Sustainable Livestock Production Systems Research Articles

Deciphering the molecular mechanisms of heat stress tolerance in goats: Insights from transcriptome and Gene Co-expression analysis

Climate change poses a significant threat to the sustainability of livestock production systems in developing countries, particularly impacting small ruminants like goats, which are highly susceptible to heat stress. This stressor not only reduces productivity but also undermines economic viability. This study aimed to delve into the molecular mechanisms underlying heat stress tolerance in goats by conducting a comprehensive transcriptome analysis of heat-tolerant (HT, n = 4) and heat-susceptible (HS, n = 6) Jamunapari goats. Physiological metrics, such as rectal temperature, respiratory rate, and heart rate, were meticulously monitored under extreme environmental conditions (Temperature Humidity Index >92) to effectively classify goats based on their distinct heat stress responses. Samples of blood were obtained, and peripheral blood mononuclear cells (PBMCs) were extracted for subsequent RNA extraction. RNA-Seq analysis revealed a sum of 734 differentially expressed genes (DEGs), comprising 251 upregulated and 483 downregulated genes in HT goats compared to their HS counterparts. The WGCNA revealed three key modules, darkorange (tolerance), paleturquoise (respiration rate), and darkmagenta (heart rate). Moreover, functional enrichment analysis revealed that DEGs within these modules played intricate roles in crucial biological processes and pathways, including mitochondrial function, cardiac function, immune response, genomic stability, and metabolic regulation. This research notably enhances our comprehension of the genetic underpinnings of thermo-tolerance in goats and provides invaluable guidance for formulating breeding strategies aimed at bolstering livestock resilience against the challenges of climate change.

459 A new approach to measuring dry matter intake, from drylot to pasture: Activities of the alliance for regenerative livestock

Abstract The current state of feed intake measurement for cattle in confinement relies on expensive monitoring systems. There is no effective method for measuring feed intake in grazing animals. To address these limitations, our research aims to tap into the potential of passively collected data, such as data from the Internet of Things (IoT), to address practical challenges in animal agriculture. This includes improving livestock management, optimizing resource allocation, and reducing ecological footprints. The benefits of our research extend beyond improved livestock management to include reducing ecological footprints, such as water, carbon, and environmental footprints. Grazing livestock have a crucial role in nutrient cycling in grasslands and advancing more sustainable livestock production systems. This requires innovation of research methods for quantifying intakes of animals housed in a variety of systems including confinement facilities that lack expensive feed intake systems and for grazing animals. Currently, the industry standard for determining feed intake are equations published in the Nutrient Requirements of Beef Cattle (NASEM, 2016). Our recent efforts using machine learning approaches (Blake et al., 2023) dramatically outperforms the equations. Using the same dataset, the NASEM (2016) approach overestimates intake by 34%. We have developed a predictive algorithm utilizing data collected from animals in confinement where individual feed intake (ground truth) is known. We have developed machine learning models such as Repeated Measures Random Forests (RMRF) and Extreme Gradient Boosting (XGB) to better predict feed intake in confined cattle. We have also used these predictive algorithms to determine feed intake of grazing animals and animals in confinement without feed intake systems and validated the predictive value of the approach.

Economic sustainability of livestock production systems in Haryana: An indicators based assessment

Economic sustainability of livestock production systems in Haryana: An indicators based assessment

Assessment of Performance in Cereal Fodder Crops with Relation to Seeding Rates and Cutting Stages

Cereal fodder crops serve as indispensable sources of nutrition for livestock, contributing significantly to the efficiency and sustainability of animal production systems worldwide. Maximizing the productivity and quality of these crops requires careful management, with seed rates and cutting stages playing pivotal roles in determining crop performance. Seeding rates play a critical role in crop establishment and growth, with both low and high rates affecting plant competition and ultimately yield. Cutting stages, on the other hand, are pivotal in determining the quality and nutrient composition of the forage. Optimal cutting stages vary depending on the intended use, such as hay, silage, or grazing and can significantly influence digestibility and overall nutritional value. The assessment of cereal fodder crops is therefore pivotal for optimizing agricultural productivity and ensuring sustainable livestock feed production. Understanding the intricate relationship between seeding rates, cutting stages and crop performance is essential for sustainable agriculture and livestock production systems, contributing to improved resource efficiency and economic viability.

Assessing the potential of phytogenic feed additives: A comprehensive review on their effectiveness as a potent dietary enhancement for nonruminant in swine and poultry.

Phytogenic feed additives (PFAs) often referred to as phytobiotics or botanical feed additives, are natural compounds derived from various plants, herbs, spicesand other botanical sources. These feed additives are intended to serve a variety of purposes, including an immune system regulator, an antimicrobial, an antimutagenic, an antioxidantand a growth promoter. They are composed of bioactive compounds extracted from plants, including essential oils, polyphenols, terpenoidsand flavonoids. They are mostly utilized as substitute antibiotic growth promoters in nonruminant (swine and poultry) livestock production, owing to the prohibition of antibiotic usage in the feed industry. It has been thoroughly examined to ascertain their impact on intestinal health and activity, correlation with animals'effective health and well-being, productivity, food securityand environmental impact. The potential uses of these feed additives depend on the properties of herbs, the comprehension of their principal and secondary components, knowledge of their mechanisms of action, the safety of animalsand the products they produce. They are gaining recognition as effective and sustainable tools for promoting animal health and performance while reducing the reliance on antibiotics in nonruminant nutrition. Their natural origins, multifaceted benefitsand alignment with consumer preferences make them a valuable addition to modern animal farming process. However, because of their inconsistent effects and inadequate knowledge of the mechanisms of action, their usage as a feed additive has been limited. This review offers a comprehensive assessment of the applications of PFAs as an effective feed supplement in swine and poultry nutrition. In summary, this comprehensive review provides current knowledge, identifies gaps in researchand emphasizes the potential of phytogenic additives to foster sustainable and healthier livestock production systems while addressing the global concerns associated with antibiotic use in livestock farming.

Microencapsulation technology for delivery of enzymes in ruminant feed.

The ruminant digestive system is uniquely designed to make efficient use of high-fibre feed, including forages. Between 40 to 100% of the ruminant diet consists of forages which are high in fibre and up to 70% of this may remain undigested in the ruminant gut, with substantial impact on feed utilisation rate and productivity and the economic and environmental sustainability of livestock production systems. In ruminants, feed costs can make up to 70% of the overall cost of producing an animal product. Increasing feed utilisation efficiency, i.e., more production with less feed lowers feeding costs and improves livestock economic viability. Strategies for improving nutrient utilisation in animal feed has been investigated over the years. Incorporation of fibre digesting enzymes in the feed to facilitate the digestion of the residual fibre in hind gut is one of the proposed strategies. However, delivering such enzymes to the hind gut in active state is challenging due to the unfavourable biochemical environment (pH, microbial proteases) of ruminant's gastrointestinal tract. This review discusses the potential application of microencapsulation for protected and targeted delivery of enzymes into the hind gut of ruminants.

Sustainable livestock production systems are key to ensuring food security resilience in response to climate change

Sustainable livestock production systems are key to ensuring food security resilience in response to climate change

Designing grazing systems that enhance the health of New Zealand high-country grasslands

More sustainable pastoral livestock production systems are required to face the challenge of reconciling agricultural production and environmental impact. Although the need for more holistic approaches, such as systems thinking and design theory, is acknowledged, systemic research applying those theories to create healthier systems remains underexplored. A multiple steps holistic approach involving modelling, geographic information systems, and decision-making analysis was used to design, assess, and contrast alternative scenarios that represent distinct grazing management to the current grazing management of a high-country station in New Zealand used as a case study to enhance grassland health. Three alternative scenarios were created, and five main parameters used to assess grassland health were obtained from the evaluation of the designed scenarios. From all the parameters, soil erosion control and increased production were ranked as the most and least important, respectively, to be considered in the design process. A multi-criteria evaluation defined that the best-compromise scenario to enhance grassland health is the scenario with lower soil erosion, as a result of applying adaptive and flexible management at the paddock level, the lower total emission of greenhouse gases (only sheep herd grazing), and greater profitability (due to production costs reduction, as cattle were removed from the station), compared to the ‘status quo’. Our design methodology produced a variety of alternatives that enhanced the health of grasslands in different parameters while still maintaining or increasing profitability. The use of multi-criteria evaluation facilitated the decision of the most contextualised and best-compromise scenario for New Zealand high country grasslands.

39 Developing Precision Agriculture Tools to Capture Behavior and Performance in Extensively Managed Sheep

Abstract Rangeland livestock provide a great opportunity to capture resilience traits due to the significant amount of the year spent grazing a resource-limited environment where they are exposed to extreme weather, predators, and varied terrain. Capturing the ability of an individual to cope with these stressors has the potential to improve animal welfare and productivity in the face of climate change. These measurements need to occur over the course of time of an animal in such an environment or capture the sum of the ability of the animal to cope with the environment. To do this, measurements of resilience and efficiency will be a useful tool to make continued improvement in rangeland livestock through genetic selection. However, the high-throughput phenotyping typically required to capture resilience traits is challenged by the remote location, limited or no access to power and internet, and limited manpower for data collection. Therefore, such tools need to be self-sustaining, automated, and cost-effective to be able to capture data on a large number of individuals in a rangeland setting. To this end, we have been exploring the use of precision livestock tools to capture sheep performance in a rangeland environment. We are currently working on developing a portable walk-over-weighing system to automatically capture an individual’s weight that uses a combination of solar powered portable batteries and an RFID system with the aim to make a compact weighing system that can easily be transported in rough mountainous terrain. This system can be used to capture longitudinal weights in challenging environments, which can be used to develop indicators of resilience, such as the variability in weight over time or changes in weight due to chronic environmental stressors such as a heat wave. Because it is RFID-based, the data can also be used to take stock inventory to track possible predation events or other stock losses. We are also using low-cost commercial-off-the-shelf GPS units to capture animal behavior in these environments. These data can be used to derive a multitude of traits relating to land-use behavior, including water usage and daily distance traveled. The data can also be used to capture social interactions, such as ewe-lamb relationships. While the information content is high for these datatypes, there are also challenges associated with missing or unreliable data. We are currently exploring methods to combat these challenges to provide robust measurements of performance. Through these data, we aim to develop traits that integrate animal performance and behavior to identify animals that are better suited to a rangeland environment. We expect that breeding of such animals will result in a positive impact on productivity, a reduced impact on the ecosystem, and lower mortality rates, thereby improving the sustainability of livestock production systems.

Machine intelligence applied to sustainability: A systematic methodological proposal to identify sustainable animals

We consider sustainable animals those which are well-adapted to the environment, productive, feed efficient in converting foods into animal products (milk, meat, wool and honey), clinically healthy and presenting a low carbon and water footprints, having their animal welfare assured. Methodologies to identify these animals are necessary, though non-existent. Here, we develop a systematic methodological approach using several machine learning techniques to identify sustainable animals through phenotypic biomarkers for sustainable livestock production systems. Thermoregulatory, morphological, haematological, serum biochemical, hormonal and productive responses, carcass traits and feed efficiency measures of 62 bulls were collected and analyzed for this study. The database contains 40 variables with 10,354 pieces of information. We identified, through machine learning, a typology for sustainable animals, which were bulls with sustainable resilience and adaptive capacity to the environment, productive sustainability with heavy carcasses and high yield and feed sustainability with negative RFI. The main phenotypic biomarkers to identify sustainable animals are rectal temperature, mean corpuscular volume and white blood cells – sustainable resilience and adaptive capacity; precocity, birth weight and carcass yield – productive sustainability; and residual feed intake – feed sustainability. We recommend using this methodological proposal to identify sustainable animals, in which they consume less food, are adapted to the environment and are more productive, increasing the farm's income and possibly reducing the water and carbon footprints.

Scientific Productions on Precision Livestock Farming: An Overview of the Evolution and Current State of Research Based on a Bibliometric Analysis.

The interest in precision livestock farming (PLF)-a concept discussed for the first time in the early 2000s-has advanced considerably in recent years due to its important role in the development of sustainable livestock production systems. However, a comprehensive bibliometric analysis of the PLF literature is lacking. To address this gap, this study analyzed documents published from 2005 to 2021, aiming to understand the historical influences on technology adoption in livestock farming, identify future global trends, and examine shifts in scientific research on this topic. By using specific search terms in the Web of Science Core Collection, 886 publications were identified and analyzed using the bibliometrix R-package. The analysis revealed that the collection consisted mostly of research articles (74.6%) and reviews (10.4%). The top three core journals were the Journal of Dairy Science, Computers and Electronics in Agriculture, and Animals. Over time, the number of publications has steadily increased, with a higher growth rate in the last five years (29.0%) compared to the initial period (13.7%). Authors and institutions from multiple countries have contributed to the literature, with the USA, the Netherlands, and Italy leading in terms of publication numbers. The analysis also highlighted the growing interest in bovine production systems, emphasizing the importance of behavioral studies in PLF tool development. Automated milking systems were identified as central drivers of innovation in the PLF sector. Emerging themes for the future included "emissions" and "mitigation", indicating a focus on environmental concerns.

Effects of different tillage systems and mowing time on nutrient accumulation and forage nutritive value of Cyperus esculentus.

Revealing the complex relationships between management practices, crop growth, forage nutritive value and soil quality will facilitate the development of more sustainable agricultural and livestock production systems. Cyperus esculentus is known as the king of oil crops and high-quality forage. However, there is little information about the effects of different planting modes {continuous cropping (CC)/rotation cropping (RC)} and initial mowing time on the plant nutrient accumulation and forage nutritive value. Here, in a field experiment, we designed two planting patterns, C. esculentus CC and C. esculentus - wheat RC. The leaves, tubers, roots, and soil samples were collected at three mowing time (on the 78th, 101th, and 124th days after seed sowing). Results revealed that RC significantly increased the total nitrogen (TN) and potassium (TK) content of the tuber (p<0.05), while significantly decreased the TN, total phosphorus (TP), crude protein (CP), and acid detergent fiber (ADF) contents of the leaves. Under the CC pattern, the TN, TP, and TK content of roots increased significantly on the 78th days after seed sowing, and the TK content of tubers increased significantly. Under the RC pattern, the ether extract (EE) content of tubers increased significantly on the 124th days after seed sowing, while the CP and TN content of leaves decreased significantly. Correlation analysis showed that soil pH was negatively correlated with TN content in leaves, tubers, and roots. The structural equation model showed that the soil pH directly affected the plant nutrient accumulation and forage nutritive value (β=0.68) via regulating these properties by changing soil available nutrients, anions, cations, and total nutrients. Overall, we propose that RC for C. esculentus-wheat is should not be recommended to maximize tubers and forage yield.

Phenotypic Evaluation of Traits and Barcode Identification using Plastid-specific Ribulose Bisphosphate Carboxylase (Rbcl) Analysis on Lablab Beans [Lablab purpureus (L.) Sweet

Background: The importance of grain legumes in world food sustainability cannot be overemphasized. Minor legumes on the other hand, contribute to agricultural strengthening, especially in the context of sustainable crop and livestock production systems. In the context of assessing different legume species for crop improvement and identification, twenty (20) accessions of Lablab purpureus (L.) Sweet collected to determine the degree of trait variability and to identify accessions with potentials, which can contribute to grain and forage production. Methods: The present study involved the evaluation of twenty (20) accessions of Lablab purpureus (L.) Sweet from IITA, Ibadan. The accessions were grown in the experimental plot and DNA from young and healthy leaves were isolated for determination of genetic diversity using ribulose bisphosphate carboxylase (rbcL). The accessions were also categorized into groups based on the performances and the highest discriminating traits that accounted for greater variability using principal component analysis (PCA) and cluster analysis (CA) respectively. Result: Cluster analysis grouped all the twenty accessions into three clusters, where cluster I, cluster II and cluster III comprised of eight, seven and five accessions respectively. The PCA revealed hundred seed-weights, number of pod per plant and seed length as the most discriminating trait that accounted for greater variability in the Lablab accessions considered and they should be considered in the hyacinth bean improvement programs. Based on diverse level of phenotypic traits, accessions from each cluster were selected for barcode identification and comparison with other cultivars from other region. Results of the molecular analysis showed two clusters and authenticated the use of universal primers, ribulose bisphosphate carboxylase (rbcL) for DNA barcoding for successful amplification, identification and discrimination of Lablab purpureus (L). This revealed diversity of the considered accessions and provided information on relatedness to other accessions from other region of the world.

Impact of Climate Change on Animal Health and Production

Purpose: To examine the impact of climate change on animal health and production.&#x0D; Methodology: To review an existing literatures concerning impact of climate change on animal health and production.&#x0D; Findings: Climate change is seen as a major threat to the survival of many species of animal, ecosystems and the sustainability of livestock production systems globally. Livestock production and health are considerably vulnerable to the impact of climate change. Since several decades back, climate change has become the major issue affecting global and regional ecosystems and people are working on it. Although yet it is real and is happening with concomitant changes in precipitation, flooding, heavy winds, and the frequency of severe events, increased temperature, and changes in humidity. It is evidenced that it will become worse in the future life. Climate change has direct and indirect impacts on emerging and re-emerging animal diseases and zoonoses since it disrupts natural ecosystems and allows disease-causing pathogens to move into new areas where they may harm wild life, domestic species, and humans.&#x0D; The interaction between animal production and climate change is complex since animal production contributes to climate change. However to the reverse and worse condition, climate change highly affects animal production. Thus, the increased threat of climate change on the animal production and health sectors needs the hands of various stakeholders to work collaboratively.

Creating a Design Framework to Diagnose and Enhance Grassland Health under Pastoral Livestock Production Systems

Grasslands and ecosystem services are under threat due to common practices adopted by modern livestock farming systems. Design theory has been an alternative to promote changes and develop more sustainable strategies that allow pastoral livestock production systems to evolve continually within grasslands by enhancing their health and enabling the continuous delivery of multiple ecosystem services. To create a design framework to design alternative and more sustainable pastoral livestock production systems, a better comprehension of grassland complexity and dynamism for a diagnostic assessment of its health is needed, from which the systems thinking theory could be an important approach. By using systems thinking theory, the key components of grasslands-soil, plant, ruminant-can be reviewed and better understood from a holistic perspective. The description of soil, plant and ruminant individually is already complex itself, so understanding these components, their interactions, their response to grazing management and herbivory and how they contribute to grassland health under different climatic and topographic conditions is paramount to designing more sustainable pastoral livestock production systems. Therefore, by taking a systems thinking approach, we aim to review the literature to better understand the role of soil, plant, and ruminant on grassland health to build a design framework to diagnose and enhance grassland health under pastoral livestock production systems.

Sustainability of livestock production systems in the high jungle of Peru

The sustainability of livestock production systems in the districts of Oxapampa, Chontabamba and Huancabamba, Oxapampa Province, Pasco Region, Peru was studied. The methodology used was the MESMIS. For the characterization of the livestock systems, the producers were grouped into three groups: traditional extensive livestock system, semi-extensive livestock system and extensive livestock system. In the first instance, the environmental sustainability, economic sustainability and social sustainability with their respective indicators were partially evaluated, to later evaluate it in a comprehensive way through IGS (general sustainability index) and finally to corroborate the grouping of producers, through the analysis agglomerative hierarchical cluster. Through the MESMIS analysis, the traditional extensive livestock system was the most sustainable in the environmental, economic and social dimension, obtaining the highest IGS. Subsequently, the same producers with their environmental, economic and social indicators were subjected to the agglomerative hierarchical conglomerate analysis, there is a cluster with the same selected producers, in the framework MESMIS, which are part of the traditional extensive system.

94 The Present and Future of Nasem Beef Nutrient Requirement Modeling

Abstract The precise and accurate prediction of animal nutrient requirements, feed intake, water intake, environmental impacts, and production efficiency is an essential function of nutrient requirement models when leveraged as tools to enhance the sustainability of livestock production systems. Historically, the legal standard for determining nutrient requirements of livestock within the United States has leveraged the National Academies of Sciences, Engineering, and Medicine (NASEM) nutrient requirement series (formerly referred to as the National Research Council (NRC) models). The objective of this work is to review the present advantages and future needs for the NASEM Beef Nutrient Requirement Models. Due to current production conditions prevalent within the United States beef industry, the adequate prediction of performance outcomes in commercial cattle in group feeding situations is arguably of the greatest importance. However, as the climate changes and interest in new genetics, production strategies, and feeding approaches expand, there will be an increasing need to additionally provide precise and accurate predictions of individual animals based on genetic potential, production system, and climate conditions. The NASEM 2016 Nutrient Requirements of Beef Cattle presented a stepwise improvement in model sophistication and customizability though the inclusion of a number of individually adjustable constants to adapt model predictions to animal performance in production settings, and through the expanded use of mechanistic solutions in estimating nutrient requirements. Another major advancement of this model release was the opportunity to push model updates and fixes as users identify challenges or issues with the model. The capacity to update nutrient requirement models in a more agile manner greatly contributes to the long-term need for more adaptable and flexible ration formulation tools. Although these improvements may enhance usability of the NASEM models, there are some additional opportunities for future iterations, including better capacity to explore individual animal requirements, leverage precision livestock farming technologies, and design rations to adapt animals to climate change.

EVALUATION OF THE SUSTAINABLE PERFORMANCE OF NATIVE AND INTENSIVE SILVOPASTORAL SYSTEMS IN THE MEXICAN TROPICS USING THE MESMIS FRAMEWORK

&lt;p&gt;&lt;strong&gt;Background. &lt;/strong&gt;It is agreed that there is a need to work on sustainable extensive livestock production systems. Silvopastoral systems are an alternative for efficient and sustainable grazing systems to increase the provision of ecosystems services and minimize the environmental costs associated to monoculture systems (MS), but the efficiency of intensively managed (IS) and unmanaged or native (NS) silvopastoral systems has never been assessed and compared to MS. The Framework for Assessing the Sustainability of Natural Resource Management (MESMIS) offers a tool to assess sustainability criteria in agroecosystems. &lt;strong&gt;Objective. &lt;/strong&gt;To use MESMIS to compare the sustainable performance of NS, IS and MS and determine the system with the best sustainable performance in the Mexican Tropics. &lt;strong&gt;Methodology. &lt;/strong&gt;One MS IS and NS per municipality (Tizimin, Merida and Tzucacab) were evaluated in the state of Yucatán, Mexico. Based on the MESMIS approach, the evaluation of the critical points of sustainability resulted in the selection of 19 indicators classified according to the attributes also defined by MESMIS (production, adaptability, stability-resilience, equity and self-management) and by sustainability dimensions (environmental, animal welfare, economic and social). After evaluation, indicator scores were obtained and integrated into attributes and dimensions through the assignation of equitable, balanced weights (W). Finally, attribute and dimension scores were aggregated in amoeba graphs to facilitate visual interpretation. &lt;strong&gt;Results. &lt;/strong&gt;NS were better for the dimensions ‘Environmental’ and ‘Economic’ and the attributes ‘Stability, ‘Reliability’and ‘Resilience,’ and ‘Production’. IS were best for the dimension ‘Animal Welfare’ and attributes ‘Adaptability’ and ‘Self-reliance’. MS were better for the ‘Social’ dimension and the ‘Equity’ attribute. &lt;strong&gt;Implications. &lt;/strong&gt;The fact that IS appeared to be more sustainable than MS does not leave out the idea of considering NS as a better option for some criteria such as the biodiversity conservation and the prevention of disease outbreaks, than IS. We suggest that more studies are carried on areas of potential improvement for IS as well as NS. &lt;strong&gt;Conclusions. &lt;/strong&gt;This information will be useful to continue working on the parametrization of sustainability criteria of cattle extensive systems to be used for more efficient policies.&lt;/p&gt;

Positive deviant strategies implemented by organic multi-species livestock farms in Europe

CONTEXTTransitions to more sustainable livestock production systems are increasingly demanded by parts of society. Scientists suggest moving towards diversified farming systems due to their potential environmental and economic benefits, especially in the organic sector. However, empirical knowledge of multi-species livestock farms, i.e. farms keeping two or more animal species, is lacking. OBJECTIVEOur objectives were to identify European organic multi-species livestock farms that outperform their peers despite having the same resources and constraints, and characterize their distinctive management principles. METHODSWe conducted surveys on 102 farms in seven European countries: Austria, Belgium, France, Germany, Italy, Sweden and Switzerland. We restricted the analysis to a sub-sample of 75 farms that had complete data and that covered 3 main livestock combinations (cattle and sheep, cattle and pigs, cattle and poultry) with similar number of farms. We implemented a positive deviant approach based on three indicators: land productivity, nitrogen input dependence and satisfaction regarding income. RESULTS AND CONCLUSIONSFive structurally diverse positive deviant farms were identified with 4 types of livestock combinations represented, and farmland area ranging from 25 to 273 ha, herd size from 33 to 146 livestock units (LU) and total workforce size from 1 to 24 annual worker units (AWU). These farms were located on a trade-off between land productivity and autonomy for feed, and all but one had high overall autonomy for feed (89–100% against a mean of 76% for the whole sample). Their diversity of pastures, crops and livestock species and their diversification beyond agricultural production were controlled (e.g. no agritourism) and below that of the other sample farms, to remain manageable by the farmers while still allowing to buffer shocks and hazards. Interactions among farm enterprises remained limited to matter (mainly grain, straw, hay, manure) flows, and practices requiring specific efforts and investments (e.g. for fencing), such as co-grazing of different livestock and crop residues grazing, were avoided. SIGNIFICANCEWe conducted the first integrated study on European organic multi-species livestock farms and identified key management principles implemented on positive deviant farms. We showed that whatever their size, farms outperforming their peers do not necessarily maximize diversity of agricultural productions and of non-agricultural activities, and interactions among farm enterprises but that they remain at a level of complexity manageable by the farmers. These principles will inform farmers running multi-species livestock farms or transitioning to this model.

Storage media and RNA extraction approaches substantially influence the recovery and integrity of livestock fecal microbial RNA.

BackgroundThere is growing interest in understanding gut microbiome dynamics, to increase the sustainability of livestock production systems and to better understand the dynamics that regulate antibiotic resistance genes (i.e., the resistome). High-throughput sequencing of RNA transcripts (RNA-seq) from microbial communities (metatranscriptome) allows an unprecedented opportunity to analyze the functional and taxonomical dynamics of the expressed microbiome and emerges as a highly informative approach. However, the isolation and preservation of high-quality RNA from livestock fecal samples remains highly challenging. This study aimed to determine the impact of the various sample storage and RNA extraction strategies on the recovery and integrity of microbial RNA extracted from selected livestock (chicken and pig) fecal samples.MethodsFecal samples from pigs and chicken were collected from conventional slaughterhouses. Two different storage buffers were used at two different storage temperatures. The extraction of total RNA was done using four different commercially available kits and RNA integrity/quality and concentration were measured using a Bioanalyzer 2100 system with RNA 6000 Nano kit (Agilent, Santa Clara, CA, USA). In addition, RT-qPCR was used to assess bacterial RNA quality and the level of host RNA contamination.ResultsThe quantity and quality of RNA differed by sample type (i.e., either pig or chicken) and most significantly by the extraction kit, with differences in the extraction method resulting in the least variability in pig feces samples and the most variability in chicken feces. Considering a tradeoff between the RNA yield and the RNA integrity and at the same time minimizing the amount of host RNA in the sample, a combination of storing the fecal samples in RNALater at either 4 °C (for 24 h) or −80 °C (up to 2 weeks) with extraction with PM kit (RNEasy Power Microbiome Kit) had the best performance for both chicken and pig samples.ConclusionOur findings provided a further emphasis on using a consistent methodology for sample storage, duration as well as a compatible RNA extraction approach. This is crucial as the impact of these technical steps can be potentially large compared with the real biological variability to be explained in microbiome and resistome studies.