Identification and discrimination of water stress in wheat leaves (Triticum aestivum L.) by means of reflectance measurements

Abstract

Available water is one of the most limiting factors in crop production. As current methods for the determination of plant water content are time-consuming and require numerous observations to characterize a field, managers could benefit from remote sensing techniques to assist in irrigation decisions and further management practices. Adoption will depend on the development of technologies, which allow real time sensing of the soil and plant water status and the discrimination of several stress factors. A greenhouse study was initiated to determine specific wavelengths and/or combinations of wavelengths indicative of water stress in wheat and to evaluate these wavelengths for discriminating water stress from other biotic stresses. Reflectance of wheat leaves from plants grown under six different water treatments ranging from 65 to 26% field capacity was determined once a week from the beginning of the fourth leaf stage until the sixth leaf stage. Reflectance measurements were performed at the fourth leaf of wheat plants with an imager (LEICA S1 Pro) under controlled light conditions. Reflectance was measured in different wavelength ranges throughout the visible and infrared spectra (380–1,300 nm). Leaf scans were evaluated within the L*a*b*-color system. Total water content of wheat leaves was calculated after the difference between total fresh and total dry weight of wheat plants. Significant reflectance changes and correlations between water status and leaf reflectance were obtained at a water content <71% and enabled the identification and quantification of water status of wheat plants. Reflectance patterns at 510780, 540780, 4901,300, and 5401,300 nm were found most suitable to describe to the water status regardless of the sampling date or growth stage. To evaluate the validity of leaf reflectance as a method for separating water stress from other biotic stresses such as nutrient deficiencies reflectance pattern of water deficient plants were compared with reflectance patterns of N, P, Mg, and Fe deficiency obtained in earlier studies by calculating the color distance ΔEab as additional reflectance parameter. ΔEab increased under different nutrient deficiencies, but remained constant under water stress, thus enabling the discrimination of the investigated stress factors. The approach indicated that various stress factors could be clearly identified by reflectance measurements, thus enhancing a better plant management by the use of remote sensing techniques.