Severe seasonal droughts driven by global climate change significantly alter the cycling of carbon and nutrients in forest ecosystems through disturbing plant physiology and phenology, soil physicochemical properties, and soil microbial activity. While, the investigation into the impacts of floor mass and plant roots on soil microbial biomass within the context of recurrent seasonal droughts is still rare. To investigate the environmental determinants governing soil microbial biomass with the escalating severity of seasonal droughts, we conducted a study on soil microbial biomass in a comprehensive block experiment, which was manipulated to explore the interplay between floor mass and plant roots contributions, crossed with a factorial irrigation treatment, in a montane subtropical moist evergreen broad–leaved forest of southwestern China. Within control and watered plots, we respectively established four experimental subplots with plant roots and floor mass included (R+F+), plant roots included but floor mass excluded (R+F−), plant roots excluded but floor mass included (R−F+), and plant roots and floor mass excluded (R−F−) from June 2019 to May 2023. The study results revealed that soil microbial biomass as well as soil moisture, floor mass, and plant roots showed an apparent single–hump modal within one year. In the comparative analysis of soil microbial biomass fluctuation amplitudes across control and watered plots, a discernible disparity was observed, indicating that significant differences in microbial biomass dynamics between the respective experimental conditions. The pooled data revealed a statistically significant influence of seasonal drought, floor mass, plant roots, and their reciprocal interactions on the soil microbial biomass, highlighting these factors as pivotal determinants of microbial community dynamics. This study elucidates the interactive regulatory mechanisms by which seasonal drought, floor mass, and plant roots collectively modulate soil microbial biomass within tropical and subtropical forests, offering insights into the complex ecological processes governing microbial community dynamics. This interactive regulation might influence the trajectory of plant species and soil microbial communities, facilitating their adaptive development and evolutionary responses.

Plant-associated yeasts can also be part of soils’ and pollinating-insects’ microbiomes, where they play significant ecological roles. Indeed, in previous studies, we have shown that yeasts may help pollinators find nectar, which is crucial for their nutrition and for the reproduction of many angiosperms, and, in the soil, can act as plant-growth promoters. Given the importance of yeasts for plant development, in this review, we first delve deep into the biochemical processes behind the ecological role of these microorganisms in soil, insects, and in direct association with plants. Based on this premise, we discuss the influence of this relationship on agricultural production and the possible effects of pesticide use on the yeast microbiota. Finally, we address the most relevant studies in the literature that support the potential of these microorganisms (either indigenous or genetically engineered) as bioremediation agents for soils and foods contaminated by pesticides. Our review indicates that yeasts can be satisfactorily employed in organic agriculture to increase plant growth or bioremediate contaminated soil or food.

This paper proposes an optimization method for the scheduling of a multi-energy virtual power plant supply-demand balance in the power market environment of Jiangxi Province. The objective of this method is to enhance the operational efficiency of the power grid, reduce energy costs, and facilitate economical and efficient energy distribution in the power market. The method comprehensively considers the characteristics and uncertainties of renewable energy sources such as solar and wind energy, and incorporates advanced multi-objective optimization algorithms. Additionally, real-time market price feedback is integrated to achieve accurate allocation of power supply and demand. Through a case study of a multi-energy virtual power plant in Jiangxi Province, this paper examines the optimal combination model for various energy sources within VPP, and analyzes the impact of different market environments on supply-demand balance. The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. Compared with traditional power supply models, it reduces average electricity costs by 15% and increases renewable energy utilization efficiency by 20%.

German chamomile (Matricaria chamomilla L.) is an essential oil-content medicinal plant widely used worldwidely. The aim of this study was (1) to gain knowledge of the phytochemical composition and the analgesic and soporific activity of M. chamomilla flowers extract and its amino acid preparations, (2) to predict the mechanisms of their effects by molecular docking, and (3) to develop aqueous printing gels and novel 3D-printed oral dosage forms for M. chamomilla flowers extracts. In total 22 phenolics and 14 amino acids were identified and quantified in the M. chamomilla extracts. The in-vivo animal studies with rodents showed that the oral administration of such extracts revealed the potential for treating of sleep disorders and diseases accompanied by pain. Amino acids were found to potentiate these effects. Glycine enhanced the analgesic activity the most, while lysine and β-alanine improved the soporific activity. The molecular docking analysis revealed a high probability of GABAA and NMDA receptor antagonism and COX-1,2 inhibition by the extracts. A polyethylene oxide (PEO) based gel composition with the M. chamomilla extracts were proposed for preparing a novel 3D-printed dosage form for the oral administration. These 3D-printed extract preparations can be used for example in dietary supplement applications.

This study presents PlanteSaine, a novel mobile application powered by Artificial Intelligence (AI) models explicitly designed for maize, tomato, and onion farmers in Burkina Faso. Agriculture in Burkina Faso, like many developing nations, faces substantial challenges from plant pests and diseases, posing threats to both food security and economic stability. PlanteSaine addresses these challenges by offering a comprehensive solution that provides farmers with real-time identification of pests and diseases. Farmers capture images of affected plants with their smartphones, and PlanteSaine's AI system analyzes these images to provide accurate diagnoses. The application's offline functionality ensures accessibility even in remote areas with limited internet connectivity, while its messaging feature facilitates communication with agricultural authorities for guidance and support. Additionally, PlanteSaine includes an emergency alert mechanism to notify farmers about pest and disease outbreaks, enhancing their preparedness to deal with these threats. An AI-driven framework, featuring an image feature extraction phase with EfficientNetB3 and an artificial neural network (ANN) classifier, was developed and integrated into PlanteSaine. The evaluation of PlanteSaine demonstrates its superior performance compared to baseline models, showcasing its effectiveness in accurately detecting diseases and pests across maize, tomato, and onion crops. Overall, this study highlights the potential of PlanteSaine to revolutionize agricultural technology in Burkina Faso and beyond. Leveraging AI and mobile computing, PlanteSaine provides farmers with accessible and reliable pest and disease management tools, ultimately contributing to sustainable farming practices and enhancing food security. The success of PlanteSaine underscores the importance of interdisciplinary approaches in addressing pressing challenges in global agriculture

In this study, the effects of food waste (FW) compost, vermicompost, and chemical fertilizers on the growth of organic red radish and soil quality are investigated to promote sustainable agriculture. Utilizing a comparative approach, it assesses the impacts of these fertilizers on various plant growth metrics and soil characteristics, highlighting the potential of converting FW into nutrient-rich amendments as a sustainable alternative to chemical fertilizers. The results indicate a significant variation in fresh weight among different treatments. For example, the FV 25% treatment demonstrated a relatively high mean fresh weight of 7.9664, while the CO 50% treatment yielded a much lower mean fresh weight of 0.2589. These numbers underscore the potential efficacy of specific FW treatments in enhancing plant growth, with VC 50% and FV 25% showing considerable promise in increasing crop yield. The study concludes that FW compost and vermicompost significantly enhance plant growth and soil quality, advocating for their use as sustainable and environmentally friendly alternatives to chemical fertilizers. The findings emphasize the importance of selecting appropriate fertilizer types and concentrations to optimize agricultural productivity and environmental sustainability, supporting the incorporation of FW into agricultural systems as a beneficial resource.

As renewable energy generation prediction systems have been introduced into the energy trading market, accurate prediction of solar photovoltaic (PV) energy generation has become a crucial challenge for ensuring stable trade of variable energy. Therefore, it is essential to quantitatively investigate and analyze current prediction technology and develop more advanced prediction systems. In this study, three models for predicting PV energy generation were investigated. Multiple regression, random forest, and gradient boosting machine (GBM) models were con-structed for 15 utility-scale power plants throughout South Korea. Model performance was evaluated in terms of root mean square error (RMSE) and mean absolute error (MAE). The multiple regression-based model had an RMSE of 12.00% and MAE of 9.06%. The random forest model had an RMSE of 11.69% and MAE of 8.61%. The GBM model had an RMSE of 11.34% and MAE of 8.18%, indicating its superior accuracy among the three models in predicting PV energy generation. These findings provide valuable insights that may contribute to the development of advanced PV energy generation models and their application in grid operations.

The introduction of any new disruptive technology in a traditionally well-established industry, such as the road construction industry, is usually associated with considerable resistance. This is especially relevant when the new technology is based on the use of granular materials traditionally considered to be of an unacceptable quality in combination with relatively new concepts such as New-age (Nano) Modified Emulsions (NME). In such cases, the fact that the material design methods are based on fundamental scientific principles and have been proven in laboratories and through Accelerated Pavement Testing (APT), may be of little influence. However, the general acceptance of new disruptive technologies, e.g. telecommunications and Information Technologies (IT), have been based on the considerable advantages it presented. The same principles are applicable to the general acceptance and use of NME stabilisation/enhancement of materials in the road construction industry. This article is aimed at the practical cost-effective demonstration of the general application of the use of nanos-silane modified emulsions in the construction of the highest order roads, i.e. inter-city multi-lane highways, lower order roads (including Low-Volume-Roads (LVR)) and even local accesses to farms and in villages/townships. The implementation of NME technologies is directly associated with ease of use, time and cost savings and the addressing and reduction of risks applicable to the use thereof.

The goods and services produced by forest and vegetation ecology system is the power by which human society can be promoted fast in high-quality and sustainable way. With the increase of population and economic development in water-limited regions, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services. To meet the demands of this situation, most of the original forest has changed into farmland, non-native forest and grass land. As a result, water-plant relationship changed from equilibrium to non-equilibrium, which led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the questions and realize the sustainable utilization of soil water resources and the high quality and sustainable development of social economy, it is necessary to apply the utilization limit theory of soil water resources by plants and the theory of soil water carrying capacity for vegetation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit of vegetation and serve high-quality and sustainable development.

Nowadays, the high demand for healthy foods and sustainable products, has led the food industry to explore innovative food technologies, such as fortification with bioactive compounds like antioxidants and polyphenols, that may be sourced from herbs or by-products. The aim of the present study was to explore the enrichment of refined olive oils with natural bioactive compounds such as the herbs rosemary (salvia rosmarinus), basil (ocimum basil), sage (salvia officinalis), lemon balm (melissa oficinallis), st. john’s wort (hypericum perforatum), pink savory (Thymbra satureja), dittany (origanum dictamnus), and by-products such as pomace from olives, olive leaves (olea europaea tree), orange peel (citrus sinensis), lemon peel (citrus limon), pomegranate peel (punica granatum) and mandarin peel (citrus reticulate). The fortification of the refined olive oils was performed with the use of different methodologies such as Conventional maceration (CM), Incubation shaking maceration (ISM), and Ultrasound assisted maceration (UAM). Their phenolic content and antioxidant capacity were measured with Folin–Ciocalteu assay and Ferric Reducing Antioxidant Power (FRAP) assay respectively. All methods demonstrated that different parameters such as time of maceration, temperature and sample concentration, play an important role in the fortification process of the refined olive oils. The predicyed bioavailability of the antioxidant and phenolic compounds in the fortified oils was determined with in vitro digestion and ranged from 4.84% to 53.11%. Furthermore, the refined olive oils fortified with pomace, basil, st. john's wort, and pomegranate peel presented the highest antioxidant and phenolic predicted bioavailability indices during the in vitro process compared to the control refined olive oil. Finally, fortification with natural herbs or by-products can be considered an innovative method for the improvement of the nutritional value of refined olive oils.

This study investigates the efficiency of a biogas-powered cooling system through the utilization of energy and exergy calculations. Biogas, which can be generated and stored in small-scale plants as needed, serves as a viable fuel source for absorption cooling systems. The present research focuses on the biogas consumption of a triple-effect absorption cooling system, specifically designed to supply a fixed cooling load of 100 kW under varying operational conditions. The study highlights the COP (Coefficient of Performance) and ECOP (Exergetic Coefficient of Performance) values of the system, along with the exergy destruction rates of its individual components, at the optimal temperatures of operation. Furthermore, to determine the necessary biogas consumption, the study explores the establishment of dedicated farms for various animal species, ensuring an adequate number of animals for biogas production. The findings reveal a COP of 1.78 and an ECOP of 35.4% at the optimized operating temperatures. The minimum mass flow rate of biogas is determined to be 0.0034 kg/s, facilitating the operation of the boiler with a methane content of 65%. The study concludes that a total of 290 head of cattle is required to generate the annual biogas consumption necessary for the cooling system. Also, number of the cattle is enough to establish 284 biogas plants in Bursa province in Türkiye.

Adaptive radiations occur mostly in response to environmental variation through the evolution of key eco-morphological innovations that allow emerging species to occupy new ecological niches. However, rapid phenotypic evolution and the evolution of key novelties are likely to also occur when a couple or few species are engaged into narrow ecological interactions. To demonstrate coevolution is a difficult task; only elusive evidences confirm that coevolution is a driver of speciation and diversification. Here we propose that the adaptive radiation of the Mediterranean orchid genus Ophrys, which gave rise to ca. 350 species since the apparition of the genus is due to the particular co-evolutionary dynamics between these plants and their pollinators. We suggest that the pollination by sexual swindle used by Ophrys orchids is the main driver of this coevolution. Flowers of each Ophrys species mimic sexually receptive females of one particular insect species, mainly bees. Male bees are attracted by pseudo-pheromones emitted by Ophrys flowers that are similar to the sexual pheromones of their females. Males lured by the flower shape, color and hairiness attempt to copulate with the flower, which glues pollen on their bodies. Pollen is eventually transferred to the stigma of another flower of the same Ophrys species during similar copulation attempts. Three observations led us to propose the scenario of an asymmetric co-evolutionary relationship between Ophrys and their pollinators. Firstly, there is a strong intra-specific competition among Ophrys individuals for the attraction of their species-specific pollinators, which is due to the high learning and memorization abilities of bees that record the pheromone signatures of kin or of previously courted partner to avoid (further) copulation attempts. Mnemonic pollinators induce thus a strong selective pressure for variation in the pseudo-pheromones emitted by individual flowers, which will potentially generate shifts in pollinator species, and hence Ophrys speciation. These pollinator shifts are adaptive for new Ophrys species because they may benefit from a competitor-free space. Secondly, such shifts in pollinator species are due to the random crossing of peaks in the olfactory landscape of the pollinator guild that is syntopic to each particular Ophrys population. This selective process on individual, random variation in pseudo-pheromone bouquets is followed by directional selection on flower phenotypes that will reinforce the attraction of the new pollinator. Thirdly, pollinators use the pseudo-pheromones emitted by Ophrys to locate suitable habitats from a distance within complex landscapes. Pollinators stay fixed for a while in these habitats by the local diversity of pseudo-pheromones, which increases their probability of encounter with a receptive female and hence the reproduction probability of both sexes. Conversely, pollinators disperse out of small suitable habitats once they have memorized the local diversity of sexual pseudo-pheromone bouquet or if fecundated Ophrys flowers repel pollinators, which decreases the probability of geitonogamy (plant advantage) but limit pollinator mating with locally emergent insect females, thus limiting inbreeding and favoring gene flow (pollinator advantage). Finally, we propose several research avenues that emerged according to this scenario of adaptive radiation by assymetric coevolution between Ophrys species and their pollinators.

Plants offer a simpler and cheaper alternative to mammalian animal models for the study of Endoplasmic Reticulum glycoprotein folding Quality Control (ERQC). In particular, the Arabidopsis thaliana (At) innate immune response to bacterial peptides provides an easy means of assaying ERQC function in vivo. A number of mutants that are useful to study ERQC in planta have been described in the literature, but only for a subset of these mutants the innate immune response to bacterial elicitors has been measured beyond monitoring plant weight and some physio-pathological parameters related to the plant immune response. In order to probe deeper into the role of ERQC in the plant immune response, we monitored expression levels of the PHI-1 and RET-OX genes in the At ER α-Glu II rsw3 and the At UGGT uggt1-1 mutant plants, in response to bacterial peptides elf18 and flg22. The elf18 response was impaired in the rsw3 but not completely abrogated in the uggt1-1 mutant plants, raising the possibility that the latter enzyme is partly dispensable for ERF signalling. In the rsw3 mutant, seedling growth was impaired only by concomitant application of the At ER α-Glu II NB-DNJ inhibitor at concentrations above 500 nM, suggesting residual activity in this mutant. The study highlights the need for extending plant innate immune response studies to assays sampling EFR signalling at the molecular level.

With the rise of long-read sequencers and long-range technologies, delivering high-quality plant genome assemblies is no longer reserved to large consortia. Indeed, sequencing techniques but also computer algorithms have reached a point where the reconstruction of assemblies at the chromosome-scale is now feasible at the laboratory scale. Current technologies, and especially long-range technologies, are numerous and selecting the most promising one for the genome of interest is crucial to obtain optimal results. In this study, we resequenced the genome of the yellow sarson, Brassica rapa cv. Z1, using the Oxford Nanopore PromethION sequencer and assembled the sequenced data using current assemblers. To reconstruct complete chromosomes, we used and compared three long-range techniques, optical mapping, Omni-C and Pore-C sequencing libraries commercialized by Bionano Genomics, Dovetail Genomics and Oxford Nanopore Technologies respectively, or a combination of the three, in order to evaluate the capability of each technology.

The import and export of tree seed carries with it risks of inadvertent introduction of pests and pathogens to hitherto unaffected regions. Although trade in seed of specified trees is regulated, phytosanitary requirements for most tree species are minimal, even those related to the most important forest tree species in a given region. A better understanding of the microbiome associated with seed intended for commercial production or ornamental use, and their potential risk with the transport from the source origin of distributors, will help regulatory agencies implement measures to prevent new and emerging risks. In this study we used high throughput sequencing to show that highly diverse fungal communities were associated with seed of 14 different Pinus species obtained from seed banks (seed orchards) and retail sources (online distributors) in North America and Europe. Fungal diversity differed among the 23 seedlots tested. Community composition did not relate to the species of Pinus nor the country of origin. Assigned potential functions based on sequence identity using FUNGuild provided an overall understanding of the likely life strategies associated fungal OTUs. Of those sequences classified to a trophic level, 453 were plant pathogens, with the Dothideomycetes having the highest prevalence. The most common plant pathogens detected included Sydowia polyspora, Lasiodiplodia theobromae, Diplodia intermedia and Diplodia sapinea. The evidence presented here illustrates an urgent need for plant protection authorities, practitioners and the general public to recognize the potential risk of introducing harmful pathogens through innocent transport of seed.

Rice blast, caused by Magnaporthe oryzae, poses significant threat to rice production. Rice blast susceptibility has been observed in Japanese rice varieties with excellent eating quality. Enhancing blast resistance is essential to ensure minimal use of agricultural chemicals. Two types of blast resistance are observed: true resistance, which is a type of qualitative resistance expressed by a major gene, and field resistance, which is a type of quantitative resistance expressed by multiple micro-acting genes. ‘Resistance collapse’, in which a variety with a true resistance gene becomes diseased by blast fungus races compatible with the resistance gene, has been observed. Varieties carrying blast-resistance genes, such as Pb1 (panicle blast resistance 1), have been developed through DNA marker-assisted selection. In this review, we focus on the Pb1, which expresses strong quantitative resistance to panicle blast and has been widely used in Japan without showing ‘resistance collapse’ for 40 years. Pb1 is an ‘adult plant resistance gene’ that does not exert strong selection pressure on the blast population during the leaf blast stage, thus preventing the selective multiplication of Pb1-compatible blast strains. This epidemiological mechanism prevents ‘resistance collapse’. Interdisciplinary research and breeding are required to sustainably use genes that induce high field resistance.

The increase in arrivals of new forest pests highlights the need for effective phytosanitary legislation and measures. This paper introduces legislation targeted at prevention and management of potential introductions of forest pests and pathogens. A summary is given on plant health regulations on a global and regional level with detailed information on the situation in the European Union (EU). The current and new European legislation is discussed and a particular focus is given on eradication and contingency plans for Fusarium circinatum.

In recent decades, both in Italy and internationally, the phenomenon of abandoned industrial buildings has grown considerably, causing inevitable social, urban and economic impacts. At the same time, the cultural debate has increased awareness of the problem and the strategic role that abandoned industrial sites can play in responding to new needs. This contribution analyzes the dismantling process of the Akragas Montedison factory in Porto Empedocle, Sicily, examining the evolution of disused industrial areas from the 20th century to the present day and the possibilities of reconversion for appropriate reuse.

Water plays a crucial role in maintaining plant functionality and drives many ecophysiological processes. The distribution of water resources is in a continuous change due to global warming affecting the productivity of ecosystems around the globe, but there is a lack of non-destructive methods capable of continuous monitoring of plant and leaf water content that would help us in understanding the consequences of the redistribution of water. We studied the utilization of novel small hyperspectral sensors in the 1350-2450 nm spectral range in non-destructive estimation of leaf water content in laboratory and field conditions. We found that the sensors captured up to 96% of the variation in equivalent water thickness (EWT, g/m²) and up to 90% of the variation in relative water content (RWC). These laboratory findings were supported by field measurements, where repeated leaf spectra measurements were in good agreement (R²=0.79) with a time-lagged change of tree xylem diameter. Further tests were done with an indoor plant (Dracaena marginate Lem.) by continuously measuring leaf spectra while drought conditions developed, which revealed detailed diurnal dynamics of leaf water content. We conclude that close-range hyperspectral spectroscopy can provide a novel tool for continuous measurement of leaf water content at the single leaf level and help us to better understand plant responses to varying environmental conditions.

A genome-wide association study (GWAS) was performed on a set of 260 lines which belong to three different bi-parental flax mapping populations. These lines were sequenced to an averaged genome coverage of 19× using the Illumina Hi-Seq platform. Phenotypic data for 11 seed yield and oil quality traits were collected in eight year/location environments. A total of 17,288 single nucleotide polymorphisms were identified, which explained more than 80% of the phenotypic variation for days to maturity (DTM), iodine value (IOD), palmitic (PAL), stearic, linoleic (LIO) and linolenic (LIN) acid contents. Twenty-three unique genomic regions associated with 33 QTL for the studied traits were detected, thereby validating four genomic regions previously identified. The 33 QTL explained 48-73% of the phenotypic variation for oil content, IOD, PAL, LIO and LIN but only 8-14% for plant height, DTM and seed yield. A genome-wide selective sweep scan for selection signatures detected 114 genomic regions that accounted for 7.82% of the flax pseudomolecule and overlapped with the 11 GWAS-detected genomic regions associated with 18 QTL for 11 traits. The results demonstrate the utility of GWAS combined with selection signatures for dissection of the genetic structure of traits and for pinpointing genomic regions for breeding improvement.

The different systems in the nuclear power plants (NPP) are critical and complex which requires a continuous rigorous monitoring for both normal and abnormal conditions. However, due to the nonlinearity of the dynamic behavior of these systems, implementation of artificial intelligence within the NPP components is crucial to enhance the monitoring and the predictability of the key operating parameters trend. On the other hand, lessons learned from large nuclear accident proves that a remote real-time coordination between the different stakeholders involved in the safety of the nuclear reactor is needed. This remote feature can be implemented in the existing power plants by embedding a mobile computing networks within the plant components. This network will send early warning and transmit the NPP data on real-time to different authorities such as the regulatory authority and the decision-making committees, to enhance the interpretability of the nuclear event and deliver a collaborative decision which in return mitigate the risk associated with these events and increase the overall safety of the plant. The integration of AI and mobile computing in NPP would be most of interest in countries where nuclear reactors data are challenged to reach during an accident. For instance, during the meltdown of Chernobyl, the Soviet government covered the accident from the news in an attempt to contain the consequences but there was a spread of radioactive contamination to some other Europe countries. Therefore, in the case of such scenario the implementation of mobile computing and AI would result in different outcomes as the European countries would be notified through the mobile networking and the spread of contamination would be forecasted by the AI algorithms. In this paper, we examine the different modern AI and mobile computing technologies, the different potential application, the associated features and challenges, and future work direction.

In plants, water flows are the major driving force behind the growth and play a crucial role in the life cycle. To study hydrodynamics, methods based on tracking small particles inside water flows occupy a special place. Due to these tools, it is possible to get information about the dynamics of the spatial distribution of the fluxes characteristics. In this paper, using contrast-enhanced MRI, we have shown that gadolinium chelate, used as an MRI contrast agent, marks the structural characteristics of xylem bundles of maize stem nodes and internodes. Supplementing MRI data, a high-precision visualization of xylem vessels by laser scanning microscopy was used to reveal structural and dimensional characteristics of the stem vascular system. In addition, we proposed the concept of using the prototype "Y-type xylem vascular bundles" as a model of the elementary connection of vessels within the vascular system. A Reynolds number can match the microchannel model with the real xylem vessels.

The bacterial wilt pathogen, first known as Bacillus solanacearum, has undergone numerous taxonomic changes since its first description in 1896. The history and significance of this pathogen is covered in this review with an emphasis on the advances in technology that were used to support each reclassification that finally led to the current separation of Ralstonia solanacearum into three genomic species. Frequent name changes occurred as methodology transitioned from phenotypic, biochemical, and molecular studies, to genomics and functional genomics. The diversity, wide host range and geographical distribution of R. solanacearum has resulted in its inclusion in a “species complex” as genomic analyses of elucidated phylogenetic relationships among strains. Current advances in phylogenetics and functional genomics now open new avenues for research into the epidemiology and control of the devastating bacterial wilt disease.

The awareness of the existence in plants of bioactive compounds namely phytochemicals (PHYs), having health properties is progressively expanding. Therefore, their massive introduction in the normal diet, in food supplements, and their use as natural therapeutics to treat several diseases are increasingly emphasized by several sectors. Particularly, most PHYs possessing antifungal, antiviral, anti-inflammatory, antibacterial, antiulcer, anti-cholesterol, hypoglycemic, immunomodulatory, and antioxidant properties have been isolated from plants. Additionally, their secondary modification with new functionalities, to further improve their intrinsic beneficial effects, is extensively investigated. Unfortunately, although the idea of exploiting PHYs as therapeutics is amazing, its realization is far from simple, and the possibility of exploiting them as effective orally administrable drugs is almost utopic. Most PHYs are insoluble in water and, when introduced orally, they scarcely reach the site of action in therapeutic concentrations. Degradation by enzymatic and microbial digestion, occurring in the mouth, stomach, and intestine, as well as fast metabolism and rapid excretion via the kidney, biliary, or lung, strongly limit their in vivo activity. To overcome these drawbacks, several nanotechnological approaches have been used and many PHYs-loaded delivery systems with dimensions of nanometers have been developed. This paper, also by reporting various recent case studies, reviews the foremost nano-suspension and nano-emulsion-based techniques developed for formulating the most relevant PHYs in more bioavailable nanoparticles (NPs), suitable or promising for clinical application. Also, the acute and chronic toxic effects due to the exposure to NPs reported so far, the possible nanotoxicity which could derive by their massive employment, as well as the ongoing actions to improve the knowledge in the field were discussed. The state of the art concerning the actual clinical application of both PHYs and the nanotechnologically engineered PHYs was also reviewed.

Cowpea chlorotic mottle virus (CCMV) is a plant virus explored as a nanotechnological platform. The robust self-assembly mechanism of its capsid protein allows for drug encapsulation and targeted delivery. Additionally, the capsid nanoparticle can be used as a programmable platform to display different molecular moieties. In view of future applications, efficient production and purification of plant viruses is a key step. In established protocols, the need for ultracentrifugation is a significant limitation due to cost, difficult scalability, and safety issues. In addition, the purity of the final virus isolate often remains unclear. Here, an advanced protocol for the purification of CCMV from infected plant tissue was developed, focusing on efficiency, economy, and final purity. The protocol involves precipitation with PEG 8000, followed by an affinity extraction using a novel peptide aptamer. The efficiency of the protocol was validated using size exclusion chromatography, MALDI-TOF mass spectrometry, reversed-phase HPLC, and sandwich immunoassay. It was demonstrated that the final eluate of the affinity column is of exceptional purity (98.4%) determined by HPLC and detection at 220 nm. The scale-up of our proposed method seems to be straightforward, which opens the way to the large-scale production of such nanomaterials. This highly improved protocol may facilitate the use and implementation of plant viruses as nanotechnological platforms for in vitro and in vivo applications.

Verticillium wilt is a soil borne disease caused by distinct vegetative compatibility groups (VCG) of the fungus Verticillium dahliae. Two V. dahliae isolates were recovered from symptomatic cot-ton plants in Australian cotton fields and were assigned to two distinct vegetative compatibility groups (VCGs). One corresponding to the defoliating (VCG 1A) and the other non-defoliating (VCG 2A) pathotypes of Verticillium, have been transformed with Red and Green Fluorescent protein genes, respectively. The transformants maintained their ability to infect cotton and both strains were observed to colonise the xylem vessels of cotton plants. Moreover, we observed that the cotton V. dahliae strains could also infect some sampled non-Gossypium species found in the Australian landscape. The fluorescently labelled strains of V. dahliae will allow us to gain a thorough understanding of the infection processes of this important pathogen.

The antimicrobial properties of the new strains of microorganisms isolated from natural sources of various ecological niches in the Moscow Region and the Republic of Tatarstan were studied. An antifungal activity of isolates was established in a test culture of toxin-producing microscopic fungi that cause various plant diseases: Fusarium oxysporum, Aspergillus flavus, Penicillium spp. and Candida albicans. Of the 46 studied microorganisms, 4 isolates (Bacillus subtilis, Propionibacterium freudenreichii, Lactobacillus plantarum and Streptomyces spp.) showed an ability to produce biologically active metabolites with a pronounced antimicrobial potential. This is promising in the growth and protection of the Scots pine, pedunculate oak and small-leaved linden forest crops from diseases caused by fungi Lophodermium pinastri Chev. and Microsphaera alphitoides stimulation. Based on selected isolates, a Bacterial product LRV composition has been developed. A Scots pine, pedunculate oak and small-leaved linden seedlings single and double foliar treatment with Bacterial product LRV at a concentration of 10 ml/l led to an increase in the growth of an above-ground part by 31.8, 51.9 and 25.4 %, respectively, and an underground part – by 25.0, 37.2 and 25.7 %, respectively, compared with the control. The weight of seedling at the end of the study exceeded the control variant by an average of 26.0, 44.0 and 78.0 %, respectively. A use of a plant protection Bacterial product LRV did not have a significant effect on a powdery mildew and Schütte disease damage to forest crops. A Biogeosystem Technique methodology has been developed to improve a long-term forest growing.

One of the earliest hallmarks of plant immune response is production of reactive oxygen spe-cies (ROS) in different subcellular compartments, which regulate plant immunity. A suitable equilibrium, which is crucial to prevent ROS over-accumulation leading to oxidative stress, is maintained by salicylic acid (SA), a chief regulator of ROS. However, ROS are not only acting downstream of SA signaling, but were also proposed to be a central component of a self-amplifying loop that regulates SA signaling as well as the interaction balance between dif-ferent phytohormones. The exact role of this crosstalk, the position where SA interferes with ROS signaling and ROS interferes with SA signaling and the outcome of this regulation depend on the origin of ROS but also on the pathosystem. The precise spatiotemporal regulation of or-ganelle specific ROS and SA levels determine the effectiveness of pathogen arrest and is there-fore crucial for a successful immune response. However, the regulatory interplay behind still remain poorly understood, as up till now, the role of organelle specific ROS and SA in HR-conferred resistance has mostly been studied by altering the level of a single component. In order to address these aspects, a sophisticated combination of research methods for monitoring the spatiotemporal dynamics of key players and transcriptional activity in plants is needed, and will most probably consist of biosensors and precision transcriptomics.

Species distribution models (SDMs) are usually used to predict current species’ geographic distributions and to forecast the impact of climate change, with different aims, such as conservation, and biodiversity management. SDMs use has been increasing in the last decades, however, they are vulnerable to parametrization and data quality input. Thus, inappropriate input can lead to potential unreliability in results. In this context, the most used data and methodologies in SDM, and putative deviations from the consensual best practices, were identified, by analysing recent literature (2018 to 2022). Results show that the parameters presented more consistently are the chosen algorithm (MaxEnt was used in 98% of the studies), the accuracy measures, and the time windows. Many papers fail to specify other parameters, limiting the reproducibility of the studies. Some papers also fail to provide information about the target species: only a fraction of the species' range is considered, or no justification for including specific variables in the model is provided. These options can decrease reliability in predictions under future scenarios since data provided to the model is inaccurate from the start or there is insufficient information for outputs discussion.

According to Swiss-American Doctor of Sciences and Agricultural Engineer Jean-Pierre Jost, "plants communicate with each other by the quality of light emitted by their leaves or by means of stress hormones and other volatile chemicals. They also make use of cocktails of chemicals, pheromones, shape and colors to attract pollinators whereas other signals repel unwanted organisms. Insects are able to decode such messages and respond accordingly. Plants are apparently also communicating by sounds and electric signals." (1) How do plants do these things? Of course, it's easy to imagine it's all purely mechanical. But at the risk of sounding like a mysticism fanatic, I wonder if plants' activities are part of a spectrum of consciousness that pervades the entire universe. This spectrum would result from everything in the universe having the BITS or BInary digiTS of electronics as their ultimate composition. As explained in this hypothesis, something I call vector-tensor-scalar geometry is essential to my hypothesis. VTS geometry produces the particles of chemicals and pheromones, and refers to communication via electric signals when it speaks of electromagnetic-gravitational interaction. There's another consequence if everything in the universe is ultimately composed of electronic BITS and the cosmos is a spectrum of consciousness/artificial intelligence. It's impossible for an absence of consciousness to exist, either after death or before conception.