• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.2
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• pp.149-153
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• 1999

Prediction of rice developmental stage is necessary for proper crop management and a prerequisite for growth simulation as well. The objectives of the present study were to find out the relationship between the plastochrone index(PI) and the developmental index(DVI) estimated by non-parametric phenology model which simulates the duration from seedling emergence(DVI=0) to heading(DVI=l) by employing daily mean air temperature and daylength as predictor variables, and to confirm the correspondency of developmental indice to panicle developmental stages based on this relationship. Four japonica rice cultivars, Kwanakbyeo, Sangpungbyeo, Dongjinbyeo, and Palgumbyeo which range from very early to very late in maturity, were grown by sowing directly in dry paddy field five times at an interval of two weeks. Data for seedling emergence, leaf appearance, differentiation stage of primary rachis branch and heading were collected. The non-parametric phenology model predicted well the duration from seedling emergence to heading with errors of less than three days in all sowings and cultivars. PI was calculated for every leaf appearance and related to the developmental index estimated for corresponding PI. The stepwise polynomial analysis produced highly significant square-rooted cubic or biquadratic equations depending on cultivars, and highly significant square-rooted biquadratic equation for pooled data across cultivars without any considerable reduction in accuracy compared to that for each cultivar. To confirm the applicability of this equation in predicting the panicle developmental stage, DVI at differentiation stage of primary rachis branch primordium was calculated by substituting PI with 82 corresponding to this stage, and the duration reaching this DVI from seedling emergence was estimated. The estimated duration revealed a good agreement with that observed in all sowings and cultivars. The deviations between the estimated and the observed were not greater than three days, and significant difference in accuracy was not found for predicting this developmental stage between those equations derived for each cultivar and for pooled data across all cultivars tested.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.789-802
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• 2021

Synthetic Aperture Radar (SAR) at C-band is an ideal remote sensing system for crop monitoring owing to its short wavelength, which interacts with the upper parts of the crop canopy. This study evaluated the potential of dual polarimetric Sentinel-1 at C-band for monitoring rice phenology. Rice phenological variations occur in a short period. Hence, the short revisit time of Sentinel-1 SAR system can facilitate the tracking of short-term temporal morphological variations in rice crop growth. The sensitivity of SAR backscattering coefficients, backscattering ratio, and polarimetric decomposition parameters on rice phenological stages were investigated through a time-series analysis of 33 Sentinel-1 Single Look Complex images collected from 10th April to 25th October 2020 in Gimhae, South Korea. Based on the observed temporal variations in SAR parameters, we could identify and distinguish the phenological stages of the Gimhae rice growth cycle. The backscattering coefficient in VH polarisation and polarimetric decomposition parameters showed high sensitivity to rice growth. However, amongst SAR parameters estimated in this study, the VH backscattering coefficient realistically identifies all phenological stages, and its temporal variation patterns are preserved in both Sentinel-1A (S1A) and Sentinel-1B (S1B). Polarimetric decomposition parameters exhibited some offsets in successive acquisitions from S1A and S1B. Further studies with data collected from various incidence angles are crucial to determine the impact of different incidence angles on polarimetric decomposition parameters in rice paddy fields.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.44-48
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• 2016

Extreme temperature impacts on field crop are of key concern and increasingly assessed, however the studies have seldom taken into account the automatic adaptations such as shifts in planting dates, phenological dynamics and cultivars. In this present study, trial data on rice phenology, agro-meteorological hazards and yields during 1981-2009 at 120 national agro-meteorological experiment stations were used. The detailed data provide us a unique opportunity to quantify extreme temperature impacts on rice yield more precisely and in a setting with automatic adaptations.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.11-20
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• 2015

This study aimed to investigate the canopy growth conditions and the accuracy of phenological stages of paddy rice using ground-based remote sensing data. Plant growth variables including Leaf Area Index (LAI) and canopy reflectance of paddy rice were measured at the experimental fields of Chonnam National University, Gwangju, Republic of Korea during the crop seasons of 2011, 2012, and 2013. LAI values were also determined based on correlations with Vegetation Indices (VIs) obtained from the canopy reflectance. Three phenological stages (tillering, booting, and grain filling) of paddy rice could be identified using VIs and a spatial index (NIR versus red). We found that exponential relationships could be applied between LAI and the VIs of interest. This information, as well as the relationships between LAI and VIs obtained in the present study, could be used to estimate and monitor the relative growth and development of rice canopies during the growing season.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• Korean Journal of Environmental Biology
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• v.38 no.2
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• pp.222-230
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• 2020

Temperature-dependent development models for Hydrochara affinis were built to estimate the ecological parameters as fundamental research for monitoring the impact of climate change on rice paddy ecosystems in South Korea. The models predicted the number of lifecycles of H. affinis using the daily mean temperature data collected from four regions (Cheorwon, Dangjin, Buan, Haenam) in different latitudes. The developmental rate of each life stage linearly increased as the temperature rose from 18℃ to 30℃. The goodness-of-fit did not significantly differ between the models of each life stage. Unlike the optimal temperature, the estimated thermal limits of development were considerably different among the models. The number of generations of H. affinis was predicted to be 3.6 in a high-latitude region (Cheorwon), while the models predicted this species to have 4.3 generations in other regions. The results of this study can be useful to provide essential information for estimating climate change effects on lifecycle variations of H. affinis and studies on biodiversity conservation in rice fields.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.56 no.3
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• pp.255-263
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• 2011

Projected increases in atmospheric $CO_2$ concentration ([$CO_2$]) and temperature ($T_a$) have the potential to alter in rice growth and yield. However, little is known about whether $T_a$ warming with elevated [$CO_2$] modify plant architecture. To better understand the vertical profiles of leaf area index (LAI) and the flag leaf morphology of rice grown under elevated $T_a$ and [$CO_2$], we conducted a temperature gradient field chamber (TGC) experiment at Gwangju, Korea. Rice (Oryza sativa L. cv. Dongjin1ho) was grown at two [$CO_2$] [386 (ambient) vs 592 ppmV (elevated)] and three $T_a$ regimes [26.8 ($\approx$ambient), 28.1 and $29.8^{\circ}C$] in six independent field TGCs. While elevated $T_a$ did not alter total LAI, elevated [$CO_2$] tended to reduce (c. 6.6%) the LAI. At a given canopy layer, the LAI was affected neither by elevated [$CO_2$] nor by elevated $T_a$, allocating the largest LAI in the middle part of the canopy. However, the fraction of LAI distributed in a higher and in a lower layer was strongly affected by elevated $T_a$; on average, the LAI distributed in the 75-90 cm (and 45-60 cm) layer of total LAI was 9.4% (and 35.0%), 18.8% (25.9%) and 18.6% (29.2%) in ambient $T_a$, $1.3^{\circ}C$ and $3.0^{\circ}C$ above ambient $T_a$, respectively. Most of the parameters related to flag leaf morphology was negated with elevated [$CO_2$]; there were about 12%, 5%, 7.5%, 15% and 21% decreases in length (L), width (W), L:W ratio, area and mass of the flag leaf, respectively, at elevated [$CO_2$]. However, the negative effect of elevated [$CO_2$] was offset to some extent by $T_a$ warming. All modifications observed were directly or indirectly associated with either stimulated leaf expansion or crop phenology under $T_a$ warming with elevated [$CO_2$]. We conclude that plant architecture and flag leaf morphology of rice can be modified both by $T_a$ warming and elevated [$CO_2$] via altering crop phenology and the extent of leaf expansion.

• Korean journal of applied entomology
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• v.61 no.2
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• pp.335-347
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• 2022

We investigated the emergence patterns of Chilo suppressalis (Lepidoptera: Crambidae) adults using sex pheromone traps in the three northeastern areas, Dandong (40°07'N 124°23'E) (Liaoning province), and Gongzhuling (43°30'N 124°49') and Longjing (42°46'N 129°26'E) (Jilin province), China, in 2020 and 2021. Two times of adult flight seasons were isolated clearly during the rice growing periods in the all areas, in which the first season from mid May to late July, and the second season from mid July to mid September were observed. The adult emergence seasons in the areas at higher latitude were later than that at lower latitude. Using the adult emergence data during the first flight seasons, the second flight seasons were estimated through insect phenology modelling, and compared with the observed data. Temperature-dependent life history models (developmental rate, development completion, survival rate, adult aging rate, total fecundity, oviposition completion, and adult survival completion) were collected or constructed for each life stage of C. suppressalis, in which the data from the four previous studies were used. Those models were combined in an insect phenology estimation software, PopModel, and operated for the observed areas. In the results, the phenology modelling operated with the models based on the data of shorter larval periods in the previous studies estimated more accurately the second flight seasons. In 2021, we investigated the change of damaged hill ratios of rice with observing the adult emergence at Dandong and Longjing, 2021. The increase periods of damaged hill ratios of rice were observed two times during the total rice cultivation season, which may be caused by different generations of C. suppressalis larvae.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.282-290
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• 2013

Biophysical and biochemical processes through which crops interact with the atmosphere have been simulated using land surface models and crop growth models. The Noah Multi Physics (MP) model and the CERES-Rice model, which are a land surface model, and a crop growth model, respectively, were used to simulate and compare rice growth and evapotranspiration (ET) in the areas near Haenam flux tower in Korea. Simulations using these models were performed from 2003 to 2012 during which flux measurements were obtained at the Haenam site. The Noah MP model failed to simulate the pattern of temporal change in leaf area index (LAI) after heading. The simulated aboveground biomass with the Noah MP model was underestimated by about 10% of the actual biomass. The ET simulated with the Noah MP model was as low as 21% of those with the CERES-Rice model. In comparison with actual ET measured at Haenam flux site, the root mean square error (RMSE) of the Noah MP model was 1.8 times larger than that of the CERES-Rice model. The Noah MP model seems to show less reliable simulation of crop growth and ET due to simplified phenology processes and assimilates partitioning compared with the CERES-Rice model. When ET was adjusted by the ratio between leaf biomass simulated using CERES-Rice model and Noah MP model, however, the RMSE of ET was reduced by 30%. This suggests that an improvement of the Noah MP model in representing rice growth in paddy fields would allow more reliable simulation of matter and energy fluxes.