Leaf Thickness As a Predictor of Water Content of Corn, Sorghum, Soybean, and Fava Bean.

Presently, methods available to determine plant water status directly are destructive. Therefore, plant water status is usually measured indirectly, for example by using soil moisture content or potential. Leaf thickness may be a measure of plant water status that would avoid many shortcomings of indirect methods. This study aimed to determine the relationship between relative water content (RWC) and leaf thickness for corn (Zea mays), sorghum (Sorghum bicolor), soybean (Glycine max), and fava bean (Vicia faba). Two leaves within the top, middle, and bottom of fifteen plants of each species were collected at sixty days of age. A procedure was conducted to leaves reach full turgor. The full turgor samples were left under lab condition to dehydrate while leaf thickness was being measured by a developed sensor to regress it on RWC. Since the pattern of relative thickness (RT) versus RWC had a curvature that could be split into two distinct lines, linear piecewise modeling was found to be a proper fit on the relationship. RT varied steeply for a given RWC above the breakpoint whereas this rate drops significantly below it. These dynamics can be explained by the changes in the cell elasticity and structure at different hydration states. The piecewise model parameters were related to the drought tolerance of the species. Leaf location was a significant factor in the relationship RT and RWC. The model parameters were related to the parameters of crop yield response to soil salinity. Generally, the crop with more drought and salinity tolerance had less leaf thickness elasticity. These relationships and the strong coefficient of determinations of the developed models promises reliability of the method of leaf thickness monitoring and dynamic analysis for estimation of plant water status and level of drought and salinity tolerance.