Next Article in Journal
Advance of Target Visual Information Acquisition Technology for Fresh Fruit Robotic Harvesting: A Review
Next Article in Special Issue
Searching of Novel Herbicides for Paddy Field Weed Management—A Case Study with Acetyl-CoA Carboxylase
Previous Article in Journal
Alternative Mulches for Sustainable Greenhouse Tomato Production
Previous Article in Special Issue
Weed Composition in Hungarian Phacelia (Phacelia tanacetifolia Benth.) Seed Production: Could Tine Harrow Take over Chemical Management?
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 12
Issue 6
10.3390/agronomy12061335
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Preliminary Study of Control and Biochemical Characteristics of Giant Hogweed (Heracleum sosnowskyi Manden.) Treated with Microwaves

by
Krzysztof Słowiński
1,*,
Beata Grygierzec
2,
Agnieszka Synowiec
2,
Sylwester Tabor
3 and
Fabrizio Araniti
4,*
1
Department of Forest Management, Engineering and Technology, University of Agriculture in Krakow, 31-425 Krakow, Poland
2
Department of Agroecology and Crop Production, University of Agriculture in Krakow, 31-120 Krakow, Poland
3
Department of Production Engineering, Logistics and Applied Computer Science, University of Agriculture in Krakow, 30-149 Krakow, Poland
4
Department of Agricultural and Environmental Sciences (DISAA), University of Milan, 20133 Milan, Italy
*
Authors to whom correspondence should be addressed.
Agronomy 2022, 12(6), 1335; https://doi.org/10.3390/agronomy12061335
Submission received: 9 May 2022 / Revised: 25 May 2022 / Accepted: 28 May 2022 / Published: 31 May 2022
(This article belongs to the Special Issue The Future of Weed Science—Novel Approaches to Weed Management)
Browse Figures
Versions Notes

Abstract

:
There is an urgent need to develop new compensatory and human-safe methods for controlling invasive Heracleum species. This research aimed to determine the effectiveness of H. sosnowskyi control under microwave radiation and biochemical changes in tissues and sap after irradiation. In field experiments in southern Poland, the plants were cut and irradiated with a device generating electromagnetic waves (2.45 GHz, 32.8 kW/m2). The control efficacy of plants in the rosette phase irradiated for 5, 10, or 15 min was 20%, 100%, and 100%, respectively. The control efficacy of plants in the flowering phase irradiated for 7.5 or 15 min was 66% and 100%. The metabolomic analysis of tissues and sap of irradiated H. sosnowskyi showed significant changes, mainly in the content and composition of proteins and sugars. In tissues, the treatments resulted in protein denaturation and significant changes in the metabolism of amino acids and the glyoxylate and galactose pathways. The sap was rich in sugars, glutamic acid, glutamine, homoserine, serine, and methionine. More changes in metabolite levels were observed in the tissues irradiated for 7.5 min. In conclusion, microwave radiation of H. sosnowskyi for longer times, e.g., 10 and 15 min, efficiently controls it.

1. Introduction

There are over 20 species of plants of the genus Heracleum known in Europe. Three species of this genus, so-called giant hogweeds, i.e., Heracleum sosnowskyi (Manden.), Heracleum mantegazzianum (Sommier & Levier), and Heracleum persicum (Desf. ex Fischer), from the Central and Eastern Caucasus, Trans-Caucasus, and Turkey, are invasive plants in Europe [1,2]. These plants pose a serious threat to habitats under changing climatic conditions [3], being highly competitive with the native flora [4]. Invasive hogweeds are characterized by an intensive growth rate, huge size (up to 4 m high), and a high reproductive rate [2,5]. Studies have proven that their competitive abilities also result from allelopathic interactions [6]. The invasive Heracleum species cause health problems in humans and animals due to the content of chemical compounds, i.e., furanocoumarins, in their tissues. Direct contact with the plants or even being in their vicinity may often result in skin and eye irritation and skin burns [7,8] and special cases of poisoning accompanied by disorders of the nervous system and heart muscle [9].
Out of the three invasive Hogweeds in Poland, two are a serious problem, i.e., Heracleum sosnowskyi and Heracleum mantegazzianum; they occur in various habitats, along roads and railways, on the banks of rivers and irrigation canals, and in agricultural areas and national parks [10,11]. Their dynamic spread in recent decades throughout northern Europe is partly explained by the increase in winter temperature [12,13]. In the European Union, the invasive Hogweeds are included in the Invasive Alien Species of Union list EU [14], which obliges the EU countries to limit their spread or eliminate them.
This research focused on Heracleum sosnowskyi due to the frequency of occurrence and the area occupied in southern Poland, which varies from a few square meters with a few specimens to several hectares of dense stands [15]. The biological and ecological characteristics of Heracleum sosnowskyi make it a species difficult to control. Mechanical mowing does not give the desired effects because plants grow back, and herbicides are a significant threat to the environment [16,17,18,19,20]. Therefore, there is an urgent need to develop new compensatory methods for controlling invasive Heracleum [21,22].
As a result, in this research, to destroy Heracleum sosnowskyi plants, the authors used a device emitting electromagnetic (microwave) radiation within the limits of radiofrequency radiation. Out of the wide range of microwave frequencies, only a few are more widely used, according to the regulations of the Federal Communications Commission. Metal reflects microwaves, which pass through electrically neutral materials such as glass, most plastics, ceramics, and paper, and when they are absorbed, they generate heat in the absorbing material. Two particularly important properties of microwaves are volumetric heating and inverted temperature gradients in the heated material [23,24,25]. Currently, the use of microwaves in many areas is becoming common, for example, in food processing and agriculture [26,27,28,29,30,31], sterilization of seed material [32] and soil [33], or in forestry to improve the quality of seed germination [34], for the disinfection of soil [35], and for the drying of wood and wood-based products [36,37,38,39]. It is known from the available literature that microwave radiation also affects the growth and development of plants. However, the effects of microwaves on plants depend on the plant family and growth stage involved [40,41], and the exposure duration, frequency, and power density [42]. The number of published studies is insufficient to conclude on the effects of microwaves on plants [43]. Thus far, studies that show the possibility of combating plants with microwaves and the biochemical changes in plants under the influence of exposure to microwave radiation are few [44,45,46]. For example, millimeter-wave irradiation of low intensity improves the growth of chickpea [47] and soybean seedlings, promoting glycolysis- and redox-related pathways under flooding conditions and activating sugar metabolism, especially trehalose synthesis [48]. Since the final effect of microwaves on plants depends on the intensity and duration of microwave treatment, we hypothesize that the stimulating effects will change under high microwave intensity to inhibiting ones. Hence, the study aimed to determine the effectiveness of Sosnowsky’s hogweed (Heracleum sosnowskyi Manden.) control under microwave radiation and to determine the biochemical changes in tissues and sap after irradiation.

2. Materials and Methods

2.1. The Description of the Microwave Device for the Destruction of Heracleum sosnowskyi Plants

A device emitting microwave radiation with an open stream directed at the plant was built (Figure 1) based on the elements of a microwave oven. Before disassembling its elements, the output microwave power was determined following the Polish norm PN-EN 60705. The device used a magnetron to generate electromagnetic waves with a frequency of 2.45 GHz and a power density of 32.8 kW/m2. A voltage-increasing transformer powered the magnetron through a voltage multiplier consisting of a capacitor and a diode. Both the magnetron and the transformer were cooled by the air stream forced by the fan. In addition to these elements, the system included fuses, bimetallic thermal switches, and a filter that eliminated disturbances in the power supply network.
The wiring diagram is shown in Figure 2. The average surface power density for the dimensions of the constructed antenna for the magnetron was 30 kW/m2. The antenna was positioned centrally to emit microwave radiation to the center of the plant, and a raise in temperature destroyed the plant.

2.2. Microwave Treatment in the Rosette Phase of Heracleum sosnowskyi

The treatment was carried out on 15 June 2021, at the Experimental Station of the Faculty of Biotechnology and Horticulture of the University of Agriculture in Krakow, which is located in Garlica Murowana (50°8′26.65″ N, 19 ° 56′5.26″ E; 274.4 m a.s.l.), ca. 5 km north of Krakow (Figure 3 left). The experimental plot was a seminatural plant community of the Molinio-Arrhenatheretea class in secondary succession. In the western part of the plot, on 800 m2, there was a dispersed population of Sosnowsky’s hogweed (Heracleum sosnowskyi Manden.) composed of ca. 25 specimens (Figure 3 right). Tall grasses and Solidago canadensis surrounded the hogweed plants. The treatment began around 10 a.m., when the air temperature was ca. 23–24 °C, and there was no wind, and was completed in the afternoon, around 4 p.m., when the air temperature increased to 30 °C. Twenty plants of Sosnowsky’s hogweed in the rosette phase (height about 50–60 cm) were selected. The plants were cut with a sickle to 4 cm from the soil surface. Next, the microwave device was placed centrally over each cut stem and irradiated for 5, 10, or 15 min. Each irradiation was carried out in 5 replications, and the remaining 5 stems served as non-treated control.

2.3. Microwave Treatment in the Flowering Phase of Heracleum sosnowskyi

The treatment was conducted in natural conditions on a 1200 m2 area covered by a dense population of Sosnowsky’s hogweed (Heracleum sosnowskyi Manden.) on 5 July 2021. The area is located in the western part of the Wielkie Błoto PLH 120080 peatbog (50°1′11,326″ N 20°15′53,481″ E; 195.6 m a.s.l.), about 20 km southeast of Kraków (Figure 4). The hogweed population was located near the local road. On the eastern side, it was limited by the post-mining reservoir in the overgrowing phase with rush vegetation belonging to the Phragmitetea class.
The microwave treatment of hogweed was performed in the early morning at an air temperature of 18 °C and air humidity of 85%. Eighteen flowering plants, ca. 3 m tall and with similar physiognomy, were selected. Whole plants were cut with a sickle at ca. 4 cm above the ground, and their location was marked with a plastic plate. Next, the microwave device was placed over each of the cut stems. Six cuts were irradiated for 7.5 min (R1) and another six for 15 min (R2). The remaining six cuts were the control without microwave irradiation (R0). In treatments R1 and R2, the microwave antenna was positioned above the cut stem to emit the radiation centrally on the stem.

2.4. Soil Analyses

The soil samples from both locations, Garlica Murowana and Wielkie Błoto, were analyzed in the accredited laboratory (AgroEkspert, Kościelec, Poland) according to the following methods: soil particle size: sand (2.0–0.05 mm), coarse silt (0.05–0.02 mm), fine silt (0.02–0.002 mm), clay (<0.002 mm) PN-R-04032: 1998 (for samples with organic matter content < 5%); total nitrogen content by the Kjeldahl method; soil pH-PN-ISO 10390: 1997; available P2O5-PN-R-04023: 1996, K2O-PB-1 (Ed. of 20 February 2013), Mg-PN-R-04020: 1994 + Az1: 2004; microelements: Mn-PN93/R-04019 (1 M HCl), Zn-PN92/R-04016 (1 M HCl), Cu-PN92/R-04017 (1 M HCl), Fe-PN-R-04021: 1994 (1 M HCl), B-PN93/R-04018 (1 M HCl); heavy metals Cd, Ni-PN-ISO 11047: 2001. The soils composition from both sites is presented in Table 1.

2.5. Assessment of the Heating Value of Microwaves and Plant Destruction of Heracleum sosnowskyi in Both Populations

The diameter of each cut stem of hogweed was measured using a roller with an accuracy of ±1 mm, at two cross-cutting positions, as the stems were elliptic. Next, the area of the stem was calculated using the equation:
P = πab,
where a and b are the ellipse driveshafts.
Before and right after each irradiation process, the temperature of the cut stems of hogweeds was measured with a thermal imaging camera FLIR E60 equipped with Wi-Fi (producer: FLIR Systems, Inc., Wilsonville, OR, USA); the camera measures temperature in a range from −20 to +120 °C (±2 °C). The camera was placed at ca. 0.5–1 m above each stem, and photos of a resolution of 320 × 240 pixels were taken. Next, each photo was analyzed using the FLIR ResearchIR MAX (producer: Teledyne FLIR LLC, Wilsonville, OR, USA), based on the mathematical processing of the pixels’ color scale. The average temperature values were calculated for each treated plant and analyzed further using regression analysis in the Excel worksheet.
The level of plant destruction following irradiation was monitored visually based on the regrowth of new leaves. The plant population in Garlica Murowana was monitored at 16 and 94 days after irradiation (DAI), and the population in Wielkie Błoto was monitored at 7 and 75 DAI.

2.6. A Sampling of Plant Material for the Metabolomic Analyses

Five hours after the R1 and R2 treatments, from the population in Wielkie Błoto, the transparent sap, excreted to the internal parts of the cut stems of hogweed, was collected separately from each plant using sterile syringes and containers of 20 mL volume. Additionally, the internal tissues of stems were cut with a sterile lancet, at 3 cm in length and about 0.3–1 cm in depth, and placed in sterile containers of 20 mL volume, separately from each hogweed plant. The collection of plant material was carried out at an air temperature of 34 °C and air humidity of 60%.
In total, 12 samples with sap and 18 samples with stem tissues were collected. The sap samples were filtered in the laboratory on the same day through Pureland PP (Stargard, Poland) syringe filters with a nominal pore size of 0.45 μm, and 0.2 mL of the filtrate was poured into the sterile Eppendorf vials. The collected plant tissues were gently scrubbed with sterile lancets to remove all the surface impurities and placed in sterile containers of 20 mL volume. The material was lyophilized at −40°C in Labconco FreeZone (Kansas City, MO, USA) freeze dry system for ca. 30 h, to quench the metabolism, and stored at room temperature.

2.6.1. Metabolite Extraction and Derivatization

Fifty milligrams of lyophilized plant material was used for each sample and replicated. Sample extraction was carried out following the protocol Lisec et al. [49] proposed with some modifications. In particular, 1400 µL of cold methanol (at −20 °C) was added to the sample. After vortexing, 60 µL of ribitol stock solution (internal standard), used at the concentration of 0.2 mg/mL in ddH2O was added. Samples were heated (70 °C) and shaken (950 rpm) for 10 min to enhance metabolome extraction and then centrifuged for 10 min at 11,000× g. The polar and non-polar classes of metabolites were separated using 750 µL CHCl3 (−20 °C), and 1500 µL ddH2O (4 °C) was sequentially added to the methanolic extracts. All the samples were vortexed and centrifuged for 15 min at 2200× g. For each sample, replicate, and treatment, 150 µL of the upper polar phases were collected and dried in a vacuum concentrator at room temperature. Then the samples were methoximated, adding 40 µL methoxyamine hydrochloride (20 mg/mL in pyridine), followed by incubation at 37 °C for 2 h in a thermomixer (950 rpm). Successively, the methoximated samples were further silylated adding 70 μL of N-methyl-N-trimethylsilyltrifluoroacetamide. Samples were then incubated for 30 min at 37 °C in a thermomixer (950 rpm). For the GC-MS analysis, derivatized samples (110 µL per each sample and treatment) were then transferred into GC-MS glass inserts.

2.6.2. GC-MS Analysis

The derivatized extracts were injected into a MEGA 5-MS capillary column (30 m × 0.25 mm × 0.25 µm + 10 m of pre-column) using a gas chromatograph apparatus (GC Agilent series 7890A) equipped with a single quadrupole mass spectrometer (MSD 5975C inert XL Perf Turbo). A CombiPAL autosampler was used for sample handling and injection.
The injector, transfer line, and source were set at 250, 250, and 260 °C, respectively. One microliter of the sample was injected in splitless mode with a helium (Elio Bip 6.0, SAPIO, Monza, Italy) flow of 1 mL/min using the following programmed temperature: isothermal 5 min at 70 °C followed by a 5 °C/ min ramp to 350 °C and a final 5 min heating at 330 °C. Mass spectra were recorded in the electronic impact (EI) mode at 70 eV, scanning at the 40–600 m/z range, with a scan time of 0.2 s. The mass spectrometric solvent delay was set as 9 min. n-Alkane standards (C10–C40 all even) and blank solvents (pyridine) were also injected for instrumental performance, tentative identification, and monitoring of shifts in retention indices (RIs).

2.6.3. GC/MS Data Analysis and Statistical Analyses

The open-source software MS-DIAL, equipped with open-source publicly available EI spectral libraries, was used for data baseline filtering and calibration, peak alignment, deconvolution analysis, peak identification, and integration. The software was employed for the analysis as previously described by Misra et al. [50].
Compounds were identified based on the mass spectral pattern compared to EI spectral libraries, using commercial (NIST17/2017) and publicly available libraries. The public libraries were archived from the MSRI spectral libraries from Golm Metabolome Database, MassBank, and MoNA (Mass Bank of North America). Metabolite annotation and assignment of the EI-MS spectra were carried out following the metabolomics standards initiative (MSI) guidelines [51], using Level 2 (identification based on the spectral database (match factor > 80%) and Level 3 (putatively characterized compound class based on spectral similarity to known compounds of a chemical class as suggested).
A completely randomized design with five biological replications was adopted. Samples were divided into two groups (stem tissue and sap) and separately analyzed. The statistical analysis was performed using MetaboAnalyst version 5.0 [52]. Briefly, relative abundance values from the MS-DIAL outputs were normalized per the internal standard, Log2 transformed, and Pareto scaled. Successively, univariate analysis (ANOVA using LSD test as post hoc p ≤ 0.05, evaluated through the false discovery rate), multivariate analysis (unsupervised principal component (PCA) analysis and supervised partial least squares discriminant analysis (PLS-DA) and machine learning analysis (random forest) were used to highlight the main metabolites involved in group separation as well as potential biomarkers.
The PLS-DA model was built using the two main latent variables (PC1 and PC2), which explained more than 70% of the total variability. The model affordability was then confirmed through cross-validation and the permutation test analysis. In particular, for cross-validation, the leave-one-out cross-validation (LOOCV) procedure and Q2 for performance evaluation were used. The separation distance statistical test, setting the permutation number to 20, was used for the permutation. The random forest analysis was built using 500 trees and 7 predictors with a randomness option. Enrichment and pathways analysis was carried out only on stem tissue samples using the MetaboAnalyst 5.0 tools and setting Arabidopsis thaliana as a metabolome reference database.

3. Results

3.1. The Effectiveness of Destroying Hogweed in the Leaf Rosette Phase

In the experiment in Garlica Murowana, a soil of medium agronomic category was found, with a clay structure and an average moisture content of 84% (Table 1). The average area of cut hogweed shoots in the rosette phase was 3.14–78.5 cm2. The mean temperature of the plants untreated with microwaves was 21.5 °C, and immediately after microwave exposure, the temperature increased to 68, 81.8, and 94.6 °C after 5, 10, and 15 min, respectively (Figure 5).
All control plants that were cut only re-grew (Figure 6). After 16 days from treatment, the effectiveness of destroying Sosnowsky’s hogweed with microwaves within 5 min was 20%. Sixteen days after the treatment, four plants irradiated for 5 min showed signs of regeneration out of the five irradiated (Figure 7). The regenerated plants developed 1–2 new leaves. Sixteen and 94 days after the irradiation for 10 and 15 min, the effectiveness of destroying hogweed was 100% (Figure 8 and Figure 9).

3.2. The Effectiveness of Destroying Hogweed in the Flowering Phase

In the experiment carried out in the Wielkie Błoto population, the soil found was loamy sand, a very light soil according to the agronomic category, with an average humidity of 89% (Table 1). The average area of cut hogweed shoots in the flowering phase was 33.7–45.4 cm2. The average temperature of the plants untreated with microwaves was 15.4 °C. Immediately after microwave exposure, the temperature of the plants increased to 62.7 and 76.3 °C after 7.5 and 15 min, respectively (Figure 10).
Seven days after the treatment, the effectiveness of hogweed irradiation for 7.5 min was 66%, which means that two plants (out of six) re-grew a new leaf (Figure 11). Seventy-five days after treatment, three plants were found to regenerate following 5-min-long irradiation; those plants were growing about 4–6 new leaves each (Figure 12). Microwave irradiation for 15 min caused 100% of plant destruction, as found 7 and 75 days after treatments (Figure 13 and Figure 14). Figure 15 shows a control plant that was cut only 7 and 75 days after cutting.

3.3. GC-MS-Driven Untargeted Metabolomic Analysis of Stem Tissues of Hogweed Irradiated in the Flowering Phase

The metabolic changes in H. sosnowskyi stem tissues were assessed following the microwave treatments using a GC/MS-driven untargeted-metabolomic analysis. The analysis allowed us to annotate and quantify 82 putatively annotated metabolites and extract 965 unknown EI-MS shared features. The data analyzed by univariate one-way ANOVA allowed us to identify 65 significantly altered features, for which the concentrations for each replicate have been reported in the text as a heat map (Figure 16).
Successively, to identify differences among the groups and the molecules involved in those differences, the data were analyzed through multivariate analysis using the unsupervised PCA (Figure 17a), revealing clear discrimination among the three sample groups with no outliers. In particular, PCA was conducted based on the first two components (PC1 and PC2), which accounted for 77.3% of the total variance. PC1 described 53.9%, whereas PC2 explained 23.4% of the total variance (Figure 17a). The PCA loading plots were analyzed to highlight the main contributors to sample separation. PC1 was mainly dominated by triethanolamine, phosphate, 3-aminopropionitrile fumarate, galactinol, and alpha-lactose, whereas for PC2 it was isoleucine, threonine, serine, phosphate, and norvaline. A partial least squares discriminant analysis (PLS-DA) was successfully applied (Figure 17b). The results confirmed the separation of groups. The PLS-DA-derived variable importance in projection (VIP) scores (built on the metabolites with a VIP score higher than 1) revealed triethanolamine, serine, alpha-lactose, maltose, melibiose, and galactinol, among others, as the main metabolites involved in group separation (Figure 17c). Finally, the machine learning random forest analysis revealed xylitol, melibiose, isocitric acid, valine, gluconic acid, alpha-ketoglutaric acid, and shikimic acid, among others, as the metabolites with the highest mean decrease accuracy (features ranked by their contributions to classification accuracy) for the three sample groups (Figure 17d).
Finally, a KEGG-based pathway analysis, which combines enrichment and topology analysis, revealed that 22 pathways were significantly altered by the microwave treatment (Table 2). The treatments significantly impacted the amino acid metabolism and the glyoxylate and the galactose pathways.

3.4. GC-MS-Driven Untargeted Metabolomic Analysis of Hogweed Sap

It was observed that plants treated with microwaves exuded a transparent sap inside the cut stem as an effect of radiation. For this reason, the chemical composition of the sap was analyzed. Metabolomic data concerning the sap produced by microwave-treated plants at the end of the experiments were handled as previously described for the stem tissue metabolome. The metabolomic analysis identified 1498 unknown molecules and 142 putatively annotated metabolites belonging to the class of amino acids, sugars, sugar alcohols, and organic acids. Among the annotated compounds, the ANOVA analysis pointed out that 111 out of 142 were significantly altered by the time of exposition to the microwave treatment. In particular, the analysis pointed out that the exposition time to microwaves was increasing/decreasing specific classes of compounds. The sap composition differed significantly among the three treatments. A clear separation was observed on PCA and PLS-DA analysis (Figure 18a,b). In particular, the PCA using the first two components explained 80.4% of the total variability. The metabolites participating in the separation for the two components were mannose, galactose, glutamic acid, N-acetyl-l-tyrosine, palmitic acid, glucose, N-acetylmannosamine, glucarate, and ferulic acid for PC1 and hexitol, 4-methylbenzoic acid, l-5-oxoproline, citramalic acid, pyrogallol, 3,4-dihydroxybenzoate, galactose, O-acetyl-l-serine and methylsuccinic acid for PC2.
Moreover, after its validation, the PLS-DA model further confirmed a clear separation among the groups, pointing out more than 30 metabolites with a VIP score higher than 1 (Figure 18c). Several sugars, i.e., galactose, glucose, and mannose, and amino acids, i.e., glutamic acid, glutamine, homoserine, serine, methionine, etc., should be annotated. Finally, the random forest analysis revealed that citric acid, norvaline, and threonic acid, among others, were the potential biomarkers of the different treatments (Figure 18d).

4. Discussion

The results presented in this study on the control of Sosnowsky’s hogweed with microwaves are pioneering. The effectiveness of combating hogweed plants in the leaf rosette and flowering phase was demonstrated using a device emitting microwaves at frequency 2.45 GHz and a power density 32.8 kW/m2. It was found that, the longer the exposure of plants to microwaves, the lesser the subsequent regeneration. In the case of hogweed, 10 and 15 min of irradiation effectively destroyed 100% of plants in the leaf rosette and flowering phases, respectively. Previous studies on microwave exposure on plants have revealed variations in the sensitivity of plants to different microwave frequencies, exposure durations, and power intensities. For example, a stimulating effect was observed at low-power microwave irradiation on in vitro Sequoia plants [53]. Continuous microwave energy at 2.45 GHz with 0.5–1.2 mW/cm2 caused no difference in growth and biomass accumulation between control and the microwave treatment of alfalfa [42]. Furthermore, horizontally and vertically polarized 2 GHz continuous microwaves at 1.8 W m−2 power density did not alter the growth parameters, e.g., shoot length, stem diameter, and internodal length of Myriophyllum aquaticum plants [54]. Contrarily, a long-term signal at 915 MHz with a maximum power density of 10 mW/m2 caused significant morphological modifications in Phaseolus vulgaris [55].
The other factors responsible for the irradiation effect include biological and environmental factors, particularly soil moisture. Research shows that the higher the soil moisture at irradiation, the higher its effectiveness [40]. For these reasons, in the present study, irradiation was carried out in the early morning when the humidity of both soils was high, 84% and 86%. The high humidity of the soils guaranteed a high degree of moisture in plant tissues. Therefore, their longer exposure time caused a significant increase in temperature, up to almost 95 °C, after 15 min of plant irradiation in the leaf rosette phase. As shown by Radzevičius et al. [56], slightly elevated temperatures (up to +30 °C) combined with 9.3 GHz frequency microwaves for 4 μs cause an incentive effect on plants, e.g., improved saccharide distribution in seeds or plants and significantly reduced content of non-structural carbohydrates, e.g., raffinose, glucose, fructose, and sucrose.
Contrarily, in our treatments, the high temperature of tissues during irradiation disintegrated the hogweed cells and tissues, resulting in the excretion and accumulation of sap in the irradiated stems. The metabolomic analysis of tissues and sap showed significant changes mainly in the content and composition of proteins and sugars. In the stem tissues, the treatments caused the denaturation of proteins and significant changes in the amino acid metabolism and the glyoxylate and the galactose pathways. The exuded sap was rich in sugars, mannose, galactose, and glucose and also in amino acids, i.e., glutamic acid, glutamine, homoserine, serine, and methionine. The random forest analysis revealed high citric acid, norvaline, and threonic acid contents in the sap. Following microwave irradiation, the observed changes in Sosnowsky’s hogweed plants could be compared to heat changes caused by the flame method in soybean crops [57]. Under high-temperature conditions, over-fluidity of membranes appears, leading to an outflow of ions. Ion efflux leads to a reduction in the activity of many enzymes [58]. The most susceptible physiological process under microwave treatment is photosynthesis [54,55]. As found by Upadhyaya et al. [59], the exposure of plants to 900 MHz electromagnetic waves for up to 72 h indicated significant detriment in phenolic compounds by 32.12%, flavonoids by 14.89%, reduction in DPPH radical scavenging activity by 56.33%, and total antioxidant activity by 42.01%.
More changes in the levels of metabolites were observed in the stem tissue after 7.5 min of microwave treatment. Some plants re-grew after this treatment, suggesting that some of the observed changes could be of defensive character. Interestingly, in the sap of plants irradiated for 7.5 min, high levels of citric acid were found. Farid et al. [60] report that citric acid alleviates environmental stress in microwave-irradiated Brassica napus L. by initiating an antioxidant defense system.

5. Patents

Application number: PL43727921A, Title: Device for controlling weeds and their seeds, especially Sosnowsky’s hogweed (Heracleum sosnowskyi Manden.). Publication date: 2022-01-17.

Author Contributions

Conceptualization, K.S. and B.G.; methodology, K.S., B.G., A.S. and. F.A.; software, K.S. and F.A.; investigation, K.S., B.G., A.S. and F.A.; resources, K.S. and F.A.; data curation, K.S., B.G., A.S. and. F.A.; writing—original draft preparation, B.G., A.S. and. F.A.; writing—review and editing, K.S. and S.T.; visualization, K.S., B.G. and F.A.; supervision, K.S. and S.T.; project administration, K.S.; funding acquisition, K.S. All authors have read and agreed to the published version of the manuscript.

Funding

The program “Incubator of Innovation 4.0”, implemented as part of the non-competitive project entitled ″Support for the management of scientific research and commercialization of the results of R&D works in research units and enterprises″, funded under the Intelligent Development Operational Program 2014–2020 (Measure 4.4).

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the study’s design; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Visockienė, J.S.; Tumelienė, E.; Maliene, V. Identification of Heracleum sosnowskyi—Invaded Land Using Earth Remote Sensing Data. Sustainability 2020, 12, 759. [Google Scholar] [CrossRef] [Green Version]
  2. Bogdanov, D.; Ram, M.; Aghahosseini, A.; Gulagi, A.; Oyewo, A.S.; Child, M.; Caldera, U.; Sadovskaia, K.; Farfan, J.; De Souza, L.; et al. Low-cost renewable electricity as the key driver of the global energy transition towards sustainability. Energy 2021, 227, 120467. [Google Scholar] [CrossRef]
  3. Clements, D.R.; DiTommaso, A. Climate change and weed adaptation: Can evolution of invasive plants lead to greater range expansion than forecasted? Weed Res. 2011, 51, 227–240. [Google Scholar] [CrossRef]
  4. Page, N.A.; Wall, R.E.; Darbyshire, S.J.; Mulligan, G.A. The biology of invasive alien plants in Canada. 4. Heracleum mantegazzianum Sommier & Levier. Can. J. Plant Sci. 2006, 86, 569–589. [Google Scholar]
  5. Nielsen, C.; Ravn, H.P.; Nentwig, W.; Wade, M. The Giant Hogweed Best Practice Manual. Guidelines for the Management and Control of an Invasive Weed in Europe. For. Landsc. Den. 2005, 44, 44. [Google Scholar]
  6. Rafikova, O.; Kiseleva, O.; Veselkin, D. Seed germination of native plants in soil transformed by invasive plants Acer negundo and Heracleum sosnowskyi. E3S Web Conf. 2020, 176, 03002. [Google Scholar] [CrossRef]
  7. Lagey, K.; Duinslaeger, L.; Vanderkelen, A. Burns induced by plants. Burns 1995, 21, 542–543. [Google Scholar] [CrossRef]
  8. CABI. Invasive Species Compendium. Detailed Coverage of Invasive Species Threatening Livelihoods and the Environment Worldwide. 2019. Available online: https://www.cabi.org/isc/datasheet/26911#tosummaryOfInvasiveness (accessed on 24 February 2022).
  9. Jakubska-Busse, A.; Śliwiński, M.; Kobylka, M. Identification of bioactive components of essential oils in and Heracleum mantegazzianum (Apiaceae). Arch. Biol. Sci. 2013, 65, 877–883. [Google Scholar] [CrossRef]
  10. Sołtysiak, J.; Brej, T.; Tomczyk, M. Inwazja barszczu Sosnowskiego (Heracleum sosnowskyi Manden.) na terenie gminy Siechnice (dolnośląskie) i perspektywy jego zwalczania. Zeszyty Naukowe Uniwersytetu Przyrodniczego we Wrocławiu. Biol. Hod. Zwierząt 2015, 78, 73–86. [Google Scholar]
  11. Podgórska, M.; Wójcik, P. Barszcz Sosnowskiego (Heracleum sosnowskyi Manden., Apiaceae) u podnóża Góry Zelejowej w gminie Chęciny (Wyżyna Małopolska). Rocz. Świętokrzyski. Ser. B-Nauk. Przyr. 2011, 32, 67–78. [Google Scholar]
  12. Collingham, Y.C.; Wadsworth, R.A.; Huntley, B.; Hume, P.E. Predicting the spatial distribution of non-indigenous riparian weeds: Issues of spatial scale and extent. J. Appl. Ecol. 2000, 37, 13–27. [Google Scholar] [CrossRef]
  13. Nielsen, C.; Hartvig, P.; Kollmann, J. Predicting the distribution of the invasive alien Heracleum mantegazzianum at two different spatial scales. Divers. Distrib. 2008, 14, 307–317. [Google Scholar] [CrossRef]
  14. EU. Commission Implementing Regulation (EU) 2017/1263 of 12 2017 Updating the List of Invasive Alien Species of Union Concern Established by Implementing Regulation (EU) 2016/1141 Pursuant to Regulation (EU) No 1143/2014 of the European Parliament and of the Council. 2017. Available online: http://data.europa.eu/eli/reg_impl/2017/1263/oj (accessed on 10 February 2022).
  15. Semchuk, N.N.; Balun, O.V. Development of a biological method to control the poisonous weed plant Heracleum sosnowskyi Manden. IOP Conf. Ser. Earth Environ. Sci. 2020, 613, 012132. [Google Scholar] [CrossRef]
  16. Klima, K.; Synowiec, A. Field emergence and the long-term efficacy of control of Heracleum sosnowski plants of different ages in southern Poland. Weed Res. 2016, 56, 377–385. [Google Scholar] [CrossRef]
  17. Nicolopoulou-Stamati, P.; Sotirios, M.; Kotampasi, C.; Stamatis, P.; Hens, L. Chemical pesticides and human health: The urgent need for a new concept in agriculture. Front. Publ. Health 2016, 4, 148. [Google Scholar] [CrossRef] [Green Version]
  18. EC. Directive 2009/128/EC of the European Parliament and of the Council of October 21 2009 Establishing a Framework for Community Action to Achieve the Sustainable Use of Pesticides. ELI. 2009. Available online: https://data.europa.eu/eli/dir/2009/128/oj (accessed on 24 February 2022).
  19. EPRS. European Parliamentary Research Service, Farming without Plant Protection Products; Scientific Foresight Unit (STOA) PE 634.416; European Union: Brussels, Belgium, 2019; ISBN 978-92-846-3993-9. [Google Scholar] [CrossRef]
  20. Postnikov, A.; Partolina, A.; Egorov, A.; Pavlyuchenkova, L.; Bubnov, A. Selective herbicides to control Sosnowsky’s hogweed (Heracleum sosnowskyi Manden.) in pine and spruce plantations. IOP Conf. Ser. Earth Environ. Sci. 2021, 876, 012062. [Google Scholar] [CrossRef]
  21. Hagner, M.; Lindqvist, B.; Vepsäläinen, J.; Samorě, C.; Keskinen, R.; Rasa, K.; Hyvönen, T. Potential of pyrolysis liquids to control the environmental weed Heracleum mantegazzianum. Environ. Technol. Innov. 2020, 20, 101154. [Google Scholar] [CrossRef]
  22. van Wilgen, B.W.; Forsyth, G.G.; Le Maitre, D.C.; Wannenburgh, A.; Kotzé, J.D.; Van den Berg, E.; Henderson, L. An assessment of the effectiveness of a large, national-scale invasive alien plant control strategy in South Africa. Biol. Conserv. 2012, 148, 28–38. [Google Scholar] [CrossRef]
  23. Dadalı, G.; Apar, D.K.; Özbek, B. Estimation of effective moisture diffusivity of okra for microwave drying. Dry. Technol. 2007, 25, 1445–1450. [Google Scholar] [CrossRef]
  24. Vadivambal, R.; Jayas, D.S. Changes in quality of microwave-treated agricultural products-a review. Biosyst. Eng. 2007, 98, 1–16. [Google Scholar] [CrossRef]
  25. Adair, R.K. Biophysical limits on athermal effects of RF and microwave radiation. Bioelectromagn. J. 2003, 24, 39–48. [Google Scholar] [CrossRef] [PubMed]
  26. Román, L.; Martínez, M.M.; Rosell, C.M.; Gómez, M. Effect of microwave treatment on physicochemical properties of maize flour. Food Bioprocess Technol. 2015, 8, 1330–1335. [Google Scholar] [CrossRef] [Green Version]
  27. Al-Harahsheh, M.; Ala’a, H.; Magee, T.R.A. Microwave drying kinetics of tomato pomace: Effect of osmotic dehydration. Chem. Eng. Processing Process Intensif. 2009, 48, 524–531. [Google Scholar] [CrossRef]
  28. Contreras, C.; Martín-Esparza, M.E.; Chiralt, A.; Martínez-Navarrete, N. Influence of microwave application on convective drying: Effects on drying kinetics, and optical and mechanical properties of apple and strawberry. J. Food Eng. 2008, 88, 55–64. [Google Scholar] [CrossRef]
  29. Zhang, M.; Tang, J.; Mujumdar, A.S.; Wang, S. Trends in microwave-related drying of fruits and vegetables. Trends Food Sci. Technol. 2006, 17, 524–534. [Google Scholar] [CrossRef]
  30. Khraisheh, M.A.M.; McMinn, W.A.M.; Magee, T.R.A. Quality and structural changes in starchy foods during microwave and convective drying. Food Res. Int. 2004, 37, 497–503. [Google Scholar] [CrossRef]
  31. Soysal, Y. Microwave drying characteristics of parsley. Biosyst. Eng. 2004, 89, 167–173. [Google Scholar] [CrossRef]
  32. Kretova, Y.; Tsirulnichenko, L.; Naumemko, N.; Popova, N.; Kalinina, I. The application of micro-wave treatment to reduce barley contamination. Eest. Maaülikool Est. Univ. Life Sci. 2018, 16, 2079–2087. [Google Scholar]
  33. Mahdi, W.M.; Al-Badri, K.S.L.; Alqaisi, M.R.M. Effect of Microwave Radiation on Bacteria, Fungi and Some Growth Characteristics of Cowpea Vigna unguiculata L. Gesunde Pflanz. 2021, 73, 161–167. [Google Scholar] [CrossRef]
  34. Jakubowski, T. Evaluating of the impact of pre—Sowing microwave stimulation of bean seeds on the germination process. Agric. Eng. 2015, 2, 45–56. [Google Scholar]
  35. Słowiński, K. Wpływ promieniowania mikrofalowego wyemitowanego do nieodkażonego podłoża szkółkarskiego na przeżywalność i wybrane cechy jakościowe sadzonek sosny zwyczajnej (Pinus sylvestris L.). Zesz. Nauk. Uniw. Rol. Hugona Kołłątaja Krakowie Rozpr. 2013, 517, 1–122. [Google Scholar]
  36. Wang, X.; Chen, H.; Luo, K.; Shao, J.; Yang, H. The influence of microwave drying on biomass pyrolysis. Energy Fuels 2007, 22, 67–74. [Google Scholar] [CrossRef]
  37. Du, G.; Wang, S.; Cai, Z. Microwave drying of wood strands. Dry. Technol. 2005, 23, 2421–2436. [Google Scholar] [CrossRef]
  38. Hong-Hai, L.; Qing-Wen, W.; Lin, Y.; Tao, J.; Ying-Chun, C.A.I. Modification of larch wood by intensive microwave irradiation. J. For. Res. 2005, 16, 237–240. [Google Scholar] [CrossRef]
  39. Henin, J.M.; Charron, S.; Luypaert, P.J.; Jourez, B.; Hebert, J. Strategy to control the effectiveness of microwave treatment of wood in the framework of the implementation of ISPM 15. For. Prod. J. 2008, 58, 75–81. [Google Scholar]
  40. Diprose, M.F.; Benson, F.A.; Willis, A.J. The effect of externally applied electrostatic fields, microwave radiation and electric currents on plants and other organisms, with special reference to weed control. Bot. Rev. 1984, 50, 171–223. [Google Scholar] [CrossRef]
  41. Tripon, C.; Muntean, C.M.; Surducan, E.; Bratu, I.; Halmagyi, A.; Coste, A. Structural response of genomic DNA from grapevine (Vitis vinifera L.) varieties to microwaves irradiation: A Fourier transform infrared spectroscopy assessment. Biomed. Spectrosc. Imaging 2016, 5, 295–312. [Google Scholar] [CrossRef]
  42. Skiles, J.W. Plant response to microwaves at 2.45 GHz. Acta Astronaut. 2006, 58, 258–263. [Google Scholar] [CrossRef]
  43. Jayasanka, S.M.D.H.; Asaeda, T. The significance of microwaves in the environment and its effect on plants. Environ. Rev. 2014, 22, 220–228. [Google Scholar] [CrossRef]
  44. Kaur, S.; Vian, A.; Chandel, S.; Singh, H.P.; Batish, D.R.; Kohli, R.K. Sensitivity of plants to high frequency electromagnetic radiation: Cellular mechanisms and morphological changes. Rev. Environ. Sci. Bio Technol. 2021, 20, 55–74. [Google Scholar] [CrossRef]
  45. Balint, C.V.; Surducan, V.; Surducan, E.; Oroian, I.G. Plant irradiation device in microwave field with controlled environment. Comput. Electron. Agric. 2016, 121, 48–56. [Google Scholar] [CrossRef]
  46. Sahin, H. Effects of Microwaves on the Germination of Weed Seeds. J. Biosyst. Eng. 2014, 39, 304–309. [Google Scholar] [CrossRef] [Green Version]
  47. Komatsu, S.; Maruyama, J.; Furuya, T.; Yin, X.; Yamaguchi, H.; Hitachi, K.; Miyashita, N.; Tsuchida, K.; Tani, M. Proteomic and biological analyses reveal the effect on growth under flooding stress of chickpea irradiated with millimeter waves. J. Proteome Res. 2021, 20, 4718–4727. [Google Scholar] [CrossRef] [PubMed]
  48. Zhong, Z.; Furuya, T.; Ueno, K.; Yamaguchi, H.; Hitachi, K.; Tsuchida, K.; Tani, M.; Tian, J.; Komatsu, S. Proteomic Analysis of Irradiation with Millimeter Waves on Soybean Growth under Flooding Conditions. Int. J. Mol. Sci. 2020, 21, 486. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Lisec, J.; Schauer, N.; Kopka, J.; Willmitzer, L.; Fernie, A.R. Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat. Protoc. 2006, 1, 387. [Google Scholar] [CrossRef]
  50. Misra, B.B.; Das, V.; Landi, M.; Abenavoli, M.; Araniti, F. Short-term effects of the allelochemical umbelliferone on Triticum durum L. metabolism through GC-MS based untargeted metabolomics. Plant Sci. 2020, 298, 110548. [Google Scholar] [CrossRef]
  51. Sansone, S.A.; Fan, T.; Goodacre, R.; Griffin, J.L.; Hardy, N.W.; Kaddurah-Daouk, R.; Kristal, B.S.; Lindon, J.; Mendes, P.; Morrison, N. The metabolomics standards initiative. Nat. Biotechnol. 2007, 25, 846. [Google Scholar]
  52. Pang, Z.; Chong, J.; Zhou, G.; de Lima Morais, D.A.; Chang, L.; Barrette, M.; Gauthier, C.; Jacques, P.É.; Li, S.; Xia, J. MetaboAnalyst 5.0: Narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 2021, 49, W388–W396. [Google Scholar] [CrossRef]
  53. Halmagyi, A.; Surducan, E.; Surducan, V. The effect of low-and high-power microwave irradiation on in vitro grown Sequoia plants and their recovery after cryostorage. J. Biol. Phys. 2017, 43, 367–379. [Google Scholar] [CrossRef]
  54. Senavirathna, M.D.H.J.; Asaeda, T. Microwaves affect Myriophyllum aquaticum plants differently depending on the wave polarization. Biol. Plant. 2017, 61, 378–384. [Google Scholar] [CrossRef]
  55. Surducan, V.; Surducan, E.; Neamtu, C.; Mot, A.C.; Ciorîță, A. Effects of Long-Term Exposure to Low-Power 915 MHz Unmodulated Radiation on Phaseolus vulgaris L. Bioelectromagnetics 2020, 41, 200–212. [Google Scholar] [CrossRef] [PubMed]
  56. Radzevičius, A.; Sakalauskienė, S.; Dagys, M.; Simniškis, R.; Karklelienė, R.; Juškevičienė, D.; Račkienė, R.; Brazaitytė, A. Differential Physiological Response and Antioxidant Activity Relative to High-Power Micro-Waves Irradiation and Temperature of Tomato Sprouts. Agriculture 2022, 12, 422. [Google Scholar] [CrossRef]
  57. Malenčić, Ð.; Malidža, G.; Rajković, M.; Kiprovski, B.; Đurić, S.; Petrović, K.; Krstić, J. Flame-weeding: Impact on soybean plants and soil microorganisms. Zb. Matice Srp. Za Prir. Nauk. 2020, 139, 51–60. [Google Scholar] [CrossRef]
  58. Korablev, R.A.; Belocurov, V.P.; Busarin, E.N. Effect mechanisms of ultrahigh-frequency radiation on biological objects. IOP Conf. Ser. Earth Environ. Sci. 2021, 875, 012017. [Google Scholar] [CrossRef]
  59. Upadhyaya, C.; Patel, I.; Upadhyaya, T.; Desai, A. Exposure Effect of 900 MHz Electromagnetic Field Radiation on Antioxidant Potential of Medicinal Plant Withania Somnifera. In Inventive Systems and Control; Suma, V., Chen, J.I.Z., Baig, Z., Wang, H., Eds.; Lecture Notes in Networks and Systems; Springer: Singapore, 2021; Volume 204. [Google Scholar] [CrossRef]
  60. Farid, M.; Ali, S.; Rizwan, M.; Saeed, R.; Tauqeer, H.M.; Sallah-Ud-Din, R.; Azam, A.; Raza, N. Microwave irradiation and citric acid assisted seed germination and phytoextraction of nickel (Ni) by Brassica napus L.: Morpho-physiological and biochemical alterations under Ni stress. Environ. Sci. Pollut. Res. 2017, 24, 21050–21064. [Google Scholar] [CrossRef]
Agronomy 12 01335 g001 550
Figure 1. The scheme of action of the microwave destruction device. 1—ground; 2—horn microwave antenna; 3—cut stem of Sosnowsky’s hogweed; 4—microwave emitter; 5—a magnetron that produces microwaves; 6—converter; 7—fan cooling magnetron and converter; 8—a plug with a microwave emitter power cord.
Figure 1. The scheme of action of the microwave destruction device. 1—ground; 2—horn microwave antenna; 3—cut stem of Sosnowsky’s hogweed; 4—microwave emitter; 5—a magnetron that produces microwaves; 6—converter; 7—fan cooling magnetron and converter; 8—a plug with a microwave emitter power cord.
Agronomy 12 01335 g001
Agronomy 12 01335 g002 550
Figure 2. The electrical diagram of the device for microwave disinfection of soil. F—filter, T1, T2—temperature switches, Tr—high-voltage transformer, M—the motor of magnetron cooling fan, Mg—magnetron, D—high-voltage diode, C—high-voltage capacitor, B1, B2—fuses.
Figure 2. The electrical diagram of the device for microwave disinfection of soil. F—filter, T1, T2—temperature switches, Tr—high-voltage transformer, M—the motor of magnetron cooling fan, Mg—magnetron, D—high-voltage diode, C—high-voltage capacitor, B1, B2—fuses.
Agronomy 12 01335 g002
Agronomy 12 01335 g003 550
Figure 3. Location of field studies in Poland (left) and Garlica Murowana (right).
Figure 3. Location of field studies in Poland (left) and Garlica Murowana (right).
Agronomy 12 01335 g003
Agronomy 12 01335 g004 550
Figure 4. Location of field studies in Poland (left) and Wielkie Błoto peat bog (right).
Figure 4. Location of field studies in Poland (left) and Wielkie Błoto peat bog (right).
Agronomy 12 01335 g004
Agronomy 12 01335 g005 550
Figure 5. The temperature of hogweed stems in Garlica Murowana before (0) and immediately after microwave exposure for 5, 10, or 15 min; n = 5.
Figure 5. The temperature of hogweed stems in Garlica Murowana before (0) and immediately after microwave exposure for 5, 10, or 15 min; n = 5.
Agronomy 12 01335 g005
Agronomy 12 01335 g006 550
Figure 6. Re-growing control plant 16 days after cutting.
Figure 6. Re-growing control plant 16 days after cutting.
Agronomy 12 01335 g006
Agronomy 12 01335 g007 550
Figure 7. Re-growing plant irradiated for 5 min, 16 days (left), and 94 days (right) after the irradiation. Stick marks the place of the irradiated plant.
Figure 7. Re-growing plant irradiated for 5 min, 16 days (left), and 94 days (right) after the irradiation. Stick marks the place of the irradiated plant.
Agronomy 12 01335 g007
Agronomy 12 01335 g008 550
Figure 8. Plant irradiated for 10 min, 16 days (left), and 94 days (right) after the irradiation.
Figure 8. Plant irradiated for 10 min, 16 days (left), and 94 days (right) after the irradiation.
Agronomy 12 01335 g008
Agronomy 12 01335 g009 550
Figure 9. Plant irradiated for 15 min, 16 days (left), and 94 days (right) after the irradiation.
Figure 9. Plant irradiated for 15 min, 16 days (left), and 94 days (right) after the irradiation.
Agronomy 12 01335 g009
Agronomy 12 01335 g010 550
Figure 10. The temperature of hogweed stems in Wielkie Błoto before (0) and immediately after microwave exposure for 7.5 or 15 min; n = 6.
Figure 10. The temperature of hogweed stems in Wielkie Błoto before (0) and immediately after microwave exposure for 7.5 or 15 min; n = 6.
Agronomy 12 01335 g010
Agronomy 12 01335 g011 550
Figure 11. Plants irradiated for 7.5 min, 7 days after irradiation. Plant sample 9 (left) is destroyed and plant sample 11 (right) is re-growing.
Figure 11. Plants irradiated for 7.5 min, 7 days after irradiation. Plant sample 9 (left) is destroyed and plant sample 11 (right) is re-growing.
Agronomy 12 01335 g011
Agronomy 12 01335 g012 550
Figure 12. Plants irradiated for 7.5 min, 75 days after irradiation. Plant sample 9 (left) is destroyed and plant sample 11 (right) is re-growing several new leaves.
Figure 12. Plants irradiated for 7.5 min, 75 days after irradiation. Plant sample 9 (left) is destroyed and plant sample 11 (right) is re-growing several new leaves.
Agronomy 12 01335 g012
Agronomy 12 01335 g013 550
Figure 13. Plants irradiated for 15 min (left and right), 7 days after irradiation. Both plants are destroyed.
Figure 13. Plants irradiated for 15 min (left and right), 7 days after irradiation. Both plants are destroyed.
Agronomy 12 01335 g013
Agronomy 12 01335 g014 550
Figure 14. Plants irradiated for 15 min (left and right), 75 days after irradiation. Both plants are destroyed.
Figure 14. Plants irradiated for 15 min (left and right), 75 days after irradiation. Both plants are destroyed.
Agronomy 12 01335 g014
Agronomy 12 01335 g015 550
Figure 15. Re-growing control plant 7 days (left) and 75 days (right) after cutting.
Figure 15. Re-growing control plant 7 days (left) and 75 days (right) after cutting.
Agronomy 12 01335 g015
Agronomy 12 01335 g016 550
Figure 16. A heat map with 65 significantly altered features following the H. sosnowskyi (Manden.) stems’ exposure to microwaves for 0 (R0), 7.5 min (R1), and 15 min (R2), as analyzed by univariate one-way ANOVA; n = 5.
Figure 16. A heat map with 65 significantly altered features following the H. sosnowskyi (Manden.) stems’ exposure to microwaves for 0 (R0), 7.5 min (R1), and 15 min (R2), as analyzed by univariate one-way ANOVA; n = 5.
Agronomy 12 01335 g016
Agronomy 12 01335 g017 550
Figure 17. Discrimination through principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) of the metabolite patterns in H. sosnowskyi (Manden.) stems exposed for 0 (R0), 7.5 min (R1), and 15 min (R2) to microwave treatments. (a) PCA and (b) PLS-DA showed score plots that allowed group discrimination by the first two principal components (PCs). (c) Variable importance of projection (VIP) features for the groups from PLS-DA analysis. (d) Random forest analysis displaying the mean decrease accuracies; n = 5.
Figure 17. Discrimination through principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) of the metabolite patterns in H. sosnowskyi (Manden.) stems exposed for 0 (R0), 7.5 min (R1), and 15 min (R2) to microwave treatments. (a) PCA and (b) PLS-DA showed score plots that allowed group discrimination by the first two principal components (PCs). (c) Variable importance of projection (VIP) features for the groups from PLS-DA analysis. (d) Random forest analysis displaying the mean decrease accuracies; n = 5.
Agronomy 12 01335 g017
Agronomy 12 01335 g018 550
Figure 18. Discrimination through principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) of the metabolite patterns in H. sosnowskyi (Manden.) sap exuded by the roots exposed for 0 (R0), 7.5 min (R1), and 15 min (R2) to microwave treatments. (a) PCA and (b) PLS-DA showed score plots that allowed group discrimination by the first two principal components (PCs). (c) Variable importance of projection (VIP) features for the groups from PLS-DA analysis. (d) Random forest analysis displaying the mean decrease accuracies; n = 4.
Figure 18. Discrimination through principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) of the metabolite patterns in H. sosnowskyi (Manden.) sap exuded by the roots exposed for 0 (R0), 7.5 min (R1), and 15 min (R2) to microwave treatments. (a) PCA and (b) PLS-DA showed score plots that allowed group discrimination by the first two principal components (PCs). (c) Variable importance of projection (VIP) features for the groups from PLS-DA analysis. (d) Random forest analysis displaying the mean decrease accuracies; n = 4.
Agronomy 12 01335 g018
Table
Table 1. Mechanical and chemical characteristics of soils from sites in Garlica Murowana and Wielkie Błoto.
Table 1. Mechanical and chemical characteristics of soils from sites in Garlica Murowana and Wielkie Błoto.
AnalysisGarlica MurowanaWielkie Błoto
Soil particlessand: 23%sand: 89%
coarse silt: 36%coarse silt: 6%
fine silt: 33%fine silt: 5%
clay: 8%
N total (g/kg d.m. soil)2.110.1
pH KCl7.37.1
Macronutrients
(mg/100 g soil)		P2O5: 26.2 (very high)P2O5: 6.7 mg (low)
K2O > 35.0 (very high)K2O: 14.8 mg (high)
Mg: 7.6 (high)Mg > 15.0 (very high)
Micronutrients
(mg/100 g soil)		Mn: 247.3 (medium)Mn: 535.7 (high)
Zn: 24.5 (high)Zn > 50.0 (high)
Cu: 4.5 (medium)Cu: 6.3 (high)
Fe: 2092.7 mg/kg soil (medium)Fe: 3425.7 mg/kg soil (medium)
B: < 0.3 mg/kg soil (low)B: 0.9 mg/kg soil (low)
Heavy metals (mg/kg soil)Cd < 5.0Cd < 5.0
Ni: 15.2Ni: 15.0
Soil humidity86%89%
Table
Table 2. The results from “Pathway Analysis” carried out on the metabolite identified in H. sosnowskyi (Manden.) stem tissues exposed for 0 (R0), 7.5 min (R1), and 15 min (R2) to microwave treatments.
Table 2. The results from “Pathway Analysis” carried out on the metabolite identified in H. sosnowskyi (Manden.) stem tissues exposed for 0 (R0), 7.5 min (R1), and 15 min (R2) to microwave treatments.
Metabolic PathwaysTotal CmpdHitsRaw pFDRImpact
Glycine serine and threonine metabolism3341.10 × 10−125.15 × 10−110.355
Alanine aspartate and glutamate metabolism2253.87 × 10−61.81 × 10−50.327
Glyoxylate and dicarboxylate metabolism2961.62 × 10−53.62 × 10−50.295
Galactose metabolism2773.00 × 10−61.81 × 10−50.249
Carbon fixation in photosynthetic organisms2131.02 × 10−71.97 × 10−60.149
Citrate cycle (TCA cycle)2030.000340.0005330.146
Pentose phosphate pathway1931.25 × 10−71.97 × 10−60.144
Butanoate metabolism1730.0003360.0005330.136
Pantothenate and CoA biosynthesis2330.040180.0472120.117
Glycolysis/Gluconeogenesis2630.0048280.0059710.103
Inositol phosphate metabolism2823.13 × 10−61.81 × 10−50.103
Starch and sucrose metabolism2220.000160.0002790.099
Fructose and mannose metabolism2024.93 × 10−61.81 × 10−50.098
Phenylalanine tyrosine and tryptophan biosynthesis2217.26 × 10−61.81 × 10−50.080
Arginine and proline metabolism3420.0001670.000280.075
Glutathione metabolism2620.0401120.0472120.071
Sulfur metabolism1516.04 × 10−61.81 × 10−50.033
Phosphatidylinositol signaling system2616.85 × 10−61.81 × 10−50.033
Glycerolipid metabolism2127.57 × 10−61.81 × 10−50.017
Fatty acid biosynthesis5620.004350.0055260.011
Glycerophospholipid metabolism3711.90 × 10−53.88 × 10−50.009
Purine metabolism6316.98 × 10−50.0001260.001
Total Cmpd: the total number of compounds in the pathway; Hits: the matched number from the uploaded data; Raw p: the statistical p-value, FDR: the false discovery rate applied to the nominal p-values to control for false-positive findings; Impact: the pathway impact value calculated from pathway topology analysis.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Słowiński, K.; Grygierzec, B.; Synowiec, A.; Tabor, S.; Araniti, F. Preliminary Study of Control and Biochemical Characteristics of Giant Hogweed (Heracleum sosnowskyi Manden.) Treated with Microwaves. Agronomy 2022, 12, 1335. https://doi.org/10.3390/agronomy12061335

AMA Style

Słowiński K, Grygierzec B, Synowiec A, Tabor S, Araniti F. Preliminary Study of Control and Biochemical Characteristics of Giant Hogweed (Heracleum sosnowskyi Manden.) Treated with Microwaves. Agronomy. 2022; 12(6):1335. https://doi.org/10.3390/agronomy12061335

Chicago/Turabian Style

Słowiński, Krzysztof, Beata Grygierzec, Agnieszka Synowiec, Sylwester Tabor, and Fabrizio Araniti. 2022. "Preliminary Study of Control and Biochemical Characteristics of Giant Hogweed (Heracleum sosnowskyi Manden.) Treated with Microwaves" Agronomy 12, no. 6: 1335. https://doi.org/10.3390/agronomy12061335

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop