What distribution function do life cycle inventories follow?

Purpose

Life cycle inventory (LCI) results are often assumed to follow a lognormal distribution, while a systematic study that identifies the distribution function that best describes LCIs has been lacking. This paper aims to find the distribution function that best describes LCIs using Ecoinvent v3.1 database using a statistical approach, called overlapping coefficient analysis.

Methods

Monte Carlo simulation is applied to characterize the distribution of aggregate LCIs. One thousand times of simulated LCI results are generated based on the unit process-level parametric uncertainty information, from each of which 1000 randomly chosen data points are extracted. The 1 million data points extracted undergo statistical analyses including Shapiro-Wilk normality test and the overlapping coefficient analysis. The overlapping coefficient is a measure used to determine the shared area between the distribution of the simulated LCI results and three possible distribution functions that can potentially be used to describe them including lognormal, gamma, and Weibull distributions.

Results and discussion

Shapiro-Wilk normality test for 1000 samples shows that average p value of log-transformed LCI results is 0.18 at 95 % confidence level, accepting the null hypothesis that LCI results are lognormally distributed. The overlapping coefficient analysis shows that lognormal distribution best describes the distribution of LCI results. The average of overlapping coefficient (OVL) for lognormal distribution is 95 %, while that for gamma and Weibull distributions are 92 and 86 %, respectively.

Conclusions

This study represents the first attempt to calculate the stochastic distributions of the aggregate LCIs covering the entire Ecoinvent 3.1 database. This study empirically shows that LCIs of Ecoinvent 3.1 database indeed follow a lognormal distribution. This finding can facilitate more efficient storage and use of uncertainty information in LCIs and can reduce the demand for computational power to run Monte Carlo simulation, which currently relies on unit process-level uncertainty data.

     

International Molybdenum Association (IMOA) life cycle assessment program and perspectives on the LCA harmonization effort

Purpose

In 2001, the International Molybdenum Association (IMOA) initiated their life cycle assessment (LCA) program performing cradle-to-gate life cycle inventories (LCIs) of three molybdenum metallurgical products, followed by LCIs of eight molybdenum chemicals and an update to the metallurgical LCIs. From 2012 to 2014, IMOA participated in a multi-metal industry initiative to harmonize the methodological approach to metal-related LCAs. This paper describes some of IMOA’s conclusions formed from its program and, coupled with its involvement in the multi-metal initiative, provides some lessons learned.

Methods

For this paper, IMOA evaluated the benefits of its LCI program, including its ability to communicate effectively with member companies and stakeholders on the development, use, and application of life cycle data. Likewise, IMOA developed the competence to recognize and provide input on potentially inappropriate use of LCA. IMOA performed a literature review to highlight some of the scientific research using the molybdenum LCI data. IMOA also reviewed the metal industry’s guidance document to provide its perspective on it, including similarities, differences, and substantiation of elements of the four topic areas.

Results and discussion

The metal industry’s guidance document identified four topic areas as essential for alignment with respect to metal-related LCAs: (1) system boundaries, (2) coproduct modelling, (3) life cycle impact assessment (LCIA), and (4) metals recycling modelling. IMOA is largely in agreement with the approaches described in the document. The paper provides examples of how these have been applied to LCAs on Mo-bearing products as well as examples of how some LCA work can benefit from the guidance document.

Conclusions

Having taken part in the harmonization effort, IMOA is poised to educate its member companies and stakeholders about some of the challenging issues encountered in LCA and will continue to lead through active industry participation. IMOA supplies its LCI data via a formal request process which enables open dialogue with stakeholders and LCA practitioners while providing IMOA with insights into how its products fit into the broader lifecycle context and facilitating stakeholders’ awareness of LCA and metals.

     

Attributional and consequential LCA in the ILCD handbook

Purpose

This discussion article aims to highlight two problematic aspects in the International Reference Life Cycle Data System (ILCD) Handbook: its guidance to the choice between attributional and consequential modeling and to the choice between average and marginal data as input to the life cycle inventory (LCI) analysis.

Methods

We analyze the ILCD guidance by comparing different statements in the handbook with each other and with previous research in this area.

Results and discussion

We find that the ILCD handbook is internally inconsistent when it comes to recommendations on how to choose between attributional and consequential modeling. We also find that the handbook is inconsistent with much of previous research in this matter, and also in the recommendations on how to choose between average and marginal data in the LCI.

Conclusions

Because of the inconsistencies in the ILCD handbook, we recommend that the handbook be revised.

     

A framework for increasing the availability of life cycle inventory data based on the role of multinational companies

Purpose

The aim of the paper is to assess the role and effectiveness of a proposed novel strategy for Life Cycle Inventory (LCI) data collection in the food sector and associated supply chains. The study represents one of the first of its type and provides answers to some of the key questions regarding the data collection process developed, managed and implemented by a multinational food company across the supply chain.

Methods

An integrated LCI data collection process for confectionery products was developed and implemented by Nestlé, a multinational food company. Some of the key features includes (1) management and implementation by a multinational food company; (2) types of roles to manage, provide and facilitate data exchange; (3) procedures to identify key products, suppliers and customers; (4) LCI questionnaire and cover letter and (5) data quality management based on the pedigree matrix. Overall, the combined features in an integrated framework provide a new way of thinking about the collection of LCI data from the perspective of a multinational food company.

Results and discussion

The integrated LCI collection framework spanned across 5 months and resulted in 87 new LCI datasets for confectionery products from raw material, primary resource use, emission and waste release data collected from suppliers across 19 countries. The data collected was found to be of medium to high quality compared with secondary data. However, for retailers and waste service companies, only partially completed questionnaires were returned. Some of the key challenges encountered during the collection and creation of data included lack of experience, identifying key actors, communication and technical language, commercial compromise, confidentiality protection and complexity of multi-tiered supplier systems. A range of recommendations are proposed to reconcile these challenges which include standardisation of environmental data from suppliers, concise and targeted LCI questionnaires and visualising complexity through drawings.

Conclusions

The integrated LCI data collection process and strategy has demonstrated the potential role of a multinational company to quickly engage and act as a strong enabler to unlock latent data for various aspects of the confectionery supply chain. Overall, it is recommended that the research findings serve as the foundations to transition towards a standardised procedure which can practically guide other multinational companies to considerably increase the availability of LCI data.

     

The EcoSpold 2 format—why a new format?

Purpose

This paper introduces the new EcoSpold data format for life cycle inventory (LCI).

Methods

A short historical retrospect on data formats in the life cycle assessment (LCA) field is given. The guiding principles for the revision and implementation are explained. Some technical basics of the data format are described, and changes to the previous data format are explained.

Results

The EcoSpold 2 data format caters for new requirements that have arisen in the LCA field in recent years.

Conclusions

The new data format is the basis for the Ecoinvent v3 database, but since it is an open data format, it is expected to be adopted by other LCI databases. Several new concepts used in the new EcoSpold 2 data format open the way for new possibilities for the LCA practitioners and to expand the application of the datasets in other fields beyond LCA (e.g., Material Flow Analysis, Energy Balancing).

     

Giving a scientific basis for uncertainty factors used in global life cycle inventory databases: an algorithm to update factors using new information

Purpose

Life cycle inventory (LCI) databases provide generic data on exchange values associated with unit processes. The “ecoinvent” LCI database estimates the uncertainty of all exchange values through the application of the so-called pedigree approach. In the first release of the database, the used uncertainty factors were based on experts’ judgments. In 2013, Ciroth et al. derived empirically based factors. These, however, assumed that the same uncertainty factors could be used for all industrial sectors and fell short of providing basic uncertainty factors. The work presented here aims to overcome these limitations.

Methods

The proposed methodological framework is based on the assessment of more than 60 data sources (23,200 data points) and the use of Bayesian inference. Using Bayesian inference allows an update of uncertainty factors by systematically combining experts’ judgments and other information we already have about the uncertainty factors with new data.

Results and discussion

The implementation of the methodology over the data sources results in the definition of new uncertainty factors for all additional uncertainty indicators and for some specific industrial sectors. It also results in the definition of some basic uncertainty factors. In general, the factors obtained are higher than the ones obtained in previous work, which suggests that the experts had initially underestimated uncertainty. Furthermore, the presented methodology can be applied to update uncertainty factors as new data become available.

Conclusions

In practice, these uncertainty factors can systematically be incorporated in LCI databases as estimates of exchange value uncertainty where more formal uncertainty information is not available. The use of Bayesian inference is applied here to update uncertainty factors but can also be used in other life cycle assessment developments in order to improve experts’ judgments or to update parameter values when new data can be accessed.

     

A scalable life cycle inventory of an electrical automotive traction machine—Part I: design and composition

Purpose

A scalable life cycle inventory (LCI) model of a permanent magnet electrical machine, containing both design and production data, has been established. The purpose is to contribute with new and easy-to-use data for LCA of electric vehicles by providing a scalable mass estimation and manufacturing inventory for a typical electrical automotive traction machine. The aim of this article (part I of two publications) is to present the machine design, the model structure, and an evaluation of the models’ mass estimations.

Methods

Data for design and production of electrical machines has been compiled from books, scientific papers, benchmarking literature, expert interviews, various specifications, factory records, and a factory site visit. For the design part, one small and one large reference machine were constructed in a software tool, which linked the machines’ maximum ability to deliver torque to the mass of its electromagnetically active parts. Additional data for remaining parts was then gathered separately to make the design complete. The two datasets were combined into one model, which calculates the mass of all motor subparts from an input of maximum power and torque. The range of the model is 20–200 kW and 48–477 Nm. The validity of the model was evaluated through comparison with seven permanent magnet electrical traction machines from established brands.

Results and discussion

The LCI model was successfully implemented to calculate the mass content of 20 different materials in the motor. The models’ mass estimations deviate up to 21% from the examples of real motors, which still falls within expectations for a good result, considering a noticeable variability in design, even for the same machine type and similar requirements. The model results form a rough and reasonable median in comparison to the pattern created by all data points. Also, the reference motors were assessed for performance, showing that the electromagnetic efficiency reaches 96–97%.

Conclusions

The LCI model relies on thorough design data collection and fundamental electromagnetic theory. The selected design has a high efficiency, and the motor is suitable for electric propulsion of vehicles. Furthermore, the LCI model generates representative mass estimations when compared with recently published data for electrical traction machines. Hence, for permanent magnet-type machines, the LCI model may be used as a generic component estimation for LCA of electric vehicles, when specific data is lacking.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Corneal Collagen Cross-Linking for the Management of Mycotic Keratitis

Purpose

To evaluate the efficiency of corneal collagen cross-linking (CXL) in addition to topical voriconazole in cases with mycotic keratitis.

Design

Retrospective case series in a tertiary university hospital.

Participants

CXL was performed on 13 patients with mycotic keratitis who presented poor or no response to topical voriconazole treatment.

Methods

The clinical features, symptoms, treatment results and complications were recorded retrospectively. The corneal infection was graded according to the depth of infection into the stroma (from grade 1 to grade 3). The visual analogue scale was used to calculate the pain score before and 2 days after surgery.

Main Outcome Measures

Grade of the corneal infection.

Results

Mean age of 13 patients (6 female and 7 male) was 42.4 ± 17.7 years (20–74 years). Fungus was demonstrated in culture (eight patients) or cytological examination (five patients). Seven of the 13 patients (54%) were healed with topical voriconazole and CXL adjuvant treatment in 26 ± 10 days (15–40 days). The remaining six patients did not respond to CXL treatment; they initially presented with higher grade ulcers. Pre- and post-operative pain score values were 8 ± 0.8 and 3.5 ± 1, respectively (p < 0.05).

Conclusions

The current study suggests that adjunctive CXL treatment is effective in patients with small and superficial mycotic ulcers. These observations require further research by large randomized clinical trials.

     

Modelling facilitation or competition within a root system: importance of the overlap of root depletion and accumulation zones

Background and aims

Relevant soil properties and nutrient distributions influencing crop root growth might be different under no-till (NT) and mouldboard plough (MP) management. The possible different root systems within different managements might have key impact on crop nutrient uptake and consequently crop production. Our objective was to assess the long-term combined effects of tillage and phosphorus (P) fertilization on corn (Zea mays L.) root distribution and morphology.

Methods

Corn root and soil samples were collected during the silking stage at five depths (0–5, 5–10, 10–20, 20–30 and 30–40 cm) and three horizontal distances perpendicular to the corn row (5, 15 and 25 cm) under MP and NT with three P fertilizations (0, 17.5, and 35 kg P ha^?1) for a long-term (22 years) experiment in eastern Canada. Root morphology and soil properties were determined.

Results

NT practice decreased corn root biomass by ?26 % compared to MP, mainly by decreasing the primary and secondary roots. Additionally, corn roots in NT tend to be more expansive on the surface layer with higher root length and surface densities for the depth of 0–5 cm at two sampling distances of 15 and 25 cm. The 35 kg P ha^?1 rate increased the root biomass by 26 and 41 % compared to the 0 and 17.5 kg P ha^?1 rates.

Conclusions

No-tillage practice and low rates of P fertilization reduce corn roots. This is probably caused by the weed competition in NT and the continued downward P status with low P rates over 22 years.

     

Minimal variation of the plasma lipidome after delayed processing of neonatal cord blood

Background

Cord blood lipids are potential disease biomarkers. We aimed to determine if their concentrations were affected by delayed blood processing.

Method

Refrigerated cord blood from six healthy newborns was centrifuged every 12 h for 4 days. Plasma lipids were analysed by liquid chromatography/mass spectroscopy.

Results

Of 262 lipids identified, only eight varied significantly over time. These comprised three dihexosylceramides, two phosphatidylserines and two phosphatidylethanolamines whose relative concentrations increased and one sphingomyelin that decreased.

Conclusion

Delay in separation of plasma from refrigerated cord blood has minimal effect overall on the plasma lipidome.

     

Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome

Background

Centrifugation is an indispensable procedure for plasma sample preparation, but applied conditions can vary between labs.

Aim

Determine whether routinely used plasma centrifugation protocols (1500×g 10 min; 3000×g 5 min) influence non-targeted metabolomic analyses.

Methods

Nuclear magnetic resonance spectroscopy (NMR) and High Resolution Mass Spectrometry (HRMS) data were evaluated with sparse partial least squares discriminant analyses and compared with cell count measurements.

Results

Besides significant differences in platelet count, we identified substantial alterations in NMR and HRMS data related to the different centrifugation protocols.

Conclusion

Already minor differences in plasma centrifugation can significantly influence metabolomic patterns and potentially bias metabolomics studies.

     

Metabolome variability for two Mediterranean sponge species of the genus <Emphasis Type="Italic">Haliclona</Emphasis>: specificity,time, and space

Introduction

The study of natural variation of metabolites brings valuable information on the physiological state of the organisms as well as their phenotypic traits. In marine organisms, metabolome variability has mostly been addressed through targeted studies on metabolites of ecological or pharmaceutical interest. However, comparative metabolomics has demonstrated its potential to address the overall and complex metabolic variability of organisms.

Objectives

In this study, the intraspecific (temporal and spatial) variability of two Mediterranean Haliclona sponges (H. fulva and H. mucosa) was investigated through an untargeted and then targeted metabolomics approach and further compared to their interspecific variability.

Methods

Samples of both species were collected monthly during 1 year in the coralligenous habitat of the Northwestern Mediterranean sae at Marseille and Nice. Their metabolomic profiles were obtained by UHPLC-QqToF analyses.

Results

Marked variations were noticed in April and May for both species including a decrease in Shannon’s diversity and concentration in specialized metabolites together with an increase in fatty acids and lyso-PAF like molecules. Spatial variations across different sampling sites could also be observed for both species, however in a lesser extent.

Conclusions

Synchronous metabolic changes possibly triggered by physiological factors like reproduction and/or environmental factors like an increase in the water temperature were highlighted for both Mediterranean Haliclona species inhabiting close habitats but displaying different biosynthetic pathways. Despite significative intraspecific variations, metabolomic variability remains minor when compared to interspecific variations for these congenerous species, therefore suggesting the predominance of genetic information of the holobiont in the observed metabolome.

     

Life cycle assessment of construction and renovation of sewer systems using a detailed inventory tool

Purpose

The objective was to provide comprehensive life cycle inventories for the construction and renovation of sewers. A detailed inventory was provided with multiple options of pipe materials, diameters and site-specific characteristics, and was embedded into the Excel^®-based tool SewerLCA. The tool allows for life cycle evaluation of different sewers. It was applied to determine the most important phases, processes, and related parameters involved in the construction and renovation of sewers from an environmental and economical perspective.

Methods

Comprehensive life cycle inventories (LCIs) for sewers construction and renovation were obtained by first identifying all processes involved after interviewing construction experts and reviewing sewer construction budgets from a Catalan company; and second transforming the processes into masses of materials and energy usage using construction databases. In order to run the life cycle impact assessment (LCIA) the materials and energy typologies from the inventories were matched to their corresponding equivalents into available LCI databases. Afterwards the potential impacts were calculated through the use of LCIA characterization factors from ReCiPe. Life cycle assessment (LCA) was run several times to assess the construction of a 1-km-long sewer with varying pipe materials, life spans for each material, diameters, transport distances, site-specific characteristics, and pipe deposition options.

Results and discussion

The environmental impacts generated by construction and renovation of a 1 km Polyvinylchloride (PVC) pipe with a diameter of 40 cm are mainly associated with pipe laying and backfilling of the trench. The evaluation of several pipe materials and diameters shows that the exclusion of renovation would underestimate the impacts by 38 to 82 % depending on the pipe materials and diameters. Including end-of-life phase for plastic pipe materials increases climate change (up to an extra 71 %) and human toxicity (up to an extra 147 %) impacts (among all diameters). The preferred pipe materials from an environmental point of view are precast concrete and High-Density Polyethylene (HDPE). Site-specific characteristics (specially the presence of rocky soil and asphalt placement) and material life span have a high influence on the overall environmental profile, whereas changes in transport distances have only a minor impact (<4 %).

Conclusions

Environmental impacts during the construction and renovation of sewers are subject to differences in material type, site-specific characteristics and material life span. Renovation of sewers has a large influence on all potential environmental impacts and costs and, hence, should not be omitted in LCA studies. The treatment and disposal processes of plastic pipes at the end of their life has to be accounted in LCA studies.

     

Recent advances in human sweat metabolomics for lung cancer screening

Introduction

Lung cancer is the leading cause of cancer related mortality owing to the advanced stage it is usually detected because the available diagnostic tests are expensive and invasive; therefore, they cannot be used for general screening.

Objectives

To increase robustness of previous biomarker panels—based on metabolites in sweat samples—proposed by the authors, new samples were collected within different intervals (4 months and 2 years), analyzed at different times (2012 and 2014, respectively) by different analysts to discriminate between LC patients and smokers at risk factor.

Methods

Sweat analysis was carried out by LC–MS/MS with minimum sample preparation and the generated analytical data were then integrated to minimize variability in statistical analysis.

Results

Panels with capability to discriminate LC patients from smokers at risk factor were obtained taken into account the variability between both cohorts as a consequence of the different intervals for samples collection, the times at which the analyses were carried out and the influence of the analyst. Two panels of metabolites using the PanelomiX tool allow reducing false negatives (95 % specificity) and false positives (95 % sensitivity). The first panel (96.9 % specificity and 83.8 % sensitivity) is composed by monoglyceride MG(22:2), muconic, suberic and urocanic acids, and a tetrahexose; the second panel (81.2 % specificity and 97.3 % sensitivity) is composed by the monoglyceride MG(22:2), muconic, nonanedioic and urocanic acids, and a tetrahexose.

Conclusion

The study has allowed obtaining a prediction model more robust than that obtained in the previous study from the authors.

     

Association of 24 h–systolic blood pressure variability and cardiovascular disease in patients with obstructive sleep apnea

Background

To evaluate association of 24 h–systolic blood pressure (SBP) variability and obstructive sleep apnea (OSA) as defined by the apnea-hypopnea index ≥5/h; and association of 24 h–SBP variability and prevalent cardiovascular disease (CVD) in OSA patients.

Methods

Participants underwent polysomongraphy to evaluate the presence of OSA, and 24 h–ambulatory blood pressure monitoring was applied to evaluate 24 h–SBP variability as indexed by weighted 24 h–standard deviation (SD) of SBP. Between-group differences were evaluated in participants with and without OSA. Participants with OSA were divided into high and low 24 h–SBP variability groups and between-group differences were evaluated.

Results

Mean age of 384 participants was 50 years old and 42.2% had OSA. Mean 24 h–systolic/diastolic BP were 130/78 mmHg, with mean weighted 24 h–SD of systolic/diastolic BP were 12.9/7.3 mmHg. Compared to those without OSA, OSA participants had higher clinic-, 24 h-, daytime- and nighttime-SBP, and weighted 24 h, daytime- and nighttime-SD of SBP. Age, prevalent CVD and OSA, usage of angiotensin converting enzyme inhibitor/angiotensin receptor blocker, calcium channel blocker and diuretic were significantly associated with 24 h–SBP variability. In OSA patients, compared to those with low variability, participants with high variability had higher weighted 24 h, daytime- and nighttime-SD of SBP. After adjusted for covariates including clinic-SBP and 24 h–SBP, per 1-SD increment weighted 24 h–SD of SBP was associated with 21% increased prevalent CVD.

Conclusions

Patients with newly-diagnosed OSA have higher 24 h–SBP variability compared to those without OSA; in OSA patients, increased 24 h–SBP variability is associated with increased prevalence of CVD.

     

Life cycle inventories of electricity generation and power supply in version 3 of the ecoinvent database—part I: electricity generation

Purpose

Life cycle inventories (LCI) of electricity generation and supply are among the main determining factors regarding life cycle assessment (LCA) results. Therefore, consistency and representativeness of these data are crucial. The electricity sector has been updated and substantially extended for ecoinvent version 3 (v3). This article provides an overview of the electricity production datasets and insights into key aspects of these v3 inventories, highlights changes and describes new features.

Methods

Methods involved extraction of data and analysis from several publically accessible databases and statistics, as well as from the LCA literature. Depending on the power generation technology, either plant-specific or region-specific average data have been used for creating the new power generation inventories representing specific geographies. Whenever possible, the parent–child relationship was used between global and local activities. All datasets include a specific technology level in order to support marginal mixes used in the consequential version of ecoinvent. The use of parameters, variables and mathematical relations enhances transparency. The article focuses on documentation of LCI data on the unlinked unit process level and presents direct emission data of the electricity-generating activities.

Results and discussion

Datasets for electricity production in 71 geographic regions (geographies) covering 50 countries are available in ecoinvent v3. The number of geographies exceeds the number of countries due to partitioning of power generation in the USA and Canada into several regions. All important technologies representing fossil, renewable and nuclear power are modelled for all geographies. The new inventory data show significant geography-specific variations: thermal power plant efficiencies, direct air pollutant emissions as well as annual yields of photovoltaic and wind power plants will have significant impacts on cumulative inventories. In general, the power plants operating in the 18 newly implemented countries (compared to ecoinvent v2) are on a lower technology level with lower efficiencies and higher emissions. The importance of local datasets is once more highlighted.

Conclusions

Inventories for average technology-specific electricity production in all globally important economies are now available with geography-specific technology datasets. This improved coverage of power generation representing 83 % of global electricity production in 2008 will increase the quality of and reduce uncertainties in LCA studies worldwide and contribute to a more accurate estimation of environmental burdens from global production chains. Future work on LCI of electricity production should focus on updates of the fuel chain and infrastructure datasets, on including new technologies as well as on refining of the local data.

     

From correlation to causation: analysis of metabolomics data using systems biology approaches

Introduction

Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.

Objectives

This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.

Methods

We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.

Results

We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.

Conclusions

Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.

     

Impact of plant growth-promoting bacteria on grain yield,protein content,and urea-<Superscript>15</Superscript> N recovery by maize in a Cerrado Oxisol

Background and aims

The inoculation of cereal crops with plant growth-promoting bacteria (PGPB) is a potential strategy to improve fertilizer-N acquisition by crops in soils with low capacity to supply N. A study was conducted to assess the impact of three inoculants on grain yield, protein content, and urea-¹⁵ N recovery in maize (Zea mays L.) under Cerrado soil and climate conditions.

Methods

The main treatments included inoculants containing (i) Azospirillum brasilense strain Sp245, (ii) A. brasilense strains AbV5 + AbV6, (iii) Herbaspirillum seropedicae strain ZAE94, and (iv) a non-inoculated control. The subtreatments were (i) urea-N fertilization (100 kg N ha^?1) at 30 days after sowing and (ii) no N addition at the stage. To determine fertilizer-N recovery, ¹⁵N–labelled urea was applied in microplots.

Results

Inoculants carrying A. brasilense improved urea-¹⁵ N acquisition efficiency in maize and also improved grain yield compared to the non-inoculated control, while urea-N fertilization enhanced grain quality by providing higher protein content.

Conclusion

Our results suggest that the inoculation of maize grains with PGPB represents a strategy to improve fertilizer-N recovery and maize yield in Cerrado soil with a low capacity to supply N.