B. A. Early detection of drought stress in. potato ( Solanum tuberosum L.) and grapevine ( Vitis vinifera L.) crops through multifractal analysis applied to remotely sensed data. Chávez P. 1,2 Ribas-Carbó M. 1 Medrano H. 1 Mares V. 2 Posadas A. 2 Yarlequé C. 2 Quiroz R. 2
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Early detection of drought stress in
potato (Solanum tuberosum L.) and grapevine (Vitis vinifera L.) crops through multifractal analysis applied to remotely sensed data
The importance of timely detection of drought stress in agricultural crops is increasing due to the imminent climate change. Several methodologies are being developed for assessing, monitoring, and managing water availability, to supply the accurate water amount to crops, while maintaining the highest WUE feasible. The objective of this work was to determine the suitability of remote sensing as a monitoring tool to detect drought stress in plants. Continuous measurements of multispectral reflectance and derived vegetation indices, taken from potato and grapevine crops, were analyzed, and compared with simultaneous measurements of photosynthesis, stomatal conductance and sap-flow. Multifractal analysis of reflectance data did discriminate between the well irrigated and drought treatments around 2 - 6 days earlier than physiological measurements. Vegetation indices of discrete regions also provided early detection of drought. Results evidenced that remotely sensed data might be useful as early detectors of drought stress and that the use of multifractal analysis of multispectral data might provide a more robust discrimination between turgent and stressed plants
The reflectance spectrum was divided into blue, green, red and near infrared sectors for calculating the percentage of reflectance against time. The differences were determined using a repeated measurements statistical analyses. The reflectance data were pre-processed applying a background correction, and then submitted to the Continuous Wavelet Transform (CWT) and the wavelet transform modulus maxima (WTMM) method (2) using as mother wavelet analyzer the second derivative of the Gaussian function (Mexican hat).
1Research Group on Plants under Mediterranean Conditions. University of Balearic Islands. Crrtra. Valldemossa km.7.5, 07122, Palma de Mallorca, Balearic Islands, Spain
2Production Systems & the Environment Division.
International Potato Center.P.O. Box 1558, Lima 12, Peru
Figure 3. Passive reflectance of potato plants (left) and their corresponding multifractal singularity spectra (centre). Daily photosynthesis (right,1a) and stomatal conductance (right,1b).
Availability of water is the most limiting factor in crop production. This problem will be exacerbated with the imminent climate change. Even if the rainfall levels are held constants, the risks of severe dryness increases due to the rise of the evaporative atmospheric demand caused by the global warming. Direct plant based measurements are mainly limited to leaf water potential by pressure chamber, stomatal conductance by gas-exchange, and porometry. These are time-consuming and require a number of observations to characterize a whole field. Non-destructive non-invasive remote sensing methods emerge as effective alternatives for assessing the status of crops through reflectance and imagery (1).Theaim of this work was to test remotely sensed reflectance as a revealing technique for retrieving invisible changes caused by drought in live plants.
Results and Discussion
The raw reflectance of plants did not discriminate among treatments (Figure 2); a situation corrected with pre-processing and multifractal analysis of data (Figure 3). In potato, discrimination was perceived 7 dpt (i.e. 2-4 days prior to the gas-exchange and RWC measurements). In grapevine, it occurred 6 dpt, i.e. 2 days earlier than the gas-exchange and sap flow measurements (Figures 4 and 5).Divided reflectance evidenced stressed plants at around 7 dpt for both potato and grapevine plants. The main bands for detecting drought stress were, from the best to the worst, the blue, followed by NIR, red and finally the green region.
Figure 4. Reflectance (left), multifractal singularity spectra (centre) and daily stomatal conductance (right) of plants from the grapevine experiment (Gray bars indicate days of irrigation).
Figure 1. (A) Measuring physiological parameters in a potato plant (Solanum tuberosum L.) using an infrared gas analyzer (IRGA) LI-6400. (B) Detail of the IRGA’s chamber.
The spectral vegetation indexes (SVI) tested did show an inconsistent response, even those indexes specifically developed to assess water content in plants.
Materials and Methods
Experiments were carried out under outdoor conditions in Mallorca, Spain, 2006. In potato, the treatments were Control (Ctrl), 100% of the daily measured evapo-transpiration (dme), moderate-drought (D75), 75% of dme, and severe-drought (D50), 50% of dme. Pots were weighted every day to determine the amount of water available with respect to the Control. Their relative water content (RWC) was determined.Drought treatments in grapevine were induced by stopping irrigation during 5 days per week, as 1) severe-drought (D1), irrigation re-initiated the evening of day 6; 2) moderate-drought (D2), irrigation re-initiated the morning of day 6; and Control (Ctrl), irrigated at field capacity. Light reflectance measurements were taken at noon, through a multispectral spectrometer. Gas exchange measurements were performed using a portable infrared gas analyzer (Figure 1). Sap flow measurements in grapevine were made through the thermo heat balance method (THB).
Figure 5. Continuous records of sap flow in grapevine. At the beginning of the experiment, a and b indicate that there were no differences among treatments. Differences among control and drought treatments are observable in c 8 days post treatment and onwards.
Figure 2.Pre-processing of reflectance data. Notice that the observable differences in the raw reflectance spectra do not allow a logical treatments discrimination. Neither the observable differences in the second order derivative nor the calculation of light absorbance, do demonstrate the drought levels as the multifractal singularity spectra does.