Anthocyanin Reflectance Index Research Articles

Enhancing salt marshes monitoring: Estimating biomass with drone-derived habitat-specific models

Salt marshes play a vital role in biodiversity conservation, coastal protection, and carbon sequestration. Estimating aboveground biomass (AGB) is crucial for quantifying the carbon sequestration capacity of the system. However, traditional fieldwork methods are time-consuming, demanding, and detrimental to marsh ecosystems. In this study, we propose utilizing low-altitude remote sensing techniques to collect high-resolution LiDAR and multispectral (MS) data for biomass assessment. With these datasets, we characterized salt marsh vegetation habitats through the analysis of vegetation indices (VIs) variability. LiDAR high-resolution topographic information aids in evaluating habitat distribution. Moreover, the Anthocyanin Reflectance Index 2 (ARI2), combined with the Digital Surface Model, allows for the identification and separation of the two habitats with distinct dominant species (Sarcocornia spp. and Sporobolus maritimus). The analysis of the annual cycle of VIs reveals the presence of seasonality. However, the VIs for the two vegetation classes exhibit dissimilar seasonal changes, indicating distinct growth mechanisms for each. Biomass models are created for each season in the annual cycle. Habitat-specific models exhibit higher precision (up to 99%) than models that treat species uniformly. Depending on whether the marsh is considered as a whole or separated into dominant habitats, differences in biomass estimation trends are observed. This implies that the two dominant species exhibit varying behaviours throughout the year, contributing to diverse biomass production. The study reveals a seasonal pattern in the total AGB, with the highest biomass value in summer and the lowest peak in spring, with annual variation accounting for only 9% of total output. The reduced AGB value in spring may be due to increased soil salinity and stress. The use of LiDAR and MS data from an unmanned aerial vehicle (UAV) is crucial for accurately distinguishing primary marsh habitats and creating detailed biomass models, with unprecedented accuracy. This method is user-friendly, repeatable, and cost-effective, enabling the study of salt marshes, evolutionary trends, and climate change response requiring less fieldwork.

Analyzing the recovery mechanisms of patchy degradation and its response to mowing and plateau pika disturbances in alpine meadow

The alpine meadow is susceptible to degradation triggered by overgrazing and rodent outbreaks, leading to uneven patches of degradation. In this regard, we conducted a study that involved the implementation of nine combined treatments utilizing a two-factor randomized block design. The treatments were established based on three levels of plateau pika densities and three levels of simulated grazing intensity (mowing), and were replicated three times, resulting in 27 test plots. Hyperspectral images were used to map healthy meadow (HM), long-term vegetated patch (LVP), and short-term vegetated patch (SVP) and characterize their spectral properties. Four vegetation indices, including modified red edge simple ratio (MRESR), photochemical reflectance index (PRI), anthocyanin reflectance index (ARI), and plant senescence reflectance index (PSRI), were used to measure the recovery rate of various patches. In order to measure the resilience of various patches, the ratio of the LVP to degraded patch coverage (RLDC) and ratio of the SVP to degraded patch coverage (RSDC) were calculated from nadir-viewing drone images of the test plots. The research findings indicate that moderate mowing negatively affects the vegetative recovery rate of grass in healthy meadow. A moderate density of plateau pika facilitates plant growth in various types of patches. The joint action of plateau pika and mowing amplifies the negative effects of both factors while neutralizing their positive effects. SVP plants improve community resilience by shortening their life cycle and sprouting in cracks of soil crust. SVPs exhibit high resilience and can withstand local severe interference by plateau pika and grazing activities. LVPs require a stable environment for healthy meadow and cannot adapt to the disturbance of plateau pika at any density. Under the joint interferences of plateau pika and mowing, the SVPs could not be replaced by the LVPs. Therefore, the restoration and management of patchily degraded meadow must consider enhancing the resilience of plant patches and maintaining the long-term and stable survival of the restored grassland.

Effect of Various LED Light Qualities, Including Wide Red Spectrum-LED, on the Growth and Quality of Mini Red Romaine Lettuce (cv. Breen).

Recently, LEDs with various light qualities have been used in closed plant factories, and they are known to have different effects on the growth and quality of crops. Therefore, this study was conducted to investigate the change in growth and quality in mini red romaine lettuce using LEDs with various light qualities. Wide red spectrum (WRS)-LEDs, blue (B)-LEDs, blue + red (BR)-LEDs, red (R)-LEDs, and white (W)-LEDs were used as the artificial light sources. Regarding growth, the R-LED treatment showed the most positive effect, but the leaf shape was not normal and the Hunter b* value was not suitable because it was higher than that of the other treatments. The Hunter a*, SPAD, and NDVI values of the B- and BR-LED treatments were effective, but this was not the case for those of the R- and W-LED treatments. The anthocyanin reflectance index 1 (ARI1) was 20 times higher in the B-LED treatment than in the R-LED treatment, and the ascorbic acid content was the highest in the WRS-LED treatment. In the sensory evaluation, bitterness and sweetness showed opposite tendencies. Regarding the overall preference, the BR-LED treatment received the highest score. Correlation analysis showed that the bitterness was closely correlated with the anthocyanin content and leaf color. Taken together, BR-LEDs provided a good top fresh weight, dark red leaves, and high anthocyanin and ascorbic acid contents, with the highest overall preference; therefore, BR-LEDs were the most suitable for the cultivation of mini red romaine lettuce.

Biophysical, Biochemical, and Photochemical Analyses Using Reflectance Hyperspectroscopy and Chlorophyll a Fluorescence Kinetics in Variegated Leaves.

The adjustments that occur during photosynthesis are correlated with morphological, biochemical, and photochemical changes during leaf development. Therefore, monitoring leaves, especially when pigment accumulation occurs, is crucial for monitoring organelles, cells, tissue, and whole-plant levels. However, accurately measuring these changes can be challenging. Thus, this study tests three hypotheses, whereby reflectance hyperspectroscopy and chlorophyll a fluorescence kinetics analyses can improve our understanding of the photosynthetic process in Codiaeum variegatum (L.) A. Juss, a plant with variegated leaves and different pigments. The analyses include morphological and pigment profiling, hyperspectral data, chlorophyll a fluorescence curves, and multivariate analyses using 23 JIP test parameters and 34 different vegetation indexes. The results show that photochemical reflectance index (PRI) is a useful vegetation index (VI) for monitoring biochemical and photochemical changes in leaves, as it strongly correlates with chlorophyll and nonphotochemical dissipation (Kn) parameters in chloroplasts. In addition, some vegetation indexes, such as the pigment-specific simple ratio (PSSRc), anthocyanin reflectance index (ARI1), ratio analysis of reflectance spectra (RARS), and structurally insensitive pigment index (SIPI), are highly correlated with morphological parameters and pigment levels, while PRI, moisture stress index (MSI), normalized difference photosynthetic (PVR), fluorescence ratio (FR), and normalized difference vegetation index (NDVI) are associated with photochemical components of photosynthesis. Combined with the JIP test analysis, our results showed that decreased damage to energy transfer in the electron transport chain is correlated with the accumulation of carotenoids, anthocyanins, flavonoids, and phenolic compounds in the leaves. Phenomenological energy flux modelling shows the highest changes in the photosynthetic apparatus based on PRI and SIPI when analyzed with Pearson's correlation, the hyperspectral vegetation index (HVI) algorithm, and the partial least squares (PLS) to select the most responsive wavelengths. These findings are significant for monitoring nonuniform leaves, particularly when leaves display high variation in pigment profiling in variegated and colorful leaves. This is the first study on the rapid and precise detection of morphological, biochemical, and photochemical changes combined with vegetation indexes for different optical spectroscopy techniques.

Spectral reflectance and fluorescence is a rapid, non-destructive tool for drought tolerance monitoring in Withania somnifera (L.) Dunal.

Withania somnifera plants were exposed to drought stress for 23days. Relative water content (RWC), gaseous exchange, fluorescence parameters, and spectral reflectance changes were monitored under drought stress. Assimilation rate and RWC decreased by 81% and 65%, respectively, during drought exposure of 23days. Photosynthetic reflectance index (PRI) and water index (WI) showed a decreasing pattern under drought stress and correlated with Amax and RWC. Anthocyanin reflectance index and anthocyanin content increased with drought stress. Similarly, rational among R727, R696, R770, and R731 reflects chlorophyll content and Chl a/b ratio and copes with actual chlorophyll content. Fluorescence changes showed the opening and closing of PSII reaction centers, while absorbance change at 830/875nm showed activity and energy balance of PSI. Non-photochemical quenching increased under drought, which showed depoxydation of xanthine cycle pigment. Energy balance at the acceptor and donor side of PSI adjusted under drought stress by increasing electron carrying limitation at donor side. Energy balance between PSI and PSII is maintained by increasing cyclic electron flux under mild drought stress. Both protective mechanism depoxydation of xanthine cycle pigment and enhancement of cyclic electron flux reduced or diminished under severe drought stress. Decrease in leaf area and stomatal closure may cause a reduction in transpiration that results into loss of RWC and altered physiological processes. Since fluorescence, absorbance change and spectral reflectance are non-invasive measurements that may be used as indicators for assessing drought tolerance in medicinal plants.

Aboveground responses to belowground root damage detected by non-destructive sensing metrics in three tree species

Abstract Root systems form a significant part of tree biomass and function. Yet, roots are hidden from our eyes, making it difficult to track the belowground processes. By contrast, our capacity to detect aboveground changes in trees has been continuously improving using optical methods. Here, we tested two fundamental questions: (1) To what extent can we detect aboveground responses to mechanical damage of the root system? (2) To what extent are roots redundant? We applied three different non-destructive remote sensing means: (1) optical means to derive leaf greenness, (2) infrared means to detect the changes in leaf surface temperature and (3) spectral means to derive five vegetation indices (i.e. the photochemical reflectance index (PRI), the chlorophyll photosynthesis index (CIRed-edge), the anthocyanin reflectance index 1, the structure insensitive pigment index and the normalized difference water index (NDWI)). We recorded the above metrics for hours and days and up to a month following induced root damage in three key Mediterranean tree species: Aleppo pine (Pinus halepensis Mill.), Palestine oak (Quercus calliprinos Webb.) and Carob (Ceratonia siliqua L.). To induce root damage, we removed 25, 50 and 75 percent of the root system in each species and compared it with control saplings. Tree aboveground (canopy) responses to root damage increased over time and with damage level. Leaf warming (up to 3°C) and decreased PRI were the most significant and rapid responses, with temperature differences being visible as early as 2 days following root damage. NDWI and greenness were the least sensitive, with responses detectable only at 75 percent root damage and as late as 14 or 30 days following root damage. Responses varied vastly among species, with carob being the most sensitive and pine being the least. Changes in leaf temperature and PRI indicated that leaf transpiration and photosynthesis were impaired by root damage. Although trees build roots in excess, mechanical damage will eventually decrease transpiration and photosynthesis across tree species.

Evaluating automated endmember extraction for classifying hyperspectral data and deriving spectral parameters for monitoring forest vegetation health.

The hyperspectral remote sensing datasets possess high capability in differentiating the spectrally similar features, and thus, they are immensely important in various forestry activities, especially vegetation classifications. But extracting endmembers for data training is a challenging task. The present study is focused on the use of automated endmember extraction technique for deriving endmembers during the unavailability of ground spectra. We used the Sequential Maximum Angle Convex Cone (SMACC) method on EO-1 Hyperion data for endmember extraction in the Barkot forest range of Dehradun district, Uttarakhand which were used for classification of the study area using support vector machine (SVM). Further, we estimated the vegetation health of the region by assigning the threshold weights for various derived environmental variables such as NDVI (Normalised Difference Vegetation Index), CRI (Carotenoid Reflectance Index), Anthocyanin Reflectance Index (ARI), Modified Simple Ratio (MSR), Modified Chlorophyll Absorption Ratio Index (MCARI) and WBI (Water Band Index). Then, to further validate the health of the forest types, we correlated it with the Land Surface Temperature (LST) from LANDSAT 5 ETM + data. The results showed a high classification accuracy of 89.13%. The healthy vegetation area coverage of the area was about 78.6% with most healthy class as Tectona grandis and Shorea robusta and its correlation with LST showed lower temperature range in healthy vegetation areas and vice versa. The study was useful in determining the superiority of SMACC automated endmember extraction and estimating the vegetation health.

Host plant intraspecific variation determines gall traits.

Galls display a multiplicity of traits, including colours, which are driven by pigment accumulation. Their conspicuousness has attracted researchers' attention and several hypotheses have been raised. However, plants themselves vary intra-specifically, including in their pigment concentrations. As galls are a result of host tissue development, colours may be a by-product of the host's own traits, being more conspicuous simply because the sites where galls develop already have the predisposition to accumulate more pigment. Here, we call this the host variation hypothesis. We test this hypothesis using the system of galls induced by Palaeomystella oligophaga on Macairea radula host plant. Using spectrophotometry, we calculated the Anthocyanin Reflectance Index (ARI) of gall projections, which are responsible for their characteristic colours. We tested the influence of occupant identity (galling insect or any natural enemy), gall volume, parenchyma thickness, height from the ground, ARI of leaf, ARI of gall surface and ARI of the respective stem. We corroborated the host variation hypothesis since the anthocyanin content in stems and in galls' projections were positively related. Moreover, anthocyanin in galls' projections was positively related to anthocyanin in the gall surface and negatively related to gall volume and parenchyma thickness. This shows that, besides the host specificities, galls' own traits may also be responsible for pigment accumulation, influencing their colours. In this study, using colour as an example, we show that although galls tend to be considered complex expressions of galling insects' stimuli, their traits may be simply influenced by previous and specific attributes of the host organs.

Response of Cyanic and Acyanic Lettuce Cultivars to an Increased Proportion of Blue Light.

Simple SummaryIndoor crop cultivation systems such as vertical farms or plant factories necessitate artificial lighting. The composition of light quality (i.e., spectral composition) within these systems plays a key role in crop growth and development. Conflicting results on the effects of the light spectrum reported for different plant species and cultivars confirm the specificity of light requirements and the dependency on interacting factors. In this paper, we have therefore investigated how a certain light quality (light with a high share of blue) affects photosynthetic and morphological parameters in two contrasting lettuce cultivars (red and green leaves) with a similar leaf shape and phenotype. The results obtained suggest the occurrence of distinctive morpho-physiological adaptive strategies in green and red pigmented lettuce cultivars to adapt to the higher proportion of blue light environment.Indoor crop cultivation systems such as vertical farms or plant factories necessitate artificial lighting. Light spectral quality can affect plant growth and metabolism and, consequently, the amount of biomass produced and the value of the produce. Conflicting results on the effects of the light spectrum in different plant species and cultivars make it critical to implement a singular lighting solution. In this study we investigated the response of cyanic and acyanic lettuce cultivars to an increased proportion of blue light. For that, we selected a green and a red leaf lettuce cultivar (i.e., ‘Aquino’, CVg, and ‘Barlach’, CVr, respectively). The response of both cultivars to long-term blue-enriched light application compared to a white spectrum was analyzed. Plants were grown for 30 days in a growth chamber with optimal environmental conditions (temperature: 20 °C, relative humidity: 60%, ambient CO2, photon flux density (PFD) of 260 µmol m−2 s−1 over an 18 h photoperiod). At 15 days after sowing (DAS), white spectrum LEDs (WW) were compared to blue-enriched light (WB; λPeak = 423 nm) maintaining the same PFD of 260 µmol m−2 s−1. At 30 DAS, both lettuce cultivars adapted to the blue light variant, though the adaptive response was specific to the variety. The rosette weight, light use efficiency, and maximum operating efficiency of PSII photochemistry in the light, Fv/Fm’, were comparable between the two light treatments. A significant light quality effect was detected on stomatal density and conductance (20% and 17% increase under WB, respectively, in CVg) and on the modified anthocyanin reflectance index (mARI) (40% increase under WB, in CVr). Net photosynthesis response was generally stronger in CVg compared to CVr; e.g., net photosynthetic rate, Pn, at 1000 µmol m−2 s−1 PPFD increased from WW to WB by 23% in CVg, compared to 18% in CVr. The results obtained suggest the occurrence of distinct physiological adaptive strategies in green and red pigmented lettuce cultivars to adapt to the higher proportion of blue light environment.

Remote sensing detection algorithm for apple fire blight based on UAV multispectral image

Apple fire blight is a common disease that seriously damages the growth of apple trees. It is urgent to detect the severity difference and spatial distribution of its infection in time and accurately. In this study, we used the DJI Matrice 200 multi-rotor UAV equipped with the MicaSense RedEdge-M multispectral camera to obtain the multispectral images of apple tree canopies. Then, based on the Minimum Redundancy Maximum Relevance (mRMR) algorithm, we selected the Ratio Vegetation Index (RVI), Anthocyanin Reflectance Index (ARI) and Triangular Vegetation Index (TVI) from 20 candidate vegetation indices as the optimal feature combinations. And then we use the isolation forest (iForest) algorithm to detect the abnormal values. The samples with the abnormal values removed were used as input to construct apple fire blight detection models using decision trees, Random Forest (RF) and Support Vector Machine (SVM) classification algorithms, respectively. The results show that the overall accuracy of the RF model reaches 94.0%, which is 6.0% and 10.0% higher than the SVM model and the decision tree model, respectively. The Kappa coefficient of the RF model is 0.904, which is the highest among all models, and the omission error and commission error are also the smallest. For healthy samples, slightly infected samples and seriously infected samples, the omission error and commission error were 0, 7.69%, 13.34%, 7.14% and 9.09%, 0, respectively. The research results prove the feasibility of UAV multi-spectral remote sensing images to detect apple fire blight.

Heritable Variation of Foliar Spectral Reflectance Enhances Genomic Prediction of Hydrogen Cyanide in a Genetically Structured Population of Eucalyptus.

Plants produce a wide diversity of specialized metabolites, which fulfill a wide range of biological functions, helping plants to interact with biotic and abiotic factors. In this study, an integrated approach based on high-throughput plant phenotyping, genome-wide haplotypes, and pedigree information was performed to examine the extent of heritable variation of foliar spectral reflectance and to predict the leaf hydrogen cyanide content in a genetically structured population of a cyanogenic eucalyptus (Eucalyptus cladocalyx F. Muell). In addition, the heritable variation (based on pedigree and genomic data) of more of 100 common spectral reflectance indices was examined. The first profile of heritable variation along the spectral reflectance curve indicated the highest estimate of genomic heritability (=0.41) within the visible region of the spectrum, suggesting that several physiological and biological responses of trees to environmental stimuli (ex., light) are under moderate genetic control. The spectral reflectance index with the highest genomic-based heritability was leaf rust disease severity index 1 (=0.58), followed by the anthocyanin reflectance index and the Browning reflectance index (=0.54). Among the Bayesian prediction models based on spectral reflectance data, Bayes B had a better goodness of fit than the Bayes-C and Bayesian ridge regression models (in terms of the deviance information criterion). All models that included spectral reflectance data outperformed conventional genomic prediction models in their predictive ability and goodness-of-fit measures. Finally, we confirmed the proposed hypothesis that high-throughput phenotyping indirectly capture endophenotypic variants related to specialized metabolites (defense chemistry), and therefore, generally more accurate predictions can be made integrating phenomics and genomics.

Interactive effects of tropospheric ozone and blast disease (Magnaporthe oryzae) on different rice genotypes

Rising tropospheric ozone concentrations can cause rice yield losses and necessitate the breeding of ozone-tolerant rice varieties. However, ozone tolerance should not compromise the resistance to important biotic stresses such as the rice blast disease. Therefore, we investigated the interactive effects of ozone and rice blast disease on nine different rice varieties in an experiment testing an ozone treatment, blast inoculation, and their interaction. Plants were exposed to an ozone concentration of 100 ppb for 7 h per day or ambient air throughout the growth period. Half of the plants were simultaneously infected with rice blast inoculum. Grain yield was significantly reduced in the blast treatment (17%) and ozone treatment (37%), while the combination of both stresses did not further decrease grain yields compared to ozone alone. Similar trends occurred for physiological traits such as vegetation indices, normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), Lichtenthaler index 2 (Lic2), and anthocyanin reflectance index 1 (ARI1), as well as stomatal conductance and lipid peroxidation. Ozone exposure mitigated the formation of visible blast symptoms, while blast inoculation did not significantly affect visible ozone symptoms. Although different genotypes showed contrasting responses to the two types of stresses, no systematic pattern was observed regarding synergies or trade-offs under the two types of stresses. Therefore, we conclude that despite the similarities in physiological stress responses to ozone and blast, the tolerance to these stresses does not appear to be genetically linked in rice.

The Effects of Ozone on Visual Attraction Traits of Erodium paularense (Geraniaceae) Flowers: Modelled Perception by Insect Pollinators.

Ozone (O3) effects on the visual attraction traits (color, perception and area) of petals are described for Erodium paularense, an endangered plant species. Plants were exposed to three O3 treatments: charcoal-filtered air (CFA), ambient (NFA) and ambient + 40 nL L−1 O3 (FU+) in open-top chambers. Changes in color were measured by spectral reflectance, from which the anthocyanin reflectance index (ARI) was calculated. Petal spectral reflectance was mapped onto color spaces of bees, flies and butterflies for studying color changes as perceived by different pollinator guilds. Ozone-induced increases in petal reflectance and a rise in ARI under NFA were observed. Ambient O3 levels also induced a partial change in the color perception of flies, with the number of petals seen as blue increasing to 53% compared to only 24% in CFA. Butterflies also showed the ability to partially perceive petal color changes, differentiating some CFA petals from NFA and FU+ petals through changes in the excitation of the UV photoreceptor. Importantly, O3 reduced petal area by 19.8 and 25% in NFA and FU+ relative to CFA, respectively. In sensitive species O3 may affect visual attraction traits important for pollination, and spectral reflectance is proposed as a novel method for studying O3 effects on flower color.

Reflectance spectroscopy to characterize the response of Corymbia calophylla to Phytophthora root rot and waterlogging stress

Abstract The health of Corymbia calophylla (marri), a keystone tree species in the native forests of southwest Western Australia, has been in decline for the past few decades. Phytophthora root disease and waterlogging have often been cited as contributing to this decline. Traditional methods (i.e., field surveys and sampling) of mapping Phytophthora root infection in the field are time-consuming and expensive; thus, the potential of reflectance spectroscopy to characterize marri response to Phytophthora and waterlogging stress was investigated. Twelve-month old marri plants were infected with either P. cinnamomi or P. multivora in two glasshouse trials and waterlogged for 24 h each fortnight. Spectral measurements with a portable high-resolution spectroradiometer were taken weekly. Plant biophysical measurements were taken at harvest time. Normalized difference spectral index (NDSI) was calculated for every combination of reflectance values between 400 and 2500 nm for all time points, correlated with the treatment effects and displayed as heat maps. Narrowband vegetation indices (VIs), utilizing different wavelengths of the electromagnetic spectrum, were also calculated from the spectral data. The Phytophthora treatments did not cause significant differences with the biophysical measurements in both trials. In the second trial, the waterlogging treatment significantly lowered plant top dry weight (P = 0.016) and diameter (P = 0.044). Reflectance values plotted against wavelength displayed differences between treatments as well as a seasonal trend. The NDSI heat maps indicated that the Phytophthora and waterlogging treatment effects were strongest correlated with bandwidths in the visible and near-infrared portions of the electromagnetic spectrum (538–558 nm and 701–709 nm). Six of the VIs (normalized difference nitrogen index 2, anthocyanin reflectance index 1, photochemical reflectance index, Carter index 1, Vogelman index 3 and water band index) were able to track the biochemical changes in the leaves over the 10 weeks, confirming the seasonal trend. The interaction effect between P. cinnamomi, waterlogging and elapsed time in the first trial was significant for water band index (P = 0.010). This study demonstrates that reflectance spectroscopy holds promise for characterizing marri response but more work needs to be done to identify the optimum wavelengths for identifying Phytophthora and waterlogging stress with marri.

Leveraging high-throughput hyperspectral imaging technology to detect cadmium stress in two leafy green crops and accelerate soil remediation efforts

Cadmium (Cd) is a toxic metal that can accumulate in soils and negatively impact crop as well as human health. Amendments like biochar have potential to address these challenges by reducing Cd bioavailability in soil, though reliance on post-harvest wet chemical methods to quantify Cd uptake have slowed efforts to identify the most effective amendments. Hyperspectral imaging (HSI) is a novel technology that could overcome this limitation by quantifying symptoms of Cd stress while plants are still growing. The goals of this study were to: 1) determine whether HSI can detect Cd stress in two distinct leafy green crops, 2) quantify whether a locally sourced biochar derived from hardwoods can reduce Cd stress and uptake in these crops, and 3) identify vegetative indices (VIs) that best quantify changes in plant stress responses. Experiments were conducted in a tightly controlled automated phenotyping facility that allowed all environmental factors to be kept constant except Cd concentration (0, 5 10 and 15 mg kg−1). Symptoms of Cd stress were stronger in basil (Ocimum basilicum) than kale (Brassica oleracea), and were easier to detect using HSI. Several VIs detected Cd stress in basil, but only the anthocyanin reflectance index (ARI) detected all levels of Cd stress in both crop species. The biochar amendment did reduce Cd uptake, especially at low Cd concentrations in kale which took up more Cd than basil. Again, the ARI index was the most effective in quantifying changes in plant stress mediated by the biochar. These results indicate that the biochar evaluated in this study has potential to reduce Cd bioavailability in soil, and HSI could be further developed to identify rates that can best achieve this benefit. The technology also may be helping in elucidating mechanisms mediating how biochar can influence plant growth and stress responses.

Heritable variation in tree growth and needle vegetation indices of slash pine (Pinus elliottii) using unmanned aerial vehicles (UAVs)

Vegetation indices (VIs) are mainly associated with plant yield, and yield-related physiological traits can assist in breeding selection. Tree breeding programs require a rapid assessment of a large number of individual trees across multiple regions. Unmanned aerial vehicle (UAV) multispectral platforms combined with high spatial, temporal and spectral resolutions can readily assess the VIs at various plant growth phases, which has been deeply detailed for evaluating the physiological status of agricultural crops and forest stands. However, the underlying genetics of foliar spectral bands, VIs and growth traits from a large scale of samples, especially in the case of forest trees, have been less investigated. In this paper, two sites of slash pine breeding populations were completely investigated to monitor the spectral bands, VIs, and tree growth traits. This allows us to determine the genotypic variation of these traits and to estimate the heritability (h2). The results show that the estimated h2 ranges from 0.04 to 0.36, and the site may affect tree growth because the traits between two sites come to different h2 values. At the two sites, the h2 values of the green red difference vegetation index (GNDVI) and anthocyanin reflectance index (ARI) at Site 1 and the red edge chlorophyll index (RECI), leaf chlorophyll index (LCI), red green blue vegetation index (RGBVI), normalized difference red edge index (NDRE), NIR and red edge at Site 2 were less than 0.1. However, breeding selection is still possible for most VIs and growth traits at both sites based on different breeding targets and families (families 3, 5, 10, 11, 14 and 17 at Site 1 and 4, 6, 8, 19 and 13 at Site 2 for optimal spectral bands; families 2, 8, 7, 13, 16, and 18 at Site 1 and 6, 7, 11, 14, 15, 18, and 20 at Site 2 for optimal VIs; families 8 and 16 at Site 1 and families 7 and 18 at Site 2 for optimal growth traits) with a variety of optimal traits are selected. This paper demonstrates the potential use of UAV-based imagery technologies in the breeding selection of slash pine trees.

Аналіз характеристик та обґрунтування індексів рослинності

In this article there has been given the analyzing of non-fiction sources in order to find out the popular indexes of the vegetable control parameters. There are such parameters as chlorophyll presence, water containing, the efficiency of a light use, nitrogen and carbon presence, foliage pigmentation.  The chlorophyll presence control is conducted by such indexes as the difference vegetation index, the global environmental monitoring index, the infrared percentage vegetation index, the modified simple ratio, the modified Soil adjusted vegetation index 2, the non-linear index, the normalized difference vegetation index, the optimized soil adjusted vegetation index, the renormalized difference vegetation index, the soil adjusted vegetation index, the simple ratio etc. The control of water content can be based on the moisture stress index, the normalized difference infrared index, the normalized difference water index, the normalized multi-band drought index, the water band index. There is the photochemical reflectance index, the structure insensitive pigment index, the red green ratio index for the efficiency control of the light use. The nitrogen presence is controlled by the normalized differential nitrogen index. The carbon presence can be detected by the implementing of cellulose absorption index, the lignin cellulose absorption index, the normalized difference lignin index, the plant senescence reflectance index. The foliage pigmentations can be controlled by the means of the anthocyanin reflectance index 1, the anthocyanin reflectance index 2, the carotenoid reflectance index 1, and the carotenoid reflectance index 2. The specificity of the presented indexes is described; the calculation formulas and its main straits are proposed.

Fire Blight Disease Detection for Apple Trees: Hyperspectral Analysis of Healthy, Infected and Dry Leaves

The effective and rapid detection of Fire Blight, an important bacterial disease caused by the quarantine pest E.amylovora, is crucial for today’s horticulture. This study explored the application of non-invasive proximal hyperspectral remote sensing (RS) in order to differentiate the healthy (H), infected (I) and dry (D) leaves of apple trees. Analysis of variance was employed in order to determine which hyperspectral narrow spectral bands exhibited the most significant differences. Spectral signatures for the range of 400–2500 nm were acquired with Thermo Scientific Evolution 220 and iS50NIR spectrometers. The selected spectral bands were then used to evaluate several RS indices, including ARI (Anthocyanin Reflectance Index), RDVI (Renormalized Difference Vegetation Index), MSR (Modified Simple Ratio) and NRI (Nitrogen Reflectance Index), for Fire Blight detection in apple tree leaves. Furthermore, a new index was proposed, namely QFI. The spectral indices were tested on apple trees infected by Fire Blight in a quarantine greenhouse. Results indicated that the short-wavelength infrared (SWIR) band located at 1450 nm was able to distinguish (I) and (H) leaves, while the SWIR band at 1900 nm differentiated all three leaf types. Moreover, tests using the Pearson correlation indicated that ARI, MSR and QFI exhibited the highest correlations with the infection progress. Our results prove that our hyperspectral remote sensing technique is able to differentiate (H), (I) and (D) leaves of apple trees for the reliable and precise detection of Fire Blight.

Cartografía del aguacate en el sur del estado de México mediante tratamiento digital de imágenes sentinel-2

El cultivo de aguacate (Persea americana Mill.) es uno de los más importantes en México, entre los estados con mayor producción se encuentra el Estado de México, que es el tercer estado productor a nivel nacional. Coatepec Harinas y Donato Guerra son dos de los municipios más representativos en lo respectivo a esta actividad; sin embargo, no existe un censo que especifique la superficie del cultivo, por lo que el objetivo de esta investigación fue probar métodos de índices de vegetación, algoritmos spectral angle mapper (SAM) y spectral information divergence (SID) y la combinación de estos en las imágenes del sensor Sentinel-2 para evaluar su desempeño en la identificación de áreas plantadas con el cultivo de aguacate. Los resultados se validaron con una matriz de confusión y la comparación de los datos de referencia de entrenamiento y validación. El algoritmo SID alcanzó una precisión de 97.5% para detectar aguacate, mientras que el tratamiento SAM obtuvo una precisión de 63.1%. La combinación de SID con el índice Anthocyanin Reflectance Index 1 (ARI1), proporcionó un mejor resultado sobre la cartografía de validación regional con 85% de precisión. Otras combinaciones de índices y tratamientos dieron resultados inferiores al 50% de la precisión por lo que no se recomiendan. Esta metodología podría ser probada para la detección de otros cultivos de interés comercial, dado que Sentinel-2 muestra ser una alternativa viable para este tipo de estudios, teniendo una buena resolución espectral, además de ser de fácil acceso y manipulación.

Time- and spatially-resolved spectroscopy to determine the bulk optical properties of ‘Braeburn’ apples after ripening in shelf life

Abstract Bulk optical properties, in terms of absorption (μa) and reduced scattering coefficients (μ′s), can be used for the non-destructive monitoring of fruit quality during ripening. In this study, the performance of time-resolved (TRS) and spatially-resolved (SRS) spectroscopy were compared by analyzing ‘Braeburn’ apples over a 21 d period of ripening. Nine batches of 20 apples each were measured on the blush side by TRS (540−1064 nm) and SRS (550−1000 nm). Every fruit was analyzed for skin color, texture characteristics, relative internal space volume (RISV), total solid soluble and titratable acidity contents. TRS absorption spectra showed two maxima, the highest at 980 nm (water) and the second at 670 nm (chlorophyll), while in SRS spectra the main peak was measured at 550 nm (anthocyanins) followed by that at 670 nm. The values of μa580SRS and of μa670SRS were much higher than those measured at the same wavelengths by TRS suggesting that TRS and SRS actually explore the apple tissue (skin and/or flesh) in a different way. The values of μa980TRS were higher than those of μa980SRS, probably due to the fact that water content was lower in the skin (mostly probed by SRS) than in the flesh (mostly probed by TRS). No significant correlations were found between μa580SRS and μa580TRS and between μa980SRS and μa980TRS but a low positive relationship was observed between μa670TRS and μa670SRS. On the contrary, high correlations were found between μa670SRS and the spectral index IAD (index of absorbance difference) related to chlorophyll in the skin and between μa580SRS and the spectral index ARI (anthocyanin reflectance index), related to anthocyanin content in the peel, suggesting that μa580SRS is linked to the development of the red color in the peel. Both μa670TRS and μa670SRS decreased during fruit ripening, indicating a decline in chlorophyll in the flesh and skin, respectively. During the shelf life period, apples became soft and mealy, as mechanical and acoustic parameters decreased and RISV increased. Fruit softening was accompanied by increasing values of both μ′sTRS and μ′sSRS. The μ′sTRS and μ′sSRS were positively related to each other, were positively correlated to RISV and negatively related to mechanical and acoustic parameters. Both the TRS and SRS technique were able to follow ripening processes in ‘Braeburn’ apples during the shelf life period, as absorption phenomena were related to changes in pigments present in the fruit flesh and skin, while scattering events mirrored changes in the flesh texture.