Plant Traits Research Articles

Proline and Glycine Betaine: A Dynamic Duo for Enhancing Salt Stress Resilience in Maize by Regulating Growth, Stomatal size, and Oxidative Stress Responses

Osmolytes proline (Pro) and glycine betaine (GB) have been reported to impart tolerance against salinity stress in many plants. However, there is no report available on the combined application of Pro and GB to mitigate salinity-induced growth inhibition in maize. Consequently, the goal of the current study is to assess Pro's and GB's potential as priming and exogenous agents in maize under salt stress. Therefore, the present study was conducted using a petri dish and hydroponic pot experiment to evaluate the morpho-physiological and biochemical characteristics of maize plants subjected to salt stress, with the addition of Pro and GB. The seeds of maize were germinated under 20 mM of each Pro or GB, with or without 120 mM salinity stress. The findings demonstrated that salt stress lessened the final germination percentage (FGP) (52.9%), photosynthetic pigments (40.0%), relative water content (RWC) (20.2%), stomatal size (59.3%), and leaf and root K+/Na+ ratios of maize seedlings compared to control. In addition, compared to the control, higher levels of malondialdehyde (MDA) (24.2%) and hydrogen peroxide (H2O2) (25.7%) were observed, whereas lower levels of catalase (CAT) (43.8%) and peroxidase (POX) (30.4%) were noted. The priming with Pro, GB, Pro+GB significantly increased FGP, germination index (GI), shoot-root biomass, seed vigor index (SVI), and reduced mean germination time (MGT) under salt stress. Foliar application of Pro, GB, or Pro+GB resulted in a significant increment in chlorophyll contents, RWC, K+ absorption, and stomatal size under salt stress. Furthermore, supplementing with Pro, GB, or Pro+GB reduced the accumulation of H2O2 (24.0, 23.3, and 31.1%, respectively) and MDA (22.8, 17.2, and 32.1%, respectively) caused by salt and augmented the levels of CAT (33.3, 22.8, and 45.2%, respectively) and POX (36.4, 23.5, and 47.2%, respectively) in the leaves. Taken together, the current study's findings indicate that combining Pro and GB is one of the most effective techniques for improving the salinity-tolerant seed germination and seedling traits of maize plants. Consequently, this study recommends that Pro and GB can be used as seed priming and exogenous agents to help maize grow faster in salt-stress situations.

Assessing the drought-tolerance and growth-promoting potential of strawberry (Fragaria × ananassa Duch.) rhizobacteria for consortium bioformulation

Plant growth-promoting rhizobacteria (PGPR) are known to influence plant root cells to regulate and induce specific traits related to growth promotion and survival. In the present study, rhizobacteria from strawberry plants were screened for stress tolerance under osmotic stress in TSB-mediated PEG 6000 (-0.73 MPa) and tested their ability to produce proline, exopolysaccharide, and free amino acids, all of which induce and regulate stress tolerance. The rhizobacteria were also distinguished for the production of 1-aminocyclopropane-1-carboxylate deaminase (ACCd) for the mitigation of drought stress. Among the 111 rhizobacterial isolates, 41 isolates grow above threshold limit in osmotic stress tolerance, 33 of which exhibited stress tolerance. Further characterization screened 27 isolates as capable growth promoters. Among the experimentally screened rhizobacteria, the isolates SBU4 and SDK8 [Pseudomonas fluorescens (OP627557) (PGPR1) and Pseudomonas glycinae (OP627558) (PGPR2)] exhibited the most promising phyto-beneficial potential. Both the isolates grew exponentially well during the log phase, with increased growth in Log CFU ml-1 under experimentally produced osmotic stress. The drought stress tolerance test results of the SBU4 and SDK8 isolates revealed the presence of proline (1.93 μg mL-1, 2.05 μg mL-1), exopolysaccharide (2.19 mg mg-1 protein, 2.58 mg mg-1 protein), and free amino acid (11.47 μmol g-1, 13.32 μmol g-1) and positive growth in ACCd-enriched DF media, an ACCd assay (α-ketobutyrate (0.56 μmol/ml, 0.64 μmol/ml) and ammonia (0.37 μg mL-1, 0.53 μg mL-1)). The isolates SBU4 and SDK8 performed well in qualitative tests for P solubilization, N fixing ability, siderophore chelation, HCN, and ammonia production, as well as in assays involving P producers (94.57 μg mL-1 and 92.86 μg mL-1), siderophore units (52.14% SU and 63.12% SU), and IAA producers (74.63 μg mL-1 and 72.64 μg mL-1). These rhizobacterial isolates were optimized under various growth factors (pH, temperature, incubation) to achieve a relatively high log CFU ml-1. The isolates achieved maximum Log CFU mL-1 when cultured in either a specific range of pH or temperature or growth period (incubation) under standard test conditions. The growth of cultures on cross-streaked nutrient agar plates was tested for an efficient, effective consortium bioformulation that enhances growth and specific traits (drought stress mitigation) in strawberry plants.

Spatial-spectral feature mining in hyperspectral corn leaf venation structure and its application in nitrogen content estimation

The growth of corn plants requires a significant amount of nitrogen nutrient supply to ensure the yield. Meanwhile, overfertilization could result in adverse environmental impacts, making it crucial to monitor the nitrogen supply condition in corn plants precisely. Hyperspectral imaging (HSI) could be the solution to this challenge, as HSI plant phenotyping technology has been widely utilized to nondestructively identify plant traits, such as mineral nutrient deficiencies in corn plants. However, limitations persist where the conventional HSI nitrogen prediction models mainly relied on the overall colors of the plant tissue extracted from the spectral domain but rarely included the spatially distributed information on the leaf level. This study aimed to examine if including new information from the spatial domain could potentially improve the performance of HSI models. Because the venation structure plays a crucial role in the distribution of various nutrients across the leaf, a series of physiological responses caused by nitrogen deficiency could result in non-uniform color patterns related to the veins. The recent advancement of HSI techniques such as LeafSpec, whose imaging quality and spatial-spectral resolution have been significantly improved, made it possible to extract the venation structure together with high-resolution spatial-spectral features. In this study, the hypothesis was that utilizing high-resolution spatial-spectral features extracted based on the venation structure could yield a better-performed nitrogen content prediction model compared to the averaged spectrum of the corn leaf. First, a venation structure segmentation algorithm was developed using the Local Binary Patterns (LBP) method for hyperspectral corn leaf images scanned with LeafSpec. Second, for every hyperspectral leaf image, 131 spectral index heatmaps were generated, and 30 leaf regions were picked based on the venation structure, resulting in 3930 spatial-spectral features. Third, the features were picked using the Least Absolute Shrinkage and Selection Operator (LASSO) regression. As the results tested with a field assay involving two different corn genotypes and two nitrogen treatments, the Partial Least Square Regression (PLS-R) model built with selected spatial-spectral features outperformed the model built with the averaged leaf spectra in terms of the Root Mean Squared Error (RMSE) of predictions. The results provided encouraging proof and guidance for the potential benefit of using high-resolution spatial-spectral features derived from hyperspectral leaf images to improve the accuracy and robustness of the nitrogen content prediction models for corn plants.

Estimates of microbiome heritability across hosts.

Microbiomes contribute to variation in many plant and animal traits, suggesting that microbiome-mediated traits could evolve through selection on the host. However, for such evolution to occur, microbiomes must exhibit sufficient heritability to contribute to host adaptation. Previous work has attempted to estimate the heritability of a variety of microbiome attributes. Here we show that most published estimates are limited to vertebrate and plant hosts, but significant heritability of microbiome attributes has been frequently reported. This indicates that microbiomes could evolve in response to host-level selection, but studies across a wider range of hosts are necessary before general conclusions can be made. We suggest future studies focus on standardizing heritability measurements for the purpose of meta-analyses and investigate the role of the environment in contributing to heritable microbiome variation. This could have important implications for the use of microbiomes in conservation, agriculture and medicine.

Role of silicon in legume‐insect interactions: Insights from a plant experiencing different levels of herbivory

Abstract Silicon (Si) supplementation can enhance symbiotic functions in some legumes (Fabaceae) with their nitrogen‐fixing rhizobia, such as root nodulation and nitrogen fixation. However, it is still poorly understood how Si influences legume–insect interactions. Here, we investigated how a symbiotic legume responds not only to Si supplementation but also to herbivory treatment with varying infestation levels in two events. We conducted a controlled climate chamber experiment by growing Medicago truncatula plants inoculated with rhizobia. For half of the plants, the soil was kept without Si (−Si), whereas the other half was regularly supplemented with Si (+Si). We then infested the plants with caterpillars of Spodoptera littoralis with 0, 1 or 3 larvae and 0, 1 or 1 larva in single herbivory attack and in double herbivory attack, respectively. To understand plant responses to such treatment combinations, we examined 16 functional traits. Nodule number, nodule fresh mass and nodule leghaemoglobin concentrations were not affected in single attack plants. However, increasing levels of herbivory led to decreases in such measured traits in double attack plants. Foliar C to N ratio increased in single attack plants but decreased in double attack plants with increasing levels of herbivory, indicating contrasting resource allocation. Herbivory did not affect the content of foliar Si, which was higher in +Si than −Si plants. Si and herbivory led to reduced foliar phenolics in double attack plants, suggesting a potential trade‐off between silicification and phenolic production. Si and herbivory led to increased trichome densities in single attack plants, but patterns were less clear in double attack plants. Herbivory but not Si reduced plant biomass with increasing levels of herbivory in double attack plants. Relative growth rates of the caterpillars, as proxy for plant resistance, decreased mainly due to herbivory treatment, when fed on single attack plants. Using a trait‐based approach, we provide novel insights to better understand the response of a legume to Si supplementation and different herbivory levels and events. We conclude that herbivory predominantly exerts much stronger effects than Si on various plant traits, pointing to a necessity to respond to herbivory by induced defence strategies. Read the free Plain Language Summary for this article on the Journal blog.

Assessment of Combining Ability and Heterosis for Seed Yield and its Attributes in Sunflower (Helianthus annuus L.)

The present study employed three lines and fifteen testers to assess the combining ability and standard heterosis of forty-five hybrids developed through a line × tester mating design. The analysis of variance for combining ability revealed significant variation in the mean sum of squares of parents, testers and the interaction between lines and testers regarding seed yield per plant and its related traits. Among the parents, testers GMU 498 and RHA 378 exhibited superior performance for seed yield/plant. In the hybrids, COSF 6A×CSFI 1862, HA 89A×GMU 1000 and HA 89A×RHA 378 demonstrated significantly better seed yield per plant compared to the checks. The variance for specific combining ability (SCA) exceeded that for general combining ability (GCA), indicating that all traits were governed by non-additive gene action. Among the lines, COSF 12A was identified as a good general combiner for yield-contributing traits, while the testers CSFI 1862, GMU 1000 and GMU 498 were recognized as good general combiners for seed yield per plant. Five hybrids, namely HA 89A × RHA 378, HA 89A × GMU 1000, COSF 12A × CSFI 1855, COSF 6A × CSFI 1862 and COSF 12A × GMU 311, exhibited significantly positive SCA for seed yield per plant. Heterosis over the standard checks (DRSH 1, COH 3 and GK 2002) was estimated and the hybrids HA 89A × GMU 1000 and COSF 6A × CSFI 1862 showed positive significant heterosis for seed yield per plant and related traits. The promising hybrids HA 89A × GMU 1000, HA 89A × RHA 378 and COSF 6A × CSFI 1862 were selected based on their mean performance, SCA effects and standard heterosis for seed yield per plant and its attributes.

The Indo–Pacific Pollen Database – a Neotoma constituent database

Abstract. The Indo–Pacific Pollen Database (IPPD) is the brainchild of the late professor Geoffrey Hope, who gathered pollen records from across the region to ensure their preservation for future generations of palaeoecologists. This noble aim is now being fulfilled by integrating the IPPD into the online Neotoma Paleoecology Database, making this compilation available for public use. Here we explore the database in depth and suggest directions for future research. The IPPD comprises 226 fossil pollen records, most postdating 20 ka but with some extending as far back as 50 ka or further. Over 80 % of the records are Australian, with a fairly even distribution between the different Australian geographical regions, with the notable exception being Western Australia, which is only represented by three records. The records are also well distributed in the modern climate space, with the largest gap being in drier regions due to preservation issues. However, many of the records contain few samples or have fewer than five chronology control points, such as radiocarbon, luminescence or Pb-210, for the younger sequences. Average deposition time for the whole database, counted as years per centimetre, is 64.8 yr cm−1, with 61 % of the records having a deposition time shorter than 50 yr cm−1. The slowest deposition time by geographical region occurs on Australia's east coast, while the fastest times are from the western Pacific. Overall, Australia has a slower deposition time than the rest of the Indo–Pacific region. The IPPD offers many exciting research opportunities to investigate past regional vegetation changes and associated drivers, including contrasting the impact of the first human arrival and European colonisation on vegetation. Examining spatiotemporal patterns of diversity and compositional turnover/rate of change, land cover reconstructions, and plant functional or trait diversity are other avenues of potential research, amongst many others. Merging the IPPD into Neotoma also facilitates inclusion of data from the Indo–Pacific region into global syntheses.

Crowd-sourced trait data can be used to delimit global biomes

Abstract. Terrestrial biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions and bioclimate or remote sensing products. However, classifying the biosphere into biomes from a functional perspective using biophysical traits has rarely been tested. Such a trait-based biome classification has been limited by data availability. Here, we aimed to exploit crowd-sourced plant observations and trait databases to systematically assess which traits are most suitable for biome classification. We derived global patterns of 33 biophysical traits covering around 50 % of the land surface by combining crowd-sourced species distribution data from the Global Biodiversity Information Facility (GBIF) and trait observations from the TRY database. Using these trait maps as predictors for supervised cluster analyses, we tested to what extent we can reconstruct 31 published biome maps. A sensitivity analysis with randomly sampled combinations of traits was performed to identify the traits that are most appropriate for biome classification. Performance was quantified by comparing modeled biome maps and the respective observation-based biome maps. Finally, spatial gaps in the resulting biome maps were filled using species distribution models to obtain continuous global biome maps. We showed that traits can be used for biome classification and that the most appropriate traits are conduit density; rooting depth; height; and different leaf traits, including specific leaf area and leaf nitrogen content. The best performance of the biome classification was obtained for biome maps based on biogeographic zonation and species distributions, in contrast to biome maps derived from optical reflectance. The availability of crowd-sourced plant observations is heterogeneous, and, despite its exponential growth, large data gaps are prevalent. Nonetheless, it was possible to derive biome classification schemes from these data to predict global biome patterns with good agreement. Therefore, our analysis is a valuable approach towards understanding biome patterns based on biophysical traits and associated ecological strategies.

Morphological Characterization of Some Capia Pepper (Capsicum annuum L.) Genotypes

Capsicum annuum (Capia), a member of the Solanaceae family, has a rich genetic diversity in fruit and plant traits. To select Capia pepper genotypes with desirable morphological traits for the development of new hybrid capia pepper varieties, this study aimed to characterize genetic accessions generated from local populations, and standard and hybrid cultivars using morphological characters. One hundred and twelve genotypes were identified using 15 morphological traits (11 qualitative and 4 quantitative) and quantitative traits were measured while qualitative traits were observed. Cluster and Principal Component Analysis (PCA) was applied to determine the relationship between the lines identified as a result of single plant selection. As a result of the cluster analysis, a dendrogram was prepared to evaluate the morphological similarity between the lines, and nineteen groups were identified based on 15 variables. In Principal Component Analysis, six PC axes explained 66.2% of the total variation. As a result of the study, high morphological variability was observed among pepper lines. This evaluation of plant trait variability can assist geneticists and breeders in identifying populations with desirable characteristics for inclusion in pepper breeding programs.

Multiomics analysis reveals the involvement of OnDIVARICATA 3 in controlling dynamic flower coloring of Oncidium hybridum

Flower color is one of the main quality and economic traits of ornamental plants, and a large amount of research on flower color mainly focuses on the differences between varieties, while there were few reports on the change of flower color at different developmental stages. In this study, the metabolome and transcriptome of a new strain ‘XM-1’ with dynamic color changes of Oncidium were analyzed. The results showed that rutin, quercetin and carotenoids metabolism decreased significantly during the change of color from yellow to white. Analyzing the correlation network between metabolites and differential expressed genes, 25 key structural genes were detected and regulated by multiple MYB-related transcription factors. The MYB-related transcription factor Cluster-100966.1_OnDIVARICATA 3 was selected for further analysis. The phylogenetic tree of DIVARICATA in different species of Orchidaceae and Arabidopsis thaliana was constructed and the most closely related members were selected for sequence comparison. The results showed that OnDIVARICATA 3 contained MYB-like conserved domains. Subcellular localization results showed that OnDIVARICATA 3 was located in the nucleus. In overexpressing OnDIVARICATA 3 transgenic hairy roots, the expression of flower color related genes FLS, ZEP, and CHYB were significantly up-regulated. In summary, this study characterized the key metabolic pathways in the formation of the dynamic flower color of Oncidium hybridum, and constructed the regulatory network of the MYB-related. These results laid a theoretical foundation for the subsequent research on flower color and genetic engineering technology breeding of Oncidium hybridum.

Virus-Induced Gene Silencing Simultaneously Exploits ‘Attract and Kill’ Traits in Plants and Insects to Manage Huanglongbing

Abstract The vector-borne disease Huanglongbing (HLB) causes severe economic losses to citrus production worldwide with no available cure. Herein, we applied virus-induced gene silencing technology to engineer citrus that preferentially attracted and specifically killed Diaphorina citri, the vector associated with HLB. We engineered the infectious citrus tristeza virus (CTV-T36) clone to carry three truncated genes. The triple construct (CTV-tAwd-tWnt-tPDS) produces small interfering RNAs (siRNAs) against phytoene desaturase, PDS, to yield a phenotype with visual, olfactory, and gustatory cues that preferentially attracted D. citri. In addition, siRNAs targeted two genes related to flight in D. citri, abnormal wing disc (DcAwd) and wingless (DcWnt), that caused wing malformations and decreased survival in psyllids that fed on plants inoculated with the engineered virus. During two successive generations, D. citri reared on CTV-tAwd-tWnt-tPDS-inoculated plants exhibited higher mortality across life stages as well as reduced fecundity and fertility as compared with those reared on non-infected plants or CTV-wt-inoculated plants. Furthermore, CTV-tAwd-tWnt-tPDS-inoculated plants shortened the lifespan of D. citri by more than 20 days. Morphological abnormalities were noted in those adults that did successfully emerge on plants inoculated with CTV-tAwd-tWnt-tPDS, including cocked wings with a bowl-shaped depression and/or a convex shape. Phloem sap from CTV-tAwd-tWnt-tPDS-inoculated plants decreased the survival of D. citri adults, confirming that siRNAs were present in the sap of these plants. Collectively, we provide proof of concept for a novel variant of the attract-and-kill method where the cultivated crop is potentially transformed into a hyper-attractive population and transmission sink for a phytopathogen vector.

Testing the contribution of vertebrate predators and leaf traits to mainland–island differences in insect herbivory on oaks

Abstract Ecological theory predicts that herbivory should be weaker on islands than on mainland based on the assumption that islands have lower herbivore abundance and diversity. However, empirical tests of this prediction are rare, especially for insect herbivores, and those few tests often fail to address the mechanisms behind island–mainland divergence in herbivory. In particular, past studies have not addressed the relative contribution of top‐down (i.e. predator‐driven) and bottom‐up (i.e. plant‐driven) factors to these dynamics. To address this, we experimentally excluded insectivorous vertebrate predators (e.g. birds, bats) and measured leaf traits associated with herbivory in 52 populations of 12 oak (Quercus) species in three island–mainland sites: The Channel Islands of California vs. mainland California, Balearic Islands vs. mainland Spain, and the island Bornholm vs. mainland Sweden (N = 204 trees). In each site, at the end of the growing season, we measured leaf damage by insect herbivores on control vs. predator‐excluded branches and measured leaf traits, namely: phenolic compounds, specific leaf area, and nitrogen and phosphorous content. In addition, we obtained climatic and soil data for island and mainland populations using global databases. Specifically, we tested for island–mainland differences in herbivory, and whether differences in vertebrate predator effects or leaf traits between islands and mainland contributed to explaining the observed herbivory patterns. Supporting predictions, herbivory was lower on islands than on mainland, but only in the case of Mediterranean sites (California and Spain). We found no evidence for vertebrate predator effects on herbivory on either islands or mainland in any study site. In addition, while insularity affected leaf traits in some of the study sites (Sweden‐Bornholm and California), these effects were seemingly unrelated to differences in herbivory. Synthesis. Our results suggest that vertebrate predation and the studied leaf traits did not contribute to island–mainland variation patterns in herbivory, calling for more nuanced and comprehensive investigations of predator and plant trait effects, including measurements of other plant traits and assessments of predation by different groups of natural enemies.

Advances in viticulture via smart phenotyping: current progress and future directions in tackling soil copper accumulation

Modern viticulture faces significant challenges including climate change and increasing crop diseases, necessitating sustainable solutions to reduce fungicide use and mitigate soil health risks, particularly from copper accumulation. Advances in plant phenomics are essential for evaluating and tracking phenotypic traits under environmental stress, aiding in selecting resilient vine varieties. However, current methods are limited, hindering effective integration with genomic data for breeding purposes. Remote sensing technologies provide efficient, non-destructive methods for measuring biophysical and biochemical traits of plants, offering detailed insights into their physiological and nutritional state, surpassing traditional methods. Smart phenotyping is essential for selecting crop varieties with desired traits, such as pathogen-resilient vine varieties, tolerant to altered soil fertility including copper toxicity. Identifying plants with typical copper toxicity symptoms under high soil copper levels is straightforward, but it becomes complex with supra-optimal, already toxic, copper levels common in vineyard soils. This can induce multiple stress responses and interferes with nutrient acquisition, leading to ambiguous visual symptoms. Characterizing resilience to copper toxicity in vine plants via smart phenotyping is feasible by relating smart data with physiological assessments, supported by trained professionals who can identify primary stressors. However, complexities increase with more data sources and uncertainties in symptom interpretations. This suggests that artificial intelligence could be valuable in enhancing decision support in viticulture. While smart technologies, powered by artificial intelligence, provide significant benefits in evaluating traits and response times, the uncertainties in interpreting complex symptoms (e.g., copper toxicity) still highlight the need for human oversight in making final decisions.

Research Progress of Spectral Imaging Techniques in Plant Phenotype Studies.

Spectral imaging technique has been widely applied in plant phenotype analysis to improve plant trait selection and genetic advantages. The latest developments and applications of various optical imaging techniques in plant phenotypes were reviewed, and their advantages and applicability were compared. X-ray computed tomography (X-ray CT) and light detection and ranging (LiDAR) are more suitable for the three-dimensional reconstruction of plant surfaces, tissues, and organs. Chlorophyll fluorescence imaging (ChlF) and thermal imaging (TI) can be used to measure the physiological phenotype characteristics of plants. Specific symptoms caused by nutrient deficiency can be detected by hyperspectral and multispectral imaging, LiDAR, and ChlF. Future plant phenotype research based on spectral imaging can be more closely integrated with plant physiological processes. It can more effectively support the research in related disciplines, such as metabolomics and genomics, and focus on micro-scale activities, such as oxygen transport and intercellular chlorophyll transmission.

Functional ecology of plant communities as a guide for vegetation management

Plant functional traits determine how individual plants cope with varying environmental conditions, and extensive literature supports their role in influencing ecosystem properties. The study of plant functional traits could help the prediction of species responses to disturbances and environmental change, thus providing invaluable knowledge to refine conservation strategies of species and vegetation. However, applications of functional ecology for vegetation management are still underrepresented.The articles in this Special Issue of FLORA offer cutting-edge insights on the variation of plant traits and ecological strategies in response to environmental drivers, such as anthropogenic disturbance, climate and land use change. The results demonstrate how trait-based approaches can be used for the prediction of climate and land use change impacts on vulnerable sets of species or on biogeochemical cycles, reinforcing the concept that functional plant ecology can help identify the most effective procedures for vegetation management, such as the choice of mowing intensity in grasslands or planning vegetation recovery after wildfires.Our knowledge of plant trait coordination at the community level is still undefined, especially concerning the integration of above- and belowground traits. This represents a missed opportunity for vegetation management, especially considering that a complete understanding of the dynamics of the entire ecosystem is crucial for complete understanding of ecosystem properties. Since plant functional traits can represent a straightforward tool for monitoring changes in ecosystem structure and functions, their use could support vegetation monitoring as required by different programs of nature conservation. It would be useful to embrace a perspective that integrates plant traits with systematic conservation planning, ensuring effective and sustainable conservation efforts.

CRISPR-Cas9: A Cutting-edge Genome-editing Technology with Many Potential Applications

Unregulated human activities are responsible for climate change which is a major factor for the emergence of new infectious (bacterial, viral, fungus, and parasitic) and non-infectious diseases (genetic disorders, cancers, etc.). To tackle this situation, we must have better therapeutics, diagnostics, and vaccines for the treatment and prevention of emerging diseases in humans and animals. To address the aforementioned issues, CRISPR-Cas9, a revolutionary genome editing tool, can help us develop better therapeutics, diagnostics, and vaccines in a short time. In addition, it can be used to achieve food security by improving productivity, adaptability, and resilience traits in plants and animals. In nature, most bacteria and archaea have CRISPR as a part of their adaptive immune system that helps bacteria defend themselves from phages, viruses, and other foreign genetic elements. CRISPR-Cas9 is a highly effective, simple, and accurate genome editing tool compared to previous genome editing tools such as meganucleases, Zinc finger nucleases (ZFNs), and transcription activators like effector nucleases (TALENs). This review article discusses the different components and working of the CRISPR-Cas9 system, and how CRISPR-Cas9 plays a significant role in the development of next-generation therapeutics, diagnostics, vaccine platforms, and improved crops and livestock species for food security.

Plant traits and seasonality shape coexistence and niche segregation patterns among spider species.

Understanding the mechanisms that enable species coexistence is a central question in ecology, as it helps to comprehend species diversity. One of the most common stabilizing mechanisms of coexistence is niche segregation, which can prevent the competitive exclusion of the fittest competitor. Niche segregation can manifest itself at various temporal and spatial scales, allowing provide essential insights into understanding the stabilizing mechanisms facilitating the coexistence of species. We assessed coexistence patterns among flower-dwelling spiders in two ways, in the first set of analyses, we investigated the factors influencing the quantity of spider individuals and species. The second approach we investigate the spatio-temporal segregation between species, effectively examining the coexistence patterns. We observed that the presence of inflorescences per plant, the number of flowers per inflorescence, and the presence of EFNs play a significant role in increasing spider abundance and richness. We find only a marginal seasonal effect, suggesting that spiders have constant access to resources throughout the year. Our niche overlap analysis demonstrated synchrony in the spatial occupation of niches by different spider species. The coexistence patterns appeared to be unaffected by the number of inflorescences. The greater number of inflorescences will enable a greater availability of niches, and consequently more abundance and richness of species of spiders the plant can sustain. Our results suggest that, to mitigate the adverse consequences of competitive interactions, spiders tend to adopt spatial partitioning as a strategy to facilitate the coexistence of spiders living in reproductive structures on plants in the Brazilian savanna.

The influence of plant genomics on plant evolution

With the increasing demand for high-quality tea, the genetic basis of ideal traits of tea plants has been widely concerned. The research on tea tree genomics, specifically focusing on “Longjing 43”, provides significant insights into plant evolution and breeding. “Longjing 43” was chosen due to its complex genome and economic importance. The study successfully assembled its genome to the chromosome level, revealing a large and heterogeneous genome with numerous repetitive sequences. Comparative genomics showed that hybridization has been a key driver of genetic diversity and adaptability in tea plants. These findings are crucial for developing marker-assisted selection (MAS) techniques, improving traits such as disease resistance, flavor, and stress response. Moreover, the research underscores the role of tea tree genomics in preserving cultural heritage and promoting economic benefits through enhanced tea quality. This study contributes to the broader understanding of plant genomics by illustrating the evolutionary processes and potential applications in agriculture, conservation, and industry, thus offering a comprehensive tool for future plant breeding and genetic improvement strategies.

Leveraging leaf spectroscopy to identify drought-tolerant soybean cultivars

Understanding cultivars' physiological traits variations under abiotic stresses is critical to improve phenotyping and selections of resistant crop varieties. Traditional methods of accessing physiological traits in plants are costly and time consuming, which prevents their use in breeding programs. Spectroscopy data and statistical approaches such as partial least square regression could be applied to rapidly collect and predict several physiological parameters at leaf-level, allowing phenotyping several genotypes in a high-throughput manner. We collected spectroscopy data of twenty soybean cultivars planted under well-watered and drought conditions during the reproductive phase. At 20 days after drought was imposed, we measured leaf pigments content (chlorophyll a and b, and carotenoids), specific leaf area, electrons transfer rate, and photosynthetic active radiation. At 28 days after drought imposition, we measured leaf pigments content, specific leaf area, relative water content, and leaf temperature. Partial least square regression models accurately predicted leaf pigments content, specific leaf area, and leaf temperature (cross-validation R2 ranging from 0.56 to 0.84). Discriminant analysis using 54 wavelengths was able to select the best-performance cultivars regarding all evaluated physiological traits. We showed the great potential of using spectroscopy as a feasible, non-destructive, and accurate method to estimate physiological traits and screening of superior genotypes.

Effects of Selenium Application on Fermentation Quality, Chemical Composition, and Bacterial Community of Hybrid Pennisetum Silage

The primary objective of this study is to facilitate the conversion of inorganic selenium (Se) into organic Se within plants via assimilation, subsequently feeding it to livestock and poultry to enhance healthy animal production and yield Se-enriched livestock and poultry products. Therefore, it is imperative to first investigate the impact of varying Se doses on the agronomic traits of plants as well as their forage storage and processing. This experiment investigated the effect of Se fertilizer application on the fermentation quality, chemical composition, and bacterial community of Pennisetum americanum × Pennisetum purpureum cv Minmu 7 (HPM7). There were nine Se fertilizer dissolution levels of HPM7 treated, which were 0 mg/kg (Se0), 0.50 mg/kg (Se1), 1.00 mg/kg (Se2), 2.00 mg/kg (Se3), 5.00 mg/kg (Se4), 10.00 mg/kg (Se5), 20.00 mg/kg (Se6), 30.00 mg/kg (Se7), 40.00 mg/kg (Se8), and 50.00 mg/kg (Se9). The results showed that after silage, the water-soluble carbohydrates of Se1, Se2, and Se3 were lower than Se0, and the pH of Se3, Se4, and Se6 were lower than the Se0. The number of OTUs in the nine groups was sequentially Se1 > Se2 > Se3 > Se8 > Se6 > Se5 > Se7 > Se4 > Se0. The dominant bacterial phyla in silage samples were Firmicutes and Proteobacteria. Compared with Se0, Bacterial Shannon index in Se1 and Se2 were higher, while Chao1 and ACE indices of Se1, Se2, Se3, Se5, and Se6 were higher. A beta diversity analysis indicated that the Se1 exhibited the highest number of significant biomarkers. Escherichia coli between Se0 and Se3 and Clostridium sardiniense and Clostridium perfringens between Se0 and Se1 exhibited significant differences at a species level. The most abundant pathways for metabolism were membrane transport, carbohydrate metabolism, translation, replication, repair, and amino acid metabolism. The correlation analysis indicated that the dry matter content was negatively correlated with Bacillus (p < 0.01), Lactobacillus (p < 0.05), Pediococcus (p < 0.05), and Hirschia (p < 0.05); the contents of neutral detergent fiber and hemi-cellulose were positively correlated with Lactobacillus (p < 0.05, p < 0.01). The protein content was negatively correlated with proteus (p < 0.05). This study demonstrated that the application of Se fertilizer could enhance the Se content in HPM7. The optimal fertilization concentration was found to range from 0.50 to 2.00 mg/kg, which facilitates the metabolism of soluble carbohydrates and enhances both the fermentation quality and microbial relative abundance of HPM7 silage.