Bieganowski Andrzej, Jaromin-Glen Katarzyna, Guz Łukasz, Łagód Grzegorz, Jozefaciuk Grzegorz, Franus Wojciech, Suchorab Zbigniew, Sobczuk Henryk
Institute of Agrophysics, Polish Academy of Sciences, Doswiadczalna 4 Str., Lublin 20-290, Poland.
Faculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B Str., Lublin 20-618, Poland.
Sensors (Basel). 2016 Jun 22;16(6):886. doi: 10.3390/s16060886.
The possibility of distinguishing different soil moisture levels by electronic nose (e-nose) was studied. Ten arable soils of various types were investigated. The measurements were performed for air-dry (AD) soils stored for one year, then moistened to field water capacity and finally dried within a period of 180 days. The volatile fingerprints changed during the course of drying. At the end of the drying cycle, the fingerprints were similar to those of the initial AD soils. Principal component analysis (PCA) and artificial neural network (ANN) analysis showed that e-nose results can be used to distinguish soil moisture. It was also shown that different soils can give different e-nose signals at the same moistures.
研究了利用电子鼻区分不同土壤湿度水平的可能性。对十种不同类型的耕地土壤进行了调查。对储存一年的风干土壤进行测量,然后将其湿润至田间持水量,最后在180天内干燥。在干燥过程中挥发性指纹图谱发生了变化。在干燥周期结束时,指纹图谱与初始风干土壤的指纹图谱相似。主成分分析(PCA)和人工神经网络(ANN)分析表明,电子鼻的结果可用于区分土壤湿度。研究还表明,不同土壤在相同湿度下可产生不同的电子鼻信号。