Hyperspectral assessment of plant responses to multi‐stress environments: Prospects for managing protected agrosystems

Abstract

Advancements in our ability to rapidly detect plant responses to stress are necessary to improve crop management practices and meet the global challenge of food security. Using optical approaches to detect plant stress before symptoms become apparent has great potential, but these approaches lack testing in multiple-stress environments and fail to fully exploit the data collected. Using hyperspectral data from lettuce, we show that optical measurements can provide growers with important stress-related information to inform crop management practices. We suggest that integrating this technology into protected agrosystems, such as greenhouses, could greatly improve crop quality and yield. Summary• Tools to detect and predict stress pre-visually are essential to optimally manage agrosystems. Here, we investigated the capability of reflectance spectroscopy to characterize responses of asymptomatic crop leaves under multi-stress conditions.• Full range (350-2,500 nm) reflectance measurements and traditional plant stress responses were collected on lettuce leaves under the combination of different supplemental light types and intensities, fertilization and salinity. Partial leastsquares discriminate analysis and regression modeling and spectral indices were employed to characterize plant responses to multiple stress conditions, both alone and in combination.• Spectral profiles (400-800 nm + 1,900-2,200 nm) of individuals grown under variable environments were statistically different (p < .05) for multiple combinations.Partial least-squares discriminate analysis accurately classified the different single stressors well (accuracy: 0.76-0.91), but generated moderate accuracies (0.63-0.65) for two-stress combinations, and low accuracy (0.33) for higher order stress combinations. Osmotic potential, and chlorophyll and phenol concentrations were well predicted by spectral data (validation R 2 : 0.70-0.84). Higher lettuce yield and quality was found under sodium light at high intensity (850 µmol m −2 s −1 photosynthetic active radiation), with high fertilization (150 ppm N) and no salinity. | 245

Hyperspectral Reflectance of Light-Adapted Leaves Can Predict Both Dark- and Light-Adapted Chl Fluorescence Parameters, and the Effects of Chronic Ozone Exposure on Date Palm (Phoenix dactylifera)

“…This might be due to a moderate O 3 susceptibility of date palm, but better outputs might be reached by raising the experimental/plant replications adopted for the hyperspectral phenotyping (this is especially true under field conditions, usually characterized by highly variable growth environments). On the one hand, these results confirm the capability of this approach (i.e., hyperspectral phenotyping through the analyses of spectral signatures) to detect O 3 effects on plants, as previously reported for various other abiotic and for biotic stressors (e.g., [ 8 , 17 , 51 , 52 ]). On the other hand, the present results confirm that the efficiency of this spectral approach is dependent on the sensitivity of the plants/cultivars to O 3 , as well as to the magnitude at which this environmental pressure is imposed on vegetation.…”

“…Standardized coefficients and VIP values of F s and F m ’ PLSR models, using the VIS-NIR (i.e., 400–1200 nm) spectral range, also highlighted the importance of including wavelengths around 420 and 500–550 nm in the prediction of these parameters, thus also containing the blue peaks of chlorophylls as well as of carotenoids [ 45 ]. Conversely, since using wider ranges means the incorporation of more signals of chemical, morphological, and physiological properties of leaves included in the spectra [ 8 ], ETR and P values were better predicted using the full range (i.e., 400–2400 nm), thus including other absorbance features contained outside the pigment-related spectral range. Effectively, profiles of standardized coefficients and the VIP of PLSR models of these traits also peaked around 1400, 1700, and 1900–1950 nm, which are well-known water and protein absorption features [ 50 ], suggesting that the variations of these compounds somehow helped the estimation of ETR and P from spectra.…”

“…The effects of O 3 on the untransformed reflectance profiles (averaged per plant) were assessed by PERMANOVA [ 66 ], employing Euclidian measurements of dissimilarity and 10,000 permutations; and PCoA was used on these spectral data to visualize the spectral responses to O 3 , always using Euclidean distances through the ‘vegan’ package in R ( ; [ 67 ]). Finally, the capability of spectroscopy to classify O 3 treatments was further determined by PLS-DA [ 8 , 68 ]. The analyses were run 500 times by splitting observations into different groups of calibration (training) and validation (testing) sets, and the number of correct classifications both in the calibration and in the validation sets across the 500 iterations was used to determine the accuracy of the tested model.…”

“…Vegetation spectroscopy is a high-throughput sensor technology based on the optical properties of living vegetation (e.g., leaf and canopy reflectance) that enables the rapid and non-destructive assessment of plant status, along with a simultaneous estimate of several plant traits in the field on a large number of plants over multiple time periods [ 8 ]. The prediction of these traits from leaf spectra is based on the exploitation of the relationships of light with molecular organic bonds, mainly C-H, N-H, and O-H, resulting in vibrational excitation at specific wavelengths through the visible (VIS: 400–700 nm), the near-infrared (NIR: 700–1100 nm) and the short-wave infrared (SWIR: 1100–2400 nm) spectral regions [ 9 ].…”

“…In this study, we tested the capability to rapidly, precisely, and simultaneously estimate the number of PAM ChlF parameters commonly calculated from both dark- and light-adapted leaves from reflectance hyperspectral data collected on light-adapted leaves of date palm seedlings chronically exposed to three levels of O 3 in an O 3 -Free Air Controlled Exposure (FACE) facility located in the Mediterranean environment (i.e., Italy). Furthermore, since spectra themselves are a phenotypic expression of the aggregate signals of chemical, morphological and physiological properties of leaves under specific environmental conditions [ 8 ], we evaluated the potential of full-range (400–2400 nm) hyperspectral phenotyping to pre-visually, and accurately detect and classify the environmental pressures induced by the gradient of O 3 concentrations on date palm, and whether these effects are in accordance with O 3 -induced variations of ChlF parameters, and other VIs estimated from spectra, thus also investigating the response of this species to chronic O 3 pollution.…”