Tae In Ahn

Uptake of nutrients and water by paprika (Capsicum annuum L.) as affected by renewal period of recycled nutrient solution in closed soilless culture

One of the problems in closed soilless cultures is to find a solution in order to reduce ion imbalance in recycled nutrient solutions when the drained nutrient solution is re-used. To reduce ion imbalance in recycled nutrient solutions, determination of renewal period is required, since uptake of individual ion by plants changes throughout the growing period. The aims of this study are to determine the appropriate renewal period to reduce ion imbalance in the recycled nutrient solution and to investigate the uptake of nutrients and water by the paprika plant and to measure fruit yield and mineral contents in plant as influenced by renewal period of recycled nutrient solution in a closed soilless culture. Paprika plants were grown in rockwool slabs with either 4-, 8-, or 12-week renewal period in the closed as compared to the open hydroponic system (control). The electrical conductivity (EC), pH, and volume of the nutrient solutions were measured every three days. The nutrient solution in the reservoir tank was constantly maintained at EC 2.5 dS·m−1 and pH 5.5–6.5. As results, the uptake of K+ was significantly influenced by the renewal period. Changes of cation and anion ratio in the recycled nutrient solution could be reduced by discharging every 4 weeks. The significantly lowest fruit yield was observed in a closed hydroponic system using a 12-week renewal period. Regarding the ion balance in the recycled nutrient solution, renewing every 4 weeks was found to be the most effective in this study. However, considering the yield along with nutrients and water uptake, a 8-week interval could also be used.

Modeling of Transpiration of Paprika (Capsicum annuum L.) Plants Based on Radiation and Leaf Area Index in Soilless Culture

Modeling of crop transpiration is important to manage the irrigation strategy in soilless culture. In this study, the transpiration of paprika plants (Capsicum annuum L.) grown in rockwool was analyzed considering the relationship between incident radiation (RAD) and leaf area index (LAI). Coefficients of the simplified Penman-Monteith formula were calibrated in order to calculate the transpiration rate of the crop (Tr). Transpiration rate per floor area was measured by weighing plants with load cells. The following model was developed: Tr = a [1 − exp(−k × LAI)] × RAD /λ + b for estimating transpiration of paprika. Determination coefficient for the linear regression between estimations and measurements of daily transpiration was 0.80 with a slope of 0.93. In validation, the model showed high agreement between estimated and measured values of daily transpiration. Radiation showed a great effect on transpiration of paprika plants. The results indicated the simplified Penman- Monteith formula could be used to predict water requirements and improve irrigation control in soilless culture. However the model coefficients require parameter adjustments for specific climate and crop conditions.

Sweet Pepper (Capsicum annuum L.) Canopy Photosynthesis Modeling Using 3D Plant Architecture and Light Ray-Tracing.

Canopy photosynthesis has typically been estimated using mathematical models that have the following assumptions: the light interception inside the canopy exponentially declines with the canopy depth, and the photosynthetic capacity is affected by light interception as a result of acclimation. However, in actual situations, light interception in the canopy is quite heterogenous depending on environmental factors such as the location, microclimate, leaf area index, and canopy architecture. It is important to apply these factors in an analysis. The objective of the current study is to estimate the canopy photosynthesis of paprika (Capsicum annuum L.) with an analysis of by simulating the intercepted irradiation of the canopy using a 3D ray-tracing and photosynthetic capacity in each layer. By inputting the structural data of an actual plant, the 3D architecture of paprika was reconstructed using graphic software (Houdini FX, FX, Canada). The light curves and A/Ci curve of each layer were measured to parameterize the Farquhar, von Caemmerer, and Berry (FvCB) model. The difference in photosynthetic capacity within the canopy was observed. With the intercepted irradiation data and photosynthetic parameters of each layer, the values of an entire plants photosynthesis rate were estimated by integrating the calculated photosynthesis rate at each layer. The estimated photosynthesis rate of an entire plant showed good agreement with the measured plant using a closed chamber for validation. From the results, this method was considered as a reliable tool to predict canopy photosynthesis using light interception, and can be extended to analyze the canopy photosynthesis in actual greenhouse conditions.

Analysis of Year-round Cultivation Characteristics of Artemisia princeps in Greenhouse and Enhancement of Eupathilin Content by Environmental Stress

Mugwort (Artemisia princeps) is a medicinal plant that has a substance called euphatilin, which is effective for cell damage and gastritis recovery. The objectives of this study were to investigate the annual growth characteristics of Artemisia princeps in greenhouse and to increase the eupatiline content by environmental stresses. Growth and eupatilin content of the plants were compared after 6 weeks of seedling and subsequent 8 weeks of greenhouse cultivation. Photosynthesis of mugwort plants did not saturate even at a relatively high light intensity of 1,200μmol m·s. Growth rate of the plants reached its highest at two weeks after transplanting and began to decrease since 8 weeks after transplanting. The plants showed typical characteristics of a perennial herbaceous plant as they were sensitive to seasonal changes. In particular, the plants showed high growth and eupatilin content in spring and summer as vegetative growth periods, but flowering and wintering caused considerable decreases in growth and eupatilin content in fall and winter. Therefore, application of night interruption is essential for year-round cultivationof the plant. Two stresses and a elicitor were treated: drought stresses by stopping irrigation at 5, 6, 7, and 8 days before harvest; salt stresses with nutrient solution concentrations of 2, 4, 6, 8, and 10 dS·m by adding sodium chloride at 3 days before harvest; and foliar applications of methyl jasmonates of 12.5, 25, 50, and 100μM at 3 days before harvest. Significant increase in eupatilin content was observed at drought stresses of 7and 8-days of irrigation stop and foliar application of 25μM methyl jasmonate, while no significant increase observed at salt stresses. From the results, it was confirmed that the environmental treatments can improve the productivity and quality of Artemisia princeps as a phamaceutical raw material. Additional key words : drought stress, greenhouse, growth, methyl jasmonate, photosynthetic rate, salinity stress

Forecasting Root-Zone Electrical Conductivity of Nutrient Solutions in Closed-Loop Soilless Cultures via a Recurrent Neural Network Using Environmental and Cultivation Information

In existing closed-loop soilless cultures, nutrient solutions are controlled by the electrical conductivity (EC) of the solution. However, the EC of nutrient solutions is affected by both growth environments and crop growth, so it is hard to predict the EC of nutrient solution. The objective of this study was to predict the EC of root-zone nutrient solutions in closed-loop soilless cultures using recurrent neural network (RNN). In a test greenhouse with sweet peppers (Capsicum annuum L.), data were measured every 10 s from October 15 to December 31, 2014. Mean values for every hour were analyzed. Validation accuracy (R2) of a single-layer long short-term memory (LSTM) was 0.92 and root-mean-square error (RMSE) was 0.07, which were the best results among the different RNNs. The trained LSTM predicted the substrate EC accurately at all ranges. Test accuracy (R2) was 0.72 and RMSE was 0.08, which were lower than values for the validation. Deep learning algorithms were more accurate when more data were added for training. The addition of other environmental factors or plant growth data would improve model robustness. A trained LSTM can control the nutrient solutions in closed-loop soilless cultures based on predicted future EC. Therefore, the algorithm can make a planned management of nutrient solutions possible, reducing resource waste.

On-site ion monitoring system for precision hydroponic nutrient management

Abstract Hydroponic solutions used in greenhouses or plant factories are usually evaluated based on their electrical conductivity (EC) and pH. However, EC and pH cannot provide sufficient information about ion imbalances in hydroponic solutions, and this may result in wastage of nutrients or poor yields. This paper reports on the development of an on-site ion monitoring system based on ion-selective electrodes (ISEs) that can automatically calibrate sensors and measure the concentrations of individual ions (NO 3 − , K + , and Ca 2+ ) in hydroponic solutions. This enables farmers to effectively manage nutrients in reused solutions by rapidly identifying any imbalances that appear in the nutrient ratios. The measurement performance of the developed system was evaluated using hydroponic solutions prepared for growing paprika crops in greenhouses. An application test was conducted to investigate the feasibility of using the developed on-site ion monitoring system for the automated measurement of three macronutrients (NO 3 − , K + , and Ca 2+ ) in a real greenhouse. The results showed that the developed system was able to measure NO 3 − concentrations, showing an almost 1:1 relationship with the results of a standard instrument, i.e., ion chromatography (slope of 0.99 and R 2 of 0.99). Although the developed system overestimated and underestimated the K + and Ca 2+ concentrations with slopes of 1.17 and 0.75, respectively, the high coefficients of determination of 0.99 and 0.97 made it possible to use calibration factors to compensate for differences in estimation. In fact, relatively low RMSEs of −1 over the range of 40–1200 mg L −1 were obtained from a comparison of the ISE method and standard analysis when tested in hydroponic samples taken on different days during the period of paprika growing. This indicates that ISEs could be applicable to measurements where there is a strong linear relationship between the ISE method and standard analysis. In the application tests, the system could monitor the temporal changes in ionic concentrations in hydroponic solutions effectively, showing sensitive responses to changes in the concentrations of the three ions with an acceptable level of performance.

Chapter 17 – Hydroponic Systems

Hydroponic systems, such as the deep flow technique, nutrient film technique, or aeroponic systems, are essential tools in plant factories. For adequate management of water and nutrients in the hydroponic system, the electrical conductivity (EC), pH, dissolved oxygen, and temperature should be measured. Because ion concentrations in the nutrient solutions change with time, resulting in a nutrient imbalance in closed hydroponic systems, real-time measurements of all nutrients are required, but such measurements are not available due to technical problems. Periodic analysis of nutrient solutions and adjustment of nutrient ratios can improve the nutrient balance. As an advanced method, ion-selective electrodes and artificial neural networks can be efficient tools for estimating the concentration of each ion. For stable crop production, disinfection systems using filters, heat, ozone, and ultraviolet radiation are required in hydroponic systems.

Precise, Real-time Measurement of the FreshWeight of Lettuce with Growth Stage in a PlantFactory using a Nutrient Film Technique

The measurement of total fresh weight of plants provides an essential indicator of crop growth for monitoring production. To measure fresh weight without damaging the vegetation, imagebased methods have been developed, but they have limitations. In addition, the total plant fresh weight is difficult to measure directly in hydroponic cultivation systems because of the amount of nutrient solution. This study aimed to develop a real-time, precise method to measure the total fresh weight of Romaine lettuce (Lactuca sativa L. cv. Asia Heuk Romaine) with growth stage in a plant factory using a nutrient film technique. The total weight of the channel, amount of residual nutrient solution in the channel, and fresh shoot and root weights of the plants were measured every 7 days after transplanting. The initial weight of the channel during nutrient solution supply (Wi) and its weight change per second just after the nutrient solution supply stopped were also measured. When no more draining occurred, the final weight of the channel (Ws) and the amount of residual nutrient solution in the channel were measured. The time constant (τ) was calculated by considering the transient values of Wi and Ws. The relationship of Wi, Ws, τ, and fresh weight was quantitatively analyzed. After the nutrient solution supply stopped, the change in the channel weight exponentially decreased. The nutrient solution in the channel slowly drained as the root weight in the channel increased. Large differences were observed between the actual fresh weight of the plant and the predicted value because the channel included residual nutrient solution. These differences were difficult to predict with growth stage but a model with the time constant showed the highest accuracy. The real-time fresh weight could be calculated from Wi, Ws, and τ with growth stage. Received: August 25, 2015