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Electrical Impedance Spectroscopy Reveals Physiological Acclimation in Apple Rootstocks During Recurrent Water Stress Episodes
by
Sun, Bo
, Chen, Jianan
, Zhou, Juan
, Di, Bao
, Wu, Shuaiyang
, Shan, Guilin
, Qian, Ji
in
Acclimation
/ Acclimatization
/ Algorithms
/ apple rootstock leaves
/ Apples
/ Aquatic resources
/ Carbohydrates
/ Chlorophyll
/ Classification
/ Correlation analysis
/ Cultivation
/ Discriminant analysis
/ Drought
/ Droughts
/ Efficiency
/ Electric properties
/ Electrical impedance
/ electrical impedance spectroscopy
/ Electrical resistivity
/ Experiments
/ Fruit cultivation
/ Impedance
/ Impedance spectroscopy
/ Leaves
/ Machine learning
/ Moisture content
/ Parameters
/ Photochemicals
/ physiological parameters
/ Physiology
/ Plant growth
/ Precipitation
/ Rhode Island
/ Rootstocks
/ Spectroscopy
/ Spectrum analysis
/ United States
/ Water
/ Water content
/ Water management
/ Water stress
/ Waterlogging
2025
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Electrical Impedance Spectroscopy Reveals Physiological Acclimation in Apple Rootstocks During Recurrent Water Stress Episodes
by
Sun, Bo
, Chen, Jianan
, Zhou, Juan
, Di, Bao
, Wu, Shuaiyang
, Shan, Guilin
, Qian, Ji
in
Acclimation
/ Acclimatization
/ Algorithms
/ apple rootstock leaves
/ Apples
/ Aquatic resources
/ Carbohydrates
/ Chlorophyll
/ Classification
/ Correlation analysis
/ Cultivation
/ Discriminant analysis
/ Drought
/ Droughts
/ Efficiency
/ Electric properties
/ Electrical impedance
/ electrical impedance spectroscopy
/ Electrical resistivity
/ Experiments
/ Fruit cultivation
/ Impedance
/ Impedance spectroscopy
/ Leaves
/ Machine learning
/ Moisture content
/ Parameters
/ Photochemicals
/ physiological parameters
/ Physiology
/ Plant growth
/ Precipitation
/ Rhode Island
/ Rootstocks
/ Spectroscopy
/ Spectrum analysis
/ United States
/ Water
/ Water content
/ Water management
/ Water stress
/ Waterlogging
2025
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Electrical Impedance Spectroscopy Reveals Physiological Acclimation in Apple Rootstocks During Recurrent Water Stress Episodes
by
Sun, Bo
, Chen, Jianan
, Zhou, Juan
, Di, Bao
, Wu, Shuaiyang
, Shan, Guilin
, Qian, Ji
in
Acclimation
/ Acclimatization
/ Algorithms
/ apple rootstock leaves
/ Apples
/ Aquatic resources
/ Carbohydrates
/ Chlorophyll
/ Classification
/ Correlation analysis
/ Cultivation
/ Discriminant analysis
/ Drought
/ Droughts
/ Efficiency
/ Electric properties
/ Electrical impedance
/ electrical impedance spectroscopy
/ Electrical resistivity
/ Experiments
/ Fruit cultivation
/ Impedance
/ Impedance spectroscopy
/ Leaves
/ Machine learning
/ Moisture content
/ Parameters
/ Photochemicals
/ physiological parameters
/ Physiology
/ Plant growth
/ Precipitation
/ Rhode Island
/ Rootstocks
/ Spectroscopy
/ Spectrum analysis
/ United States
/ Water
/ Water content
/ Water management
/ Water stress
/ Waterlogging
2025
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Electrical Impedance Spectroscopy Reveals Physiological Acclimation in Apple Rootstocks During Recurrent Water Stress Episodes
Journal Article
Electrical Impedance Spectroscopy Reveals Physiological Acclimation in Apple Rootstocks During Recurrent Water Stress Episodes
2025
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Overview
Waterlogging and drought have become major challenges in many regions worldwide. Under water stress, plants exhibit a range of physiological and electrical responses, including changes measurable by electrical impedance spectroscopy (EIS). Monitoring these parameters can provide valuable insights into plant growth status under adverse conditions. This study investigated changes in relative chlorophyll content (SPAD), maximum photochemical efficiency (Fv/Fm), relative water content (RWC), non-structural carbohydrates (NSC), and EIS parameters in apple rootstocks subjected to different water stress treatments. Results indicated that all physiological indicators, except NSC, showed a declining trend under two water stress episodes. Critically, the initial water stress episode elicited significantly greater physiological disruption than its subsequent counterpart. This suggests that plants developed a degree of physiological adaptation—such as osmotic adjustment and enhanced antioxidant activity—reducing their sensitivity to subsequent stress. Correlation analysis revealed that high-frequency resistivity (r) and intracellular resistivity (ri) were strongly associated with key physiological parameters. Thus, r and ri may serve as effective indicators for assessing plant water stress status. Furthermore, classification algorithms—Fuzzy K-Nearest Neighbors (FKNN) and sparse Linear Discriminant Analysis (sLDA)—were applied to distinguish water status in apple rootstocks, achieving high classification accuracy. These findings provide a theoretical basis for improved water management in apple cultivation.
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