Hasil untuk "Plant ecology"

Trevor Padgett, Huei‐Jiun Su, Shu‐Hui Wu et al.

ABSTRACT Parasitic plants are a diverse and unique polyphyletic assemblage of flowering plants that survive by obtaining resources via direct vascular connections to a host plant. Ecologically important in their native ecosystems, these typically cryptic plants remain understudied and fundamental knowledge of the biology, ecology, and evolution of most species is lacking. This gap limits our understanding of ecosystems and conservation management. We established a multistep protocol to conduct the first investigation of the reproductive life history of root parasite genus Balanophora, testing the hypotheses of perenniality, cryptic perenniality, and plasticity across five geographically isolated populations in Taiwan. A review of 123 Balanophora publications found contradictory determinations, including no determination (87%), perennial (9%), annual (1%), biennial (1%), or a combination (2%). No primary study investigated the question, and no determination was accompanied by reference. Between 2021 and 2024, we tested a hypothesis of perenniality (109 individuals, 135 patches) and cryptic perenniality (73 host samples), monitored population dynamics (whole population), and potential for endophytic/dormant haustorial tissue (101 roots) across five isolated populations of Balanophora fungosa ssp. fungosa in Taiwan. Our results support semelparous annuality. After reproduction, individuals senesce and die, and the following year's population is recruited from newly germinated individuals which together develop in size and number during a vegetative growth period, undergo reproduction, and then themselves senesce and die. Each cycle is completed within a 12‐month period. Synthesis: Our study provides the first quantitative determination of a semelparous annual reproductive life‐history strategy for any species of Balanophora. This determination is important in our progress toward better understanding the species—and parasitic plants in general—as well as ecological roles within ecosystems and conservation management. Our study further provides a template for future work to expand life‐history strategy determination across cryptic root parasitic plants.

Yuxiang Li, Siyue Zhang, Di Liu et al.

Abstract Changing climate and changes in cropping systems have greatly affected outbreaks of plant diseases. Wheat stripe rust is a disease posing a threat to global wheat production, caused by Puccinia striiformis f. sp. tritici (Pst). Pst oversummering regions play a crucial role in the emergence of new races in China. To unveil the migration pattern of oversummering to adjacent regions, we develop a set of KASP-SNP marker from 28 Pst whole-genome sequences to investigate the population structure in the oversummering and its adjacent regions. A set of 19 Chinese wheat differentials is used to characterize the virulence patterns of 308 sampled Pst isolates. By integrating virulence characterization, population genetic analysis, air trajectory simulation and field disease monitoring, two main Pst dispersal routes are identified. Inocula from Eastern Qinghai are dispersed to Western and Eastern Liupan Mountain, and reach Guanzhong Plain. The second route originates from Middle Gansu, then through Longnan, and reaches the Guanzhong Plain via Eastern Liupan Mountain. Both dispersal routes result in Pst inoculum spreading to the Huang-Huai-Hai region, the main wheat-growing region in China. The proposed migration routes can be used to develop disease management strategies at a regional and national scale.

Hengyue Zhao

This paper asks whether our relationship with nature can move from human dominance to genuine interdependence, and whether artificial intelligence (AI) can mediate that shift. We examine a new ecological-design paradigm in which AI interacts with non-human life forms. Through case studies we show how artists and designers apply AI for data analysis, image recognition, and ecological restoration, producing results that differ from conventional media. We argue that AI not only expands creative methods but also reframes the theory and practice of ecological design. Building on the author's prototype for AI-assisted water remediation, the study proposes design pathways that couple reinforcement learning with plant-based phytoremediation. The findings highlight AI's potential to link scientific insight, artistic practice, and environmental stewardship, offering a roadmap for future research on sustainable, technology-enabled ecosystems.

David Peede, Trevor Cousins, Arun Durvasula et al.

Genomes contain the mutational footprint of an organism's evolutionary history, shaped by diverse forces including ecological factors, selective pressures, and life history traits. The sequentially Markovian coalescent (SMC) is a versatile and tractable model for the genetic genealogy of a sample of genomes, which captures this shared history. Methods that utilize the SMC, such as PSMC and MSMC, have been widely used in evolution and ecology to infer demographic histories. However, these methods ignore common biological features, such as gene flow events and structural variation. Recently, there have been several advancements that widen the applicability of SMC-based methods: inclusion of an isolation with migration model, integration with the multi-species coalescent, incorporation of ecological variables (such as selfing and dormancy), inference of dispersal rates, and many computational advances in applying these models to data. We give an overview of the SMC model and its various recent extensions, discuss examples of biological discoveries through SMC-based inference, and comment on the assumptions, benefits and drawbacks of various methods.

Jiakai Lin, Jinchang Zhang, Ge Jin et al.

Plant roots typically exhibit a highly complex and dense architecture, incorporating numerous slender lateral roots and branches, which significantly hinders the precise capture and modeling of the entire root system. Additionally, roots often lack sufficient texture and color information, making it difficult to identify and track root traits using visual methods. Previous research on roots has been largely confined to 2D studies; however, exploring the 3D architecture of roots is crucial in botany. Since roots grow in real 3D space, 3D phenotypic information is more critical for studying genetic traits and their impact on root development. We have introduced a 3D root skeleton extraction method that efficiently derives the 3D architecture of plant roots from a few images. This method includes the detection and matching of lateral roots, triangulation to extract the skeletal structure of lateral roots, and the integration of lateral and primary roots. We developed a highly complex root dataset and tested our method on it. The extracted 3D root skeletons showed considerable similarity to the ground truth, validating the effectiveness of the model. This method can play a significant role in automated breeding robots. Through precise 3D root structure analysis, breeding robots can better identify plant phenotypic traits, especially root structure and growth patterns, helping practitioners select seeds with superior root systems. This automated approach not only improves breeding efficiency but also reduces manual intervention, making the breeding process more intelligent and efficient, thus advancing modern agriculture.

Ahmed S. Alahmed, Audun Botterud, Saurabh Amin et al.

We develop a mathematical framework to jointly schedule water and electricity in a profit-maximizing renewable colocated water desalination plant that integrates both thermal and membrane based technologies. The price-taking desalination plant sells desalinated water to a water utility at a given price and engages in bidirectional electricity transactions with the grid, purchasing or selling power based on its net electricity demand. We show that the optimal scheduling policy depends on the plant's internal renewable generation and follows a simple threshold structure. Under the optimal policy, thermal based water output decreases monotonically with renewable output, while membrane based water output increases monotonically. We characterize the structure and intuition behind the threshold policy and examine key special properties.

Tsitsi Sithandiwe Maponga, Hilton Garikai Taambuka Ndagurwa, Justice Muvengwi et al.

By increasing resource heterogeneity, mistletoe-infected trees can restructure plant community processes and distribution patterns. No information is available on how mistletoe-infected Vachellia (Acacia) karroo trees within V. karroo dominated stands are spatially distributed, and on how they influence the spatial patterns of their surrounding conspecifics and heterospecifics. Each woody plant was stem mapped using a cartesian plane (x, y) within three 50×50 m plots located in V. karroo dominated stands in a semi-arid savanna, South West Zimbabwe. Pair correlations g(r) were used for the univariate analysis and Poisson process null models were applied to quantify and detect overall departure from randomness. For the bivariate analysis, pair correlations g12(r) under the null model of independence were used, whilst the mark correlation function (kmm(r)) was used to analyse the correlation of tree canopy area and mistletoe infection intensity. For each plot, size class distributions, based on tree height and basal stem diameter displayed negative J curves, with steep negative regression slopes across the size classes, clearly indicating a strongly recruiting population of V. karroo. The univariate patterns of all trees (infected and non-infected) were consistent with a random pattern, which is attributed to unsystematic mistletoe seed dispersal by birds. The univariate analysis of all woody plants (adults and juveniles) exhibited aggregation at small spatial scales due to the high abundance of clustered seedlings and saplings. At small spatial scales, understory woody plants (both conspecifics and non-conspecifics) were positively associated with mistletoe-infected trees due to mistletoephily which is the facilitation (or nurse protégé interactions) within the more resource-rich mistletoe-infected tree subcanopies. These results provide strong evidence suggesting that the variations in spatial pattern modification by mistletoe-infected trees could further increase spatial heterogeneity in this semi-arid savanna. As such, by increasing heterogeneity, mistletoe-infected trees can increase the resilience of semi-arid savannas in the face of perturbations and stochastic events.

Ning Yan, Weichi Wang, Tong Mi et al.

Soil salinization is a critical issue that not only hampers the efficiency and sustainability of global agricultural production but also poses significant challenges to the achievement of sustainable development goals across environmental, economic, and social dimensions. Halotolerant plant growth-promoting rhizobacteria (HPGPR) have the potential to mitigate abiotic stress, foster plant growth, and bolster the stress resistance capabilities of crops. This study conducted the isolation, identification, and characterization of HPGPR originating from a saline-alkali orchard area in northwest China. The efficacy of the isolated bacterial strains was evaluated through potted plant experiments, assessing the growth of tomato plants under in vitro conditions and under varying salinity stress. Ultimately, the study investigated the influence of these HPGPR on soil physicochemical properties, enzymatic activities, and the structure and composition of the microbial community. Upon isolating 12 bacterial strains, we conducted an in vitro assessment of their salt tolerance, ultimately singling out three robust isolates, which exhibited exceptional salt tolerance. Detailed 16S rRNA gene sequencing and meticulous taxonomic evaluation systematically assigned these isolates to Priestia endophyticus GSCK1 (accession number: OR569048), Bacillus atrophaeus GSCK2 (accession number: OR569061), and Serratia fonticola GSCK6 (accession number: OR569062), respectively. These strains exhibited notable biochemical and plant growth-promoting traits, including enzymatic activities and the production of indole-3-acetic acid. They significantly enhanced plant growth metrics and soil fertilities, particularly strain GSCK6, which also reshaped the soil microbial community, augmenting beneficial microbe abundance. The HPGPR treatment notably improved soil pH, nutrient availability, enzymatic activities, and reduced soil electrical conductivity, underscoring their potential in agricultural resilience against salinity. The eco-friendly salt stress mitigation strategy of HPGPR not only enhances soil quality and promotes plant growth by regulating the composition and function of microbial communities, but also provides a novel solution for global agricultural production. This approach is conducive to increasing crop yield and quality, reducing the limitations of saline-alkali land on agricultural production, and promoting food security and sustainable agricultural development.

Mohammed-Younes Gueddari, Walid Hachem, Jamal Najim

Approximate Message Passing (AMP) algorithmshave recently gathered significant attention across disciplines such as statistical physics, machine learning, and communication systems. This study aims to extend AMP algorithms to non-symmetric (elliptic) matrices, motivated by analyzing equilibrium properties in ecological systems featuring elliptic interaction matrices.In this article, we provide the general form of an AMP algorithm associated to a random elliptic matrix, the main change lying in a modification of the corrective (Onsager) term. In order to establish the statistical properties of this algorithm, we use and prove a generalized form of Bolthausen conditioning argument, pivotal to proceed by a Gaussian-based induction.We finally address the initial motivating question from theoretical ecology. Large foodwebs are often described by Lotka-Volterra systems of coupled differential equations, where the interaction matrix is elliptic random. In this context, we design an AMP algorithm to analyze the statistical properties of the equilibrium point in a high-dimensional regime. We rigorously recover the results established by [Bunin, 2017] and [Galla,2018] who used techniques from theoretical physics, and extend them with the help of propagation of chaos type arguments.

Jie Sun, Xiaoqian Zhang, Chun Fu et al.

Background Gibberellins (GAs) play important roles in regulating peanut growth and development. GA20ox and GA3ox are key enzymes involved in GA biosynthesis. These enzymes encoded by a multigene family belong to the 2OG-Fe (II) oxygenase superfamily. To date, no genome-wide comparative analysis of peanut AhGA20ox and AhGA3ox-encoding genes has been performed, and the roles of these genes in peanut pod development are not clear. Methods A whole-genome analysis of AhGA20ox and AhGA3ox gene families in peanut was carried out using bioinformatic tools. The expression of these genes at different stage of pod development was analyzed using qRT-PCR. Results In this study, a total of 15 AhGA20ox and five AhGA3ox genes were identified in peanut genome, which were distributed on 14 chromosomes. Phylogenetic analysis divided the GA20oxs and GA3oxs into three groups, but AhGA20oxs and AhGA3oxs in two groups. The conserved pattern of gene structure, cis-elements, and protein motifs further confirmed their evolutionary relationship in peanut. AhGA20ox and AhGA3ox genes were differential expressed at different stages of pod development. The strong expression of AhGA20ox1/AhGA20ox4, AhGA20ox12/AhGA20ox15, AhGA3ox1 and AhGA3ox4/AhGA3ox5 in S1-stage indicated that these genes could have a key role in controlling peg elongation. Furthermore, AhGA20ox and AhGA3ox also showed diverse expression patterns in different peanut tissues including leaves, main stems, flowers and inflorescences. Noticeably, AhGA20ox9/AhGA20ox11 and AhGA3o4/AhGA3ox5 were highly expressed in the main stem, whereas the AhGA3ox1 and AhGA20ox10 were strongly expressed in the inflorescence. The expression levels of AhGA20ox2/AhGA20ox3, AhGA20ox5/AhGA20ox6, AhGA20ox7/AhGA20ox8, AhGA20ox13/AhGA20ox14 and AhGA3ox2/AhGA3ox3 were high in the flowers, suggesting their involvement in flower development. These results provide a basis for deciphering the roles of AhGA20ox and AhGA3ox in peanut growth and development, especially in pod development.

Yingjie Miao, Gaowei Hu, Xiaolong Sun et al.

To evaluate the flavor characteristics of Chinese bayberry alcoholic beverages, fermented bayberry wine (FBW) and integrated bayberry wine (IBW) were investigated for their volatile and soluble profiles using HS-SPME GC–MS and UHPLC Q-TOF and were analyzed with multidimensional statistical analysis, including PCA and OPLS-DA. The volatile compounds 1-pentanol, β-caryophyllene and isopentanol were only detected in IBW. β-caryophyllene, the key flavor component of bayberry, was found to be the most abundant volatile compound in IBW (25.89%) and was 3.73 times more abundant in IBW than in FBW. The levels of ethyl octanoate, ethyl nonanoate, and ethyl decanoate were also several times higher in IBW than in FBW. These compounds contributed to the strong bayberry aroma and better fruity flavor of IBW. On the other hand, high levels of ethyl acetate and octanoic acid in FBW, representing pineapple/overripe or sweat odor, were key contributors to the fermented flavor of FBW. Soluble sugars, such as sucrose, D-glucose, and D-tagatose, as well as amino acids, such as L-glutamate and L-aspartate, had much higher levels in IBW. The anthocyanin pigment cyanidin 3-glucoside, which generates red color, was also higher in IBW. On the other hand, most of the differentially expressed alcohols, acids, amino acids, purines/pyrimidines and esters were present in higher concentrations in FBW compared to IBW. This demonstrated that IBW has a much sweeter and more savory taste as well as a better color generated by more anthocyanins, while FBW presents a more acidic and drier taste as well as a complex formation of alcohols and esters. The study also prompts the need for further research on the flavor profiles of IBW and its potential application and market value.

Tamara Pečenková, Martin Potocký

Small secreted proteins play an important role in plant development, as well as in reactions to changes in the environment. In Arabidopsis thaliana, they are predominantly members of highly expanded families, such as the pathogenesis-related (PR) 1-like protein family, whose most studied member PR1 is involved in plant defense responses by a so far unknown mechanism, or Clavata3/Endosperm Surrounding Region (CLE) protein family, whose members’ functions in the development are well described. Our survey of the existing literature for the two families showed a lack of details on their localization, trafficking, and exocytosis. Therefore, in order to uncover the modes of their secretion, we tested the hypothesis that a direct link between the secreted cargoes and the secretion regulators such as Rab GTPases, SNAREs, and exocyst subunits could be established using in silico co-expression and clustering approaches. We employed several independent techniques to uncover that only weak co-expression links could be found for limited numbers of secreted cargoes and regulators. We propose that there might be particular spatio-temporal requirements for PR1 and CLE proteins to be synthesized and secreted, and efforts to experimentally cover these discrepancies should be invested along with functional studies.

Kincső Decsi, Barbara Kutasy, Géza Hegedűs et al.

Recently, climate change has had an increasing impact on the world. Innate defense mechanisms operating in plants - such as PAMP-triggered Immunity (PTI) - help to reduce the adverse effects caused by various abiotic and biotic stressors. In this study, the effects of ELICE16INDURES® plant conditioner for organic farming, developed by the Research Institute for Medicinal Plants and Herbs Ltd. Budakalász Hungary, were studied in a soybean population in Northern Hungary. The active compounds and ingredients of this product were selected in such a way as to facilitate the triggering of general plant immunity without the presence and harmful effects of pathogens, thereby strengthening the healthy plant population and preparing it for possible stress effects. In practice, treatments of this agent were applied at two different time points and two concentrations. The conditioning effect was well demonstrated by using agro-drone and ENDVI determination in the soybean field. The genetic background of healthier plants was investigated by NGS sequencing, and by the expression levels of genes encoding enzymes involved in the catalysis of metabolic pathways regulating PTI. The genome-wide transcriptional profiling resulted in 13 contigs related to PAMP-triggered immunity and activated as a result of the treatments. Further analyses showed 16 additional PTI-related contigs whose gene expression changed positively as a result of the treatments. The gene expression values of genes encoded in these contigs were determined by in silico mRNA quantification and validated by RT-qPCR. Both - relatively low and high treatments - showed an increase in gene expression of key genes involving AOC, IFS, MAPK4, MEKK, and GST. Transcriptomic results indicated that the biosyntheses of jasmonic acid (JA), salicylic acid (SA), phenylpropanoid, flavonoid, phytoalexin, and cellular detoxification processes were triggered in the appropriate molecular steps and suggested that plant immune reactions may be activated also artificially, and innate immunity can be enhanced with proper plant biostimulants.

Thomas Schmitt, Jens Engel, Martin Kopp et al.

The replacement of fossil fuels in combination with an increasing share of renewable energy sources leads to an increased focus on decentralized microgrids. One option is the local production of green hydrogen in combination with fuel cell vehicles (FCVs). In this paper, we develop a control strategy based on Model Predictive Control (MPC) for an energy management system (EMS) of a hydrogen plant, which is currently under installation in Offenbach, Germany. The plant includes an electrolyzer, a compressor, a low pressure storage tank, and six medium pressure storage tanks with complex heuristic physical coupling during the filling and extraction of hydrogen. Since these heuristics are too complex to be incorporated into the optimal control problem (OCP) explicitly, we propose a novel approach to do so implicitly. First, the MPC is executed without considering them. Then, the so-called allocator uses a heuristic model (of arbitrary complexity) to verify whether the MPC's plan is valid. If not, it introduces additional constraints to the MPC's OCP to implicitly respect the tanks' pressure levels. The MPC is executed again and the new plan is applied to the plant. Simulation results with real-world measurement data of the facility's energy management and realistic fueling scenarios show its advantages over rule-based control.

Muhammad Salman Ikrar Musyaffa, Novanto Yudistira, Muhammad Arif Rahman et al.

The rich diversity of herbal plants in Indonesia holds immense potential as alternative resources for traditional healing and ethnobotanical practices. However, the dwindling recognition of herbal plants due to modernization poses a significant challenge in preserving this valuable heritage. The accurate identification of these plants is crucial for the continuity of traditional practices and the utilization of their nutritional benefits. Nevertheless, the manual identification of herbal plants remains a time-consuming task, demanding expert knowledge and meticulous examination of plant characteristics. In response, the application of computer vision emerges as a promising solution to facilitate the efficient identification of herbal plants. This research addresses the task of classifying Indonesian herbal plants through the implementation of transfer learning of Convolutional Neural Networks (CNN). To support our study, we curated an extensive dataset of herbal plant images from Indonesia with careful manual selection. Subsequently, we conducted rigorous data preprocessing, and classification utilizing transfer learning methodologies with five distinct models: ResNet, DenseNet, VGG, ConvNeXt, and Swin Transformer. Our comprehensive analysis revealed that ConvNeXt achieved the highest accuracy, standing at an impressive 92.5%. Additionally, we conducted testing using a scratch model, resulting in an accuracy of 53.9%. The experimental setup featured essential hyperparameters, including the ExponentialLR scheduler with a gamma value of 0.9, a learning rate of 0.001, the Cross-Entropy Loss function, the Adam optimizer, and a training epoch count of 50. This study's outcomes offer valuable insights and practical implications for the automated identification of Indonesian medicinal plants.

Yiqing Guo, Karel Mokany, Cindy Ong et al.

The diversity of terrestrial vascular plants plays a key role in maintaining the stability and productivity of ecosystems. Airborne hyperspectral imaging has shown promise for measuring plant diversity remotely, but to operationalise these efforts over large regions we need to advance satellite-based alternatives. The advanced spectral and spatial specification of the recently launched DESIS (the DLR Earth Sensing Imaging Spectrometer) instrument provides a unique opportunity to test the potential for monitoring plant species diversity with spaceborne hyperspectral data. This study provides a quantitative assessment on the ability of DESIS hyperspectral data for predicting plant species richness in two different habitat types in southeast Australia. Spectral features were first extracted from the DESIS spectra, then regressed against on-ground estimates of plant species richness, with a two-fold cross validation scheme to assess the predictive performance. We tested and compared the effectiveness of Principal Component Analysis (PCA), Canonical Correlation Analysis (CCA), and Partial Least Squares analysis (PLS) for feature extraction, and Kernel Ridge Regression (KRR), Gaussian Process Regression (GPR), and Random Forest Regression (RFR) for species richness prediction. The best prediction results were $r=0.76$ and $\text{RMSE}=5.89$ for the Southern Tablelands region, and $r=0.68$ and $\text{RMSE}=5.95$ for the Snowy Mountains region. Relative importance analysis for the DESIS spectral bands showed that the red-edge, red, and blue spectral regions were more important for predicting plant species richness than the green bands and the near-infrared bands beyond red-edge. We also found that the DESIS hyperspectral data performed better than Sentinel-2 multispectral data in the prediction of plant species richness.

Milan Koumans, Daan Meulendijks, Haiko Middeljans et al.

Signal processing techniques are of vital importance to bring THz spectroscopy to a maturity level to reach practical applications. In this work, we illustrate the use of machine learning techniques for THz time-domain spectroscopy assisted by domain knowledge based on light-matter interactions. We aim at the potential agriculture application to determine the amount of free water on plant leaves, so-called leaf wetness. This quantity is important for understanding and predicting plant diseases that need leaf wetness for disease development. The overall transmission of a moist plant leaf for 12,000 distinct water patterns was experimentally acquired using THz time-domain spectroscopy. We report on key insights of applying decision trees and convolutional neural networks to the data using physics-motivated choices. Eventually, we discuss the generalizability of these models to determine leaf wetness after testing them on cases with increasing deviations from the training set.

Yuan Fang, Kim Stanford, Xianqin Yang

ABSTRACT To explore the effect of beef processing on Escherichia coli populations in relation to lactic acid resistance, this study investigated the links among acid response, phylogenetic structure, genome diversity, and genotypes associated with acid resistance of meat plant E. coli. Generic E. coli isolates (n = 700) were from carcasses, fabrication equipment, and beef products. Acid treatment was carried out in Luria-Bertani broth containing 5.5% lactic acid (pH 2.9). Log reductions of E. coli ranged from <0.5 to >5 log CFU/mL (median: 1.37 log). No difference in lactic acid resistance was observed between E. coli populations recovered before and after a processing step or antimicrobial interventions. E. coli from the preintervention carcasses were slightly more resistant than E. coli isolated from equipment, differing by <0.5 log unit. Acid-resistant E. coli (log reduction <1, n = 45) had a higher prevalence of genes related to energy metabolism (ydj, xap, ato) and oxidative stress (fec, ymjC) than the less resistant E. coli (log reduction >1, n = 133). The ydj and ato operons were abundant in E. coli from preintervention carcasses. In contrast, fec genes were abundant in E. coli from equipment surfaces. The preintervention E. coli contained phylogroups A and B1 in relatively equal proportions. Phylogroup B1 predominated (95%) in the population from equipment. Of note, E. coli collected after sanitation shared either the antigens of O8 or H21. Additionally, genome diversity decreased after chilling and equipment sanitation. Overall, beef processing did not select for E. coli resistant to lactic acid but shaped the population structure. IMPORTANCE Antimicrobial interventions have significantly reduced the microbial loads on carcasses/meat products; however, the wide use of chemical and physical biocides has raised concerns over their potential for selecting resistant populations in the beef processing environment. Phenotyping of acid resistance and whole-genome analysis described in this study demonstrated beef processing practices led to differences in acid resistance, genotype, and population structure between carcass- and equipment-associated E. coli but did not select for the acid-resistant population. Results indicate that genes coding for the metabolism of long-chain sugar acids (ydj) and short-chain fatty acids (ato) were more prevalent in carcass-associated than equipment-associated E. coli. These results suggest E. coli from carcasses and equipment surfaces have been exposed to different selective pressures. The findings improve our understanding of the microbial ecology of E. coli in food processing environments and in general.

Raúl Marín-Aragón, Leandro Sampaio, Laura Guerrero-Meseguer et al.

Seagrass meadows are productive ecosystems and many animal species are dependent on them, including a wide diversity of invertebrates. This study aims to explore spatial diversity patterns of benthic invertebrates associated with <i>Zostera noltei</i>. Three areas with <i>Z. noltei</i> meadows were sampled along the Mira Channel (Ria de Aveiro). At each area, two sites were selected and four cores were taken at each site. Fauna was sorted, counted, and identified to the lowest taxonomical level. Results showed significant differences in the number of taxa among meadows. It was also observed that some taxa presented differences in the abundance among meadows.

S. Shahin, A. Mahmoud, Amal El-Fouly et al.

An investigation was consummated under shade condition at the nursery of Orman Botanical Garden, Giza, Egypt during 2020 and 2021 seasons to study the effect of pre-sowing treatments; i.e. seeds without any treatment (as control), soaking in tap water for 24 h at ambient temperature and soaking in hot water (70-80 °C) for 24 h, seed orientation treatments; horizontal with the micropyle oriented laterally and vertical with the micropyle positioned either upwards or downwards and their interactions on germination characters and seedling growth traits of African mahogany timber tree (Khaya senegalensis (Desr.) A. Juss) seeds. The results indicated that seeds soaked in hot water for 24 h failed to germinate in both seasons, while those soaked in tap water at room temperature for 24 h gave the highest percent of germination, the least No. days to either maximum or 50% germination as well as the best means of germination rate index, vigour index, seed viability and plumule length compared to control in the two seasons. Horizontal sowing method recorded the maximal germination percent, quickest germination, strongest vigour index and seed viability as well as the longest plumule length and followed by vertical one, in which the micropyle oriented upwards. So, the best results at all were obtained from combining soaking the seeds in tap water treatment and positioned them horizontally. A similar trend to that of germination characteristics was also occurred regarding seedling growth parameters. Accordingly, it can be proposed to soak Khaya senegalensis seeds in ordinary water pre-sowing for 24 h at ambient temperature and embedding them horizontally at 2 cm depth with the micropyle positioned laterally to obtain better germination and the best growth traits of the seedlings