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Livestock expresses complex traits influenced by several factors. The response of animals to variations in climatic factors, such as increases in temperature, may induce heat stress conditions. In this study, animals living at different temperatures were compared using the genome-wide Wright fixation index (FST). A total of 825 genotypes of Sarda breed ewes were divided into two groups based on the flocks’ average temperature over a 20-year period to compute the FST: 395 and 430 sheep were represented in colder and hotter groups, respectively. After LOWESS regression and CONTROL CHART application, 623 significant markers and 97 selection signatures were found. A total of 280 positional candidate genes were retrieved from a public database. Among these genomic regions, we found 51 annotated genes previously associated with heat stress/tolerance in ruminants (FCGR1A, MDH1, UGP2, MYO1G, and HSPB3), as well as immune response and cellular mechanisms related to how animals cope with thermal stress (RIPK1, SERPINB1, SERPINB9, and PELI1). Moreover, other genes were associated with milk fat (SCD, HERC3, SCFD2, and CHUK), body weight, body fat, and intramuscular fat composition (AGPAT2, ABCD2, MFAP32, YTHDC1, SIRT3, SCD, and RNF121), which might suggest the influence of environmental conditions on the genome of Sarda sheep.

Biochar can be useful for the functional recovery of soils contaminated with potentially toxic elements (PTEs), even if its effectiveness is variable and sometimes limited, and conflicting results have been recently reported. To shed some light on this regard, softwood-derived biochar was added at 2.5 (2.5-Bio) and 5.0% w/w (5.0-Bio) rates to an acidic (pH 5.74) soil contaminated by Cd (28 mg kg−1), Pb (10,625 mg kg−1), and Zn (3407 mg kg−1). Biochar addition increased soil pH, available P and CEC, and reduced labile Cd, Pb, and Zn (e.g., by 27, 37, and 46% in 5.0-Bio vs. the unamended soil). The addition of biochar did not change the number of total heterotrophic bacteria, actinomycetes, and fungi, while it reduced the number of Pseudomonas spp. and soil microbial biomass. Dehydrogenase activity was reduced in amended soils (e.g., by ~60 and 75% in 2.5- and 5.0-Bio, respectively), while in the same soils, urease increased by 48 and 78%. Approximately 16S rRNA gene amplicon sequencing and the Biolog community-level physiological profile highlighted a significant biochar impact (especially at a 5% rate) on soil bacterial diversity. Tomato (but not triticale) yield increased in the amended soils, especially in 2.5-Bio. This biochar rate was also the most effective at reducing Cd and Pb concentrations in shoots. Overall, these results demonstrate that 2.5% (but not 5.0%) biochar can be useful to restore the soil chemical fertility of PTE-polluted soils with limited (or null) impact on soil microbial and biochemical parameters.

The agro-livestock sector produces about one third of global greenhouse gas (GHG) emissions. Since more energy is needed to meet the growing demand for food and the industrial revolution in agriculture, renewable energy sources could improve access to energy resources and energy security, reduce dependence on fossil fuels, and reduce GHG emissions. Hydrogen production is a promising energy technology, but its deployment in the global energy system is lagging. Here, we analyzed the theoretical and practical application of green hydrogen generated by electrolysis of water, powered by renewable energy sources, in the agro-livestock sector. Green hydrogen is at an early stage of development in most applications, and barriers to its large-scale deployment remain. Appropriate policies and financial incentives could make it a profitable technology for the future.

Individual dry matter intake (DMI) is a relevant factor for evaluating feed efficiency in livestock. However, the measurement of this trait on a large scale is difficult and expensive. DMI, as well as other phenotypes, can be predicted from milk spectra. The aim of this work was to predict DMI from the milk spectra of 24 lactating Sarda dairy sheep ewes. Three models (Principal Component Regression, Partial Least Squares Regression, and Stepwise Regression) were iteratively applied to three validation schemes: records, ewes, and days. DMI was moderately correlated with the wavenumbers of the milk spectra: the largest correlations (around ±0.30) were observed at ~1100–1330 cm−1 and ~2800–3000 cm−1. The average correlations between real and predicted DMI were 0.33 (validation on records), 0.32 (validation on ewes), and 0.23 (validation on days). The results of this preliminary study, even if based on a small number of animals, demonstrate that DMI can be routinely estimated from the milk spectra.

A total of 112 dogs (49 males and 63 females) belonging to different breeds (i.e., Boxer, Cirneco dell’Etna, Fonni’s Dog, Labrador, Crossbreed, German Shepherd, Pit Bull, Shar-Pei, Yorkshire) were analyzed to compare the serum concentration of serotonin, dopamine, norepinephrine, prolactin, beta-endorphins, thyroxine (T4), triiodothyronine (T3), thyroid-stimulating hormone (TSH), and assess whether these parameters can be correlated with the behavioral phenotype of the investigated breeds. T4 was above or below the threshold in 61% and 14% of dogs, respectively; T3, in contrast, 41% of dogs showed values below the limit, while 26% above it. TSH was within the reference range in 58% of dogs; 94% of the dogs had prolactin in the reference range and only five animals showed values above the limit. For beta-endorphins, 49% of dogs had values above the limit, while 46% had values within the reference range. Serotonin and dopamine values below physiological limits were found in 62% and 70% of dogs, respectively. Finally, 61% of the dogs showed norepinephrine values within the reference range. The study confirmed that the assessment of the serum values of hormones and neurotransmitters in dogs could be useful to better understand the behavioral phenotype of the animal and could be useful for breeders and trainers for the selection of the most suitable subjects for specific tasks.

In this study, we investigated the sorption–desorption behavior of imazamox (IMZ) and 2,4-DB (DB) in two typical acidic Mediterranean agricultural soils and the impact of these herbicides on culturable soil bacterial populations, enzyme activities and functional diversity when applied at concentrations higher than recommended doses (10×, 50×, 500×). Herbicide sorption was similar in both soils and IMZ was less retained compared to DB (~0.5 vs. 40 µg g−1 soil, respectively). IMZ desorption was remarkable (70–100%) while that of DB was more limited, i.e., ~40%. Three days after spiking (DAS), IMZ and DB significantly increased the number of soil-culturable heterotrophic bacteria, actinomycetes and Pseudomonas spp., soil respiration and the potential catabolic capacity of soil microbial communities. Soil dehydrogenase activity increased by ~56–70% in IMZ-treated soils while being reduced by ~33–41% in DB-treated ones. β-glucosidase activity showed a soil-dependent behavior, while the pattern of C source utilization suggested a change of soil microbial community structure after herbicide (especially DB) spiking. At 30 DAS, the herbicides’ impact on soil microorganisms, enzyme activity and functional diversity was still visible. Moreover, a toxic effect of DB (at 50× and 500×), but not IMZ, was recorded vs. Rhizobium sullae, the bacterial symbiont of Hedysarum coronarium. The obtained results indicated that IMZ and DB are poorly sorbed and highly desorbed by both soils. Moreover, at the tested concentrations, IMZ and DB can have short- and medium-term impacts on the microbial component and the related activity of the investigated soils, likely affecting a range of ecosystem services provided by soil microorganisms.

The inbreeding coefficient is an important parameter for livestock management. Small ruminant breeders and associations mainly rely on pedigree information, but genomic tools are gaining relevance, overcoming possible pedigree inconsistencies. This study investigates the relationship between pedigree-based and genomic inbreeding in two goat and four sheep dairy breeds. Pedigree and genomic data (medium-density SNPchip) were obtained for 3107 goats and 2511 sheep. We estimated pedigree depth (number of fully traced generations, FullGen) and inbreeding (FPED), as well as two genomic inbreeding indexes, using runs of the homozygosity (FROH) and genomic relationship matrix (FGRM). The correlation between the inbreeding coefficients was assessed. A linear regression model (LRM) was fitted for estimating FPED from FROH. After quality control on genomic data, we retained 5085 animals. Mean inbreeding values were low, with higher FROH than FPED and FGRM. Breed differences can partially depend on different managements. The correlation between FPED and FROH was the highest and directly related to pedigree depth. The best LRM was chosen for FullGen ≥4 and ≥6 for goats and sheep, respectively; after excluding animals with extreme residuals, a new refined regression equation was calculated. Since massive genotyping is not affordable to small ruminant breeders, it is important to understand the distinction and relationship between differently calculated inbreeding coefficients, also in view of the introduction of genomic enhanced breeding values. Our study highlights the importance of accurate pedigree information and, especially if not obtainable, of calculating genomic-based inbreeding coefficients. A better estimation of animals’ relatedness contributes to improve animal breeding and conservation.

Copper (Cu) is a ubiquitous trace element in the aquatic environment, and is usually found at low levels. Copper environmental concentrations can be altered as a result anthropogenic activities. Shellfish are useful bioindicators to ensure adequate environmental monitoring. Thus, the aim of the present study was as follows: (a) determine the LC50 of copper(I) chloride in grooved carpet shell (Ruditapes decussatus) collected in the Santa Gilla lagoon (Sardinia, Italy), and (b) analyze the antioxidant biomarkers in digestive gland and gills of same specimens exposed to different concentrations of the above-mentioned metal (0.045, 0.45, and 0.90 mg/L) for 96 h. A withdrawal period of 96 h was considered for the treated clam, carrying out the same biochemical analyses, superoxide dismutase (SOD), catalase (CAT), selenium-dependent glutathione peroxidase (Se-GPx), glutathione S-transferases (GSTs), and total glutathione (GSH+2GSSG) in the two tissues. Different time and dose responses of the antioxidant biomarkers were recorded in the digestive glands and gills. Oxidative stress biomarkers highlighted the ability of Cu to induce oxidative stress in R. decussatus. Clam, following the withdrawal period of 96 h, has not been able to achieve the control levels of all biochemical markers in the digestive gland and gills. R. decussatus can be a suitable model to assess the ecotoxicity of copper in aquatic ecosystems. These findings may advance knowledge on the role and the effects of copper on oxidative stress biomarkers in grooved carpet shell. The metal ecotoxicity response can be useful to perform accurate biomarker-based monitoring programs using this bivalve species.

Defining optimal nutrition in animals and humans remains a main scientific challenge. The objective of the work was to develop a dynamic model of reactive oxygen species (ROS)–polyunsaturated fatty acid (PUFA)–antioxidant homeostasis using the rabbit as a model. The problem entity was to evaluate the main metabolites generated from interactions between traits included in the conceptual model and identified by three main sub–models: (i) ROS generation, (ii) PUFA oxidation and (iii) antioxidant defence. A mathematical model (VENSIM software) that consisted of molecular stocks (INPUTs, OUTPUTs), exchange flows (intermediate OUTPUTs) and process rates was developed. The calibration was performed by using standard experimental data (Experiment 1), whereas the validation was carried out in Experiments 2 and 3 by using supra–nutritional dietary inputs (VIT E+ and PUFA+). The accuracy of the models was measured using 95% confidence intervals. Analytical OUTPUTs (ROS, PUFA, Vit E, Ascorbic acid, Iso–/NeuroProstanes, Aldehydes) were well described by the standard model. There was also good accuracy for the VIT E+ scenario, whereas some compensatory rates (Kc1–Kc4) were added to assess body compensation when high levels of dietary PUFA were administered (Experiment 3). In conclusion, the model can be very useful for predicting the effects of dietary treatments on the redox homeostasis of rabbits.

Annual and interannual dynamics of shellfish toxins and associated harmful algal species (HAS) were analyzed from 2015 to 2020 in Tortolì Lagoon (Sardinia, west Mediterranean Sea). Analysis of seasonal occurrence of different harmful algae, such as Dinophysis spp., Prorocentrum spp., Pseudo-nitzschia spp. and Alexandrium minutum, was performed. The species Dinophysis acuminata and Dinophysis sacculus were responsible for the accumulation of lipophilic toxins belonging to the okadaic acid group (OAs) and pectenotoxins2 (PTX2) in bivalve mollusks. The highest HAS detection was recorded in the winter months; in particular, Dinophysis spp. was mostly present in January–February. Out of 1090 analyzed mollusk samples, 39 were non-compliant, exceeding the legal limits (160 μg OA eq/kg e.p.) reported in Regulation 853/2004 of the European Commission. A statistical analysis related to the presence of OA and PTX2 in mollusks with various environmental parameters (pH, water temperature, dissolved oxygen, algal density) was implemented, proving a clear winter seasonality. The present study highlights the necessity to better understand the different factors able to influence the production and accumulation of toxins in bivalve mollusks bred in an important Sardinian production area. The contribution of this research is important not only from an environmental and productive point of view but also from the view of implementing management in order to mitigate any harm to human health.

The concept of welfare applied to farm animals has undergone a remarkable evolution. The growing awareness of citizens pushes farmers to guarantee the highest possible level of welfare to their animals. New perspectives could be opened for animal welfare reasoning around the concept of domestic, especially farm, animals as partial human artifacts. Therefore, it is important to understand how much a particular behavior of a farm animal is far from the natural one of its ancestors. This paper is a contribution to better understand the role of genetics of the farm animals on their behavior. This means that the naïve approach to animal welfare regarding returning animals to their natural state should be challenged and that welfare assessment should be considered.

The ultimate goal of genetic selection is to improve genetic progress by increasing favorable alleles in the population. However, with selection, homozygosity, and potentially harmful recessive alleles can accumulate, deteriorating genetic variability and hampering continued genetic progress. Such potential adverse side effects of selection are of particular interest in populations with a small effective population size like the Romosinuano beef cattle in Mexico. The objective of this study was to evaluate the genetic background and inbreeding depression in Mexican Romosinuano cattle using pedigree and genomic information. Inbreeding was estimated using pedigree (FPED) and genomic information based on the genomic relationship matrix (FGRM) and runs of homozygosity (FROH) of different length classes. Linkage disequilibrium (LD) was evaluated using the correlation between pairs of loci, and the effective population size (Ne) was calculated based on LD and pedigree information. The pedigree file consisted of 4875 animals born between 1950 and 2019, of which 71 had genotypes. LD decreased with the increase in distance between markers, and Ne estimated using genomic information decreased from 610 to 72 animals (from 109 to 1 generation ago), the Ne estimated using pedigree information was 86.44. The reduction in effective population size implies the existence of genetic bottlenecks and the decline of genetic diversity due to the intensive use of few individuals as parents of the next generations. The number of runs of homozygosity per animal ranged between 18 and 102 segments with an average of 55. The shortest and longest segments were 1.0 and 36.0 Mb long, respectively, reflecting ancient and recent inbreeding. The average inbreeding was 2.98 ± 2.81, 2.98 ± 4.01, and 7.28 ± 3.68% for FPED, FGRM, and FROH, respectively. The correlation between FPED and FGRM was −0.25, and the correlations among FPED and FROH of different length classes were low (from 0.16 to 0.31). The correlations between FGRM and FROH of different length classes were moderate (from 0.44 to 0.58), indicating better agreement. A 1% increase in population inbreeding decreased birth weight by 0.103 kg and weaning weight by 0.685 kg. A strategy such as optimum genetic contributions to maximize selection response and manage the long-term genetic variability and inbreeding could lead to more sustainable breeding programs for the Mexican Romosinuano beef cattle breed.

Arthrogryposis and macroglossia are congenital pathologies known in several cattle breeds, including Piemontese. As variations in single genes were identified as responsible for arthrogryposis in some breeds, we decided: (i) to test the hypothesis of a similar genetic determinism for arthrogryposis in the Piemontese breed by genotyping affected and healthy animals with a high-density chip and applying genome-wide association study (GWAS), FST and canonical discriminant analysis (CDA) procedures, and (ii) to investigate with the same approach the genetic background of macroglossia, for which no genetic studies exist so far. The study included 125 animals (63 healthy, 30 with arthrogryposis, and 32 with macroglossia). Differently from what reported for other breeds, the analysis did not evidence a single strong association with the two pathologies. Rather, 23 significant markers on different chromosomes were found (7 associated to arthrogryposis, 11 to macroglossia, and 5 to both pathologies), suggesting a multifactorial genetic mechanism underlying both diseases in the Piemontese breed. In the 100-kb interval surrounding the significant SNPs, 20 and 26 genes were identified for arthrogryposis and macroglossia, respectively, with 12 genes in common to both diseases. For some genes (NTN3, KCNH1, KCNH2, and KANK3), a possible role in the pathologies can be hypothesized, being involved in processes related to muscular or nervous tissue development. The real involvement of these genes needs to be further investigated and validated.

Genome-wide association studies (GWAS) are traditionally carried out by using the single marker regression model that, if a small number of individuals is involved, often lead to very few associations. The Bayesian methods, such as BayesR, have obtained encouraging results when they are applied to the GWAS. However, these approaches, require that an a priori posterior inclusion probability threshold be fixed, thus arbitrarily affecting the obtained associations. To partially overcome these problems, a multivariate statistical algorithm was proposed. The basic idea was that animals with different phenotypic values of a specific trait share different allelic combinations for genes involved in its determinism. Three multivariate techniques were used to highlight the differences between the individuals assembled in high and low phenotype groups: the canonical discriminant analysis, the discriminant analysis and the stepwise discriminant analysis. The multivariate method was tested both on simulated and on real data. The results from the simulation study highlighted that the multivariate GWAS detected a greater number of true associated single nucleotide polymorphisms (SNPs) and Quantitative trait loci (QTLs) than the single marker model and the Bayesian approach. For example, with 3000 animals, the traditional GWAS highlighted only 29 significantly associated markers and 13 QTLs, whereas the multivariate method found 127 associated SNPs and 65 QTLs. The gap between the two approaches slowly decreased as the number of animals increased. The Bayesian method gave worse results than the other two. On average, with the real data, the multivariate GWAS found 108 associated markers for each trait under study and among them, around 63% SNPs were also found in the single marker approach. Among the top 118 associated markers, 76 SNPs harbored putative candidate genes.