Leaf Layers Research Articles

Seasonal Shifts in Bacterial and Fungal Microbiomes of Leaves and Associated Leaf-Mining Larvae Reveal Persistence of Core Taxa Regardless of Diet.

Microorganisms are key mediators of interactions between insect herbivores and their host plants. Despite a substantial interest in studying various aspects of these interactions, temporal variations in microbiomes of woody plants and their consumers remain understudied. In this study, we investigated shifts in the microbiomes of leaf-mining larvae (Insecta: Lepidoptera) and their host trees over one growing season in a deciduous temperate forest. We used 16S and ITS2 rRNA gene metabarcoding to profile the bacterial and fungal microbiomes of leaves and larvae. We found pronounced shifts in the leaf and larval microbiota composition and richness as the season progressed, and bacteria and fungi showed consistent patterns. The quantitative similarity between leaf and larval microbiota was very low for bacteria (~9%) and decreased throughout the season, whereas fungal similarity increased and was relatively high (~27%). In both leaves and larvae, seasonality, along with host taxonomy, was the most important factor shaping microbial communities. We identified frequently occurring microbial taxa with significant seasonal trends, including those more prevalent in larvae (Streptococcus, Candida sake, Debaryomyces prosopidis, and Neoascochyta europaea), more prevalent in leaves (Erwinia, Seimatosporium quercinum, Curvibasidium cygneicollum, Curtobacterium, Ceramothyrium carniolicum, and Mycosphaerelloides madeirae), and frequent in both leaves and larvae (bacterial strain P3OB-42, Methylobacterium/Methylorubrum, Bacillus, Acinetobacter, Cutibacterium, and Botrytis cinerea). Our results highlight the importance of considering seasonality when studying the interactions between plants, herbivorous insects, and their respective microbiomes, and illustrate a range of microbial taxa persistent in larvae, regardless of their occurrence in the diet. IMPORTANCE Leaf miners are endophagous insect herbivores that feed on plant tissues and develop and live enclosed between the epidermis layers of a single leaf for their entire life cycle. Such close association is a precondition for the evolution of more intimate host-microbe relationships than those found in free-feeding herbivores. Simultaneous comparison of bacterial and fungal microbiomes of leaves and their tightly linked consumers over time represents an interesting study system that could fundamentally contribute to the ongoing debate on the microbial residence of insect gut. Furthermore, leaf miners are ideal model organisms for interpreting the ecological and evolutionary roles of microbiota in host plant specialization. In this study, the larvae harbored specific microbial communities consisting of core microbiome members. Observed patterns suggest that microbes, especially bacteria, may play more important roles in the caterpillar holobiont than generally presumed.

Grapevine leaf physiology and morphological characteristics to elevated CO2 in the VineyardFACE (Free air Carbon dioxide Enrichment) experiment.

Atmospheric carbon dioxide (CO2) concentration has continuously increased since pre-industrial times and has currently reached an average growth rate of 2.3 ppm per year. For the majority of plant species elevated CO2 (eCO2) improves photosynthesis and thus plant biomass production. To investigate the effects of eCO2 on leaf physiology and morphological leaf characteristics two Vitis vinifera L. cultivars, Riesling and Cabernet Sauvignon, grown in the VineyardFACE (Free Air Carbon dioxide Enrichment) system were used. The VineyardFACE is located at Geisenheim, Rheingau comparing future atmospheric CO2-concentrations (eCO2, predicted for the mid-21st century) with current ambient CO2-conditions (aCO2). Experiments were operated under rain-fed conditions for two consecutive years (2015 and 2016). For both varieties and CO2 treatments, leaf gas exchange measurements were performed as well as measures of epidermal flavonoid (Flav) and leaf chlorophyll (Chl) indices by using a portable leaf clip. Furthermore, leaves were sampled for spectrophotometric analysis of the leaf pigments chlorophyll a (Chl a), chlorophyll b (Chl b) and carotenoid (Car). Additionally, leaf cross-sections were produced as permanent preparations to investigate morphological characteristics of the leaf structure. Both cultivars did not differ in leaf chlorophyll meter readings or leaf pigments between the two CO2 treatments while net assimilation was highly stimulated under elevated CO2 for both seasons. Differences found in leaf cross-sections were detected in palisade parenchyma and epidermal thickness of Cabernet Sauvignon under eCO2, whereas Riesling net assimilation increased by 40% under a 20% CO2 enrichment while remaining unaffected in different leaf layer thickness. The observed results within grapevine leaf tissues provide insights to seasonal adaptation strategies of grapevines under elevated CO2 concentrations predicted in future.

Remote synchronization in multi-layered community networks with star-like topology

Remote synchronization (RS) is currently a hot topic in the fields of nonlinear science and complex network and has a close relationship with signal propagation in brain networks. So far, most studies of RS are focused on star graphs. However, realistic networks with RS are much more complicated than a purely star graph, such as various cognitive networks in human brain. Thus, we here present a model of multi-layered community network to extend the study of RS from star graphs to star-like community topologies, i.e. each node of star graph becoming a community. We find that RS may appear in this multi-layered network model, provided that the hub community has a stronger coupling while the leaf communities have a weaker coupling. A measure of RS is introduced to investigate the influence of key parameters such as the frequency distributions, network size, and natural frequency difference between the hub and leaf layers. Moreover, these results have been confirmed in the sub-networks from a real brain network. And a brief theoretical analysis is provided to explain the mechanism of RS in multi-layered community networks.

Estimation of nitrogen nutrition index in chrysanthemum using chlorophyll meter readings

The nitrogen nutrition index (NNI) plays a critical role in improving crop nitrogen (N) diagnosis and predicting crop yield. Proximal sensing chlorophyll meters (CMs) have been widely used in precision agriculture, but few studies have focused on its utilization for estimating the NNI of chrysanthemum ( Dendranthema morifolium Ramat.). This study aimed to develop a model for NNI estimation in chrysanthemums using CM readings. Field experiments were conducted with five N fertilization treatments during two growing seasons (in 2019 and 2020). Chrysanthemum canopies were sampled across multiple days after planting (DAP) to determine plant N concentrations (PNC) and plant dry matter (PDM). CM measurements were recorded at defined DAP at different leaf layer positions (L1, L2, and L3 represent leaves that were 1/3, 1/2, and 2/3 apart from the top of the plant, respectively), and the normalized CM index (NCMI 1 , NCMI 2 , and NCMI 3 ) was calculated. All PNC and PDM data from the two seasons were then applied to fit the critical N (N c ) dilution curve using a Bayesian statistical model to estimate the NNI. Regression models were established to predict chrysanthemum NNI using CM readings and the NCMI as predictor variables. This study determined the N c of chrysanthemum to be N c = 2.318 ×PDM −0.204 . L1 was found to be the optimal leaf layer position for NNI estimation. Additionally, the NCMI-based prediction of NNI was found to be more reliable than that from the CM readings. NCMI 1 was the best predictor of chrysanthemum NNI across multiple DAP (NNI = 0.0741 ×e 2.6285NCMI1 , coefficient of determination = 0.59 *** , root mean square error = 0.110 NNI). The findings of this study can be applied to accurately predict chrysanthemum NNI from CM readings to provide technical support for N nutrition diagnosis in chrysanthemums. • This is the first study establishing the critical N dilution curve in chrysanthemum. • The upper leaf layer is optimal for chrysanthemum N nutrition index (NNI) estimations. • The normalized chlorophyll meter index showed to be the best predictor of chrysanthemum NNI .

Analysis of the multilayer organization of a sunflower leaf during dehydration with terahertz time-domain spectroscopy.

We apply reverse engineering techniques (RET) to analyze the dehydration process of a sunflower leaf with terahertz time-domain spectroscopy. The multilayer structure of the leaf is extracted with accuracy during the entire process. Time variations of thickness and the complex index are emphasized for all leaf layers (2 cuticules, 2 epiderms, and 2 mesophylls). The global thickness of the sunflower leaf is reduced by up to 40% of its initial value.

Nitrogen rates and plant density interactions enhance radiation interception, yield, and nitrogen use efficiencies of maize

The contributions of the different leaf layers to maize yields identified as middle leaf > lower leaf > upper leaf, where the vertical photosynthetically active radiation (PAR) in the canopy gradually decreases. We hypothesized that the allocation of more PAR and nitrogen (N) to the highest contributing leaves will would be beneficial for higher yields and N use efficiencies. The N application rate and plant density effectively regulated the canopy light and N distribution. We evaluated the interactive effects of N rate and plant density on the agronomic and ecophysiological characteristics of leaves at different orientations in a 2019/2020 field experiment. In this study, an N application rate of 180 kg ha–1 coupled with a plant density of 82,500 plants ha–1 achieved the highest yield and N recovery efficiency (NRE). In contrast to the traditional farming practices in northern China, the density was increased and N rate was reduced. Densification from 52,500 to 82,500 plants ha–1 increased the population leaf area index (LAI) by 37.1% and total photosynthetically active radiation (TPAR) by 29.2%; however, excessive density (from 82,500 to 97,500 plants ha–1) drastically reduced the proportion of TPAR by 28.0% in the lower leaves. With increased density, the leaf areas and angles of the upper leaves decreased much more than those of the other leaves, which allowed the middle and lower leaves to access more light, which manifested a smaller extinction coefficient for light (KL). A high yield (>1,000 kg ha–1) of maize could be achieved simultaneously with higher NRE; however, it was negatively correlated with internal N use efficiency (IEN). Higher N concentrations and lower total performance index (PItotal) in the lower leaves may be an important rationale for the reduction of IEN in high-yielding maize. Additionally, decreased N rate without yield reduction under higher densities was primarily attributed to the more uniform vertical N distribution [a smaller extinction coefficient for N (KN)]. These results suggest that the N fertilizer rate can be moderately reduced without a reduction in maize yield under high plant densities in northern China.

Evaluation of Phytochemical Content and the Antioxidant and Antiproliferative Potentials of Leaf Layers of Cabbage Subjected to Hot Air and Freeze-Drying

Cabbage (Brassica oleracea var. capitata f. alba), a cruciferous vegetable, is one of the most widely consumed vegetables worldwide. However, research on whether there are differences in its contents of phytochemicals and biological activities according to the drying method for each portion of the vegetable remains insufficient. The present study investigated the contents of representative polyphenols and isothiocyanates, the antioxidant capacity, and the antiproliferative effects among six leaf layers of cabbage subjected to hot air and freeze-drying. High-performance liquid chromatography analysis showed that most phenolic and flavonoid bioactive compounds were significantly accumulated in the outer cabbage leaf layer (P1), whereas isothiocyanates were most abundant in the leaf layer close to the core of the head (P5). The contents of isothiocyanates, gallic acid, epicatechin, p-coumaric acid, sinapic acid, and myricetin were significantly higher in the hot air-dried sample than in the freeze-dried sample, whereas the contents of catechin hydrate, chlorogenic acid, 4-hydroxybenzoic acid, and rutin hydrate were significantly higher in the freeze-dried sample. Compared to other leaf layers, P1 exhibited high antiproliferative efficacy against pancreatic, breast, and gastric cancer cells. P1 also showed excellent DPPH·(EC 50–4.208 ± 0.033 and 4.611 ± 0.053 mg/mL for hot air and freeze-dried samples, respectively) and ABTS· (2.422 ± 0.068 and 2.224 ± 0.070 mg/mL for hot air and freeze-dried samples, respectively) radical-scavenging effects. These results indicate that the contents of polyphenols and isothiocyanates in cabbage may vary depending on the leaf layer and the drying method. Our findings provide insight for applying appropriate food drying methods that can be used to produce cabbage leaf-based products with enhanced bioactivity.

Investigating the Effects of Temperature, Relative Humidity, Leaf Collection Date, and Foliar Penetration on Leaf–Air Partitioning of Chlorpyrifos

Leaf-air partition coefficient (Kleaf-air) values are needed to understand and predict pesticide volatilization and persistence in agroecosystems. The objectives of this work were to measure Kleaf-air values and foliar penetration for the insecticide chlorpyrifos (as an active ingredient alone and in a pesticide formulation) on alfalfa (lucerne) leaves at a range of temperatures and relative humidities and when using leaves collected in different summer months. Kleaf-air values were measured using a solid-phase fugacity meter. A portion of the leaves were also used for foliar penetration experiments. Kleaf-air values for chlorpyrifos as an active ingredient alone decreased with temperature, while the effects of temperature on chlorpyrifos in the formulation were negligible. No correlations between Kleaf-air values and relative humidity were observed. Foliar penetration increased with temperature for chlorpyrifos both as an active ingredient and in the formulation. Increasing foliar penetration with temperature is attributed to increasing diffusion into inner leaf layers. Both volatilization and foliar penetration affect the measured Kleaf-air values, so understanding the link between these processes is necessary to predict Kleaf-air values. The leaf collection date had a substantial effect on the measured Kleaf-air values, highlighting the need for a better understanding of the role of leaf properties on Kleaf-air.

Automatic Modulation Classification for MASK, MPSK, and MQAM Signals Based on Hierarchical Self-Organizing Map.

Automatic modulation classification (AMC) plays a fundamental role in common communication systems. Existing clustering models typically handle fewer modulation types with lower classification accuracies and more computational resources. This paper proposes a hierarchical self-organizing map (SOM) based on a feature space composed of high-order cumulants (HOC) and amplitude moment features. This SOM with two stacked layers can identify intrinsic differences among samples in the feature space without the need to set thresholds. This model can roughly cluster the multiple amplitude-shift keying (MASK), multiple phase-shift keying (MPSK), and multiple quadrature amplitude keying (MQAM) samples in the root layer and then finely distinguish the samples with different orders in the leaf layers. We creatively implement a discrete transformation method based on modified activation functions. This method causes MQAM samples to cluster in the leaf layer with more distinct boundaries between clusters and higher classification accuracies. The simulation results demonstrate the superior performance of the proposed hierarchical SOM on AMC problems when compared with other clustering models. Our proposed method can manage more categories of modulation signals and obtain higher classification accuracies while using fewer computational resources.

Molecular mapping of quantitative trait loci for 3 husk traits using genotyping by sequencing in maize (Zea mays L.)

The maize (Zea mays L.) husk consists of multiple leaf layers and plays an important role in grain growth and development. Despite significant achievements in physiological and morphological research, few studies have focused on the detection of genetic loci underlying husk-related traits due to the lack of efficient tools. In this study, we constructed an ultra-high-density linkage map using genotyping by sequencing based on a recombinant inbred line population to estimate the genetic variance and heritability of 3 husk traits, i.e. husk length, husk width, and husk layer number in 3 field environments and the combined environment. The 3 husk traits showed broad phenotypic variation and high heritability; the broad-sense heritability (H2) was 0.92, 0.84, and 0.86. Twenty quantitative trait loci were consistently detected more than 1 environment, including 9 for husk length, 6 for husk width, and 5 for husk layer number. These loci were considered as stable quantitative trait loci. Based on the quantitative trait loci mapping in the recombinant inbred line population, qHL6 and qHN4 were detected across all environments and inferred to be reliable and major-effect quantitative trait loci for husk length and husk layer number, respectively. In addition, several predicted candidate genes were identified in the region of qHL6 and qHN4, of which 17 candidate genes potentially play a role in biological processes related to development process and energy metabolism. These results will be as a useful resource for performing functional studies aimed at understanding the molecular pathways involved in husk growth and development.

Maintaining Canopy Density under Summer Stress Conditions Retains PSII Efficiency and Modulates Must Quality in Cabernet Franc

Shoot topping and other summer grapevine management practices are considered crucial for producing high-quality wine. However, in recent years, climate change is increasing the need to reassess these strategies, as excessive radiation and high temperatures can negatively impact canopy functionality and berry quality. Indeed, it has been hypothesized that limiting summer vegetative pruning may protect the bunch, via shading, and the leaf by maintaining a more favorable environment for leaf functionality (e.g., lower VPD, reduced high light stress) owing to a denser canopy. In this work, a series of canopy manipulation treatments (shoot topping vs. long-shoot bundling; secondary shoot trimming vs. untrimmed) were tested in a replicated factorial block design over two seasons in field-grown grapevine plants (cv. Cabernet Franc grafted in SO4). Overall, treatments in which secondary shoot removal and/or shoot topping were not applied produced a higher canopy area, increased pruning wood and leaf layers, and had a higher Fv/Fm on warm days when compared to pruned canopies. These were associated with a year-dependent modulation of quality parameters of the must in which long-shoot bundling treatment, overall, produced the highest polyphenol and anthocyanin contents and must acidity. Our data provide evidence of a potential usefulness of preserving dense canopies under high temperature – high irradiance conditions with desirable effects on leaf photosynthesis and must quality when long-shoot bundling was applied.

Resistance characteristics of broad-leaf crop canopy in air-assisted spray field and their effects on droplet deposition.

Air-assisted spray technology is widely applied in high-efficiency pesticide applications. The resistance characteristics of the crop canopy reflect its energy dissipation effect on the assisted airflow, connecting the structure of the crop canopy, assisted airflow velocity, and droplet deposition effect. Using a common broad-leaf crop canopy as the research object, the resistance characteristics of the crop canopy in the air-assisted field were investigated in this study by performing theoretical analysis and wind tunnel tests. Further, the feasibility of using the resistance characteristics of the crop canopy was assessed to evaluate its droplet deposition effect. The results showed that under the conditions of different number of leaf layers and initial leaf azimuth angles, the canopy pressure drop experiences a non-linear increasing trend with increasing assisted airflow velocity and that its regression function conforms to the Darcy–Forchheimer function. Moreover, when the initial azimuth angles of single- and multi-layer leaves were 90°–270°, the change rate of the canopy pressure drop with airflow velocity was 7–9 m/s, and there was a critical wind speed. However, with an increasing number of leaf layers in the crop canopy and changes in the initial leaf azimuth angle, the corresponding changes between the maximum canopy pressure drop and resistance coefficient were non-linear. Thus, it is proposed that the resistance characteristics of multi-layer leaves cannot be quantified as the results of the linear superposition of the resistance characteristics of several single-layer leaves—that is, it should be regarded as a whole research object. Combined with the analysis of the influence of the crop canopy resistance on droplet deposition, it is considered that when the crop canopy has multiple leaf layers in the airflow direction, the existing air-assisted spray technology cannot guarantee droplet deposition and canopy penetration simultaneously.

BIOMIMICKING HYDROPHOBICITY USING MICROSCALE STRUCTURES FOR BIOMEDICAL APPLICATIONS

Hydrophobic surfaces provide special characteristics for biomedical applications ranging from tunable protein adsorption, cellular interactions, and hemocompatibility to antibacterial coatings. In this research, we biomimic the hair-like micro-whisker structures of magnolia leaf using a synthetic polymeric formulation. Optical and scanning electron microscopy images revealed the presence of micro-whiskers resulting in higher water contact angles. The top layer of the magnolia leaf had a contact angle of 50º as compared to the hydrophobic bottom layer at 98º. A synthetic polymeric formulation was coated on different materials to study its effect on hydrophobicity. The coating was replicated (n=3) on each of the materials used such as glass, polymer, fabric, wood, and stainless steel. A surface tensiometer was used to measure the transition from hydrophilic to hydrophobic interactions between water and the substrate materials. Contact angle measurements revealed an increase in hydrophobicity for all the materials from their original uncoated surface. Glass displayed the highest increase in contact angle from 37º to 90º. Phase analysis of the coated region was performed to characterize the surface exposure of glass substrate to the synthetic polymeric formulation. An increase in the coated region showed a significant increase in contact angle from 50º to 95º. This research lays the foundation to develop and understand hydrophobic coatings for several biomedical applications including non-fouling implant surfaces, lab-on-chip devices, and other diagnostic tools.

Leaf layer-based transcriptome profiling for discovery of epidermal-selective promoters in Medicago truncatula.

Transcriptomics of manually dissected leaf layers from Medicago truncatula identifies genes with preferential expression in upper and/or lower epidermis. The promoters of these genes confer epidermal-specific expression of transgenes. Improving the quality and quantity of proanthocyanidins (PAs) in forage legumes has potential to improve the nitrogen nutrition of ruminant animals and protect them from the risk of pasture bloat, as well as parasites. However, ectopic constitutive accumulation of PAs in plants by genetic engineering can significantly inhibit growth. We selected the leaf epidermis as a candidate tissue for targeted engineering of PAs or other pathways. To identify gene promoters selectively expressed in epidermal tissues, we performed comparative transcriptomic analyses in the model legume Medicago truncatula, using five tissue samples representing upper epidermis, lower epidermis, whole leaf without upper epidermis, whole leaf without lower epidermis, and whole leaf. We identified 52 transcripts preferentially expressed in upper epidermis, most of which encode genes involved in flavonoid biosynthesis, and 53 transcripts from lower epidermis, with the most enriched category being anatomical structure formation. Promoters of the preferentially expressed genes were cloned from the M. truncatula genome and shown to direct tissue-selective promoter activities in transient assays. Expression of the PA pathway transcription factor TaMYB14 under control of several of the promoters in transgenic alfalfa resulted in only modest MYB14 transcript accumulation and low levels of PA production. Activity of a subset of promoters was confirmed by transcript analysis in field-grown alfalfa plants throughout the growing season, and revealed variable but consistent expression, which was generally highest 3-4weeks after cutting. We conclude that, although the selected promoters show acceptable tissue-specificity, they may not drive high enough transcription factor expression to activate the PA pathway.

Into the Shadows and Back into Sunlight: Photosynthesis in Fluctuating Light.

Photosynthesis is an important remaining opportunity for further improvement in the genetic yield potential of our major crops. Measurement, analysis, and improvement of leaf CO2 assimilation (A) have focused largely on photosynthetic rates under light-saturated steady-state conditions. However, in modern crop canopies of several leaf layers, light is rarely constant, and the majority of leaves experience marked light fluctuations throughout the day. It takes several minutes for photosynthesis to regain efficiency in both sun-shade and shade-sun transitions, costing a calculated 10-40% of potential crop CO2 assimilation. Transgenic manipulations to accelerate the adjustment in sun-shade transitions have already shown a substantial productivity increase in field trials. Here, we explore means to further accelerate these adjustments and minimize these losses through transgenic manipulation, gene editing, and exploitation of natural variation. Measurement andanalysis of photosynthesis in sun-shade and shade-sun transitions are explained. Factors limiting speeds of adjustment and how they could be modified to effect improved efficiency are reviewed, specifically nonphotochemical quenching (NPQ), Rubisco activation, and stomatal responses.

Quantification and dynamic monitoring of nitrogen utilization efficiency in summer maize with hyperspectral technique considering a non-uniform vertical distribution at whole growth stage

As one of the most mobile indicators, nitrogen utilization (assimilation) efficiency (NU t E) exhibits a pronounced heterogeneity in its vertical distribution in summer maize canopies. Although the vertical heterogeneity of summer maize NU t E has been recognized, the vertical NU t E gradient in canopies has not been considered in canopy hyperspectral remote sensing (CHRS) so far. The main goal of this study was to quantitatively define the effects of the interactive changes in N nutrition and growth stages on the vertical distribution of NU t E, identify the sensitive leaf layers and effective wavelengths, and develop a monitoring model considering the vertical NU t E distribution using canopy hyperspectral data. Four field experiments were conducted for three consecutive years (2018–2020) to demonstrate how the maize canopies influences the CHRS estimation of NU t E distribution in the vertical canopy at different growth stages. Canopies of each treatment were divided into three layers of equal vertical at elongation stage (V6) and flare opening stage (V12) ( i.e., 1st layer, 2nd layer and 3rd layer), and four layers at silking stage (R1), filling stage (R2) and milk stage (R3) ( i.e., 1st layer, 2nd layer, 3rd layer and 4th layer). Continuous wavelet transform (CWT) was ufsed to process the collected spectral reflectance; partial least square (PLS) and lambda-lambda r 2 (LL r 2 ) models were applied to analyze the relationships between NU t E in different layer and the spectral reflectance. Results showed that a vertical distribution pattern of NU t E existed, presenting an evident increase characteristics from the upper to lower layer. CWT technique can significantly improve the monitoring accuracy of summer maize NU t E in different layers among various growth stages, and the best decomposition scales are CWT-4, CWT-5, and CWT-6. The PLS model for NU t E prediction in the three decomposition scales yielded a relatively higher accuracy compared to the canopy raw spectra based on the full range hyperspectra, however, the prediction accuracy varied greatly in different layers and growth stages, the effect of the 2nd layer and 3rd layer and earlier stages were the best. The effective wavelengths for NU t E estimation were exhibited significant differences among the different layers and growing stages. Compared with the upper layer and V6-V12 stage, a strong “red shift” phenomenon towards the longer wavelengths was observed at lower layer and R1-R3 stage. Additionally, the newly developed PLS model using the effective wavelengths at different growth stages for NU t E prediction in various leaf layers also performed well (RPD>1.40). These findings will provide theoretical basis and effective methods for applying CHRS technology to real-time detection of NU t E and high yield and high efficiency of crop precision management for summer maize. • The vertical heterogeneity of NU t E within summer maize canopies was presented. • Continuous wavelet transform was proposed to process the collected hyperspectral reflectance. • PLS and LL r 2 model was used to assess NU t E in various layers. • Effective wavelengths and critical growth stages were identified for NU t E prediction. • Robust model was developed for NU t E prediction considering the vertical distribution.

Investigation of Wood Species and Conservation Status of Wooden Seated Amitabha Buddha Triad and Wooden Amitabha Buddha Altarpiece of Yongmunsa Temple, Yecheon, Korea (Treasure)

The Wooden Seated Amitabha Buddha Triad and Altarpiece have not been the subjects of definitive species identification and scientific analysis. In this study, visual investigation, portable X-ray fluorescence (p-XRF), species identification, and lacquer layer observations were carried out to determine the original materials and conservation status. Cracks, exfoliation and discoloration were detected during the visual investigation. The p-XRF data indicated that chrome oxide green, malachite, gold, cadmium red, cinnabar, minium, hematite, lead white, ink stick (Carbon), and copper were used for pigments and the coronet accessory. Tilia spp., Abies spp., and Pinus spp. were identified from both the Buddha Triad and Altarpiece. Finally, lacquer layer analyses of the base layer, lacquer layer, orange pigment layer, and gold leaf layer observed modern synthetic pigments likely used in previous conservation. As the Korean Cultural Heritage Charter and the International Charter for the Conservation and Restoration of Monuments and Sites clearly state that objects of cultural heritage must be conserved using their original materials, future conservation of these objects should utilize the data obtained in this study to employ traditional materials. Furthermore, a deterioration map diagnosis can be applied together with the obtained analysis data to understand the conservation status of and inform an appropriate and authentic conservation treatment for the Buddha Triad and Altarpiece.

Estimating the Impacts of Plant Internal Nitrogen Deficit at Key Top Dressing Stages on Corn Productivity and Intercepted Photosynthetic Active Radiation.

Accurate and timely appraisal of plant nitrogen (N) demand is imperative to regulate the canopy structure and corn production. The strength and time of plant N deficit can be quantified by critical N concentration. The study was aimed to analyze nitrogen nutrition index (NNI), nitrogen deficit content (NDC), plant nitrogen productivity (PNP), and a fraction of intercepted photosynthetic active radiation (FIPAR) across different N treatments and to develop NNI-NDC, NNI-PNP, NNI-FIPAR, NDC-PNP, and NDC-FIPAR relationships from V6 to V12 stages of corn to quantify the suitable PNP and FIPAR values under the optimal plant N condition. Four multi-N rates (0, 75, 90, 150, 180, 225, 270, and 300 kg N ha−1) field experiments were conducted with two cultivars of corn in Henan province of China. Results indicated that N fertilization affected yield, plant biomass, plant N content, and leaf area index. The values of NNI and NDC were from 0.54 to 1.28 kg ha−1 and from −28.13 to 21.99 kg ha−1 under the different treatments of N rate, respectively. The NDC and NNI showed significantly negative relationships from V6 to V12 stages. The values of PNP and FIPAR increased gradually with the crop growth process. The PNP values gradually declined while the FIPAR values of every leaf layer increased with the increase of N supply. The NDC-PNP and NNI-FIPAR relationships were significantly positive; however, the relationships between NNI-PNP and NDC-FIPAR were significantly negative during the vegetative period of corn. The coefficient of determination (R2) based on NNI was better than that on NDC. The FIPAR values were ~0.35, 0.67, and 0.76% at the upper, middle, and bottom of leaf layers, respectively, and PNP values were ~39, 44, and 51 kg kg−1 at V6, V9, and V12 stages, respectively, when NNI and NDC values were equal to 1 and 0 kg ha−1, respectively. This study described the quantitative information about the effect of a plant's internal N deficit on plant N productivity and canopy light intercept. The projected results would assist in predicting the appropriate plant growth status during key N top-dressing stages of corn, which can optimize N application and improve N use efficiency.

Comparing Time-Lapse PhenoCams with Satellite Observations across the Boreal Forest of Quebec, Canada

Intercomparison of satellite-derived vegetation phenology is scarce in remote locations because of the limited coverage area and low temporal resolution of field observations. By their reliable near-ground observations and high-frequency data collection, PhenoCams can be a robust tool for intercomparison of land surface phenology derived from satellites. This study aims to investigate the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology by comparing fortnightly the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) extracted using the Google Earth Engine (GEE) platform with the daily PhenoCam-based green chromatic coordinate (GCC) index. Data were collected from 2016 to 2019 by PhenoCams installed in six mature stands along a latitudinal gradient of the boreal forests of Quebec, Canada. All time series were fitted by double-logistic functions, and the estimated parameters were compared between NDVI, EVI, and GCC. The onset of GCC occurred in the second week of May, whereas the ending of GCC occurred in the last week of September. We demonstrated that GCC was more correlated with EVI (R2 from 0.66 to 0.85) than NDVI (R2 from 0.52 to 0.68). In addition, the onset and ending of phenology were shown to differ by 3.5 and 5.4 days between EVI and GCC, respectively. Larger differences were detected between NDVI and GCC, 17.05 and 26.89 days for the onset and ending, respectively. EVI showed better estimations of the phenological dates than NDVI. This better performance is explained by the higher spectral sensitivity of EVI for multiple canopy leaf layers due to the presence of an additional blue band and an optimized soil factor value. Our study demonstrates that the phenological observations derived from PhenoCam are comparable with the EVI index. We conclude that EVI is more suitable than NDVI to assess phenology in evergreen species of the northern boreal region, where PhenoCam data are not available. The EVI index could be used as a reliable proxy of GCC for monitoring evergreen species phenology in areas with reduced access, or where repeated data collection from remote areas are logistically difficult due to the extreme weather.

INVESTIGATION OF THE PROCESS OF PROCESSING LIQUID WASTE OF UREA PRODUCTION USING A BIOFILTER

The kinetic regularities of the recycling process of liquid waste of urea on the combined filter which contains the immobilized layer of enzymes at the process of their purification from the suspended substances, dissolved nitrate anions; the effect of pH on the filtration process are investigated and established in our research. A stable positive result was obtained on the filters with layers of:
 – oak and birch, the concentration of nitrate anions decreased from 12 to 0,06 — 0,05 mg/dm3 after 80 minutes of filtration. The content of suspended solids decreased from 37 g/dm3 to 6 — 7 g/dm3. At the same time, the increased content of tannins and the natural structure of oak and birch leaves contributes to the resistance of the leaf layer to fermentation processes, helps to use such kind of filter repeatedly.
 – linden and maple leaves, the concentration of nitrate anions decreased from 12 mg/dm3 to 0,08 mg/dm3 after 80 minutes of filtration. The content of suspended solids decreased from 37 g/dm3 to 15 g/dm3 after the third use of the filter, due to increased activity of microorganisms. At the same time, the natural structure of linden and maple leaves is thin, has a biofilm that is easily destroyed and accelerates the process of natural aerobic fermentation.
 The scientific substantiation of the direction of improvement of technology of processing of liquid waste with the increased content of nitrogen is executed. A bio filtration unit on a combined filter with a layer of oak and birch leaves with the use of an immobilized layer of enzymes is proposed. The combined filter consists of a layer of gravel, sand and dry oak and/or birch leaves. The enzyme Chymotrypsin at a concentration of 0,005 g/dm3 is fed into the formed bio filter from above. After 30 minutes, liquid waste with a temperature of 10 25 °С is gradually fed into the filter over 60 — 80 minutes. The initial concentration of suspended particles in liquid waste should not exceed a concentration of 37 — 40 g/dm3. It is determined that the optimal rate of processing of liquid waste of urea production is achieved in solutions with active reaction of hydrogen ions in the range of 6,5—7,3.