Utilization of irrigation, drainage, and electrical conductivity data for efficient use of nitrate in a soilless culture system

Nitrate management in agricultural systems has mainly been established based on nitrate supply and the yield response curve. In the case of intensive fertilization systems such as soilless culture, the nitrate amount usually remains above the curve's optimal point. A surplus nutrient supply under these conditions could result in the excessive emission of chemical fertilizers. However, very few studies have developed a decision-making process for the efficient use of nitrate under the soilless culture system online. This study was conducted to develop an indicator related to the absorption of nitrate that can be applied in online systems utilizing the monitored irrigation and drainage amount data, electrical conductivity (EC), and the nitrate analysis data of irrigation and drainage. In the simulation, a stochastic change was generated for the nutrient absorption rate. The cultivation experiment verified the theoretical prediction, and a higher correlation of tomato yield with the nitrate absorption indicator was confirmed than with the nitrate supply amount. Also, the normalization of indicator and tomato yield showed dynamic time-series responses. The simulation and cultivation experiments showed that the indicator related to nitrate absorption estimated by online EC, irrigation, and drainage monitoring provides useful theoretical and experimental frameworks regarding efficient resource management decisions.

Simulation and Experimental Analyses of Nitrate Absorption for Indicator Utilization in Soilless Culture

Background: Under intensive fertilization systems such as soilless cultures, a surplus nutrient supply could result in the excessive discharge of fertilizers. However, very few studies have developed nitrate absorption indicators for plants that can be used for decision-making under these systems. This study was conducted to develop indicators related to the absorption of nitrate that can be applied in online systems utilizing the monitored irrigation and drainage amount data, electrical conductivity (EC), and the nutrient analysis data of irrigation and drainage. Results: In the simulation, a stochastic change was generated for the nutrient absorption rate. The theoretical prediction was verified by the cultivation experiment and a higher correlation of tomato yield with the nitrate absorption indicator was confirmed than with the nitrate supply amount. Conclusions: The results of the simulation and cultivation experiments showed that the indicators related to nitrate absorption provide useful information regarding decision-making for efficient resource management through online monitoring.