• Proceedings of the Korean Society of Crop Science Conference
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• 2000.11a
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• pp.165-166
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• 2000

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.126-127
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• 2005

• Proceedings of the Korean Society of Crop Science Conference
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• 1998.04a
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• pp.127-128
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• 1998

• The Plant Pathology Journal
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• v.32 no.6
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• pp.508-518
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• 2016

Early blight of tomato caused by Alternaria solani, is responsible for severe yield losses in tomato. The conidia survive on soil surface and old dry lower leaves of the plant and spread when suitable climatic conditions are available. Macroclimatic study reveals that highest inoculum concentration of Alternaria spores appeared in May 2012 to 2013 and lowest concentration during January 2012 to 2013. High night temperature positively correlated and significantly (P < 0.01) involved in conidial spore dispersal and low relative humidity (RH) displayed significant (P < 0.05) but negative correlation with conidial dispersal. The objective of the study was to modify microclimatic conditions of tomato crop canopy which may hamper conidial dispersal and reduce disease severity. We evaluated effect of marigold intercropping and plastic mulching singly and in consortia on A. solani conidial density, tomato leaf damage and microclimatic parameters as compar to tomato alone (T). Tomato-marigold intercropping-plastic mulching treatment (T + M + P) showed 35-39% reduction in disease intensity as compared to tomato alone. When intercropped with tomato, marigold served as barrier to conidial movement and plastic mulching prevented evapotranspiration and reduced the canopy RH that resulted in less germination of A. solani spores. Marigold intercropping and plastic mulching served successfully as physical barrier against conidial dissemination to diminish significantly the tomato foliar damage produced by A. solani.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.187-195
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• 2019

The needs for precise diagnostics and farm management-decision aids have increased to reduce the risk of climate change and environmental stress. Crop simulation models have been widely used to search optimal solutions for effective cultural practices. However, limited knowledge on physiological responses to environmental variation would make it challenging to apply crop simulation models to a wide range of studies. Advanced research facilities would help investigation of plant response to the environment. In the present study, the sunlit controlled environment chambers, known as Korean SPAR (Soil-Plant-Atmosphere-Research) system, was developed by renovating existing SPAR system. The Korean SPAR system controls and monitors major environmental variables including atmospheric carbon dioxide concentration, temperature and soil moisture. Furthermore, plants are allowed to grow under natural sunlight. Key physiological and physical data such as canopy photosynthesis and respiration, canopy water and nutrient use over the whole growth period are also collected automatically. As a case study, it was shown that the Korean SPAR system would be useful for collection of data needed for understanding the growth and developmental processes of a crop, e.g., soybean. In addition, we have demonstrated that the canopy photosynthetic data of the Korean SPAR indicate the precise representation of physiological responses to environment variation. As a result, physical and physiological data obtained from the Korean SPAR are expected to be useful for development of an advanced crop simulation model minimizing errors and confounding factors that usually occur in field experiments.

• Journal of Bio-Environment Control
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• v.29 no.1
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• pp.20-27
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• 2020

The study was performed to calculate canopy temperatures and crop water stress index (CWSI) of 2-year-old 'Yumi' peach trees using thermal infrared imaging under different soil water conditions, and to evaluate availability for water stress determination. Canopy temperatures showed similar daily variations to air temperatures and they were higher during the daytime than air temperatures. Canopy temperatures for 24 h were correlated highly to air temperatures (r² =0.95), solar radiations (r² =0.74), and relative humidity (r² =-0.88). In addition, soil water potential showed a highly negative correlation to canopy temperatures (r² =-0.57), temperature differences between leaf and air (TD) (r² =-0.71), and CWSI (r² =-0.72) during the daytime (11 to 16 h). CWSI for 24 h was highly related to canopy temperatures (r² =0.90) and TD (r² =0.92), whereas CWSI was not correlated to soil water potential (r² =-0.27) for 24 h but related highly to water potential (r² =-0.72) during the daytime (11 to 16 h). Correlation coefficients between CWSI (y) and soil water potential (x) were highest from 11 to 12 h and a regression equation was deduced as y = -0.0087x + 0.14. CWSI was calculated as 0.575 at -50 kPa, which soil water stress generally occurs. Thus our result suggests that this regression equation using thermal infrared imaging is useful to evaluate soil water stress of peach trees.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.387-397
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• 2023

Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R² = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.216-217
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• 2019

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.340-345
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• 2020

In this study, we developed the quality control and assurance method of measurement data of SPAR (Soil-Plant-Atmosphere-Research) system, a climate change research facility, for the first time. It was found that the precise processing of CO2 flux data among many observations were sig nificantly important to increase the accuracy of canopy photosynthesis measurements in the SPAR system. The collected raw CO2 flux data should first be removed error and missing data and then replaced with estimated data according to photosynthetic lig ht response curve model. Comparing the correlation between cumulative net assimilation and soybean biomass, the quality control and assurance of the raw CO2 flux data showed an improved effect on canopy photosynthesis evaluation by increasing the coefficient of determination (R2) and lowering the root mean square error (RMSE). These data processing methods are expected to be usefully applied to the development of crop growth model using SPAR system.