A remote sensing-integrated crop model (RSCM) able to simulate crop growth processes using proximal or remote sensing data was formulated for simulation of soybean through estimating parameters required for modelling. The RSCM-soybean was then evaluated for its capability of simulating leaf area index (LAI), above-ground dry mass (AGDM), and yield, utilising the proximally sensed data integration into the modelling procedure. Field experiments were performed at two sites, one in 2017 and 2018 at Chonnam National University, Gwangju, and the other in 2017 at Jonnam Agricultural Research and Extension Services in Naju, Chonnam province, South Korea. The estimated parameters of radiation use efficiency, light extinction coefficient, and specific leaf area were 1.65 g MJ⁻¹, 0.71, and 0.017 m² g⁻¹, respectively. Simulated LAI and AGDM values agreed with the measured values with significant model efficiencies in both calibration and validation, meaning that the proximal sensing data were effectively integrated into the crop model. The RSCM reproduced soybean yields in significant agreement with the measured yields in the model assessment. The study results demonstrate that the well-calibrated RSCM-soybean scheme can reproduce soybean growth and yield using simple input requirement and proximal sensing data. RSCM-soybean is easy to use and applicable to various soybean monitoring projects.

Extremely high air temperature at the heading stage of paddy rice causes a yield reduction due to the increasing spikelet sterility. Quantifying the damage to crops caused by high temperatures can lead to more accurate estimates of crop yields. The remote sensing technique evaluates crop conditions indirectly but provides information related to crop physiology, growth, and yield. In this study, we aim to assess the crop damage caused by heat stress in paddy rice examined under elevated air temperatures in a temperature gradient field chamber from 2016 to 2019, using remote-sensed vegetation indices. A leaf-spectrometer, field-spectrometers, and a multi-spectral camera were used to monitor the conditions of paddy rice. Although, in the leaf- and canopy-scales, the values of normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI) decreased after the heading of rice under normal conditions, the decreasing sensitivity of NDVI and PRI was different depending on the degree of physiological heat stress by high temperature conditions. The NDVI after the heading under extremely high air temperature was not dropped and remained the value before heading. The PRI decreased at all air temperature conditions after the heading; the PRI of the plot exposed to the elevated air temperature was higher than that under ambient air temperature. Further, the relative change in NDVI and PRI after the heading exhibited a strong relationship with the ripening ratio of paddy rice, which is the variable related to crop yield. These remote-sensing results aid in evaluating the crop damage caused by heat stress using vegetation indices.

In temperate monsoon areas, major constraints of soybean production in drained paddy fields are excess soil water during monsoon seasons. To further understand how agronomic practices and weather course affect the yield of soybeans, we conducted field experiments at Gwangju, Korea (35°10′ N, 126°53′ E) over three years (2018–2020). Double-crop soybeans were grown at two tillage systems (TS) [rotary tillage (RT), deep plowing followed by rotary tillage (DPRT)] and three sowing dates (SD) (June 10–15, June 25–30, and July 10–15) in drained paddy fields. Flowering phenology (R2) was accelerated by 5 days with each 15-day delay in SD. This resulted in a significant reduction in vegetative growth up to R2, with subsequent reductions in CGR and NAR through R2–R5 (beginning of grain filling). With a 30-day delay in SD, yield was significantly reduced by 27.0%. The better performance of RT over DPRT was demonstrated by greater yields (13.7%). In addition, yield was greatly varied with weather volatility among years, ranging from 123.8 to 552.0 g m⁻². Weather volatility was the greatest contributor to yield variability (30.4%), followed by SD (17.0%) and TS (10.3%). Our results suggest that the yield might be mainly determined by how much growth has already been achieved before flowering and through R2–R5.

The effects of biochar (BC) on methane (CH 4) emission may vary with nitrogen (N) fertilization rate, organic inputs, and water management. In this short review, we studied the changes in the direction and magnitude of CH 4 emission by BC under these different conditions. Literature data indicated that co-application of BC with N fertilizer may increase or decrease CH 4 emission depending on the N fertilization rates. Although the threshold N fertilization rate for the enhanced CH 4 emission by BC is unclear, it was suggested that N fertilization may enhance BC-induced CH 4 oxidation via the supply of N to methanotrophs. Although organic inputs stimulate CH 4 emission, co-application of BC with organic inputs efficiently decreases CH 4 emission by reducing C substrate availability for methanogens via sorption onto BC particles. The application of BC also enhances CH 4 oxidation under water-saving irrigation to stimulate the methanotroph activity under aerobic conditions. Our study suggests that application of BC may be a measure to mitigate CH 4 emission from paddy soils amended with organic inputs and it may further enhance CH 4 oxidation under water-saving irrigation.

Rice (Oryza sativa L.) fields are major sources of methane (CH 4) which is the second most important greenhouse gas after carbon dioxide. Methane is known to be released mainly through aerenchyma tissues of rice plants; however, CH 4 is also released from soil surface through ebullition and diffusion. However, little information is available for CH 4 emission directly from soil surface (MDFS). In this study, in order to enlarge our understanding of CH 4 emission from rice paddy fields, we investigated MDFS under different rice growth conditions such as temperature, fertilization, and rice straw input. Rice was cultivated using pots with different fertilization regime (chemical fertilizer vs. organic fertilizer + manure compost) with or without rice straw input under ambient or elevated (+3°C) temperature. Methane emissions from rice plants (including MDFS) and MDFS alone without rice plants were measured three times before mid-season drainage (MSD), in the course of MSD, and after MSD. The MDFS flux and its contribution to the total CH 4 emissions was not affected by temperature, fertilization, and rice straw inputs across the rice growing season. The mean total CH 4 flux and MDFS flux were 20.7 mg m-2 hr-1 and 0.22 mg m-2 hr-1 , respectively, and thus the portion of MDFS to total CH 4 emission was about 1%. However, MDFS flux in the early rice season increased by rice straw input and MDFS accounted for 5% of total CH 4 emission, probably due to increased CH 4 production by rice straw inputs at higher levels than the capacity of aerenchyma tissue to intake and transport the CH 4 produced in the early rice season with low tiller number. Our result indicate that MDFS may substantially contribute to the total CH 4 emission in the early season of rice cultivation with organic inputs.