IRTA Institute of Agrifood Research and Technology
Recent publications
Background The rabbit cecum hosts and interacts with a complex microbial ecosystem that contributes to the variation of traits of economic interest. Although the influence of host genetics on microbial diversity and specific microbial taxa has been studied in several species (e.g., humans, pigs, or cattle), it has not been investigated in rabbits. Using a Bayes factor approach, the aim of this study was to dissect the effects of host genetics, litter and cage on 984 microbial traits that are representative of the rabbit microbiota. Results Analysis of 16S rDNA sequences of cecal microbiota from 425 rabbits resulted in the relative abundances of 29 genera, 951 operational taxonomic units (OTU), and four microbial alpha-diversity indices. Each of these microbial traits was adjusted with mixed linear and zero-inflated Poisson (ZIP) models, which all included additive genetic, litter and cage effects, and body weight at weaning and batch as systematic factors. The marginal posterior distributions of the model parameters were estimated using MCMC Bayesian procedures. The deviance information criterion (DIC) was used for model comparison regarding the statistical distribution of the data (normal or ZIP), and the Bayes factor was computed as a measure of the strength of evidence in favor of the host genetics, litter, and cage effects on microbial traits. According to DIC, all microbial traits were better adjusted with the linear model except for the OTU present in less than 10% of the animals, and for 25 of the 43 OTU with a frequency between 10 and 25%. On a global scale, the Bayes factor revealed substantial evidence in favor of the genetic control of the number of observed OTU and Shannon indices. At the taxon-specific level, significant proportions of the OTU and relative abundances of genera were influenced by additive genetic, litter, and cage effects. Several members of the genera Bacteroides and Parabacteroides were strongly influenced by the host genetics and nursing environment, whereas the family S24-7 and the genus Ruminococcus were strongly influenced by cage effects. Conclusions This study demonstrates that host genetics shapes the overall rabbit cecal microbial diversity and that a significant proportion of the taxa is influenced either by host genetics or environmental factors, such as litter and/or cage.
Background Feed efficiency during lactation involves a set of phenotypic traits that form a complex system, with some traits exerting causal effects on the others. Information regarding such interrelationships can be used to predict the effect of external interventions on the system, and ultimately to optimize management practices and multi-trait selection strategies. Structural equation models can be used to infer the magnitude of the different causes of such interrelationships. The causal network necessary to fit structural equation models can be inferred using the inductive causation (IC) algorithm. By implementing these statistical tools, we inferred the causal association between the main energy sources and sinks involved in sow lactation feed efficiency for the first time, i.e., daily lactation feed intake (dLFI) in kg/day, daily sow weight balance (dSWB) in kg/day, daily litter weight gain (dLWG) in kg/day, daily back fat thickness balance (dBFTB) in mm/day, and sow metabolic body weight (SMBW) in kg 0.75 . Then, we tested several selection strategies based on selection indices, with or without dLFI records, to improve sow efficiency during lactation. Results The IC algorithm using 95% highest posterior density (HPD 95% ) intervals resulted in a fully directed acyclic graph, in which dLFI and dLWG affected dSWB, the posterior mean of the corresponding structural coefficients (PM λ ) being 0.12 and − 0.03, respectively. In turn, dSWB influenced dBFTB and SMBW, with PM λ equal to 0.70 and − 1.22, respectively. Multiple indirect effects contributed to the variances and covariances among the analyzed traits, with the most relevant indirect effects being those involved in the association between dSWB and dBFTB and between dSWB and SMBW. Selection strategies with or without phenotypic information on dLFI, or that hold this trait constant, led to the same pattern and similar responses in dLFI, dSWB, and dLWG. Conclusions Selection based on an index including only dBFTB and dLWG records can reduce dLFI, keep dSWB constant or increase it, and increase dLWG. However, a favorable response for all three traits is probably not achievable. Holding the amount of feed provided to the sows constant did not offer an advantage in terms of response over the other strategies.
During storage, premium extra virgin olive oils (PEVOO), which are oils of exceptional sensory quality, may lose the organoleptic characteristics that define them. This study assessed the effect of applying modified atmospheres and low temperatures (refrigeration and freezing) on the quality of 4 PEVOO for 24 months. Also, the effect of two freezing methods was studied (in the freezer at − 20 °C and in a bath of liquid nitrogen), along with the impact of freezing on the quality of the oils after thawing and storing at room temperature. Official quality parameters, organoleptic assessment, phenolic compounds, volatile compounds and oxidative stability index were measured periodically. While no significant effect of headspace composition was found, the oils stored at − 20 °C maintained their initial quality better than the oils stored at room temperature. Physicochemical quality parameters remained unchanged throughout the 24 months at − 20 °C. Polar phenolic and volatile compounds associated with green and fruity aromas were better preserved at − 20 °C, which translated into a minimum change in the sensory profile of the oils. While no significant difference was observed regarding oxidative parameters, freezing at − 20 °C maintained the initial volatile and sensory profile of the oils better than freezing with liquid nitrogen. Lastly, quality of thawed oils showed no significant differences compared to control oils during storage at room temperature. In conclusion, storage at − 20 °C maintains the quality of PEVOO, especially their sensory profile, and does not compromise their quality after thawing.
Carbon sequestration and storage in biomass is one of the most important measures to mitigate climate change. Mediterranean woody crops can sequestrate carbon in the biomass of their permanent structures for decades; however, very few studies have focused on an assessment of biomass and carbon sequestration in these types of crops. This study is the first to estimate above- and belowground biomass carbon stock in Mediterranean woody crops through a bottom-up approach in the NE Iberian Peninsula in 2013. Moreover, this is the first time that an assessment of the annual changes in carbon stock in the study area over a six-year period is presented. For this purpose, eight crop- and site-specific equations relating biomass or biometric variables to crop age were calculated. Most of the data were our own measurements, but unpublished data supplied from other authors as well as data from literature were also considered. Census of Agriculture data was used to scale results from individual data up to the municipality level at the regional scale. Results show that in woody cropland in NE Spain the total biomass carbon stock in 2013 was 5.48 Tg C, with an average value of 16.44 ± 0.18 Mg C ha−1. Between 2013 and 2019, although there was a 2.8% mean annual decrease in the area covered by woody crops, the carbon stock in the biomass of these crops increased annually by 3.8% due to the growth of the remaining woody cropland. This new estimation of carbon stocks may contribute to better understand carbon balances and serve as a baseline to global inventories. It may also serve to assess and manage carbon storage as an ecosystem service provided by Mediterranean woody cropland for mitigating climate change and, in combination with adaptive strategies, for supporting a productive and resilient agro-food system.
Campylobacter on poultry meat needs to be controlled to reduce the risk of infection caused by the consumption of chicken meat. Pulsed light (PL) application on poultry meat was studied to control Campylobacter spp. The effect of this technology was evaluated regarding poultry meat colour and volatile compound changes. Two breast sample groups were prepared: inoculated with Campylobacter (107 bacteria of Campylobacter jejuni strains) and not inoculated. Samples were submitted to PL, five pulses/s of 300 ms, 1 Hz, and 1 J/cm2 in the apparatus, PL Tecum unit (Claranor). A response surface experimental design was applied regarding the factors of voltage (1828 to 3000 W) and distance to the source UV lamp (2.6 to 5.4 cm). The binomial factorial treatment (voltage and distance) with PL induced different energy doses (fluence J/cm2) received by samples, 2.82 to 9.67 J/cm2. Poultry meat pulsed light treated had a significant decrease of Enterobacteriaceae counts. The treatments applied were unable to reduce 1 log Campylobacter cfu/g of poultry meat. The poultry meat PL treated became slightly light, redder, and yellower than those not treated. PL can decrease the proportion of aldehydes on total volatiles in meat, particularly on those associated with chicken-like, chicken skin-like, and sweet odour notes in fresh poultry meat. Further studies of PL with higher energy doses will be necessary to confirm if there are Campylobacter reductions and about poultry meat treated under storage to evaluate if volatile compounds can affect the flavour of PL-treated meat samples.
Reduced river discharge and flow regulation are significant threats to freshwater biodiversity. An accurate representation of potential damage of water consumption on freshwater biodiversity is required to quantify and compare the environmental impacts of global value chains. The effect of discharge reduction on fish species richness was previously modeled in life cycle impact assessment, but models were limited by the restricted geographical scope of underlying species-discharge relationships and the small number of species data. Here, we propose a model based on a novel regionalized species-discharge relationship (SDR). Our SDR-based model covers 88 % of the global landmass (2320 river basins worldwide excluding deserts and permanently frozen areas) and is based on a global dataset of 11,450 riverine fish species, simulated river discharge, elevation, and climate zones. We performed 10-fold cross-validation to select the best set of predictors and validated the obtained SDRs based on observed discharge data. Our model performed better than previous SDRs employed in life cycle impact assessment (Kling-Gupta efficiency coefficient about 4 times larger). We provide both marginal and average models with their uncertainty ranges for assessing scenarios of small and large-scale water consumption, respectively, and include regional and global species loss. We conducted an illustrative case study to showcase the method's applicability and highlight the differences with the currently used approach. Our models are useful for supporting sustainable water consumption and riverine fish biodiversity conservation decisions. They enable a more specific, reliable, and complete impact assessment by differentiating impacts on regional riverine fish species richness and irreversible global losses, including up-to-date species data, and providing spatially explicit values with high geographical coverage.
A total of 2,880 one-day-old male and female broiler chicks from two breeds, Ross308 and Cobb500 were randomly assigned to 72 pens. Broilers were offered three diets: a wheat-soybean diet without (CO), or with either a probiotic (probiotic; 2.4 x 10 ⁹ CFU/kg diet of Bacillus subtilis DSM32324 and DSM32325 and B. amyloliquefaciens DSM25840) or a phytobiotic (phytobiotic; grape extract with 165 ppm procyanidin and 585 ppm polyphenol) product. The trial was conducted with a 3 × 2 × 2 factorial arrangement of diet, breed and sex in a completely randomized design and consisted of 6 replicate-pens per treatment (40 birds per pen). At day 7, 21, and 35, one chicken per pen was slaughtered for caecal sampling to quantify bacterial metabolites (digesta) as well as evaluate mRNA abundance and histomorphology (tissue). Data were subjected to ANOVA using GLM procedure to evaluate age, diet, breed and sex and their interactions. Spearman’s correlation (r) was analyzed between metabolite concentration and mRNA abundance. Overall, the concentration of short chain fatty acids increased with age, while lactate decreased from day 7 to 21 ( p < 0.05). The mRNA abundance of IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, IL-17α, IL-18, IFN-γ and TGF-β2 increased with age but IL-1β and TNF-α increased in abundance from day 7 to 21 and then decreased ( p < 0.05). Abundance of MUC2 and CLDN5 increased after day 21 ( p < 0.05). Caecal crypt depth increased with age ( p < 0.05). Acidic goblet cell (GC) number peaked at day 21 ( p < 0.05), while mixed GC number was not affected by age. A few impacts of breed, diet and interactions on the investigated variables showed no meaningful biological pattern. Propionate positively correlated with all cytokines investigated (r = 0.150–0.548), except TNF-α. Lactate negatively correlated with pro-inflammatory cytokines like IL-1β (r = −0.324). Aging affected caecal histomorphology, bacterial activity and genes responsible for barrier integrity and inflammatory response. This effect could be attributed to the interaction between gut microbiota and immune system as well as the direct effect of metabolites on gut histomorphology and cytokine mRNA abundance.
Fast optimisation of farming practices is essential to meet environmental sustainability challenges. Hologenomics, the joint study of the genomic features of animals and the microbial communities associated with them, opens new avenues to obtain in-depth knowledge on how host-microbiota interactions affect animal performance and welfare, and in doing so, improve the quality and sustainability of animal production. Here, we introduce the animal trials conducted with broiler chickens in the H2020 project HoloFood, and our strategy to implement hologenomic analyses in light of the initial results, which despite yielding negligible effects of tested feed additives, provide relevant information to understand how host genomic features, microbiota development dynamics and host-microbiota interactions shape animal welfare and performance. We report the most relevant results, propose hypotheses to explain the observed patterns, and outline how these questions will be addressed through the generation and analysis of animal-microbiota multi-omic data during the HoloFood project.
A trial was conducted to analyze the effect of the inclusion of yeast and spent grain obtained from breweries in feeds for rainbow trout ( Oncorhynchus mykiss ), taking into account the availability of these by-products, produced in large quantities in Europe. The ingredients were assayed in both dried and hydrolyzed format and compared with a commercial dried or hydrolyzed yeast. According to the results, the inclusion of 20% yeast and 15% spent grain in the feed, formulated with only 15% inclusion of fish meal, produced similar results in growth among all the groups, a food conversion significantly lower for the control and spent grain formulated feeds, and rainbow trout muscle composition similar to the fish fed with a control commercial feed and showed a protein digestibility of 87%–89% without differences with the commercial yeast. Hydrolysis of the ingredients had no effects on the protein digestibility of the feeds. Protein digestibility of the ingredients was lower for spent grain. An inclusion rate not higher than 15% for spent grain is recommended. These industrial by-products can be a good source to reduce the use of plant-based ingredients and increase the sustainability of both sectors, brewery industry, and aquaculture.
The aim of this study was to investigate whether tactile stimulation in rabbits during the gestation phase improve the maternal behavior and human-animal relationships as well as the effects on reproductive behavior of male kits when reached maturity compared to induced stress. A total of 33 primiparous New Zealand does were selected after pregnancy confirmation and allocated in a randomized complete block design. The treatments applied were as follows: (C) animals not stimulated during the experimental period; (TS) animals that received tactile stimulation; and (SS) does which were immobilized. The nest building behavior as well as the weight, sexual behavior, mortality, and semen analysis of the offspring was recorded. In addition, the novel object, flight distance, social isolation, and human-approach tests were conducted. Under the conditions of the present trial, TS animals showed more trust in the unfamiliar observer when compared to the other two treatments. The treatments applied to the females (TS and SS) were sufficient to confirm that the control group presented better values for the number of stillbirths and the proportion of deaths in the first week. Finally, the handling of does reduce the males’ ejaculation and sperm presence but not inhibited sexual behavior or impaired semen quality. It is possible to conclude that TS did not impair does welfare or maternal behavior and it improved the human-animal relationship, however there was a negative impact on the litter. More studies that directly assess impact on the future reproductive capacity of the offspring are necessary.
Human activities put pressure on the natural environmental and the Life Cycle Assessment methodology (LCA) is becoming a more prevalent tool to assess the relevant environmental impacts from products and processes on terrestrial, marine and freshwater ecosystems. The Global Life Cycle Impact Assessment Method (GLAM) project of the Life Cycle Initiative hosted by the UN Environment Programme aims at making recommendations for new impact assessment models (such as for land use, water consumption and eutrophication) and improving the consistency and comparability across impact categories. An important aspect to ensure the comparability of these categories across geographic regions is to identify and quantify the scale of impacts, i.e., distinguish if an impact to an area results in local species losses or global species extinctions. This distinction is of high relevance because a species lost at a local level may still exist in other regions of the world and could potentially reestablish in that area, whereas global extinctions are irreversible. A consistent approach to scale impacts from local to global scales is currently not implemented within the LCIA framework, but is crucial to appropriately consider potential biodiversity impacts across impact categories. Here we present an updated approach for calculating a scaling factor, called the Global Extinction Probability (GEP), and calculate it for more than 98 000 species in 20 species groups across marine, terrestrial and freshwater ecosystems. We also provide the GEPs for different spatial scales, such as grid cells, ecoregions or watersheds and country averages. We found that GEP varies over orders of magnitude across the world, emphasizing the relevance of considering the spatial dimension of such extinction probabilities. We recommend quantifying global extinctions based on local species loss by multiplying local species loss within a certain spatial unit with the GEP corresponding to the same spatial unit. GEPs harmonize the quantification of biodiversity impacts across impact categories, improving information to support environmental decision-making.
Rice cultivation is a major source of methane (CH4) emissions. Intermittent irrigation systems in rice cultivation, such as the mid-season drainage (MSD), are effective strategies to mitigate CH4 emissions during the growing season, though the reduction rates are variable and dependent on the crop context. Aeration periods induce alteration of soil CH4 dynamics that can be prolonged after flooding recovery. However, whether these changes persist beyond the growing season remains underexplored. A field experiment was conducted in Spain to study the effect of MSD implemented during the rice growing season on greenhouse gas (GHG) emissions in relation to the standard permanently flooded water management (PFL). Specifically, the study aimed at (1) assessing the CH4 mitigation capacity of MSD in the studied area and (2) testing the hypothesis that the mitigating effect of MSD can be extended into the following winter flooded fallow season. Year-round GHG sampling was conducted, seasonal and annual cumulative emissions of CH4 and N2O as well as the global warming potential were calculated, and grain yield was measured. MSD reduced growing season CH4 emissions by ca. 80% without yield penalties. During the flooded fallow season, MSD reduced CH4 emissions by ca. 60%, despite both fields being permanently flooded. The novelty of our observations lies in the amplified mitigation capacity of MSD by extending the CH4 mitigation effect to the following flooded winter fallow season. This finding becomes especially relevant in rice systems with flooded winter fallow season given the large contribution of this season to the annual CH4 emissions.
Legume/cereal intercropping has the potential to maximize the use of resources to raise yields due to enhanced nitrogen (N) fixation by legume root nodules, while high N fertilization may inhibit the nodulation of legume. However, whether legume/cereal intercropping can promote the accumulation of soil N storage with N fertilization and its underlying mechanism are less clear. Here, we evaluated the long-term (5 years) effects of maize/peanut intercropping and mineral N fertilization on peanut soil total N content and soil N cycling functional genes. The experiment includes two planting patterns (peanut maize intercropping and peanut monocropping) with three N fertilization rates (0, 150, and 300 kg N ha⁻¹). Intercropping increased soil total N content (STN) by average 18.2%, and the positive effect of intercropping on STN decreased with N application rate. Highest N application decreased the nodule fresh weight (NFW) by 64.3% and 46.0% in intercropping and monocropping system, respectively. However, intercropping has no effect on NFW. Intercropping increased the nifH gene abundance by average 26.5%. SEM analysis indicated that NFW and nifH gene abundance combined can explain 46% of the variance of STN. Our results indicate that biological N fixation but not mineral N fertilization enhances the accumulation of N in soil planted with peanut in maize/peanut intercropping system.
Recombinant protein production in bacteria is often accompanied by the formation of aggregates, known as inclusion bodies (IBs). Although several strategies have been developed to minimize protein aggregation, many heterologous proteins are produced in aggregated form. For these proteins, purification necessarily requires processes of solubilization and refolding, often involving denaturing agents. However, the presence of biologically active recombinant proteins forming IBs has driven a redefinition of the protocols used to obtain soluble protein avoiding the protein denaturation step. Among the different strategies described, the detergent n-lauroylsarcosine (NLS) has proved to be effective. However, the impact of the NLS on final protein quality has not been evaluated so far. Here, the activity of three antimicrobial proteins (all as GFP fusions) obtained from the soluble fraction was compared with those solubilized from IBs. Results showed that NLS solubilized proteins from IBs efficiently, but that protein activity was impaired. Thus, a solubilization protocol without detergents was evaluated, demonstrating that this strategy efficiently solubilized proteins embedded in IBs while retaining their biological activity. These results showed that the protocol used for IB solubilization has an impact on final protein quality and that IBs can be solubilized through a very simple step, obtaining fully active proteins.
The present work focused on the identification of durum wheat QTL hotspots from a collection of genome-wide association studies, for quality traits, such as grain protein content and composition, yellow color, fiber, grain microelement content (iron, magnesium, potassium, selenium, sulfur, calcium, cadmium), kernel vitreousness, semolina, and dough quality test. For the first time a total of 10 GWAS studies, comprising 395 marker-trait associations (MTA) on 57 quality traits, with more than 1,500 genotypes from 9 association panels, were used to investigate consensus QTL hotspots representative of a wide durum wheat genetic variation. MTA were found distributed on all the A and B genomes chromosomes with minimum number of MTA observed on chromosome 5B (15) and a maximum of 45 on chromosome 7A, with an average of 28 MTA per chromosome. The MTA were equally distributed on A (48%) and B (52%) genomes and allowed the identification of 94 QTL hotspots. Synteny maps for QTL were also performed in Zea mays, Brachypodium, and Oryza sativa, and candidate gene identification allowed the association of genes involved in biological processes playing a major role in the control of quality traits.
This paper highlights the potential of using polarimetric methods for the inspection of plant diseased tissues. We show how depolarizing observables are a suitable tool for the accurate discrimination between healthy and diseased tissues due to the pathogen infection of plant samples. The analysis is conducted on a set of different plant specimens showing various disease symptoms and infection stages. By means of a complete image Mueller polarimeter, we measure the experimental Mueller matrices of the samples, from which we calculate a set of metrics analyzing the depolarization content of the inspected leaves. From calculated metrics, we demonstrate, in a qualitative and quantitative way, how depolarizing information of vegetal tissues leads to the enhancement of image contrast between healthy and diseased tissues, as well as to the revelation of wounded regions which cannot be detected by means of regular visual inspections. Moreover, we also propose a pseudo-colored image method, based on the depolarizing metrics, capable to further enhance the visual image contrast between healthy and diseased regions in plants. The ability of proposed methods to characterize plant diseases (even at early stages of infection) may be of interest for preventing yield losses due to different plant pathogens.
Struvite (St) recovered from wastewaters is a sustainable option for phosphorus (P) recovery and fertilization, whose solubility is low in water and high in environments characterized by a low pH, such as acidic soils. To broaden the use of struvite in the field, its application as granules is recommended, and thus the way of application should be optimized to control the solubility. In this study struvite slow-release fertilizers were designed by dispersing St particles (25, 50, and 75 wt%) in a biodegradable and hydrophilic matrix of thermoplastic starch (TPS). It was shown that, in citric acid solution (pH = 2), TPS promoted a steadier P-release from St compared to the pure St pattern. In a pH neutral sand, P-diffusion from St-TPS fertilizers was slower than from the positive control of triple superphosphate (TSP). Nevertheless, St-TPS featured comparable maize growth (i.e. plant height, leaf area, and biomass) and similar available P as TSP in sand after 42 days of cultivation. These results indicated that St-TPS slow P release could provide enough P for maize in sand, achieving a desirable agronomic efficiency while also reducing P runoff losses in highly permeable soils.
There is a growing realisation that the complexity of model ensemble studies depends not only on the models used, but also on the experience and approach used by modellers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modellers in a model ensemble study where twelve process-based biogeochemical models were compared across five successive calibration stages. The modellers shared a common level of agreement about the importance of the variables used to initialise their models for calibration. However, we found inconsistency among modellers when judging the importance of input variables across the different calibration stages. The level of subjective weighting attributed by modellers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as fertilisation rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks were statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, net ecosystem exchange, varied significantly according to the length of the modeller’s experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modellers, with cognitive bias in “trial-and-error” calibration routines. Our study highlights that overlooked human and social attributes is critical in the outcomes of modelling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterisation are important, we contend that (1) the modeller’s assumptions on the extent to which parameters should be altered, and (2) modeller perceptions of the importance of model parameters, are just as critical in obtaining a quality model calibration as numerical or analytical details.
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371 members
Simo Alegre
  • Fruit Production Programme
Jose A. Garcia-Regueiro
  • Functionality and Nutrition Programme
Luis Guerrero
  • Process Technology Unit
Nuria Agusti
  • Sustainable Plant Protection Programme
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