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TECHNICAL REPORTS

Plant and Environment Interactions

Estimating Yields of Salt- and Water-Stressed Forages with Remote Sensing in the Visible and Near Infrared

USDA-ARS George E. Brown, Jr. Salinity Laboratory, 450 West Big Springs Road, Riverside, CA 92507

^* Corresponding author (Jposs{at}ussl.ars.usda.gov)

Received for publication May 18, 2006. In arid irrigated regions, the proportion of crop production under deficit irrigation with poorer quality water is increasing as demand for fresh water soars and efforts to prevent saline water table development occur. Remote sensing technology to quantify salinity and water stress effects on forage yield can be an important tool to address yield loss potential when deficit irrigating with poor water quality. Two important forages, alfalfa (Medicago sativa L.) and tall wheatgrass (Agropyron elongatum L.), were grown in a volumetric lysimeter facility where rootzone salinity and water content were varied and monitored. Ground-based hyperspectral canopy reflectance in the visible and near infrared (NIR) were related to forage yields from a broad range of salinity and water stress conditions. Canopy reflectance spectra were obtained in the 350- to 1000-nm region from two viewing angles (nadir view, 45° from nadir). Nadir view vegetation indices (VI) were not as strongly correlated with leaf area index changes attributed to water and salinity stress treatments for both alfalfa and wheatgrass. From a list of 71 VIs, two were selected for a multiple linear-regression model that estimated yield under varying salinity and water stress conditions. With data obtained during the second harvest of a three-harvest 100-d growing period, regression coefficients for each crop were developed and then used with the model to estimate fresh weights for preceding and succeeding harvests during the same 100-d interval. The model accounted for 72% of the variation in yields in wheatgrass and 94% in yields of alfalfa within the same salinity and water stress treatment period. The model successfully predicted yield in three out of four cases when applied to the first and third harvest yields. Correlations between indices and yield increased as canopy development progressed. Growth reductions attributed to simultaneous salinity and water stress were well characterized, but the corrections for effects of varying tissue nitrogen (N) and very low leaf area index (LAI) are necessary.

Abbreviations: EC, electrical conductivity • ET, evapotranspiration • ETR, evapotranspiration ratio • LAI, leaf area index • NDVI, normalized difference vegetation index • NIR, near-infrared spectral region • R, canopy reflectance • VI, vegetation index • VLS, volumetric lysimeter system

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