Legume biofortification and the role of plant growth-promoting bacteria in a sustainable agricultural era

World population growth, together with climate changes and increased hidden hunger, bring an urgent need for finding sustainable and eco-friendly agricultural approaches to improve crop yield and nutritional value. The existing methodologies for enhancing the concentration of bioavailable micronutrients in edible crop tissues (i.e., biofortification), including some agronomic strategies, conventional plant breeding, and genetic engineering, have not always been successful. In recent years, the use of plant growth-promoting bacteria (PGPB) has been suggested as a promising approach for the biofortification of important crops, including legumes. Legumes have many beneficial health effects, namely, improved immunological, metabolic and hormonal regulation, anticarcinogenic and anti-inflammatory effects, and decreased risk of cardiovascular and obesity-related diseases. These crops also play a key role in the environment through symbiotic nitrogen (N) fixation, reducing the need for N fertilizers, reducing CO2 emissions, improving soil composition, and increasing plant resistance to pests and diseases. PGPB act by a series of direct and indirect mechanisms to potentially improve crop yields and nutrition. This review will focus on the: (i) importance of legumes in the accomplishment of United Nations Sustainable Development Goals for production systems; (ii) understanding the role of PGPB in plant nutrition; (iii) iron biofortification of legumes with PGPB, which is an interesting case study of a green technology for sustainable plant-food production improving nutrition and promoting sustainable agriculture.info:eu-repo/semantics/publishedVersio

Phenotypic evaluation of the IDC profile of soybean plants after inoculation with plant growth-promoting bacteria

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Evidence on the use of gait analysis - A review

Gait analysis consists of evaluating the individual through kinematic analysis, while walking along a surface. Kinematic analysis relates the relative movement between rigid bodies and finds applications in gait analysis. The purpose of this paper is to find the applications of gait analysis, the methodologies used to perform it and conclude about the different methodologies’ uses. A literature search was performed using PRISMA Guidelines. Twenty-two documents fulfilled the inclusion criteria. A total of 15 different countries presented researches in this topic. The areas within which these papers are published include Sports Medicine (7), Pediatric Medicine (1), General Medicine (11), Occupational Medicine (1), Engineering (2). Gait analysis has many different areas of intervention. Some gait parameters are interrelated and there are a few different methodologies available to perform gait analysis. A comprehensive table of results has been developed, where results are presented.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Pattern matching through Chaos Game Representation: bridging numerical and discrete data structures for biological sequence analysis

This work was partially supported by FCT through the PIDDAC Program funds (INESC-ID multiannual funding) and under grant PEst-OE/EEI/LA0008/2011 (IT multiannual funding). In addition, it was also partially funded by projects HIVCONTROL (PTDC/EEA-CRO/100128/2008, S. Vinga, PI), TAGS (PTDC/EIA-EIA/112283/2009) and NEUROCLINOMICS (PTDC/EIA-EIA/111239/2009) from FCT (Portugal).Background: Chaos Game Representation (CGR) is an iterated function that bijectively maps discrete sequences into a continuous domain. As a result, discrete sequences can be object of statistical and topological analyses otherwise reserved to numerical systems. Characteristically, CGR coordinates of substrings sharing an L-long suffix will be located within 2(-L) distance of each other. In the two decades since its original proposal, CGR has been generalized beyond its original focus on genomic sequences and has been successfully applied to a wide range of problems in bioinformatics. This report explores the possibility that it can be further extended to approach algorithms that rely on discrete, graph-based representations. Results: The exploratory analysis described here consisted of selecting foundational string problems and refactoring them using CGR-based algorithms. We found that CGR can take the role of suffix trees and emulate sophisticated string algorithms, efficiently solving exact and approximate string matching problems such as finding all palindromes and tandem repeats, and matching with mismatches. The common feature of these problems is that they use longest common extension (LCE) queries as subtasks of their procedures, which we show to have a constant time solution with CGR. Additionally, we show that CGR can be used as a rolling hash function within the Rabin-Karp algorithm. Conclusions: The analysis of biological sequences relies on algorithmic foundations facing mounting challenges, both logistic (performance) and analytical (lack of unifying mathematical framework). CGR is found to provide the latter and to promise the former: graph-based data structures for sequence analysis operations are entailed by numerical-based data structures produced by CGR maps, providing a unifying analytical framework for a diversity of pattern matching problems.publishersversionpublishe

Pattern matching through Chaos Game Representation: bridging numerical and discrete data structures for biological sequence analysis

BACKGROUND: Chaos Game Representation (CGR) is an iterated function that bijectively maps discrete sequences into a continuous domain. As a result, discrete sequences can be object of statistical and topological analyses otherwise reserved to numerical systems. Characteristically, CGR coordinates of substrings sharing an L-long suffix will be located within 2(-L )distance of each other. In the two decades since its original proposal, CGR has been generalized beyond its original focus on genomic sequences and has been successfully applied to a wide range of problems in bioinformatics. This report explores the possibility that it can be further extended to approach algorithms that rely on discrete, graph-based representations. RESULTS: The exploratory analysis described here consisted of selecting foundational string problems and refactoring them using CGR-based algorithms. We found that CGR can take the role of suffix trees and emulate sophisticated string algorithms, efficiently solving exact and approximate string matching problems such as finding all palindromes and tandem repeats, and matching with mismatches. The common feature of these problems is that they use longest common extension (LCE) queries as subtasks of their procedures, which we show to have a constant time solution with CGR. Additionally, we show that CGR can be used as a rolling hash function within the Rabin-Karp algorithm. CONCLUSIONS: The analysis of biological sequences relies on algorithmic foundations facing mounting challenges, both logistic (performance) and analytical (lack of unifying mathematical framework). CGR is found to provide the latter and to promise the former: graph-based data structures for sequence analysis operations are entailed by numerical-based data structures produced by CGR maps, providing a unifying analytical framework for a diversity of pattern matching problems

Exploring tomato phenotypic variability under combined nitrogen and water deficit

Background: Despite drought and nitrogen (N) deficit being two of the most important crops’ growth limiting factors, only few studies have explored tomato phenotypic variability in response to both abiotic stresses. Aims: In this study, we aimed to perform a phenotypic evaluation and an analysis of the growth traits of 40 tomato genotypes (mostly focusing on old cultivars, but also including modern hybrids and wild tomato relatives’ accessions as anchors) grown in pots that were subjected to combined N and water deficit. Methods: Each genotype was divided into two groups: control (100% N, 100% field capacity) and combined deficit (20% N, 50% field capacity). A total of 14 morpho-physiological traits were evaluated and further analyzed using multivariate statistical methods. Results: The Principal Component Analyses revealed considerable phenotypical diversity among tomato genotypes, with four principal components explaining 82% of the variability. Data integration on a cluster analysis separated the studied genotypes into three distinct clusters based on their ability to handle the combined deficit. Tolerance was associated with traits such as lower specific leaf area, lower leaf area ratio and higher water use efficiency, comparing to the sensitive genotypes. Conclusions: This study shows that tomato tolerance to combined N and water deficit largely varies between genotypes and that old cultivars represent a valuable gene pool towards more sustainable food production systems.info:eu-repo/semantics/publishedVersio

Mitigation of emergent bacterial pathogens using pseudomonas syringae pv. Actinidiae as a case study — from orchard to gene and everything in between

Globalization propelled human migration and commercial exchanges at the global level, but woefully led to the introduction of non-indigenous organisms into several agroecological systems. These include pathogenic bacteria with devastating consequences for numerous crops of agronomical importance for food production worldwide. In the last decade, research efforts have focused on these noxious organisms, aiming to understand their evolutionary processes, degree of pathogenicity, and mitigation strategies, which have allowed stakeholders and policymakers to develop evidence-based regulatory norms to improve management practices and minimize production losses. One of these cases is the bacterium Pseudomonas syringae pv. actinidiae (Psa), the causal agent of the kiwifruit bacterial canker, which has been causing drastic production losses and added costs related to orchard management in the kiwifruit industry. Although Psa is presently considered a pandemic pathogen and far from being eradicated, the implementation of strict regulatory norms and the efforts employed by the scientific community allowed the mitigation, to some extent, of its negative impacts through an integrated pest management approach. This included implementing directive guidelines, modifying cultural practices, and searching for sources of plant resistance. However, bacterial pathogens often have high spatial and temporal variability, with new strains constantly arising through mutation, recombination, and gene flow, posing constant pressure to agroecosystems. This review aims to critically appraise the efforts developed to mitigate bacterial pathogens of agronomical impact, from orchard management to genome analysis, using Psa as a case study, which could allow a prompter response against emerging pathogens in agroecosystems worldwide.info:eu-repo/semantics/publishedVersio

Preserving the nutritional quality of crop plants under a changing climate: importance and strategies

Background: Global climate is changing more rapidly than ever, threatening plant growth and productivity while exerting considerable direct and indirect effects on the quality and quantity of plant nutrients. Scope: This review focuses on the global impact of climate change on the nutritional value of plant foods. It showcases the existing evidence linking the effects of climate change factors on crop nutrition and the concentration of nutrients in edible plant parts. It focuses on the effect of elevated CO2 (eCO2), elevated temperature (eT), salinity, waterlogging and drought stresses, and what is known regarding their direct and indirect influence on nutrient availability. Furthermore, it provides possible strategies to preserve the nutritional composition of plant foods under changing climates. Conclusions: Climate change has an impact on the accumulation of minerals and protein in crop plants, with eCO2 being the underlying factor of most of the reported changes. The effects are clearly dependent on the type, intensity and duration of the imposed stress, plant genotype and developmental stage. Strong interactions (both positive and negative) can be found between individual climatic factors and soil availability of nitrogen (N), potassium (K), iron (Fe) and phosphorous (P). The development of future interventions to ensure that the world's population has access to plentiful, safe and nutritious food may need to rely on breeding for nutrients under the context of climate change, including legumes in cropping systems, better farm management practices and utilization of microbial inoculants that enhance nutrient availability.info:eu-repo/semantics/publishedVersio