Abstract
Crop water stress is a deficiency in plants in water supply when the transpiration rate becomes higher than the water absorption capacity. The stress may be detected by a reduction in soil water content, or by the change in physiological properties of the crop. The leaf water content (LWC) is commonly used to assess the water status of plants, which is one of the indicators of crop water stress. In this work, the leaf relative water contents of four different crops: canola, wheat, soybeans, and corn—all in vegetative growth stage—were determined by a noninvasive tool called, electrical impedance spectroscopy (EIS). Using a frequency range of 5–15 kHz, a strong correlation between leaf water contents and leaf impedances was obtained using multiple linear regression. The trained dataset was validated by analysis of variance tests. Regression results were obtained using the least square method. The optimized regression model coefficients for different crops were proposed by selecting features using the wrapper backward elimination method. Multi-collinearity among the features was considered and individual T-tests were made in the feature selection. A maximum correlation coefficient (R) of 0.99 was obtained for canola compared to the other crops; the corresponding coefficient of determination (R2) of 0.98, an adjusted R2 of 0.93, and root mean square error (rmse) of 0.30% were obtained for 36 features. Therefore, the results show that the proposed technique using EIS can be used to develop a low-cost and effective tool for determining the leaf water contents rapidly and efficiently in multiple crops.
Highlights
The leaf impedance profiles were examined at different water status to obtain the correlations with the leaf water contents
The optimized regression model coefficients were proposed for canola, wheat, soybeans, and corn to determine the leaf water contents rapidly and efficiently using a portable and non-invasive electrical impedance spectroscopy (EIS) method
A comparative statistical analysis among the four different crops was performed, and the maximum correlation coefficient (R) of 0.99, the coefficient of determination (R2) of 0.98, and rmse of 0.30% were obtained for canola in the frequency range of 5–10.4 kHz
Summary
Water stress reduces the efficiency of photosynthesis and limits crop productivity [1,2]. It occurs when the water demand exceeds the available moisture during a certain period. Since plant growth and productivity are adversely affected by water stress, it is important to accurately determine the water status in plants to make timely irrigation decisions [1,2,3]. Water status of plant can be indicated by different tissues (such as root, stem, and leaf or the whole canopy). Compared with the other plant tissues, leaf analysis is the most important tool for evaluating nutrient and water status of a plant, which aids in fertilization and irrigation [4,5,6,7]. The leaf water content (LWC) is an important indicator of plant water status
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