Spectral ecophysiology: hyperspectral pressure-volume curves to estimate leaf turgor loss

Turgor loss point (TLP) is an important proxy for plant drought tolerance, species habitat suitability, and drought-induced plant mortality risk. Thus, TLP serves as a critical tool for evaluating climate change impacts on plants, making it imperative to develop high-throughput and in situ methods to measure TLP. We developed hyperspectral pressure-volume curves (PV curves) to estimate TLP using leaf spectral reflectance. We used partial least square regression models to estimate water potential (Ψ) and relative water content (RWC) for two species, Frangula caroliniana and Magnolia grandiflora. RWC and Ψ's model for each species had R2 ≥ 0.7 and %RMSE = 7-10. We constructed PV curves with model estimates and compared the accuracy of directly measured and spectra-predicted TLP. Our findings indicate that leaf spectral measurements are an alternative method for estimating TLP. F. caroliniana TLP's values were -1.62 ± 0.15 (means ± SD) and -1.62 ± 0.34 MPa for observed and reflectance predicted, respectively (P > 0.05), while M. grandiflora were -1.78 ± 0.34 and -1.66 ± 0.41 MPa (P > 0.05). The estimation of TLP through leaf reflectance-based PV curves opens a broad range of possibilities for future research aimed at understanding and monitoring plant water relations on a large scale with spectral ecophysiology.

Impact of treated wastewater on plant growth: leaf fluorescence, reflectance, and biomass-based assessment

The study evaluated the impact of treated wastewater on plant growth through the use of hyperspectral and fluorescence-based techniques coupled with classical biomass analyses, and assessed the potential of reusing treated wastewater for irrigation without fertilizer application. Cherry tomato (Solanum lycopersicum) and cabbage (Brassica oleracea L.) were irrigated with tap water (Tap), secondary effluent (SE), and membrane effluent (ME). Maximum quantum yield of photosystem II (Fv/Fm) of tomato and cabbage was between 0.78 to 0.80 and 0.81 to 0.82, respectively, for all treatments. The performance index (PI) of Tap/SE/ME was 2.73, 2.85, and 2.48 for tomatoes and 4.25, 3.79, and 3.70 for cabbage, respectively. Both Fv/Fm and PI indicated that the treated wastewater did not have a significant adverse effect on the photosynthetic efficiency and plant vitality of the crops. Hyperspectral analysis showed higher chlorophyll and nitrogen content in leaves of recycled water-irrigated crops than tap water-irrigated crops. SE had 10.5% dry matter composition (tomato) and Tap had 10.7% (cabbage). Total leaf count of Tap/SE/ME was 86, 111, and 102 for tomato and 37, 40, and 42 for cabbage, respectively. In this study, the use of treated wastewater did not induce any photosynthetic-related or abiotic stress on the crops; instead, it promoted crop growth.

Mechanistic links between physiology and spectral reflectance enable previsual detection of oak wilt and drought stress

Tree mortality due to global change-including range expansion of invasive pests and pathogens-is a paramount threat to forest ecosystems. Oak forests are among the most prevalent and valuable ecosystems both ecologically and economically in the United States. There is increasing interest in monitoring oak decline and death due to both drought and the oak wilt pathogen (Bretziella fagacearum). We combined anatomical and ecophysiological measurements with spectroscopy at leaf, canopy, and airborne levels to enable differentiation of oak wilt and drought, and detection prior to visible symptom appearance. We performed an outdoor potted experiment with Quercus rubra saplings subjected to drought stress and/or artificially inoculated with the pathogen. Models developed from spectral reflectance accurately predicted ecophysiological indicators of oak wilt and drought decline in both potted and field experiments with naturally grown saplings. Both oak wilt and drought resulted in blocked water transport through xylem conduits. However, oak wilt impaired conduits in localized regions of the xylem due to formation of tyloses instead of emboli. The localized tylose formation resulted in more variable canopy photosynthesis and water content in diseased trees than drought-stressed ones. Reflectance signatures of plant photosynthesis, water content, and cellular damage detected oak wilt and drought 12 d before visual symptoms appeared. Our results show that leaf spectral reflectance models predict ecophysiological processes relevant to detection and differentiation of disease and drought. Coupling spectral models that detect physiological change with spatial information enhances capacity to differentiate plant stress types such as oak wilt and drought.

Non-Destructive Monitoring of Foliar Fungicide Efficacy with Hyperspectral Sensing in Grapevine

Frequent fungicide applications are required to manage grapevine powdery mildew (Erysiphe necator). However, this practice is costly and has led to widespread fungicide resistance. A method of monitoring in-field fungicide efficacy could help growers maximize spray-interval length, thereby reducing costs and the rate of fungicide resistance emergence. The goal of this study was to evaluate if hyperspectral sensing in the visible to shortwave infrared range (400 to 2,400 nm) can quantify foliar fungicide efficacy on grape leaves. Commercial formulations of metrafenone, Bacillus mycoides isolate J (BmJ), and sulfur were applied on Chardonnay grapevines in vineyard or greenhouse settings. Foliar reflectance was measured with handheld hyperspectral spectroradiometers at multiple days post-application. Fungicide efficacy was estimated as a proxy for fungicide residue and disease control measured with the Blackbird microscopy imaging robot. Treatments could be differentiated from the untreated control with an accuracy of 73.06% for metrafenone, 67.76% for BmJ, and 94.10% for sulfur. The change in spectral reflectance was moderately correlated with the cube root of the area under the disease progress curve for metrafenone- and sulfur-treated samples (R2 = 0.38 and 0.36, respectively) and with sulfur residue (R2 = 0.42). BmJ treatment impacted foliar physiology by enhancing the leaf mass/area and reducing the nitrogen and total phenolic content as estimated from spectral reflectance. The results suggest that hyperspectral sensing can be used to monitor in-situ fungicide efficacy, and the prediction accuracy depends on the fungicide and the time point measured. The ability to monitor in-situ fungicide efficacy could facilitate more strategic fungicide applications and promote sustainable grapevine protection. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

A data fusion approach for nondestructive tracking of the ripening process and quality attributes of green Hayward kiwifruit using artificial olfaction and proximal hyperspectral imaging techniques

A data fusion strategy based on hyperspectral imaging (HSI) and electronic nose (e-nose) systems was developed in this study to inspect the postharvest ripening process of Hayward kiwifruit. The extracted features from the e-nose and HSI techniques, in single or combined mode, were used to develop machine learning algorithms. Performance evaluations proved that the fusion of olfactory and reflectance data improves the performance of discriminative and predictive algorithms. Accordingly, with high classification accuracies of 100% and 94.44% in the calibration and test stages, the data fusion-based support vector machine (SVM) outperformed the partial least square discriminant analysis (PLSDA) for discriminating the kiwifruit samples into eight classes based on storage time. Moreover, the data fusion-based support vector regression (SVR) was a better predictor than partial least squares regression (PLSR) for kiwifruit firmness, soluble solids content (SSC), and titratable acidity (TA) measures. The prediction R 2 and RMSE criteria of the SVR algorithm on the test data were 0.962 and 0.408 for firmness, 0.964 and 0.337 for SSC, and 0.955 and 0.039 for TA, respectively. It was concluded that the hybrid of e-nose and HSI systems coupled with the SVM algorithm delivers an effective tool for accurate and nondestructive monitoring of kiwifruit quality during storage.

High-Dynamic-Range Spectral Reflectance for the Segmentation of Paint Pigment: Application to Dalí's Oil Painting Dos Figuras (1926)

Restorers and curators in museums sometimes find it difficult to accurately segment areas of paintings that have been contaminated with other pigments or areas that need to be restored, and work on the painting needs to be carried out with minimum possible damage. It is therefore necessary to develop measurement systems and methods that facilitate this task in the least invasive way possible. The aim of this study was to obtain high-dynamic-range (HDR) spectral reflectance and spatial resolution for Dalí's painting entitled Two Figures (1926) in order to segment a small area of black and white pigment that was affected by the contact transfer of reddish pigment from another painting. Using Hypermatrixcam to measure the HDR spectral reflectance developed by this research team, an HDR multispectral cube of 12 images was obtained for the band 470-690 nm in steps of 20 nm. With the values obtained for the spectral reflectance of the HDR cube, the colour of the area of paint affected by the transfer was studied by calculating the a*b* components with the CIELab system. These a*b* values were then used to define two methods of segmenting the exact areas in which there was a transfer of reddish pigment. The area studied in the painting was originally black, and the contamination with reddish pigment occupied 13.87% to 32% of the total area depending on the selected method. These different solutions can be explained because the lower limit is segmentation based on pure pigment and the upper limit considers red as an exclusion of non-black pigment. Over- and under-segmentation is a common problem described in the literature related to pigment selection. In this application case, as red pigment is not original and should be removed, curators will choose the method that selects the highest red area.

Monitoring Drought Stress in Common Bean Using Chlorophyll Fluorescence and Multispectral Imaging

Drought is a significant constraint in bean production. In this study, we used high-throughput phenotyping methods (chlorophyll fluorescence imaging, multispectral imaging, 3D multispectral scanning) to monitor the development of drought-induced morphological and physiological symptoms at an early stage of development of the common bean. This study aimed to select the plant phenotypic traits which were most sensitive to drought. Plants were grown in an irrigated control (C) and under three drought treatments: D70, D50, and D30 (irrigated with 70, 50, and 30 mL distilled water, respectively). Measurements were performed on five consecutive days, starting on the first day after the onset of treatments (1 DAT-5 DAT), with an additional measurement taken on the eighth day (8 DAT) after the onset of treatments. Earliest detected changes were found at 3 DAT when compared to the control. D30 caused a decrease in leaf area index (of 40%), total leaf area (28%), reflectance in specific green (13%), saturation (9%), and green leaf index (9%), and an increase in the anthocyanin index (23%) and reflectance in blue (7%). The selected phenotypic traits could be used to monitor drought stress and to screen for tolerant genotypes in breeding programs.

[Hyperspectral monitoring on proline content in winter wheat under water stress]

Frequent occurrence of drought disaster will seriously affect the growth and development of winter wheat (Triticum aestivum). We set different water stress treatments (80%, 60%, 45%, 35%, 30% of field water capacity) to simulate the severity of drought disaster. We measured free proline content (Pro) of winter wheat, and investigated the responses of Pro to canopy spectral reflectance under water stress. Three methods, i.e., correlation analysis and stepwise multiple linear regression (CA+SMLR), partial least squares and stepwise multiple linear regression (PLS+SMLR), and successive projections algorithm (SPA) were used to extract the hyperspectral cha-racteristic region and characteristic band of proline. Furthermore, partial least square regression (PLSR) and multiple linear regression (MLR) methods were used to establish the predicted models. The results showed that Pro content of winter wheat was higher under water stress, and that the spectral reflectance of canopy changed regularly in different bands, indicating that Pro content of winter wheat was sensitive to water stress. The content of Pro was highly correlated with the red edge of canopy spectral reflectance, with the 754, 756 and 761 nm bands being sensitive to Pro change. The PLSR model performed good, followed by the MLR model, both showing good predictive ability and high model accuracy. In general, it was feasible to monitor Pro content of winter wheat by hyperspectral technique.

Improving Generalizability of Spectral Reflectance Reconstruction Using L1-Norm Penalization

Spectral reflectance reconstruction for multispectral images (such as Weiner estimation) may perform sub-optimally when the object being measured has a texture that is not in the training set. The accuracy of the reconstruction is significantly lower without training samples. We propose an improved reflectance reconstruction method based on L1-norm penalization to solve this issue. Using L1-norm, our method can provide the transformation matrix with the favorable sparse property, which can help to achieve better results when measuring the unseen samples. We verify the proposed method by reconstructing spectral reflection for four types of materials (cotton, paper, polyester, and nylon) captured by a multispectral imaging system. Each of the materials has its texture and there are 204 samples in each of the materials/textures in the experiments. The experimental results show that when the texture is not included in the training dataset, L1-norm can achieve better results compared with existing methods using colorimetric measure (i.e., color difference) and shows consistent accuracy across four kinds of materials.

Optimized clustering method for spectral reflectance recovery

An optimized method based on dynamic partitional clustering was proposed for the recovery of spectral reflectance from camera response values. The proposed method produced dynamic clustering subspaces using a combination of dynamic and static clustering, which determined each testing sample as a priori clustering center to obtain the clustering subspace by competition. The Euclidean distance weighted and polynomial expansion models in the clustering subspace were adaptively applied to improve the accuracy of spectral recovery. The experimental results demonstrated that the proposed method outperformed existing methods in spectral and colorimetric accuracy and presented the effectiveness and robustness of spectral recovery accuracy under different color spaces.

Concurrent herbivory and metal accumulation: The outcome for plants and herbivores

The effects of metals on plants and herbivores, as well as the interaction among the latter, are well documented. However, the effects of simultaneous herbivory and metal accumulation remain poorly studied. Here, we shed light on this topic by infesting cadmium-accumulating tomato plants (Solanum lycopersicum), either exposed to cadmium or not, with herbivorous spider mites, Tetranychus urticae or T. evansi during 14 days. Whereas on plants without cadmium T. evansi had higher growth rate than T. urticae, on plants with cadmium both mite species had similar growth rates, which were lower than on plants without metal. Plants were affected by both cadmium toxicity and by herbivory, as shown by leaf reflectance, but not on the same wavelengths. Moreover, changes in leaf reflectance on the wavelength affected by herbivores were similar on plants with and without cadmium, and vice versa. Long-term effects of cadmium and herbivory did not affect H₂O₂ concentrations in the plant. Finally, plants infested with spider mites did not accumulate more cadmium, suggesting that metal accumulation is not induced by herbivory. We thus conclude that cadmium accumulation affects two congeneric herbivore species differently and that the effects of herbivory and cadmium toxicity on plants may be disentangled, via leaf reflectance, even during simultaneous exposure.

Measuring High Dynamic Range Spectral Reflectance of Artworks through an Image Capture Matrix Hyperspectral Camera

Commercial hyperspectral imaging systems typically use CCD or CMOS sensors. These types of sensors have a limited dynamic range and non-linear response. This means that when evaluating an artwork under uncontrolled lighting conditions and with light and dark areas in the same scene, hyperspectral images with underexposed or saturated areas would be obtained at low or high exposure times, respectively. To overcome this problem, this article presents a system for capturing hyperspectral images consisting of a matrix of twelve spectral filters placed in twelve cameras, which, after processing these images, makes it possible to obtain the high dynamic range image to measure the spectral reflectance of the work of art being evaluated. We show the developed system and describe all its components, calibration processes, and the algorithm implemented to obtain the high dynamic range spectral reflectance measurement. In order to validate the system, high dynamic range spectral reflectance measurements from Labsphere's Spectralon Reflectance Standards were performed and compared with the same reflectance measurements but using low dynamic range images. High dynamic range hyperspectral imaging improves the colorimetric accuracy and decreases the uncertainty of the spectral reflectance measurement based on low dynamic range imaging.

Non-invasive Estimation of Foliar Nitrogen Concentration Using Spectral Characteristics of Menthol Mint (Mentha arvensis L.)

Menthol mint (Mentha arvensis L., Family: Lamiaceae), popularly known as corn mint or Japanese mint, is an important industrial crop that is widely grown for its valued essential oil. Nitrogen (N) is an important macro-nutrient and an essential factor for optimizing the yield and quality of crops. Hence, rapid and accurate estimation of the N content is crucial for nutrient diagnosis in plants and to make precise N fertilizer recommendations. Generally, N concentration is estimated by destructive sampling methods; however, an indirect assessment may be possible based on spectral characteristics. This study aimed to compare the foliar N concentration based on non-destructive (reflectance) and destructive (laboratory analyses) methods in menthol mint. Foliar N concentration was measured through the Kjeldahl method and reflectance by Miniature Leaf Spectrometer C-710 (CID Bio-Science). Using reflectance data, several vegetation indices (VIs), that is, normalized difference red edge (NDRE), red edge normalized difference vegetation index (reNDVI), simple ratio (SR), green-red vegetation index (GRVI), canopy chlorophyll content index (CCCI), photochemical reflectance index (PRI), green chlorophyll index (CI Green ), red edge chlorophyll index (CI Red Edge ), canopy chlorophyll index (CCI), normalized pigment chlorophyll ratio index (NPCI), and structure insensitive pigment index (SIPI), were developed to determine the foliar N concentration. The highest correlation (r) between VIs and foliar N concentrations was achieved by NDRE (0.89), followed by reNDVI (0.84), SR (0.83), GRVI (0.78), and CCCI (0.76). Among the VIs, the NDRE index has been found to be the most accurate index that can precisely predict the foliar N concentration (R 2 = 0.79, RMSE = 0.18). In summary, the N deficiencies faced by the crop during its growth period can be detected effectively by calculating NDRE and reNDVI, which can be used as indicators for recommending precise management strategies for the application of nitrogenous fertilizers.

Spectral Reflectance as a Unique Tissue Identifier in Healthy Humans and Inhalation Injury Subjects

Tracheal intubation is the preferred method of airway management, a common emergency trauma medicine problem. Currently, methods for confirming tracheal tube placement are lacking, and we propose a novel technology, spectral reflectance, which may be incorporated into the tracheal tube for verification of placement. Previous work demonstrated a unique spectral profile in the trachea, which allowed differentiation from esophageal tissue in ex vivo swine, in vivo swine, and human cadavers. The goal of this study is to determine if spectral reflectance can differentiate between trachea and other airway tissues in living humans and whether the unique tracheal spectral profile persists in the presence of an inhalation injury. Reflectance spectra were captured using a custom fiber-optic probe from the buccal mucosa, posterior oropharynx, and trachea of healthy humans intubated for third molar extraction and from the trachea of patients admitted to a burn intensive care unit with and without inhalation injury. Using ratio comparisons, we found that the tracheal spectral profile was significantly different from buccal mucosa or posterior oropharynx, but the area under the curve values are not high enough to be used clinically. In addition, inhalation injury did not significantly alter the spectral reflectance of the trachea. Further studies are needed to determine the utility of this technology in a clinical setting and to develop an algorithm for tissue differentiation.

Relationship of Mineralogical Composition to Thermal Expansion, Spectral Reflectance, and Physico-Mechanical Aspects of Commercial Ornamental Granitic Rocks

The aim of the present study is to link the thermal expansion, spectral reflectance, and physico-mechanical aspects of different types of commercial granitic rocks with their mineralogical and chemical composition. The granitic rock types were characterized using several analyses, including petrography, chemical, mineralogical, and thermo-gravimetrical analysis using XRF, XRD, and TG/DTG/DSC techniques. The rock types were subjected to several performance tests, such as tests of their thermal expansion, spectral reflectance, and physico-mechanical properties. The results revealed that quartz, albite, and potash feldspar with minor amounts of mica (biotite/muscovite/annite) are the main mineralogical constitutes, in addition to some alteration minerals, such as kaolinite, saussorite, and prehnite. The studied granitic rocks were classified as monzogranite/syenogranite of high K-calc-alkaline and peraluminous characters and are related to late- to post-collisional settings. The thermogravimetrical analysis revealed that the overall mass loss over the whole temperature range up to 978 °C did not exceed 3% of the initial weight for all studied rocks. The results of thermal expansion revealed that the maximum change in linear thermal expansion for all rock types did not exceed 0.015% of their initial lengths at an unusual air temperature of 50 °C. The spectral analysis revealed that iron and hydroxyl ions are the main spectral absorption features that appeared in the VIS-NIR and SWIR regions, in addition to the appearance of the common and distinctive absorption peaks of the main mineral composition. Furthermore, the spectral reflectance demonstrated that the granitic rock types of low iron oxide content achieved a high reflectivity percent in the VIS-NIR and SWIR spectral regions compared with those of high iron content. As a general trend, the granitic rock types of high iron content and/or lower quartz content exhibited a high performance regarding their physical and mechanical properties, such as water absorption, apparent porosity, bulk density, compressive strength, and abrasion resistance. The results of water absorption, density, strength, and abrasion resistance of the studied granitic rocks are in the range of 0.14–0.31%, 2582–2644 kg/m³, 77.85–222.75 MPa, and 26.27–55.91 Ha, respectively, conforming to the requirements of ornamental stones according to the ASTM standard.

Prediction of South American Leaf Blight and Disease-Induced Photosynthetic Changes in Rubber Tree, Using Machine Learning Techniques on Leaf Hyperspectral Reflectance

The efficiency of visible and near-infrared (VIS/NIR) sensors and predictive modeling for detecting and classifying South American Leaf Blight (SALB) (Pseudocercospora ulei) in rubber trees (Hevea brasiliensis) has been poorly explored. Furthermore, the performance of VIS/NIR analysis combined with machine learning (ML) algorithms for predicting photosynthetic alterations caused by SALB is unknown. Therefore, this study aimed to detect and classify the SALB levels, as well as to predict, for the first time, disease-induced photosynthetic changes in rubber trees. Leaf hyperspectral reflectance combined with five ML techniques (random forest (RF), boosted regression tree (BRT), bagged classification and regression trees (BCART), artificial neural network (ANN), and support vector machine (SVM)) were used. The RF, ANN, and BCART models achieved the best performance for classifying the SALB levels on the training dataset (accuracies of 98.0 to 99.8%), with 10-fold cross-validation repeated five times, and test dataset (accuracies of 97.1 to 100%). The ANN and RF models were better at predicting leaf gas exchange-related traits such as net CO₂ assimilation rate (A) and extrinsic water use efficiency (WUEe) in the training (R² ranged from 0.97 to 0.99) and testing (R² ranged from 0.96 to 0.99) phases. In comparison, lower performances (R² ranged from 0.24 to 0.52) were evidenced for the photochemical traits. This research provides a basis for future designs of a remote monitoring system based on early detection and accurate diagnosis of biotic stress caused by SALB, which is fundamental for more effective rubber crop protection.

Frequency of processed kaolin application to prevent Diaphorina citri infestation and dispersal in flushing citrus orchards

BACKGROUND

Processed kaolin is a promising tactic that can be utilized for managing Diaphorina citri Kuwayama infestation. However, the frequency of kaolin application to protect citrus trees during flushing remains undetermined. The objective of this study was to ascertain the frequency of kaolin application (2%) required to reduce D. citri infestation and dispersal in flushing citrus orchards and to measure the spectral reflectance of kaolin-sprayed leaves.

RESULTS

Trees sprayed with kaolin at 7- and 14-day intervals showed an 80% psyllid reduction compared to untreated trees. In addition, there was lower psyllid dispersal in the kaolin-sprayed plots. Spectral measurements (wavelengths between 320 and 700 nm) showed an increased reflectance of 35.4% (adaxial leaf side) and 21.9% (abaxial leaf side) in mature leaves, and 9% (adaxial leaf side) and 2.2% (abaxial leaf side) in kaolin-sprayed immature leaves compared to untreated trees.

CONCLUSION

Application of kaolin (2%) at 7- and 14-day intervals can be an important and sustainable tool for reducing D. citri infestation and dispersal in flushing citrus orchards. The reduced D. citri population in plots with both kaolin application intervals may be related to the visual effect (whitish aspect) and increased light reflectance in citrus trees, which are probably the main mechanisms by which kaolin interferes on D. citri host finding behavior. © 2021 Society of Chemical Industry.

Evidence for coloration plasticity in the yellow-bellied toad, Bombina variegata

Phenotypic adaptation in terms of background color matching to the local habitat is an important mechanism for survival in prey species. Thus, intraspecific variation in cryptic coloration is expected among localities with dissimilar habitat features (e.g., soil, vegetation). Yellow-bellied toads (Bombina variegata) display a dark dorsal coloration that varies between populations, assumed to convey crypsis. In this study, we explored I) geographic variation in dorsal coloration and II) coloration plasticity in B. variegata from three localities differing in substrate coloration. Using avian visual modeling, we found that the brightness contrasts of the cryptic dorsa were significantly lower on the local substrates than substrates of other localities. In experiments, individuals from one population were able to quickly change the dorsal coloration to match a lighter substrate. We conclude that the environment mediates an adaptation in cryptic dorsal coloration. We suggest further studies to test the mechanisms by which the color change occurs and explore the adaptive potential of coloration plasticity on substrates of varying brightness in B. variegata and other species.

Protective Effects of Salicylic Acid and Calcium Chloride on Sage Plants (Salvia officinalis L. and Salviaelegans Vahl) under High-Temperature Stress

High-temperature stress is a major risk to fresh-market Salvia production, and heat intolerance is a major constraint in sage cultivation, particularly during the hot summer season. Previously, we investigated heat tolerance in five common-market cultivars of sage plants using leaf relative injury (RI) values and found that S. elegans Vahl (SE) and S. officinalis L. (SO) were the most and least heat-tolerant species, respectively. The exogenous applications of salicylic acid (SA) and calcium chloride (CaCl₂) to alleviate heat stress in various species have been extensively studied, but reports of the effects of SA and CaCl₂ treatments on the heat tolerance of sage plants are scarce. The objective of this study was to investigate how SA and CaCl₂ affect the physiology and morphology of SE and SO plants under high-temperature conditions. Potted plants were pretreated with SA (0, 100, 200, 400, and 800 μM) and CaCl₂ (0, 5, 10, and 15 mM), alone and combined, exposed to 55 °C and 80% humidity for 30 min, then placed in an environment-controlled chamber at 30 °C for three days and evaluated for changes in phenotypic appearance, RI, spectral reflectance, and chlorophyll fluorescence indices at different time intervals. Plants watered without chemical solutions were used as controls. Our results show that the growth of SO plants pretreated with SA and CaCl₂ was more robust, compared with control plants, which were considerably affected by heat stress, resulting in brown, withered leaves and defoliation. The effects of the combined applications of SA (100 μM) and CaCl₂ (5 mM) to SO plants were superior to control plants in increasing values of soil-plant analysis development (SPAD), normalized difference vegetation index (NDVI), and the maximal quantum yield of photosystemII photochemistry (Fv/Fm), while reducing RI%. Furthermore, SO plants exhibited higher SPAD and Fv/Fm values and lower RI% than SE plants in combined treatments at all time intervals after heat stress, implying that different genotypes displayed variations in their SPAD, Fv/Fm, and RI%. Thus, a combined treatment of 100 μM of SA and 5 mM of CaCl₂ is effective and beneficial to plant appearance and ability to ameliorate heat stress. These indices can be used as indicators to characterize the physiology of these plants and applied on a commercial scale for informing the development of rapid and precise management practices on bedded sage plants grown in plant factories to achieve maximum market benefit.

Trophic state in a tropical lake based on Chlorophyll-a profiler data and Sentinel-2 images: The onset of an algal bloom event

The condition of Lake Zirahuén was evaluated before and after a significant algal bloom took place. The state of the lake was tracked using measurements of chlorophyll-a concentration from a fluorometer attached to a conductivity, temperature, and depth (CTD) profiler and complemented with the use of satellite images from Sentinel-2. It was found that the current state of the lake is in transition from an oligotrophic to a mesotrophic level with some evidence of deterioration, but still being considered as a clear lake. With the use of empirical algorithms to retrieve chlorophyll-a from satellite data it was found that the images presented an acceptable feasibility (R²  = 0.64). The observed algal bloom was detected one month before the algae reached its major extent, being the reflectiveness of the green band a good indicator of the onset of the algal bloom event. Favorable conditions for the algal bloom were also recorded two months before its major extend through a chain of thermistors. PRACTITIONER POINTS: The trophic state of Lake Zirahuén was evaluated before and after a significant algal bloom took place. The lake is classified as being in transition from oligotrophic to mesotrophic. Nonetheless, it continues to have good clarity. Satellite images improve in the description of the spatial-temporal variability of the lake. In particular, the green band reflectiveness.

Resistance of Antarctic moss Sanionia uncinata to photoinhibition: chlorophyll fluorescence analysis of samples from the western and eastern coasts of the Antarctic Peninsula

Interspecific differences in sensitivity of the Antarctic moss Sanionia uncinata from King George Island (KGI) and James Ross Island (JRI) to photoinhibitory treatment were studied in laboratory conditions using chlorophyll fluorescence techniques. Slow (Kautsky) and fast (OJIP) kinetics were used for the measurements. Samples were exposed to a short-term (60 min) photoinhibitory treatment (PIT, 2000 μmol·m^-2 ·s^-1 PAR). The photoinhibitory treatment (PIT) led to photoinhibition which was indicated by the decrease in F_V /F_M and Φ_PSII in KGI but not in JRI samples. However, this decrease was small and full recovery was reached 90 min after PIT termination. Non-photochemical quenching (NPQ) was activated during the PIT, and rapidly relaxed during recovery. Early stages of photoinhibition showed a drop in F_V /F_M and Φ_PSII to minimum values within the first 10 s of the PIT, with their subsequent increase apparent within fast (0-5 min PIT) and slow (5-50 min PIT) phases of adjustment. The PIT caused a decrease in the performance index (Pi_Abs), photosynthetic electron transport per reaction centre (RC) (ET₀ /RC). The PIT induced an increase in thermal dissipation per RC (DI₀ /RC), effectivity of thermal dissipation (Phi_D₀ ), absorption per RC (ABS/RC) and trapping rate per RC (TR₀ /RC). In conclusion, PIT led to only slight photoinhibition followed by fast recovery in S. uncinata from KGI and JRI, since F_V /F_M and Φ_PSII returned to pre-photoinhibitory conditions. Therefore, S. uncinata might be considered resistant to photoinhibition even in the wet state. The KGI samples showed higher resistance to photoinhibition than the JRI samples.

Using Spectral Reflectance to Estimate the Leaf Chlorophyll Content of Maize Inoculated With Arbuscular Mycorrhizal Fungi Under Water Stress

Leaf chlorophyll content is an important indicator of the growth and photosynthesis of maize under water stress. The promotion of maize physiological growth by (AMF) has been studied. However, studies of the effects of AMF on the leaf chlorophyll content of maize under water stress as observed through spectral information are rare. In this study, a pot experiment was carried out to spectrally estimate the leaf chlorophyll content of maize subjected to different durations (20, 35, and 55 days); degrees of water stress (75%, 55% and 35% water supply) and two inoculation treatments (inoculation with Funneliformis mosseae and no inoculation). Three machine learning algorithms, including the back propagation (BP) method, least square support vector machine (LSSVM) and random forest (RF) method, were used to estimate the leaf chlorophyll content of maize. The results showed that AMF increased the leaf chlorophyll content, net photosynthetic rate (A), stomatal conductance (gs), transpiration rate (E), and water use efficiency (WUE) of maize but decreased the intercellular carbon dioxide concentration (Ci) of maize and atmospheric vapor pressure deficit (VPD) regardless of the water stress duration and degree. The first-order differential spectral data can better reflect the correlation between leaf chlorophyll content and spectrum of inoculated maize when compared with original spectral data. The BP model performed bestin modeling the maize leaf chlorophyll content, yielding the largest R ²-values and smallest root mean square error (RMSE) values, regardless of stress duration. These results provide a reliable basis for the effective monitoring of the leaf chlorophyll content of maize under water stress.

Retrieval of Vegetation Indices Related to Leaf Water Content from a Single Index: A Case Study of Eucalyptus globulus (Labill.) and Pinus radiata (D. Don.)

The vegetation indices derived from spectral reflectance have served as an indicator of vegetation's biophysical and biochemical parameters. Some of these indices are capable of characterizing more than one parameter at a time. This study examines the feasibility of retrieving several spectral vegetation indices from a single index under the assumption that all these indices are correlated with water content. The models used are based on a linear regression adjusted with least squares. The spectral signatures of Eucalyptus globulus and Pinus radiata, which constitute 97.5% of the forest plantation in Valparaiso region in Chile, have been used to test and validate the proposed approach. The linear models were fitted with an independent data set from which their performance was assessed. The results suggest that from the Leaf Water Index, other spectral indices can be recovered with a root mean square error up to 0.02, a bias of 1.12%, and a coefficient of determination of 0.77. The latter encourages using a sensor with discrete wavelengths instead of a continuum spectrum to estimate the forestry's essential parameters.

Spectral Reflectance Can Differentiate Tracheal and Esophageal Tissue in the Presence of Bodily Fluids and Soot

Endotracheal intubation is a common life-saving procedure implemented in emergency care to ensure patient oxygenation, but it is difficult and often performed in suboptimal conditions leading to high rates of patient complications. Undetected misplacement in the esophagus is a preventable complication that can lead to fatalities in 5–10% of patients who undergo emergency intubation. End-tidal carbon dioxide monitoring and other proper placement detection methods are useful, yet the problem of misplacement persists. Our previous work demonstrated the utility of spectral reflectance sensors for differentiating esophageal and tracheal tissues, which can be used to confirm proper endotracheal tube placement. In this study, we examine the effectiveness of spectral characterization in the presence of saline, blood, “vomit”, and soot in the trachea. Our results show that spectral properties of the trachea that differentiate it from the esophagus persist in the presence of these substances. This work further confirms the potential usefulness of this novel detection technology in field applications.

EcoSpec: Highly Equipped Tower-Based Hyperspectral and Thermal Infrared Automatic Remote Sensing System for Investigating Plant Responses to Environmental Changes

Despite an advanced ability to forecast ecosystem functions and climate at regional and global scales, little is known about relationships between local variations in water and carbon fluxes and large-scale phenomena. To enable data collection of local-scale ecosystem functions to support such investigations, we developed the EcoSpec system, a highly equipped remote sensing system that houses a hyperspectral radiometer (350-2500 nm) and five optical and infrared sensors in a compact tower. Its custom software controls the sequence and timing of movement of the sensors and system components and collects measurements at 12 locations around the tower. The data collected using the system was processed to remove sun-angle effects, and spectral vegetation indices computed from the data (i.e., the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), and Moisture Stress Index (MSI)) were compared with the fraction of photochemically active radiation (fPAR) and canopy temperature. The results showed that the NDVI, NDWI, and PRI were strongly correlated with fPAR; the MSI was correlated with canopy temperature at the diurnal scale. These correlations suggest that this type of near-surface remote sensing system would complement existing observatories to validate satellite remote sensing observations and link local and large-scale phenomena to improve our ability to forecast ecosystem functions and climate. The system is also relevant for precision agriculture to study crop growth, detect disease and pests, and compare traits of cultivars.

Use of Non-Destructive Measurements to Identify Cucurbit Species (Cucurbita maxima and Cucurbita moschata) Tolerant to Waterlogged Conditions

Limited information is available regarding the physiology of squash plants grown under waterlogging stress. The objectives of this study were to investigate the growth and physiological performances of three cucurbit species, Cucurbita maxima cultivar (cv.) OK-101 (OK) and Cucurbita moschata cv. Early Price (EP) and Strong Man (SM), in response to waterlogging conditions, and to develop a precise, integrated, and quantitative non-destructive measurement of squash genotypes under stress. All tested plants were grown in a growth chamber under optimal irrigation and growth conditions for a month, and the pot plants were then subjected to non-waterlogging (control) and waterlogging treatments for periods of 1, 3, 7, and 13 days (d), followed by a 3-d post-waterlogging recovery period after water drainage. Plants with phenotypes, such as fresh weight (FW), dry weight (DW), and dry matter (DM) of shoots and roots, and various physiological systems, including relative water content (RWC), soil and plant analysis development (SPAD) chlorophyll meter, ratio of variable/maximal fluorescence (Fv/Fm), quantum photosynthetic yield (YII), normalized difference vegetation index (NDVI), and photochemical reflectance index (PRI) values, responded differently to waterlogging stress in accordance with the duration of the stress period and subsequent recovery period. When plants were treated with stress for 13 d, all plants exhibited harmful effects to their leaves compared with the control, but EP squash grew better than SM and OK squashes and exhibited stronger tolerance to waterlogging and showed less injury. Changes in the fresh weight, dry weight, and dry matter of shoots and roots indicated that OK plants suffered more severely than EP plants at the 3-d drainage period. The values of RWC, SPAD, Fv/Fm, YII, NDVI, and PRI in both SM and OK plants remarkably decreased at waterlogging at the 13-d time point compared with controls under identical time periods. However, the increased levels of SPAD, Fv/Fm, YII, NDVI, and PRI observed on 7 d or 13 d of waterlogging afforded the EP plant leaf with improved waterlogged tolerance. Significant and positive correlations were observed among NDVI and PRI with SPAD, Fv/Fm, and YII, indicating that these photosynthetic indices can be useful for developing non-destructive estimations of chlorophyll content in squashes when screening for waterlogging-tolerant plants, for establishing development practices for their cultivation in fields, and for enhanced cultivation during waterlogging in frequently flooded areas.

Simulation and Verification of Vertical Heterogeneity Spectral Response of Winter Wheat Based on the mSCOPE Model

Vertical heterogeneity of the biochemical characteristics of crop canopy is important in diagnosing and monitoring nutrition, disease, and crop yield via remote sensing. However, the research on vertical isomerism was not comprehensive. Experiments were carried out from the two levels of simulation and verification to analyze the applicability of this recently development model. Effects of winter wheat on spectrum were studied when input different structure parameters (e.g., leaf area index (LAI)) and physicochemical parameters (e.g., chlorophyll content (Chla+b) and water content (Cw)) to the mSCOPE (Soil Canopy Observation, Photochemistry, and Energy fluxes) model. The maximum operating efficiency was 127.43, when the winter wheat was stratified into three layers. Meanwhile, the simulation results also proved that: the vertical profile of LAI had an influence on canopy reflectance in almost all bands; the vertical profile of Chla+b mainly affected the reflectivity of visible region; the vertical profile of Cw only affected the near-infrared reflectance. The verification results showed that the vegetation indexes (VIs) selected of different bands were strongly correlated with the parameters of the canopy. LAI, Chla+b and Cw affected VIs estimation related to LAI, Chla+b and Cw respectively. The Root Mean Square Error (RMSE) of the new-proposed NDVIgreen was the smallest, which was 0.05. Sensitivity analysis showed that the spectrum was more sensitive to changes in upper layer parameters, which verified the rationality of mSCOPE model in explaining the law that light penetration in vertical nonuniform canopy gradually decreases with the increase of layers.

Plot-level rapid screening for photosynthetic parameters using proximal hyperspectral imaging

Photosynthesis is currently measured using time-laborious and/or destructive methods which slows research and breeding efforts to identify crop germplasm with higher photosynthetic capacities. We present a plot-level screening tool for quantification of photosynthetic parameters and pigment contents that utilizes hyperspectral reflectance from sunlit leaf pixels collected from a plot (~2 m×2 m) in <1 min. Using field-grown Nicotiana tabacum with genetically altered photosynthetic pathways over two growing seasons (2017 and 2018), we built predictive models for eight photosynthetic parameters and pigment traits. Using partial least squares regression (PLSR) analysis of plot-level sunlit vegetative reflectance pixels from a single visible near infra-red (VNIR) (400-900 nm) hyperspectral camera, we predict maximum carboxylation rate of Rubisco (Vc,max, R2=0.79) maximum electron transport rate in given conditions (J1800, R2=0.59), maximal light-saturated photosynthesis (Pmax, R2=0.54), chlorophyll content (R2=0.87), the Chl a/b ratio (R2=0.63), carbon content (R2=0.47), and nitrogen content (R2=0.49). Model predictions did not improve when using two cameras spanning 400-1800 nm, suggesting a robust, widely applicable and more 'cost-effective' pipeline requiring only a single VNIR camera. The analysis pipeline and methods can be used in any cropping system with modified species-specific PLSR analysis to offer a high-throughput field phenotyping screening for germplasm with improved photosynthetic performance in field trials.

Color-matching between pollen and corolla: hiding pollen via visual crypsis?

Visual signals attractive to friends may also attract enemies.  The bright colors of anthers and pollen have generally been thought to attract pollinators. We hypothesize that visual crypsis of anthers, and particularly pollen, should be favored in flowering plants because protection from pollen collectors reduces the loss of male gametes. To understand adaptive strategies relating to the color of pollen, we measured the color of pollen, undehisced anther sacs, and their background, the corolla, with a spectrometer for 104 insect-pollinated flowering species from a natural community in Hengduan Mountains, southwest China. The colors of anthers, pollen and corollas were diverse in these species. The color diversity of exposed pollen was significantly higher than that of concealed pollen (i.e. where anthers are enclosed or shielded by corollas). The color contrast between pollen and corolla was significantly smaller in species with exposed pollen than in those with concealed pollen. Unlike anther color, exposed pollen color tended to match its background corolla color. Our phylogenetic comparative analysis showed contrasting effects of pollen color patterns between flowers with exposed pollen and those with concealed pollen, revealing a strategy of hiding pollen from pollen thieves via visual crypsis.

Lighting Deviation Correction for Integrating-Sphere Multispectral Imaging Systems

In an integrating sphere multispectral imaging system, measurement inconsistency can arise when acquiring the spectral reflectances of samples. This is because the lighting condition can be changed by the measured samples, due to the multiple light reflections inside the integrating sphere. Besides, owing to non-uniform light transmission of the lens and narrow-band filters, the measured reflectance is spatially dependent. To deal with these problems, we propose a correction method that consists of two stages. The first stage employs a white board to correct non-uniformity and a small white patch to correct lighting deviation, both under the assumption of ideal Lambertian reflection. The second stage uses a polynomial regression model to further remove the lighting inconsistency when measuring non-Lambertian samples. The method is evaluated on image data acquired in a real multispectral imaging system. Experimental results illustrate that our method eliminates the measurement inconsistency considerably. This consequently improves the spectral and colorimetric accuracy in color measurement, which is crucial to practical applications.

Improved Bathymetric Mapping of Coastal and Lake Environments Using Sentinel-2 and Landsat-8 Images

The bathymetry of nearshore coastal environments and lakes is constantly reworking because of the change in the patterns of energy dispersal and related sediment transport pathways. Therefore, updated and accurate bathymetric models are a crucial component in providing necessary information for scientific, managerial, and geographical studies. Recent advances in satellite technology revolutionized the acquisition of bathymetric profiles, offering new vistas in mapping. This contribution analyzed the suitability of Sentinel-2 and Landsat-8 images for bathymetric mapping of coastal and lake environments. The bathymetric algorithm was developed using an empirical approach and a random forest (RF) model based on the available high-resolution LiDAR bathymetric data for Mobile Bay, Tampa Bay, and Lake Huron regions obtained from the National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center (NGDC). Our results demonstrate that the satellite-derived bathymetry is efficient for retrieving depths up to 10 m for coastal regions and up to 30 m for the lake environment. While using the empirical approach, the root-mean-square error (RMSE) varied between 1.99 m and 4.74 m for the three regions. The RF model, on the other hand, provided an improved bathymetric model with RMSE between 1.13 m and 1.95 m. The comparative assessment suggests that Sentinel-2 has a slight edge over Landsat-8 images while employing the empirical approach. On the other hand, the RF model shows that Landsat-8 retrieves a better bathymetric model than Sentinel-2. Our work demonstrated that the freely available Sentinel-2 and Landsat-8 imageries proved to be reliable data for acquiring updated bathymetric information for large areas in a short period.

Fast Optical Humidity Sensor Based on Hydrogel Thin Film Expansion for Harsh Environment

With the application of a recently developed deposition method called initiated chemical vapor deposition (iCVD), responsive hydrogel thin films in the order of a few hundred nanometers were created. When in contact with humid air, the hydrogel layer increases its thickness considerably. The measurement of the thickness change was realized interferometrically with a laser and a broadband light source in two different implementations. The relative change in thickness with respect to humidity can be described with the Flory⁻Huggins theory. The required Flory⁻Huggins interaction parameter was determined for the actual hydrogel composition. The setup was designed without electric components in the vicinity of the active sensor layer and is therefore applicable in harsh environments such as explosive or corrosive ones. The implemented sensor prototype delivered reproducible relative humidity ( R H ) values and the achieved response time for an abrupt change of the humidity τ 63 ≤ 2.5 s was about three times faster compared to one of the fastest commercially available sensors on the market.

Association between community assemblage of flower colours and pollinator fauna: a comparison between Japanese and New Zealand alpine plant communities

BACKGROUND AND AIMS

Flower colour plays a major role in the attraction and decision-making of pollinators. Different functional groups of pollinators tend to prefer different flower colours, and therefor may lead to different flower colour compositions among different communities depending on the visual system of the dominant pollinators. However, few studies have investigated the linkage between pollinator fauna and flower colour composition in natural communities, a theme we explored in the present study.

METHODS

Flower spectral reflectance of 106 Japanese and 96 New Zealand alpine plants in the wavelength range 300-700 nm were measured. The composition of pollinator fauna in the communities and the types of pollinators for each plant species were also investigated.

KEY RESULTS

Based on bee and fly colour vision models, as well as a principal components analysis, considering phylogenetic non-independence between plant species, flower colours appeared to vary according to pollinator type rather than geographical region. Consequently, flower colour composition differed between the regions, reflecting the bee/fly mixed pollinator fauna of Japan and the fly-dominant pollinator fauna of New Zealand. According to the bee colour vision model, the majority of the colours of hymenopteran-pollinated flowers appeared to be discriminated by bees. In contrast, many of the colours of dipteran-pollinated flowers would not be discriminated by bees and flies.

CONCLUSION

The results suggest that the differences in flower colour composition between Japanese and New Zealand alpine communities are due to differences in the pollinator fauna in these communities rather than differences in abiotic factors between the geographical regions and the phylogenetic origin of the communities.

Removal of soil biota alters soil feedback effects on plant growth and defense chemistry

We examined how the removal of soil biota affects plant-soil feedback (PSF) and defense chemistry of Jacobaea vulgaris, an outbreak plant species in Europe containing the defense compounds pyrrolizidine alkaloids (PAs). Macrofauna and mesofauna, as well as fungi and bacteria, were removed size selectively from unplanted soil or soil planted with J. vulgaris exposed or not to above- or belowground insect herbivores. Wet-sieved fractions, using 1000-, 20-, 5- and 0.2-μm mesh sizes, were added to sterilized soil and new plants were grown. Sieving treatments were verified by molecular analysis of the inocula. In the feedback phase, plant biomass was lowest in soils with 1000- and 20-μm inocula, and soils conditioned with plants gave more negative feedback than without plants. Remarkably, part of this negative PSF effect remained present in the 0.2-μm inoculum where no bacteria were present. PA concentration and composition of plants with 1000- or 20-μm inocula differed from those with 5- or 0.2-μm inocula, but only if soils had been conditioned by undamaged plants or plants damaged by aboveground herbivores. These effects correlated with leaf hyperspectral reflectance. We conclude that size-selective removal of soil biota altered PSFs, but that these PSFs were also influenced by herbivory during the conditioning phase.

Reproductive success of soybean (Glycine max L. Merril) cultivars and exotic lines under high daytime temperature

The objectives were to (a) quantify the effects of high daytime temperature (HDT) from gametogenesis to full bloom on photosynthesis and pod set in soybean (Glycine max L. Merril) genotypes and (b) assess the relationships among photosynthesis, cardinal temperatures for pollen germination, in vitro pollen germination percentage, canopy reflectance, and pod-set percentage. Three field experiments were conducted, and Experiment I had HDT between gametogenesis and full bloom (36.5°C to 38.6°C) compared with Experiments II and III (29.5°C to 31.6°C; optimum temperature). HDT decreased photosynthesis (22%) and pod-set percent (11%) compared with Experiment III. Cultivars had higher photosynthesis and pod-set percent than plant introduction (PI) lines. The cultivars (i.e., IA3023 and KS4694) and PI lines (i.e., PI393540 and PI588026A) were HDT tolerant and susceptible, respectively. The decreased pod-set percentage in susceptible genotypes (PI lines) was associated with pollen characteristics. Significant positive (r2  ≥ 0.67) association between photosynthesis, cardinal temperatures for pollen germination (Topt and Tmax ) with pod-set percentage was observed. However, a negative (r2  ≥ -0.43) association between photosynthesis and pod set with canopy reflectance at visible spectrum was observed. In vitro pollen germination and canopy reflectance at visible spectrum can be used as a high-throughput phenotypic tool for breeding HDT-tolerant genotypes.

Biochemical and Physiological Characteristics of Photosynthesis in Plants of Two Calathea Species

Plants of the genus Calathea possess many leaf colors, and they are economically important because they are widely used as ornamentals for interior landscaping. Physiological performances and photosynthetic capacities of C. insignis and C. makoyana were investigated. The photosynthetic efficiencies of C. insignis and C. makoyana were significantly increased when the photosynthetic photon flux density (PPFD) increased from 0 to 600 μmol photons·m-2·s-1 and became saturated with a further increase in the PPFD. The two Calathea species had lower values of both the light saturation point and maximal photosynthetic rate, which indicated that they are shade plants. No significant differences in predawn Fv/Fm values (close to 0.8) were observed between dark-green (DG) and light-green (LG) leaf sectors in all tested leaves. However, the effective quantum yield of photosystem II largely decreased as the PPFD increased. An increase in the apparent photosynthetic electron transport rate was observed in both species to a maximum at 600 μmol·m-2·s-1 PPFD, following by a decrease to 1500 μmol·m-2·s-1 PPFD. Compared to LG leaf extracts, DG leaf extracts contained higher levels of chlorophyll (Chl) a, Chl b, Chls a + b, carotenoids (Cars), anthocyanins (Ants), flavonoids (Flas), and polyphenols (PPs) in all plants, except for the Ant, Fla and PP contents of C. insignis plants. Calathea insignis also contained significantly higher levels of total protein than did C. makoyana. The adjusted normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), red-green, and flavonol index (FlavI) were significantly correlated to leaf Chls a + b, Cars, Ants, and Flas in C. makoyana, respectively, and can be used as indicators to characterize the physiology of these plants.

Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues

Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer‐level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content‐chroma ratio, anthocyanin content‐chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r² and normalized root‐mean‐square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the anthocyanin concentrations in both floral and vegetative tissues. This method is efficient, completely noninvasive, applicable to both uniform and patterned color, and works with samples of any size.

Hyperspectral Imaging and K-Means Classification for Histologic Evaluation of Ductal Carcinoma In Situ

Hyperspectral imaging (HSI) is a non-invasive optical imaging modality that shows the potential to aid pathologists in breast cancer diagnoses cases. In this study, breast cancer tissues from different patients were imaged by a hyperspectral system to detect spectral differences between normal and breast cancer tissues. Tissue samples mounted on slides were identified from 10 different patients. Samples from each patient included both normal and ductal carcinoma tissue, both stained with hematoxylin and eosin stain and unstained. Slides were imaged using a snapshot HSI system, and the spectral reflectance differences were evaluated. Analysis of the spectral reflectance values indicated that wavelengths near 550 nm showed the best differentiation between tissue types. This information was used to train image processing algorithms using supervised and unsupervised data. The K-means method was applied to the hyperspectral data cubes, and successfully detected spectral tissue differences with sensitivity of 85.45%, and specificity of 94.64% with true negative rate of 95.8%, and false positive rate of 4.2%. These results were verified by ground-truth marking of the tissue samples by a pathologist. In the hyperspectral image analysis, the image processing algorithm, K-means, shows the greatest potential for building a semi-automated system that could identify and sort between normal and ductal carcinoma in situ tissues.

EPIC Spectral Observations of Variability in Earth's Global Reflectance

NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) satellite observes the entire sunlit Earth every 65 to 110 min from the Sun-Earth Lagrangian L1 point. This paper presents initial EPIC shortwave spectral observations of the sunlit Earth reflectance and analyses of its diurnal and seasonal variations. The results show that the reflectance depends mostly on (1) the ratio between land and ocean areas exposed to the Sun and (2) cloud spatial and temporal distributions over the sunlit side of Earth. In particular, the paper shows that (a) diurnal variations of the Earth's reflectance are determined mostly by periodic changes in the land-ocean fraction of its the sunlit side; (b) the daily reflectance displays clear seasonal variations that are significant even without including the contributions from snow and ice in the polar regions (which can enhance daily mean reflectances by up to 2 to 6% in winter and up to 1 to 4% in summer); (c) the seasonal variations of the sunlit Earth reflectance are mostly determined by the latitudinal distribution of oceanic clouds.

Leaf Spectral Reflectance Shows Thalassia testudinum Seedlings More Sensitive to Hypersalinity than Hyposalinity

Thalassia testudinum (turtle grass) is the dominant and climax-successional seagrass species in the subtropical/tropical Atlantic and Caribbean region. Two die-offs of T. testudinum in Florida Bay, United States have raised concerns regarding the resilience of this species to environmental disturbances. Seedlings are important in recovery of T. testudinum, following disturbance events. Leaf spectral reflectance [R(λ)] was measured in T. testudinum seedlings exposed for 2 weeks to three salinities (20, 35, and 50) and two light levels (full sun and 50-70% light reduction) in experimental mesocosms. Multivariate analyses indicated that hypersalinity had a greater effect on spectral reflectance than hyposalinity or light reduction. There was an increase in variability and flattening of reflectance spectra at the highest salinity. All three salinity treatments had distinct reflectance spectra across green wavelengths (530-580 nm), with additional discrimination between 20 versus 50 and 35 versus 50 treatments across red wavelengths (630-690 nm). Red:Green reflectance ratios were highest and photochemical reflective index values were lowest for the salinity 50 treatment, but were not significantly different between the salinity 20 and 35 treatments. The changes in the R(λ) spectra for the salinity 50 seedlings were consistent with previously observed reductions in leaf pigments and maximum photochemical efficiency of photosystem II. These observations indicate that leaf spectral reflectance is a sensitive indicator of plant stress in T. testudinum seedlings and that seedlings are more sensitive to short-term exposures to hypersalinity than hyposalinity.

Non-destructive prediction of pigment content in lettuce based on visible-NIR spectroscopy

BACKGROUND

Lettuce (Lactuca sativa L.) is one of the most important salad vegetables in the world, with a number of head shapes, leaf types and colors. The lettuce pigments play important physiological functions, such as photosynthetic processes and light stress defense, but they also benefit human health because of their antioxidant action and anticarcinogenic properties. In this study three lettuce cultivars were grown under different farming systems, and partial least squares models were built to predict the leaf chlorophyll, carotenoid and anthocyanin content.

RESULTS

The three proposed models resulted in high coefficients of determination and variable importance for the projection values, as well as low estimative errors for calibration and external validation datasets. These results confirmed that it is possible to accurately predict chlorophyll, carotenoid and anthocyanin content of green and red lettuces, grown in different farming systems, based on the spectral reflectance from 500 to 1000 nm.

CONCLUSION

The proposed models were adequate for estimating lettuce pigments in a quick and non-destructive way, representing an alternative to conventional measurement methods. Prediction accuracies were improved by using the detrending, smoothing and first derivative pretreatments to the original spectral signatures prior to estimating lettuce chlorophyll, carotenoid and anthocyanin content, respectively. © 2016 Society of Chemical Industry.

acuteserrata and its spectral reflectance response under throughfall elimination]

Our objective was to explore the mechanism of spectral reflectance response to leaf photosynthetic pigment seasonal dynamic of Quercus aliena var. acuteserrata under throughfall elimination. We simulated rainfall decline through throughfall elimination (TFE) treatment in the experiment plots of Baotianman Natural Reserve in Henan, measured leaf pigment content and its spectral reflectance during growing season in both TFE and control plots. We analyzed seasonal changes of photosynthetic pigments and changes of pigments induced by TFE and their spectral reflectance responses. The results showed that all photosynthetic pigments content and pigment-ratios exhibited clear seasonal patterns. Leaf photosynthetic pigments content and ratio had differences between TFE plot and control plot during the whole growing season, and significant difference was found in chlorophyll b (Chl b) indicating that Chl b had higher sensitivity than other pigments. Carotenoids (Car) content showed minor difference compared with other pigments, indicating that Car had less sensitivity to TFE. The spectral reflectance of 550 nm was found to be the waveband most sensitive to seasonal changes of pigments, so we formulated the sample ratio index (SR_750,550) based on it. The strong positive relationships between SR_750,550 and Chl a, Chl b, Chl and Car contents were found with high significant level. Similarly, significant negative relationships were also been found between photochemical reflectance index (PRI) and Car/Chl. The spectral reflectance of 550 nm was most sensitive to changes of pigments induced by TFE. SR_750,550 was sensitive to changes of leaf Chl a, Chl b and Chl content induced by TFE (P＜0.01), but not to change of Chl a/b. PRI was sensitive to change of leaf Car/Chl induced by TFE (P＜0.01).

Recent Prospects in the Inline Monitoring of Nanocomposites and Nanocoatings by Optical Technologies

Nanostructured materials have emerged as a key research field in order to confer materials with unique or enhanced properties. The performance of nanocomposites depends on a number of parameters, but the suitable dispersion of nanoparticles remains the key in order to obtain the full nanocomposites' potential in terms of, e.g., flame retardance, mechanical, barrier, thermal properties, etc. Likewise, the performance of nanocoatings to obtain, for example, tailored surface affinity with selected liquids (e.g., for self-cleaning ability or anti-fog properties), protective effects against flame propagation, ultra violet (UV) radiation or gas permeation, is highly dependent on the nanocoating's thickness and homogeneity. In terms of recent advances in the monitoring of nanocomposites and nanocoatings, this review discusses commonly-used offline characterization approaches, as well as promising inline systems. All in all, having good control over both the dispersion and thickness of these materials would help with reaching optimal and consistent properties to allow nanocomposites to extend their use.

Evaluating Leaf and Canopy Reflectance of Stressed Rice Plants to Monitor Arsenic Contamination

Arsenic contamination is a serious problem in rice cultivated soils of many developing countries. Hence, it is critical to monitor and control arsenic uptake in rice plants to avoid adverse effects on human health. This study evaluated the feasibility of using reflectance spectroscopy to monitor arsenic in rice plants. Four arsenic levels were induced in hydroponically grown rice plants with application of 0, 5, 10 and 20 µmol·L(-1) sodium arsenate. Reflectance spectra of upper fully expanded leaves were acquired over visible and infrared (NIR) wavelengths. Additionally, canopy reflectance for the four arsenic levels was simulated using SAIL (Scattering by Arbitrarily Inclined Leaves) model for various soil moisture conditions and leaf area indices (LAI). Further, sensitivity of various vegetative indices (VIs) to arsenic levels was assessed. Results suggest that plants accumulate high arsenic amounts causing plant stress and changes in reflectance characteristics. All leaf spectra based VIs related strongly with arsenic with coefficient of determination (r²) greater than 0.6 while at canopy scale, background reflectance and LAI confounded with spectral signals of arsenic affecting the VIs' performance. Among studied VIs, combined index, transformed chlorophyll absorption reflectance index (TCARI)/optimized soil adjusted vegetation index (OSAVI) exhibited higher sensitivity to arsenic levels and better resistance to soil backgrounds and LAI followed by red edge based VIs (modified chlorophyll absorption reflectance index (MCARI) and TCARI) suggesting that these VIs could prove to be valuable aids for monitoring arsenic in rice fields.

Relationship between leaf optical properties, chlorophyll fluorescence and pigment changes in senescing Acer saccharum leaves

The ability of plants to sequester carbon is highly variable over the course of the year and reflects seasonal variation in photosynthetic efficiency. This seasonal variation is most prominent during autumn, when leaves of deciduous tree species such as sugar maple (Acer saccharum Marsh.) undergo senescence, which is associated with downregulation of photosynthesis and a change of leaf color. The remote sensing of leaf color by spectral reflectance measurements and digital repeat images is increasingly used to improve models of growing season length and seasonal variation in carbon sequestration. Vegetation indices derived from spectral reflectance measurements and digital repeat images might not adequately reflect photosynthetic efficiency of red-senescing tree species during autumn due to the changes in foliar pigment content associated with autumn phenology. In this study, we aimed to assess how effectively several widely used vegetation indices capture autumn phenology and reflect the changes in physiology and photosynthetic pigments during autumn. Chlorophyll fluorescence and pigment content of green, yellow, orange and red leaves were measured to represent leaf senescence during autumn and used as a reference to validate and compare vegetation indices derived from leaf-level spectral reflectance measurements and color analysis of digital images. Vegetation indices varied in their suitability to track the decrease of photosynthetic efficiency and chlorophyll content despite increasing anthocyanin content. Commonly used spectral reflectance indices such as the normalized difference vegetation index and photochemical reflectance index showed major constraints arising from a limited representation of gradual decreases in chlorophyll content and an influence of high foliar anthocyanin levels. The excess green index and green-red vegetation index were more suitable to assess the process of senescence. Similarly, digital image analysis revealed that vegetation indices such as Hue and normalized difference index are superior compared with the often-used green chromatic coordinate. We conclude that indices based on red and green color information generally represent autumn phenology most efficiently.

Division of Labor Brings Greater Benefits to Clones of Carpobrotus edulis in the Non-native Range: Evidence for Rapid Adaptive Evolution

Why some species become invasive while others do not is a central research request in biological invasions. Clonality has been suggested as an attribute that could contribute to plant invasiveness. Division of labor is an important advantage of clonal growth, and it seems reasonable to anticipate that clonal plants may intensify this clonal attribute in an invaded range because of positive selection on beneficial traits. To test this hypothesis, we collected clones of Carpobrotus edulis from native and invasive populations, grew pairs of connected and severed ramets in a common garden and under negative spatial covariance of nutrients and light to induce division of labor, and measured biomass allocation ratios, final biomass, and photochemical efficiency. Our results showed that both clones from the native and invaded range develop a division of labor at morphological and physiological level. However, the benefit from the division of labor was significantly higher in apical ramets from the invaded range than in ramets from the native area. This is a novel and outstanding result because it provides the first evidence that the benefit of a key clonal trait such as division of labor may have been subjected to evolutionary adaptation in the invaded range. The division of labor can therefore be considered an important trait in the invasiveness of C. edulis. An appropriate assessment of the influence of clonal traits in plant invasions seems key for understanding the underlying mechanisms behind biological invasions of new environments.

Night life on the beach: selfing to avoid pollinator competition between two sympatric Silene species

BACKGROUND AND AIMS

Evolution of autonomous selfing may be advantageous because it allows for reproductive assurance. In co-flowering plants competing for pollinators, the least common and/or attractive could suffer pollen limitations. Silene niceensis and S. ramosissima are taxonomically related species sharing the same habitat, although S. ramosissima is less abundant and has a more restricted distribution. They also have the same a priori nocturnal pollinator syndrome, and show an overlapping flowering phenology. The aim of this study was to investigate whether a selfing strategy in S. ramosissima allows it to avoid pollinator competition and/or interspecific pollen transfer with S. niceensis, which would thus enable both species to reach high levels of fruit and seed set.

METHODS

The breeding system, petal colour, flower life span and degree of overlap between male and female phases, floral visitor abundance and visitation rates were analysed in two sympatric populations of S. niceensis and S. ramosissima in southern Spain.

KEY RESULTS

Autonomous selfing in S. ramosissima produced very high fruit and seed set, which was also similar to open-pollinated plants. Silene niceensis showed minimum levels of autonomous selfing, and pollen/ovule ratios were within the range expected for the breeding system. In contrast to S. niceensis, flower life span was much shorter in S. ramosissima, and male and female organs completely overlapped in space and time. Upper surface petals of both species showed differing brightness, chroma and hue. Flowers of S. niceensis were actively visited by moths, hawkmoths and syrphids, whereas those of S. ramosissima were almost never visited.

CONCLUSIONS

The findings show that different breeding strategies exist between the sympatric co-flowering S. niceensis and S. ramosissima, the former specializing in crepuscular-nocturnal pollination and the latter mainly based on autonomous selfing. These two strategies allow both species to share the restricted dune habitat in which they exist, with a high female reproductive success due to the absence of pollinator competition and/or interspecific pollen flow.

The effect of polyploidy and hybridization on the evolution of floral colour in Nicotiana (Solanaceae)

BACKGROUND AND AIMS

Speciation in angiosperms can be accompanied by changes in floral colour that may influence pollinator preference and reproductive isolation. This study investigates whether changes in floral colour can accompany polyploid and homoploid hybridization, important processes in angiosperm evolution.

METHODS

Spectral reflectance of corolla tissue was examined for 60 Nicotiana (Solanaceae) accessions (41 taxa) based on spectral shape (corresponding to pigmentation) as well as bee and hummingbird colour perception in order to assess patterns of floral colour evolution. Polyploid and homoploid hybrid spectra were compared with those of their progenitors to evaluate whether hybridization has resulted in floral colour shifts.

KEY RESULTS

Floral colour categories in Nicotiana seem to have arisen multiple times independently during the evolution of the genus. Most younger polyploids displayed an unexpected floral colour, considering those of their progenitors, in the colour perception of at least one pollinator type, whereas older polyploids tended to resemble one or both of their progenitors.

CONCLUSIONS

Floral colour evolution in Nicotiana is weakly constrained by phylogeny, and colour shifts do occur in association with both polyploid and homoploid hybrid divergence. Transgressive floral colour in N. tabacum has arisen by inheritance of anthocyanin pigmentation from its paternal progenitor while having a plastid phenotype like its maternal progenitor. Potentially, floral colour evolution has been driven by, or resulted in, pollinator shifts. However, those polyploids that are not sympatric (on a regional scale) with their progenitor lineages are typically not divergent in floral colour from them, perhaps because of a lack of competition for pollinators.

Estimation of soil moisture content from the spectral reflectance of bare soils in the 0.4-2.5 µm domain

This work aims to compare the performance of new methods to estimate the Soil Moisture Content (SMC) of bare soils from their spectral signatures in the reflective domain (0.4-2.5 µm) in comparison with widely used spectral indices like Normalized Soil Moisture Index (NSMI) and Water Index SOIL (WISOIL). Indeed, these reference spectral indices use wavelengths located in the water vapour absorption bands and their performance are thus very sensitive to the quality of the atmospheric compensation. To reduce these limitations, two new spectral indices are proposed which wavelengths are defined using the determination matrix tool by taking into account the atmospheric transmission: Normalized Index of Nswir domain for Smc estimatiOn from Linear correlation (NINSOL) and Normalized Index of Nswir domain for Smc estimatiOn from Non linear correlation (NINSON). These spectral indices are completed by two new methods based on the global shape of the soil spectral signatures. These methods are the Inverse Soil semi-Empirical Reflectance model (ISER), using the inversion of an existing empirical soil model simulating the soil spectral reflectance according to soil moisture content for a given soil class, and the convex envelope model, linking the area between the envelope and the spectral signature to the SMC. All these methods are compared using a reference database built with 32 soil samples and composed of 190 spectral signatures with five or six soil moisture contents. Half of the database is used for the calibration stage and the remaining to evaluate the performance of the SMC estimation methods. The results show that the four new methods lead to similar or better performance than the one obtained by the reference indices. The RMSE is ranging from 3.8% to 6.2% and the coefficient of determination R2 varies between 0.74 and 0.91 with the best performance obtained with the ISER model. In a second step, simulated spectral radiances at the sensor level are used to analyse the sensitivity of these methods to the sensor spectral resolution and the water vapour content knowledge. The spectral signatures of the database are then used to simulate the signal at the top of atmosphere with a radiative transfer model and to compute the integrated incident signal representing the spectral radiance measurements of the HYMAP airborne hyperspectral instrument. The sensor radiances are then corrected from the atmosphere by an atmospheric compensation tool to retrieve the surface reflectances. The SMC estimation methods are then applied on the retrieve spectral reflectances. The adaptation of the spectral index wavelengths to the HyMap sensor spectral bands and the application of the convex envelope and ISER models to boarder spectral bands lead to an error on the SMC estimation. The best performance is then obtained with the ISER model (RMSE of 2.9% and R2 of 0.96) while the four other methods lead to quite similar RMSE (from 6.4% to 7.8%) and R² (between 0.79 and 0.83) values. In the atmosphere compensation processing, an error on the water vapour content is introduced. The most robust methods to water vapour content variations are WISOIL, NINSON, NINSOL and ISER model. The convex envelope model and NSMI index require an accurate estimation of the water vapour content in the atmosphere.

Shift from bird to butterfly pollination in Clivia (Amaryllidaceae)

PREMISE OF THE STUDY

Pollinator shifts have been implicated as a driver of divergence in angiosperms. We tested the hypothesis that there was a transition from bird- to butterfly pollination in the African genus Clivia (Amaryllidaceae) and investigated how floral traits may have been either modified or retained during this transition.

METHODS

We identified pollinators using field observations, correlations between lepidopteran wing scales and pollen on stigmas, and single-visit and selective exclusion experiments. We also quantified floral rewards and advertising traits.

KEY RESULTS

The upright trumpet-shaped flowers of C. miniata were found to be pollinated effectively by swallowtail butterflies during both nectar-feeding and brush visits. These butterflies transfer pollen on their wings, as evidenced by positive correlations between wing scales and pollen loads on stigmas. All other Clivia species have narrow pendulous flowers that are visited by sunbirds. Selective exclusion of birds and large butterflies from flowers of two Clivia species resulted in a significant decline in seed production.

CONCLUSIONS

From the distribution of pollination systems on available phylogenies, it is apparent that a shift took place from bird- to butterfly pollination in Clivia. This shift was accompanied by the evolution of trumpet-shaped flowers, smaller nectar volume, and emission of scent, while flower color and nectar chemistry do not appear to have been substantially modified. These results are consistent with the idea that pollinator shifts can explain major floral modifications during plant diversification.