Continuous nitrate and ammonium monitoring under different VPD conditions in hydroponic cultivation via IoT environmental control and ion sensing
學年 115
學期 1
出版（發表）日期 2027-01-01
作品名稱 Continuous nitrate and ammonium monitoring under different VPD conditions in hydroponic cultivation via IoT environmental control and ion sensing
作品名稱（其他語言）
著者 Yi-Min Wu; Wei-Lun Kuo; Shao-Yuan Liu; Hsing-Ying Chung; Chi-Yi Lin; Wei Fang; Lin-Chi Chen
單位
出版者
著錄名稱、卷期、頁數 Computers and Electronics in Agriculture 256, p. 112400
摘要 Vapor pressure deficit (VPD), a critical environmental factor, drives plant transpiration and dynamic changes in nutrient absorption for hydroponics. However, its effects on specific ion concentration profiles at high temporal resolution remain uncharacterized, as conventional monitoring systems rely on EC and pH. An IoT environment simulation system (IoESS) was developed for automatic VPD regulation and integrated with an IoT nutrient sensor system (IoNSS) based on solid-contact ion-selective electrodes. This integration enabled investigation of how VPD affects ion profiles in arugula cultivation, with EC included as an additional cultivation parameter. Real-time NO3− and NH4+ monitoring over 10 days revealed distinct ion concentration patterns under different VPD conditions. Under appropriate VPD (0.9 kPa), both ion concentrations declined steadily. Under temperature-induced high VPD (1.6 kPa), NO3− concentration shifted to an increasing trend. In a two-stage VPD experiment, the transition in ion concentration patterns following a VPD shift from 0.9 to 1.6 kPa was detectable within the same day. This result demonstrates the capability of the IoNSS to capture ion profile changes under dynamic cultivation conditions at the hourly scale. A proof-of-concept machine learning model based on PCA and SVM classified three VPD–EC cultivation conditions from NO3− profiles with an accuracy of 8 out of 9 on external validation samples. These results demonstrate the potential of ion profiles as a basis for cultivation condition identification. Expanding datasets and incorporating multi-ion inputs will further advance this approach toward real-time early warning in hydroponic management.
關鍵字
語言 en_US
ISSN 0168-1699
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Lin-Chi Chen
審稿制度 是
國別 NLD
公開徵稿
出版型式 ,電子版
SDGS 消除飢餓,優質教育,產業創新與基礎設施,負責任的消費與生產