A smart agricultural system is necessary for monitoring crop growth and stress conditions using near-ground-based remote sensing techniques. Crop growth can be estimated using several standard crop growth parameters. However, obtaining timed sequential data for observing leaf area index (LAI) is challenging, and normalized difference vegetation index (NDVI) estimation in crop fields requires the installation of sensors on frames structure that are taller than the crop. Canopy light transmittance (CLT) indicates the degree of decrease in the amount of light passing through some material. It was conventionally used to understand canopy radiative transfer. This study examined the viability of CLT as a novel crop parameter for monitoring crop growth conditions. The CLT, LAI, and NDVI of a garlic field were recorded for five years. The correlation between daily CLT and LAI was higher than that between NDVI and LAI. Thus, CLT has the potential to sequentially estimate crop LAI values, particularly for capturing the temporal patterns of LAI. In addition, like NDVI, CLT showed sensitivity in representing the canopy structure and the amount of biomass because CLT is conceptually related to the sky gap fraction. Thus, CLT has the potential to serve as a novel growth parameter for continuous crop growth monitoring.

Vegetation indices based on selected wavelength reflectance measurements are used to represent crop growth and physiological conditions. However, it has been determined that the anisotropic properties of the crop canopy surface can govern both the spectral reflectance and vegetation indices. In this study, in order to investigate how crop surface reflectance and vegetation indices varied according to the direction of the light source and sensor viewing, a hyper -spectrometer of visible to nearinfrared wavelengths mounted on a field goniometer was used at vegetative and reproductive growth stages in rice paddy. It was found that most of the wavelength reflectance measurements produced by the sparse vegetation cover fraction were not sensitive to solar -illumination and sensor -viewing angles. In addition, the reflectance of visible wavelengths was found to be less sensitive to the solar and sensor angles than the red -edge and near -infrared wavelengths. The lowest normalized difference vegetation index value in a day occurred at the nadir sensor -viewing angle before rice heading, but after heading, when ripened grains began to bow, the lowest value was recorded at the sensor zenith angle of 25(degrees). Enhanced vegetation index measurements were found to be more sensitive to the direction of sensor viewing and less affected by sun glint than normalized difference vegetation index measurements. Additional field observation measurements should increase our level of understanding of how vegetation indices change on anisotropic crop surfaces.

Abs tr ac t. The soil CO2 emissions from rice paddy fields have a significant influence on net CO2 fluxes throughout the year. Unlike other agroecosystems, rice paddy fields are flooded for most of the growing season. Over the course of this study, soil CO2 emissions in rice paddy fields were observed under fallow, flooded, and drainage conditions using a closed-system portable chamber. It was found that the dried and bare soil in fallow paddy systems emit a significant amount of CO2. On the other hand, the CO2 released from the soil during flooding periods was suppressed by the water layer. In drainage conditions, the exponential curve of the relationship between soil CO2 emissions and soil temperature was particularly evident. These results suggest that soil CO2 emissions during fallow and drainage periods can exceed the level of CO2 emissions that is suppressed under flooded conditions. However, immediately after draining or the occurrence of a rainfall event, the suppression of soil CO2 emission by residual paddy water will provide valuable insights in the interpretation of agricultural carbon cycle models.

Rice is one of the major food crops, particularly in Asia. However, it is vulnerable to high temperature and has high yield fluctuations. Monitoring crop growth and physiological responses to high temperatures can help us better understand the agricultural impacts of global warming. The aim of this study is to monitor growth, development, and physiological responses to high temperature conditions on paddy rice and to assess their combined effects on yield. In this study, changes to growth, maturity, and senescence in paddy rice throughout the growing season were identified under elevated air temperature conditions created by a temperature gradient field chamber (TGFC). That facility provides a gradient from the ambient air temperature (AT) to 3 °C above AT (AT + 3 °C). To represent crop physiology and productivity, we measured the plant height, chlorophyll, normalized difference vegetation index (NDVI), and maximum photosynthetic rate (Amax) to assess growth and physiological processes, and heat stress effects on four yield measurements were assessed using the heating degree day index. Rice height increased more rapidly in the AT + 3 °C treatment from the early growth stage to heading, while SPAD and NDVI decreased more rapidly at AT after heading. The Amax of AT and AT + 3 °C was not significantly different in the tillering stage. However, it was higher at AT in the booting stage but higher at AT + 3 °C in the grain filling stage. These results indicate that paddy rice was not affected by heat stress at the tillering stage, but a cumulative effect emerged by the booting stage. Further, photosynthetic capacity was maintained much later into the grain filling stage at AT + 3 °C. These results will be useful for understanding the growth and physiological responses of paddy rice to global warming.

Vegetation indices based on selected wavelength reflectance measurements are used to represent crop growth and physiological conditions. However, the anisotropic properties of the crop canopy surface can govern spectral reflectance and vegetation indices. In this study, we applied an ensemble of bidirectional reflectance distribution function (BRDF) models to high-resolution Sentinel -2 satellite imagery and compared the differences between correction results before and after reflectance. In the red and near-infrared (NIR) band reflectance images, BRDF-corrected outlier values appeared in certain urban and paddy fields of farmland areas and forest shadow areas. These effects were equally observed when calculating the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2). Furthermore, the outlier values in corrected NIR band were shown in pixels shadowed by mountain terrain. These results are expected to contribute to the development and improvement of BRDF models in high-resolution satellite images.

considering not only soil moisture deficit but also heat conditions. In this study, we measured the MERIS terrestrial chlorophyll index (MTCI) and chlorophyll/carotenoid index (CCI) under drought and heat wave conditions. The MTCI, sensitive to chlorophyll concentration, sensitively decreased on non irrigation conditions and the degree was larger with heat waves. On the other hand, the CCI, correlated with photosynthesis efficiency, showed less sensitivity to water deficit but had decreased significantly with heat waves. After re-irrigation, the MTCI was increased than before damage and CCI became more sensitive to heat stress. These results are expected to contribute to evaluating the intensity of crop water stress through remote sensing techniques. The intensity of crop water stress caused by moisture deficit is affected by growth and heat conditions. For more accurate detection of crop water stress state using remote sensing techniques, it is necessary to select vegetation indices sensitive to crop response and to understand their changes

The irrigation schedule system using early detection of crop water stress is required to maintain crop production and save water resource. However, because previous studies focused on the crop under stress dominant condition, the crop physiological properties, which can be measured by remote sensing technique, on early crop water stress condition are not well known. In this study, the canopy temperature, MERIS Terrestrial Chlorophyll Index (MTCI), and Chlorophyll/Carotenoid Index (CCI) are observed on the soybeans given the early water stress using thermal imaging camera and hyperspectral camera. The increased canopy temperature and decreased MTCI are consist with the previous studies which are for the crop of stress dominant-sign. However, the CCI was increased contrary to expectation because it may faster the reduction of carotenoid than chlorophyll in early stage. These behaviors will be useful to not only develop the irrigation system but also using the early detection of crop stress.

The leaf temperature is principally regulated by the opening and closing of stomata that is sensitive to various kinds of plant physiological stress. Thus, the analysis of thermal imagery, one of remote sensing technique, will be useful to detect crop physiological condition on smart farm system and phenomics platform. However, there are few case studies using a thermal imaging camera on the agricultural application. In this study, three cases are presented: the effect of lime fertilizer on the rice, the different physiological properties of soybean under shading condition, and the screening of soybean breeds for salinity tolerance characteristic. The leaf temperature measured by thermal imaging camera on the three cases was used effectively to the physiological change and characteristics. However, the thermal imagery analysis requires considering the accuracy of measured temperature and the weather conditions that affects to the leaf temperature.