Global warming has an impact on crop growth and development. Flowering time is particularly sensitive to environmental factors such as day length and temperature. In this study, we investigated the effects of global warming on flowering using an open-top Climatron chamber, which has a higher temperature and CO₂ concentration than in the field. Two different soybean cultivars, Williams 82 and IT153414, which exhibited different flowering times, were promoted flowering in the open-top Climatron chamber than in the field. We more specifically examined the expression patterns of soybean flowering genes on the molecular level under high-temperature conditions. The elevated temperature induced the expression of soybean floral activators, GmFT2a and GmFT5a as well as a set of GmCOL genes. In contrast, it suppressed floral repressors, E1 and E2 homologs. Moreover, high-temperature conditions affected the expression of these flowering genes in a day length-independent manner. Taken together, our data suggest that soybean plants properly respond and adapt to changing environments by modulating the expression of a set of flowering genes in the photoperiod pathway for the successful production of seeds and offspring.

Quinoa is an annual plant that grows well in high altitude regions with high radiation and ultraviolet intensity. It has known that high-dose radiation damages living organisms, but low-dose radiat...

Proper seed germination is important for seedling establishment and growth in fields under drought caused by climate change. In the present study, the beneficial effects of hydrogen peroxide on seed germination were investigated by proteome analysis. Sorghum seeds were subjected to drought stress adjusted to the various water potentials of 0, −0.2, and −0.5 MPa using polyethylene glycol (PEG) 6000 and treated with hydrogen peroxide at different concentrations (0, 10, 20, 50, and 100 mM). Germination percentage and seedling growth were determined at 6 days after imbibition, and proteins from embryos were analyzed. As a result of the study, it was found that the reduced germination percentage and seedling growth under drought stress were alleviated by hydrogen peroxide treatment. Proteins induced in hydrogen peroxide-treated embryos included glycolysis-related enzymes (25%) and stress-defense proteins (30%). Among the glycolysis-related enzymes, fructokinase-1 was higher only under drought and 0 mM H₂O₂ treatment, and phosphoglycerate kinase was higher than control under drought and 100 mM H₂O₂ treatment. Hydrogen peroxide treatment also increased the expression of antioxidant enzymes related to stress defense. The results that hydrogen peroxide treatment increases germination rate and seedling growth by increasing energy production and defense activity suggest a practical application of H₂O₂ at 100 mM for reducing the drought stress in sorghum.

Due to global climate change, adverse environments like drought in agricultural production are occurring frequently, increasing the need for research to ensure stable crop production. This study was conducted to determine the effect of artificial hydrogen peroxide treatment on sorghum growth to induce stress resistance in drought conditions. Hyperspectral analysis was performed to rapidly find out the effects of drought and hydrogen peroxide treatment to estimate the physiological parameters of plants related to drought and calculate the vegetation indices through PLS analysis based on hyperspectral data. The partial least squares (PLS) analysis collected chlorophyll fluorescence variables, photosynthetic parameters, leaf water potential, and hyperspectral reflectance during the stem elongation and booting stage. To find out the effect of hydrogen peroxide treatment in sorghum plants grown under 90% and 60% of field capacity in greenhouses, growth and hyperspectral reflectance were measured on the 10th and 20th days after foliar application of H₂O₂ at 30 mM from 1st to 5th leaf stage. The PLS analysis shows that the maximum variable fluorescence of the dark-adapted leaves was the most predictable model with R² = 0.76, and the estimation model suitability gradually increased with O (R² = 0.51), J (R² = 0.73), and P (R² = 0.75) among OJIP parameters of chlorophyll fluorescence analysis. However, the estimation suitability of predictions for moisture-related traits, vapor pressure deficit (VPD, R² = 0.18), and leaf water potential (R² = 0.15) using hyperspectral data was low. The hyperspectral reflectance was 10% higher at 20 days after treatment (DAT) and 3% at 20 DAT than the non-treatment in the far red and infra-red light regions under drought conditions. Vogelmann red edge index (VOG REI) 1, chlorophyll index red edge (CIR), and red-edge normalized difference vegetation index (RE-NDVI) efficiently reflected moisture stress among the vegetation indices. Photochemical reflectance index (PRI) can be used as an indicator for early diagnosis of drought stress because hydrogen peroxide treatment showed higher values than untreated in the early stages of drought damage.

It is important to be able to predict the yield and monitor the growth conditions of crops in the field to increase productivity. One way to assess field-based geospatial crop productivity is by integrating a crop model with a remote-controlled aerial system (RAS). The objective of this study was to simulate spatiotemporal barley growth and yield based on the development of a crop-modeling system integrated with RAS-based remote sensing images. We performed field experiments to obtain ground truth data and RAS images of crop growth conditions and yields at Chonnam National University (CNU), Gwangju, South Korea in 2018, and at Gyeongsang National University (GNU), Jinju, South Gyeongsang, South Korea in 2018 and 2019. In model calibration, there was no significant difference (p = 0.12) between the simulated barley yields and measured yields, based on a two-sample t-test at CNU in 2018. In model validation, there was no significant difference between simulated yields and measured yields at p = 0.98 and 0.76, according to two-sample t-tests at GNU in 2018 and 2019, respectively. The remote sensing-integrated crop model accurately reproduced geospatial variations in barley yield and growth variables. The results demonstrate that the crop modeling approach is useful for monitoring at-field barley conditions.