain weight decreased by 38% as a result of reduction in the grain filling rate. BNUE, indicative of the nitrogen use efficiency in plant biomass, exhibited a high value under climate change conditions. However, both NUEg and ANUE, associated with grain production, experienced a notable and significant decrease. In comparison to the current conditions, nitrogen uptake in leaves and stems increased by 100% and 151%, respectively. However, there was a 25% decrease in nitrogen uptake in the panicle. Likewise, the nitrogen content and NDFF (Nitrogen Derived from Fertilizer) in the sink organs, namely leaves and roots, were elevated in comparison to current levels. Therefore, it is imperative to ensure resources by mitigating the decrease in ripening rates under climate change conditions. Moreover, there seems to be a requirement for follow-up research to enhance the flow of photosynthetic products under climate change conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.398-403
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• 2023

Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R²=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.88-96
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• 2024

This study was conducted to determine the optimal light conditions for the in situ and ex situ conservation and restoration of Osmanthus insularis, a rare plant species in South Korea. Evaluations included the growth performance, leaf morphological features, photosynthetic characteristics, and photosynthetic pigment contents of seedlings grown from April to November under different light conditions (100%, 55%, 20%, and 10% relative light intensity). The shoot lengths and root collar diameters did not differ significantly with relative light intensity. The dry weights of leaves, stems, and roots and the leaf number were highest at 55% relative light intensity. The leaf shape showed morphological acclimation to light intensity, with leaf area decreasing and thickness increasing as the relative light intensity increased. Several leaf parameters, including photosynthetic rate and stomatal conductance at light saturation point, net apparent quantum yield, and dark respiration, as well as chlorophyll a, chlorophyll b, and carotenoid contents, were all highest at 55% relative light intensity. Under full light conditions, the leaves were the smallest and thickest, but the chlorophyll content was lower than at 55% relative light intensity, resulting in lower photosynthetic ability. Plants grown at 10% and 20% relative light intensity showed lower chlorophyll a, chlorophyll b, and carotenoid contents, as well as decreased photosynthetic and dark respiration rates. In conclusion, O. insularis seedlings exhibited morphological adaptations in response to light intensity; however, no physiological responses indicating enhanced photosynthetic efficiency in shade were evident. The most favorable light condition for vigorous photosynthesis and maximum biomass production in O. insularis seedlings appeared to be 55% relative light intensity. Therefore, shading to approximately 55% of full light is suggested for the growth of O. insularis seedlings.