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<jats:p>Wheat yield can be limited by many biotic and abiotic factors. Heat stress at the grain filling stage is a factor that reduces wheat production tremendously. The potential role of endophytic microorganisms in mitigating plant stress through various biomolecules like enzymes and growth hormones and also by improving plant nutrition has led to a more in-depth exploration of the plant microbiome for such functions. Hence, we devised this study to investigate the abundance and diversity of wheat seed endophytic bacteria (WSEB) from heat<jats:sup>S</jats:sup> (heat susceptible, GW322) and heat<jats:sup>T</jats:sup> (heat tolerant, HD3298 and HD3271) varieties by culturable and unculturable approaches. The results evidenced that the culturable diversity was higher in the heat<jats:sup>S</jats:sup> variety than in the heat<jats:sup>T</jats:sup> variety and <jats:italic>Bacillus</jats:italic> was found to be dominant among the 10 different bacterial genera identified. Though the WSEB population was higher in the heat<jats:sup>S</jats:sup> variety, a greater number of isolates from the heat<jats:sup>T</jats:sup> variety showed tolerance to higher temperatures (up to 55°C) along with PGP activities such as indole acetic acid (IAA) production and nutrient acquisition. Additionally, the metagenomic analysis of seed microbiota unveiled higher bacterial diversity, with a predominance of the phyla Proteobacteria covering &amp;gt;50% of OTUs, followed by Firmicutes and Actinobacteria. There were considerable variations in the abundance and diversity between heat sensitivity contrasting varieties, where notably more thermophilic bacterial OTUs were observed in the heat<jats:sup>T</jats:sup> samples, which could be attributed to conferring tolerance against heat stress. Furthermore, exploring the functional characteristics of culturable and unculturable microbiomes would provide more comprehensive information on improving plant growth and productivity for sustainable agriculture.</jats:p>

<jats:sec><jats:title>Introduction</jats:title><jats:p>The leaf, the main product organ, is an essential factor in determining the Chinese cabbage growth, yield and quality.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>To explore the regulatory mechanism of leaf size development of Chinese cabbage, we investigated the leaf size difference between two high-generation inbred lines of Chinese cabbage, Y2 (large leaf) and Y7 (small leaf). Furtherly, the transcriptome and cis-acting elements analyses were conducted.</jats:p></jats:sec><jats:sec><jats:title>Results and Discussion</jats:title><jats:p>According to our results, Y2 exhibited a higher growth rate than Y7 during the whole growth stage. In addition, the significant higher leaf number was observed in Y2 than in Y7. There was no significant difference in the number of epidermal cells and guard cells per square millimeter between Y2 and Y7 leaves. It indicated that cell numbers caused the difference in leaf size. The measurement of phytohormone content confirmed that GA1 and GA3 mainly play essential roles in the early stage of leaf growth, and IPA and ABA were in the whole leaf growth period in regulating the cell proliferation difference between Y2 and Y7. Transcriptome analysis revealed that cyclins BraA09g010980.3C (CYCB) and BraA10g027420.3C (CYCD) were mainly responsible for the leaf size difference between Y2 and Y7 Chinese cabbage. Further, we revealed that the transcription factors BraA09gMYB47 and BraA06gMYB88 played critical roles in the difference of leaf size between Y2 and Y7 through the regulation of cell proliferation.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This observation not only offers essential insights into understanding the regulation mechanism of leaf development, also provides a promising breeding strategy to improve Chinese cabbage yield.</jats:p></jats:sec>

<jats:p>The molecular nature of mutations induced by ionizing radiation and chemical mutagens in plants is becoming clearer owing to the availability of high-throughput DNA sequencing technology. However, few studies have compared the induced mutations between different radiation qualities and between different irradiated materials with the same analysis method. To compare mutation induction between dry-seeds and seedlings irradiated with carbon ions and gamma rays in Arabidopsis, in this study we detected the mutations induced by seedling irradiation with gamma rays and analyzed the data together with data previously obtained for the other irradiation treatments. Mutation frequency at the equivalent dose for survival reduction was higher with gamma rays than with carbon ions, and was higher with dry-seed irradiation than with seedling irradiation. Carbon ions induced a higher frequency of deletions (2−99 bp) than gamma rays in the case of dry-seed irradiation, but this difference was less evident in the case of seedling irradiation. This result supported the inference that dry-seed irradiation under a lower water content more clearly reflects the difference in radiation quality. However, the ratio of rearrangements (inversions, translocations, and deletions larger than 100 bp), which are considered to be derived from the rejoining of two distantly located DNA breaks, was significantly higher with carbon ions than gamma rays irrespective of the irradiated material. This finding suggested that high-linear energy transfer radiation induced closely located DNA damage, irrespective of the water content of the material, that could lead to the generation of rearrangements. Taken together, the results provide an overall picture of radiation-induced mutation in Arabidopsis and will be useful for selection of a suitable radiation treatment for mutagenesis.</jats:p>

<jats:sec><jats:title>Introduction</jats:title><jats:p>Plants release a large variety of metabolites via their roots to shape physico-chemical soil properties and biological processes in the rhizosphere. While hydroponic growth conditions facilitate accessibility of the root system and recovery of root exudates, the natural soil environment can alter root metabolism and exudate secretion, raising the question to what extent the quantity and composition of root exudates released in hydroponic growth systems reflect those recovered from soil-grown roots.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Using a root washing method, we sampled root exudates from four field-grown cover crop species with wide taxonomic distance, namely white mustard, lacy phacelia, bristle oat, and Egyptian clover. A set of primary metabolites and secondary metabolites were analysed in a targeted and untargeted LC-MS-based approach, respectively, for comparison with exudates obtained from hydroponically cultured plants.</jats:p></jats:sec><jats:sec><jats:title>Results and discussion</jats:title><jats:p>We found that hydroponically cultivated plants released a larger amount of total carbon, but that the recovery of total carbon was not indicative for the diversity of metabolites in root exudates. In the field, root exudates from phacelia and clover contained 2.4 to 3.8 times more secondary metabolites, whereas carbon exudation in hydroponics was 5- to 4-fold higher. The composition of the set of metabolites identified using the untargeted approach was much more distinct among all species and growth conditions than that of quantified primary metabolites. Among secondary metabolite classes, the presence of lipids and lipid-like molecules was highly indicative for field samples, while the release of a large amount of phenylpropanoids, organoheterocyclic compounds or benzenoids was characteristic for clover, mustard or oat, respectively, irrespective of the cultivation condition. However, at the compound level the bulk of released metabolites was specific for cultivation conditions in every species, which implies that hydroponically sampled root exudates poorly reflect the metabolic complexity of root exudates recovered from field-grown plants.</jats:p></jats:sec>

<jats:p>Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platforms, such as unmanned aerial vehicles (UAVs), can carry multiple sensors and collect numerous phenotypic traits with efficient, non-invasive field surveys. However, modeling the complex relationships between the observed phenotypic traits and biomass remains a challenging task, as the ground reference data are very limited for each genotype in the breeding experiment. In this study, a Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) model is proposed for sorghum biomass prediction. The architecture is designed to exploit the time series remote sensing and weather data, as well as static genotypic information. As a large number of features have been derived from the remote sensing data, feature importance analysis is conducted to identify and remove redundant features. A strategy to extract representative information from high-dimensional genetic markers is proposed. To enhance generalization and minimize the need for ground reference data, transfer learning strategies are proposed for selecting the most informative training samples from the target domain. Consequently, a pre-trained model can be refined with limited training samples. Field experiments were conducted over a sorghum breeding trial planted in multiple years with more than 600 testcross hybrids. The results show that the proposed LSTM-based RNN model can achieve high accuracies for single year prediction. Further, with the proposed transfer learning strategies, a pre-trained model can be refined with limited training samples from the target domain and predict biomass with an accuracy comparable to that from a trained-from-scratch model for both multiple experiments within a given year and across multiple years.</jats:p>

<jats:p>Non-rhizobial endophytes (NREs) are active colonizers inhabiting the root nodules. Though their active role in the lentil agroecosystem is not well defined, here we observed that these NREs might promote the growth of lentils, modulate rhizospheric community structure and could be used as promising organisms for optimal use of rice fallow soil. NREs from root nodules of lentils were isolated and examined for plant growth-promoting traits, exopolysaccharide (EPS) and biofilm production, root metabolites, and the presence of nifH and nifK elements. The greenhouse experiment with the chosen NREs, i.e., Serratia plymuthica 33GS and Serratia sp. R6 significantly increased the germination rate, vigour index, development of nodules (in non-sterile soil) and fresh weight of nodules (33GS 94%, R6 61% growth) and length of the shoot (33GS 86%, R6 51.16%) as well as chlorophyll levels when compared to the uninoculated control. Scanning Electron Microscopy (SEM) revealed that both isolates could successfully colonize the roots and elicit root hair growth. The inoculation of the NREs resulted in specific changes in root exudation patterns. The plants with 33GS and R6 treatment significantly stimulated the exudation of triterpenes, fatty acids, and their methyl esters in comparison to the uninoculated plants, altering the rhizospheric microbial community structure. Proteobacteria dominated the rhizospheric microbiota in all the treatments. Treatment with 33GS or R6 also enhanced the relative abundance of other favourable microbes, including Rhizobium, Mesorhizobium, and Bradyrhizobium. The correlation network analysis of relative abundances resulted in numerous bacterial taxa, which were in cooperation with each other, having a possible role in plant growth promotion. The results indicate the significant role of NREs as plant growth promoters, which also includes their role in root exudation patterns, enhancement of soil nutrient status and modulation of rhizospheric microbiota, suggesting their prospects in sustainable, and bio-based agriculture.</jats:p>

<jats:p>Lantana weed (<jats:italic>Lantana camara</jats:italic> L.) is among the most noxious weeds in the world. Keeping in mind its invasive behavior and great ecological tolerance, it becomes imperative to analyze the structure and function of associated microbiome. In this perspective, Illumina-based metagenome sequencing was performed to gain a better understanding of prokaryotic diversity and community structure in the rhizosphere soil of <jats:italic>L. camara</jats:italic> L. The organic carbon, nitrogen, phosphorus, and potassium contents in the rhizosphere soil were 0.91% (± 0.21%); 280 Kg ha<jats:sup>-1</jats:sup> (± 4.02 Kg ha<jats:sup>-1</jats:sup>), 54.5 Kg ha<jats:sup>-1</jats:sup> (± 3.12 Kg ha<jats:sup>-1</jats:sup>), and 189 Kg ha<jats:sup>-1</jats:sup> (± 6.11 Kg ha<jats:sup>-1</jats:sup>), respectively. The metagenome analysis revealed the existence of 41 bacterial and 2 archaeal phyla, with only 12 showing ≥1% abundances. Pseudomonadota was the dominant phylum with 31.3% abundance, followed by Actinomycetota (20.9%). Further, 54 different genera were identified with the highest abundance of <jats:italic>Devosia</jats:italic> (2.8%). The PICRUSt analysis predicted various functional traits in the soil metagenome, with general cellular functions dominating, followed by stress tolerance. Moreover, 10% of the functions were associated with nitrogen fixation, phosphate solubilization, and potassium mobilization. In conclusion, the present study revealed the existence of diverse prokaryotic communities in the rhizosphere of the <jats:italic>L. camara</jats:italic> L. which was primarily associated with stress response and plant growth promotion. To the best of our knowledge, this study documents for the first time the <jats:italic>L. camara</jats:italic> L. microbiome. Furthermore, the identified genera can be explored for agricultural needs in future.</jats:p>

<jats:sec><jats:title>Introduction</jats:title><jats:p>Fresh pomegranate fruit is susceptible to bruising, a common type of mechanical damage during harvest and at all stages of postharvest handling. Accurate and early detection of such damages in pomegranate fruit plays an important role in fruit grading. This study investigated the detection of bruises in fresh pomegranate fruit using hyperspectral imaging technique.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A total of 90 sample of pomegranate fruit were divided into three groups of 30 samples, each representing purposefully induced pre-scanning bruise by dropping samples from 100 cm and 60 cm height on a metal surface. The control has no pre-scanning bruise (no drop). Two hyperspectral imaging setups were examined: visible and near infrared (400 to 1000 nm) and short wavelength infrared (1000 to 2500 nm). Region of interest (ROI) averaged reflectance spectra was implemented to reduce the image data. For all hypercubes a principal components analysis (PCA) based background removal were done prior to segmenting the region of interest (ROI) using the Evince® multi-variate analysis software 2.4.0. Then the average spectrum of the ROI of each sample was computed and transferred to the MATLAB 2022a (The MathWorks, Inc., Mass., USA) for classification. A two-layer feed-forward artificial neural network (ANN) is used for classification.</jats:p></jats:sec><jats:sec><jats:title>Results and discussion</jats:title><jats:p>The accuracy of bruise severity classification ranged from 80 to 96.7%. When samples from both bruise severity (Bruise damage induced from a 100cm and 60 cm drop heights respectively) cases were merged, class recognition accuracy were 88.9% and 74.4% for the SWIR and Vis-NIR, respectively. This study implemented the method of selecting out informative bands and disregarding the redundant ones to decreases the data size and dimension. The study developed a more compact classification model by the data dimensionality reduction method. This study demonstrated the potential of using hyperspectral imaging technology in sensing and classification of bruise severity in pomegranate fruit. This work provides the foundation to build a compact and fast multispectral imaging-based device for practical farm and packhouse applications.</jats:p></jats:sec>

<jats:p>Fusarium wilt caused by <jats:italic>Fusarium oxysporum</jats:italic> f. sp. <jats:italic>lentis</jats:italic> (<jats:italic>Fol</jats:italic>) is the most devastating disease of lentil present worldwide. Identification of multi-race fusarium wilt resistance genes and their incorporation into existing cultivars will help to reduce yield losses. In the present study, 100 lentil germplasms belonging to seven lentil species were screened against seven prevalent races of <jats:italic>Fol</jats:italic>, and accessions IC201561 (<jats:italic>Lens culinaris</jats:italic> subsp. <jats:italic>culinaris)</jats:italic>, EC714243 (<jats:italic>L. c</jats:italic>. subsp. <jats:italic>odemensis)</jats:italic>, and EC718238 (<jats:italic>L. nigricans)</jats:italic> were identified as resistant. The typical R gene codes for the nucleotide-binding site and leucine-rich repeats (NBS-LRR) at the C terminal are linked to either the Toll/interleukin 1-like receptor (TIR) or coiled coil (CC) at the N terminal. In the present study, degenerate primers, designed from the NBS region amplifying the P-loop to the GLPLA motif, isolated forty-five resistance gene analogues (RGAs) from identified resistant accessions. The sequence alignment identified both classes of RGAs, TIR and non-TIR, based on the presence of aspartate (D) and tryptophan (W) at the end of the kinase motif, respectively. The phylogenetic analysis grouped the RGAs into six classes, from LRGA1 to LRGA6, which determined the diversity of the RGAs present in the host. Grouping of the RGAs identified from <jats:italic>Lens nigricans</jats:italic>, LnRGA 2, 9, 13 with I2 revealed the structural similarity with the fusarium resistance gene. The similarity index ranged from 27.85% to 86.98% among the RGAs and from 26.83% to 49.41% among the known R genes, I2, Gpa2, M, and L6. The active binding sites present along the conserved motifs grouped the RGAs into 13 groups. ADP/ATP, being the potential ligand, determines the ATP binding and ATP hydrolysis activity of the RGAs. The isolated RGAs can be used to develop markers linked to the functional R gene. Furthermore, expression analysis and full-length gene isolation pave the path to identifying the molecular mechanism involved in resistance.</jats:p>