Development of a Soil Moisture Prediction Model Based on Recurrent Neural Network Long Short-Term Memory (RNN-LSTM) in Soybean Cultivation.

Due to climate change, soil moisture may increase, and outflows could become more frequent, which will have a considerable impact on crop growth. Crops are affected by soil moisture; thus, soil moisture prediction is necessary for irrigating at an appropriate time according to weather changes. Therefore, the aim of this study is to develop a future soil moisture (SM) prediction model to determine whether to conduct irrigation according to changes in soil moisture due to weather conditions. Sensors were used to measure soil moisture and soil temperature at a depth of 10 cm, 20 cm, and 30 cm from the topsoil. The combination of optimal variables was investigated using soil moisture and soil temperature at depths between 10 cm and 30 cm and weather data as input variables. The recurrent neural network long short-term memory (RNN-LSTM) models for predicting SM was developed using time series data. The loss and the coefficient of determination (R2) values were used as indicators for evaluating the model performance and two verification datasets were used to test various conditions. The best model performance for 10 cm depth was an R2 of 0.999, a loss of 0.022, and a validation loss of 0.105, and the best results for 20 cm and 30 cm depths were an R2 of 0.999, a loss of 0.016, and a validation loss of 0.098 and an R2 of 0.956, a loss of 0.057, and a validation loss of 2.883, respectively. The RNN-LSTM model was used to confirm the SM predictability in soybean arable land and could be applied to supply the appropriate moisture needed for crop growth. The results of this study show that a soil moisture prediction model based on time-series weather data can help determine the appropriate amount of irrigation required for crop cultivation.

The effect of concurrent elevation in CO2 and temperature on the growth, photosynthesis, and yield of potato crops.

Global climate change accompanied by continuous increases in atmospheric carbon dioxide (CO2) concentration and temperature affects the growth and yield of important crops. The present study investigated the effect of elevated temperature and CO2 concentrations on the growth, yield, and photosynthesis of potato (Solanum tuberosum L. cv. Superior) crops using Korean Soil-Plant-Atmosphere-Research chambers that allow the regulation of temperature and CO2 concentration under daylight conditions. Based on the average temperature from 1991 to 2010 in the Jeonju area, South Korea, potato plants were exposed to four different conditions: ambient weather (400 µmol mol-1, aCaT), elevated temperature (+4°C, aCeT), elevated CO2 concentration (800 µmol mol-1, eCaT), and concurrently elevated CO2 concentration and temperature (eCeT). Under aCeT conditions, the temperature exceeded the optimal growth temperature range towards the late growth phase that decreased stomatal conductance and canopy net photosynthetic rate and subsequently reduced biomass and tuber yield. Stomatal conductance and chlorophyll concentration were lower under eCaT conditions than under aCaT conditions, whereas late-growth phase biomass and tuber yield were greater. Compared to other conditions, eCeT yielded a distinct increase in growth and development and canopy net photosynthetic rate during tuber initiation and bulking. Consequently, biomass and canopy net photosynthesis increased, and tuber yield increased by 20.3%, which could be attributed to the increased tuber size, rather than increased tuber number. Elevated CO2 reduced chlorophyll, magnesium, and phosphorus concentrations; reducing nitrogen concentration (by approximately 39.7%) increased the C:N ratio. The data indicate that future climate conditions will likely change nutrient concentration and quality of crops. The present study shows that while elevated temperature may negatively influence the growth and yield of potato crops, especially towards the late-growth phase, the concurrent and appropriate elevation of CO2 and temperature could promote balanced development of source and sink organs and positively effect potato productivity and quality.