Technology & Engineering

• Provides a comprehensive overview of the main crop models developed in North America, Europe, Asia and the Pacific
• Considers how current crop models can be improved with future enhancements, such as the incorporation of genetics
• Details examples of current applications of crop models, focussing on genotype-environment-management (G x E x M) interactions

• Provides a detailed overview of the range of techniques and treatments used to optimise safety at the pre-harvest and postharvest stages of egg production
• Outlines key shell egg quality standards and ways of meeting quality requirements
• Considers the environmental impact of egg production systems and how these can be better optimised to improve sustainability

• Reviews the range of techniques for measuring soil biological activity, including DNA-based, quantitative PCR and enzyme assay methods
• Combines coverage of soil microorganisms with assessment of micro-, meso- and macrofauna
• Shows how biological indicators can be integrated into soil health testing programmes to improve the quality of different soils

• Provides a comprehensive overview of the latest research in grassland science and management
• Includes a selection of case studies which highlight current challenges facing alpine/mountain grasslands, as well as grasslands in Europe and New Zealand
• Discusses recent developments in botanical composition of grasslands, including the design of multi-species swards and herbal leys

• Provides a comprehensive overview of the ways agroforestry can support key ecosystem services
• Reviews the range of silvopastoral and silvoarable systems and their application in agriculture to optimise crop and livestock production
• Considers the benefits of temperate agroforestry in mitigating/adapting to climate change

• Provides a comprehensive overview of the major technologies used in precision agriculture, from proximal/remote sensing and use of unmanned aerial vehicles to the wide range of variable rate delivery systems
• Discusses the breadth of precision agriculture applications both in crop and livestock farming, from precision tillage and variable-rate seeding to precision pasture management
• Includes new developments such as multi-sensor fusion, robotics, artificial intelligence and big data

This chapter describes the MONICA agroecosystem model, its development from the original HERMES model, its main features, and example applications for various tasks across scales. MONICA allows a balanced view on crop and soil processes when simulating cropping systems over a wide range of environments and management regimens. Developed and parameterised at the plot scale, recent advances have made MONICA fit to be applied over large scales, using remote sensing to identify spatio-temporal patterns of key inputs. MONICA’s output helps answer a wide range of questions for research and decision making, including future scenarios, trade-off analyses, and strategic development in crop production and related ecosystem services and disservices under climate change.

The CropGrow series model, comprising WheatGrow and RiceGrow, was developed by the Engineering and Technology Center for Information Agriculture at Nanjing Agricultural University. The model integrates cutting-edge methodologies, such as system analysis, dynamic modeling, scenario simulation, and decision support system. The series model consists of multiple sub-models that comprehensively address wheat or rice growth and development processes, including phasic development and phenology, organ development and population establishment, photosynthetic production and biomass accumulation, assimilate partitioning and yield and quality formation, nutrient dynamics, and water balance. This holistic approach provides a detailed, dynamic understanding of wheat and rice response to different factors, supporting precision agriculture and optimized crop management.

Process-level crop models integrate mathematical representations of the soil-plant-atmosphere with genetic, environment, and management factors. These tools support a range of needs including on-farm decision support, scientific inquiry, crop breeding, and climate impact assessments. The USDA-ARS Adaptive Cropping Systems Laboratory models include the current state of empirical knowledge and theories regarding crop and soil processes. These simulators incorporate mechanistic representations of gas exchange, energy balances, relationships between crop development and temperature, and responses to short- and long-term stresses. Unique sets of genetic coefficients account for phenotypic differences among crop varieties, accounting for responses to temperature, photoperiod, fertility and drought, as well as inherent growth rates. ACSL models are integrated with a two-dimensional soils module which allows representation of row topography and vertical / lateral movement of roots, water, solutes, gases, and heat through the soil profile. Recent improvements provide a broader, more accurate range of agricultural system assessments.

This chapter offers a general presentation of the STICS soil-crop model. Through numerous illustrations dealing notably with genetic x environment x management interactions, it presents an overview of the wide domain of validity of the model, along with its performances, demonstrating its potential for a wide range of agronomic and environmental applications. Since the beginning of its story in the early 90’s, STICS has been able to remain a generic and robust model that allows to simulate the functioning of agro-ecosystems, both in temperate and tropical environments. As highlighted in this chapter, and particularly in the last two sections, many efforts were, and are still, put to keep the model up-to-date and in a permanent state of evolution towards better representation of cropping systems, allowing to analyze novel research and applied questions.

The process-based model Daisy simulates complex crop traits in different environments through various process descriptions for water and solute/nitrogen transport and crop growth of diverse agroecosystems and managements. Daisy runs in one or two dimensions, in the field (basic management unit) or several fields (distributed mode). An important aspect influencing the accuracy of the phenotype simulations is the choice of environment(s) used for parameterization, which should capture the heterogeneity in the target population of environments. Uncertainty and sensitivity analyses improve the differentiation between well predictable (repeatable) from badly predictable crop traits under genotype × environment × management interactions. Alongside history of the model and the most important applications, challenges and opportunities are presented through the need for diverse experimental data needed for parameterisations of major crops and less known or minor crops. Finally, Daisy is part of high-performance data-driven modelling platform for developing agricultural systems with minimum environmental impacts.

The WOFOST cropping system model is a process-based model developed by Wageningen University & Research (WUR) for a wide array of applications such as yield forecasting, climate impact assessments, yield gap analysis and agronomic decision support. The latest versions, WOFOST 7.3 and 8.1, introduce significant advancements, including a multi-layer soil water balance, a soil carbon/nitrogen model (SNOMIN), crop nitrogen dynamics and biomass reallocation to improve the simulation of N limited growth. These enhancements allow for a more realistic representation of Genotype × Environment × Management (G×E×M) interactions and facilitate the modeling of multi-year cropping systems, extending WOFOST’s utility beyond single-season crop growth simulations. Future developments in WOFOST 8.2 aim to improve modeling of C4 crops, include the impact of capillary rise from shallow groundwater and facilitate parameterization using external soil and climate databases.

Process-based crop models have become a central tool for agricultural systems analysis, allowing scientists to explicitly define model structures most suited to a given research question and data availability. With the evolution of computation and programming language paradigms, algorithms describing well-established physiological processes at different levels of detail have become modular and exchangeable across modelling platforms. In this chapter, we present the flexible modelling platform SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management). A brief overview is given about how SIMPLACE's core engine and modularisation scheme can represent crop and genetic differences in contrasting environments. We also show SIMPLACE applications with emphasis on genotype x environment (G x E) interactions and areas for further model enhancement in this topic.

The USDA Root Zone Water Quality Model (RZWQM), developed in the 1980s and released in 1992, simulates root zone processes based on earlier models like CREAMS, GLEAMS, and NTRM. It includes modules for water balance, soil carbon and nitrogen cycling, plant growth, energy balance, solute transport, phosphorus dynamics, and management practices. The original version featured a generic plant module (GPM) and was primarily used for maize, soybean, and wheat. In the early 2000s, RZWQM was combined with the DSSAT crop model to create RZWQM2 including 30 crop-specific modules. Later, the HERMES model was added with support for 15 crops. RZWQM2 features a Windows interface for data handling and parameter estimation. The model has over 450 publications and has been used for real-time irrigation scheduling of cotton and maize. Maintained by USDA-ARS scientists, RZWQM2 is available online and, with proper calibration, can simulate crop production and environmental quality under diverse conditions.

The Genotype-by-Environment interaction on CROp growth Simulator (GECROS) is a generic crop model that specifically addresses carbon-nitrogen, root-shoot, and source-sink interactions to predict crop responses to weather variables and soil water and nitrogen supply. GECROS uses relatively few, easily measurable parameters across many genotypes, making it useful for linking crop physiology with genetic mapping to predict genotype-by-environment interactions. Owing to its coupled modelling of carbon and nitrogen assimilates, the model predicts not only biomass yield, but also the protein content of harvestable products (grains, seeds, tubers, fruits). The chapter discusses the development and components of the GECROS model as well as its wide range of potential applications in improving decision making to make agriculture more resilient and sustainable. The chapter also highlights major uncertainties e.g. in simulating sink size and root nitrogen (N) uptake that currently prevent the model from accurately predicting subtle genotype-phenotype relations in a genetic population.

DNDC is a well-established biogeochemical crop model that has been featured in over 400 peer-reviewed publications and excels at quantifying agricultural impact under diverse environmental and management conditions. DNDC employs a thermal time-driven biomass accumulation sub-model across all crops with differences arising from regionspecific parameters which serve as proxies for genetic variation and from simulation approaches tailored to crop physiology and environment. For instance, DNDC simulates the nitrogen fixation of legumes and nitrous oxide emissions from flooded rice fields. Deriving these parameters for new locations requires calibration data, typically sourced from site-specific literature. This chapter outlines DNDC’s history and functionality and introduces a methodology that uses aggregated yield data to generate local crop parameters. A case study in the US Corn Belt compares simulated yield results from parameters calibrated with different approaches. The chapter highlights that less data- intensive calibration methodologies are critical for maximizing the benefits of models like DNDC.

SAMARA was developed to study in-silico plant type (ideotype) concepts submitted to different climatic/soil environments and management practices. The originality of the model relies on (1) the integration of substantial morphological detail of plants organ cohorts (leaves, tillers, internodes), and (2) the partitioning of biomass to organs on the basis of inter-organ competition for a single assimilate pool. This chapter details the main characteristics of the model, its recent developments, and finally key applications to the Global South illustrating the strengths of the model to capture Genotype by Environment interactions.

Cycles is a process-based model of the soil–plant–atmosphere continuum that functions as both a knowledge repository and analytical tool. This chapter outlines its structure, highlights its use in in-silico trait exploration and modeling of biogenic carbon and water cycles, and presents three case studies. The model integrates energy, water, carbon, and nitrogen cycles, coupling plant photosynthesis, partially based on stomatal optimization theory, with soil heterotrophic respiration based partially on carbon saturation theory. These features reflect theoretical and empirical rigor adapted for practical applications. The input/output system is streamlined and high-performance computing compatible. Applications include: (1) exploring maize root phenotypes under variable hydric regimes; (2) comparing greenhouse gas emissions in till and no-till systems across more than 871,000 fields in Iowa; and (3) evaluating maize–sorghum polycultures for stabilizing silage yield in the U.S. Together, these examples illustrate how Cycles advances agroecosystem modeling for both scientific discovery and landscape management.

FAO (the Food and Agriculture Organization of the United Nations) launched in 2009 the dynamic crop growth model “AquaCrop” to predict yield response to water of herbaceous crops. After a brief description of the calculation scheme and the input requirements, the chapter discusses the parametrization of AquaCrop for crops and the simulation of the effect of climate change. In 2022 the model was expanded to simulate perennial herbaceous forage crops and scaled up for regional applications.

This chapter explores SALUS (Systems Approach to Land Use Sustainability), a process-based crop model designed to simulate interactions between soil, climate, genetics and agronomic management, focusing on their effects on crop growth and yield, soil organic matter and nitrogen dynamics. SALUS explores how different components of an agricultural field system interact and influence plant growth and soil nutrient dynamics. A particular strength is its ability to simulate multiple years of a cropping system. The chapter explores how the model works in terms of: genetics; soil and carbon dynamics; and soil, weather, and agronomic data. The chapter includes three case studies showing the use of SALUS: to evaluate optimal locations for bioenergy crop implementation while quantifying both productivity and environmental impacts; to determine optimal variable rate fertilizer applications; and to assess the long-term impact of differing tillage practices across the US Midwest.

The ecohydrological and crop growth simulation model combination SwapWofost is a model that can be used for crop simulation when detailed soil moisture processes, such as for example capillairy rise, salination, etc., have to be considered. It has been succesfully used in the Netherlands, Argentina and Bangladesh.

There is a wide range of models in the LINTUL family of crop growth models. All are based on a simple relationship between leaf area index and light interception and the concept of light or radiation use efficiency to convert intercepted radiation into dry matter. This chapter provides an overview of key relationships that are part of LINTUL implementations to describe potential, water limited and nutrient limited production situations. Some extra attention is paid to recent improvements to account for CO2 fertilization, N limitation and N, P and K limitations.

This chapter explains the development, key components, and applications of InfoCrop: a process-based, dynamic simulation model developed by Indian scientists to simulate the growth, development, and yield of major tropical crops. These include wheat, rice, maize, sorghum, pearl millet, soybean, chickpea, pigeon pea, groundnut, mustard, potato, and cotton. InfoCrop has also been expanded to cover sugarcane and perennial crops such as Coconut with specific modifications of the base model. A case study is provided on the development of InfoCrop for coconut.

Process based simulation model combining an easily parameterized plant model with readily available soils data and weather data, are valuable tools for a wide variety of management, environmental, and climate change scenarios. The Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model has proven useful for many applications. In this chapter the basic processes simulated by this model will be described. Examples of several applications will be provided. The process of deriving parameters for various plant types will be described. The ALMANAC model did an acceptable job simulating the yields of diverse grasses, annual crops, and tropical tree crops. Thus the overall conclusion was that the ALMANAC model shows great promise in simulating grasses, trees, and crops in a wide range of locations.

Models can be effective tools, and in many cases essential tools, to understand and predict the development, growth, and yield of crops in response to variation in environment, plant genetics, and management. Criteria for such effective models are that they are transparent and robust. The family of Simple Simulation Models (SSM) meets these criteria to a large extent by rigorously seeking simplicity in describing functional relationships. The approach was to use conservative relationships and summary expressions at a single explanatory level to output explanation at the next higher level. As described in this chapter, relationships are generally simulated on a daily time step for a canopy to give seasonal crop growth. In addition to describing the fey functions in SSM, examples are presented showing the robustness of the model and uses to which it has been applied.

A revolution in sequencing and bioinformatics technology has led to a steep increase in research studies that include microbial community characterization. Many of these studies utilize amplicon sequencing, targeting bacteria and fungi and seek to draw correlations between the presence and abundance of certain taxa and soil properties indicative of soil health. More recently, shotgun metagenomics have been applied to soils to investigate the microbial community’s functional potential. This chapter will describe the methods used in generating amplicon and metagenomics data, emphasizing key decisions that researchers must make in the workflow that can influence community composition descriptions. We will discuss the pros and cons of these approaches and the scope of inference that sequencing data has in connection to the healthy functioning of soil.

Soil microorganisms play a critical role in soil health and in delivery of key ecosystem services. However, we still know relatively little about what role individual taxa play in soil processes. Quantifying microbial processes with taxonomic resolution is thus one of the key research challenges in agriculture. By quantifying the incorporation of heavy isotopes into microbial DNA, coupled with taxonomic identifications from DNA sequencing, quantitative stable isotope probing (qSIP) makes it possible to measure taxon-specific activity. This chapter explores how qSIP works and the exciting range of its potential applications in understanding and optimizing the role of soil microorganisms in achieving a more sustainable agriculture.

This chapter aims to discuss the advantages and limits of enzyme assays used as proxies for nutrient availability in soil and as indicators of soil health. The chapter also discusses the complexity of interpreting soil enzyme activities. It underlines research shortcomings and proposes future research lines that will address some of the current knowledge gaps. Finally, the chapter proposes further studies to improve the use of enzyme activities as indicators of soil health.

In this study, we define forest soil health as “the continued capacity of soil to function as a vital living ecosystem that sustains native biodiversity, ecological balances, and ecosystem services in forests.” Soil health, a cornerstone of forest ecosystem health, has seen its assessment methods evolve from traditional chemical and physical property measurements to include comprehensive assessments that incorporate biological indicators. The purpose of this chapter is to illustrate the challenges facing forest soil health, how to evaluate forest soil health based on biological indicators, and the issues that need to be considered, with the aim of providing valuable insights for ultimately constructing a simple and effective biological-based forest soil health indicator system.

For more than a century, soil respiration measurements have been used to understand soil microbial activity in different ecosystems and contexts. Continued methodological development and advances in sensing technologies are opening new avenues for exploration and insight. Nonetheless, the underlying mechanisms of many of these measurements continue to be debated. This chapter reviews commonly used respiration-based methods for assessing soil microbial characteristics, including the historical context and biological bases of different applications in laboratory and field settings. Along with this history, it address some of the most critical challenges and uncertainties related to respiration-based measurements, and provides a case study showing how different respiration tests were used to assess how cover cropping, tillage, and fertility management practices affect soil microbial functioning in two agricultural fields in Virginia, U.S. The chapter concludes by discussing future needs and trends in soil respiration research and by providing resources for further information.

Ways of improving soil health are increasingly seen as central to sustainable crop production. However, sustainable soil management clearly requires accurate, standardized and accessible ways to measure and monitor soil health that can be used by farmers. There is a need to translate measures of different aspects of soil biology and other measures into overall measures of soil health that encompass different soil properties, functions, and ecosystems services. This requires a sound foundation of scientific knowledge in an appropriate biophysical context (e.g., region or soil type) and set of management factors. This chapter explores ways this can be achieved using particular examples such as the Soil Health Assessment Protocol and Evaluation (SHAPE).

This review aims to demonstrate the influence of farming systems on biological indicators that are relevant to soil health. Empirical data from published studies informs the hypothetical model that soil health outcomes are related to more diverse cropping systems, coupled with high inputs of organic amendments and less frequent and shallow tillage, due to the ability of such practices to promote soil organic carbon accumulation. This view is supported by the fact that conservation agriculture promotes soil health under diverse climatic conditions.

Phospholipid fatty acid (PLFA) analysis is a widely used biomarker-based method for assessing microbial community structure and soil health. This technique provides insights into microbial biomass, community composition, and physiological status by extracting and analyzing microbial lipids from soil samples. Phospholipid fatty acid analysis has been extensively applied in environmental and agricultural research for over 40 years, offering a rapid and sensitive approach to studying microbial responses to environmental changes, disturbances, and management practices. Advances in gas chromatography-mass spectrometry and statistical tools have enhanced the method's robustness and reproducibility. Despite the increasing popularity of molecular techniques, PLFA remains valuable in soil health monitoring, especially in agricultural systems, where it can assess the impact of tillage, crop rotation, organic amendments, and chemical inputs. This chapter discusses the principles, applications, and recent advances in PLFA analysis, highlighting its continued relevance in monitoring and managing soil health.

Soil nematode communities are composed of both plant-parasitic and beneficial taxa, and are distributed across five trophic groups within the soil food web. These nematodes contribute up to 12% of nitrogen mineralization, making them valuable indicators of ecosystem function. Ecological succession and food web complexity indices are useful for detecting the effects of management practices such as cultivation, fertilizer use, pollutants, and pesticide application. These indices are derived from the abundance of nematodes categorized by their trophic group and colonizer-persister (cp) characteristics. However, future research is needed to empirically validate these cp assignments which are often inferred based on morphology alone. Identifying sentinel taxa that respond consistently to specific types of disturbance would further enhance the interpretation of results and reduce the ambiguity caused by certain taxa. Customizing sentinel taxa to specific ecoregions and ecosystems would also improve molecular diagnostic kits, making it easier for non-specialists to employ nematode indicators on large geographic scales.

This chapter explores advances in quantitative PCR (qPCR) techniques for identifying and studying soil microbial communities. The authors begin by describing the principles of qPCR. This is followed by sections discussing factors affecting the reproducibility of qPCR assays, and qPCR targets. They then explain linking soil communities to measured processes. This is then followed by two sections covering case studies and recent developments.

This chapter briefly summarizes current knowledge on microarthropod abundance and diversity in soils, their roles in soil processes and ecosystem services, and the agricultural management practices affecting soil microarthropod community. It also provides an overview of sampling, extraction and identification methods, including the importance of accounting for spatial and temporal variability. Potential soil health indicators derived from microarthropod abundance, diversity, and traits are reviewed, with case studies illustrating important aspects of the use of microarthropods as soil health indicators. The chapter concludes with several important challenges and perspectives for future research for use of these indicators in practice.

Actual exposure observed by biomonitoring studies in humans provides data on the sum of exposures by different routes and sources of exposure. For dietary risk assessment, these data are essential for determining whether observed exposures are below toxicological reference values and for validating external exposure estimation models. They are also compared with HBM guidance values derived from toxicological reference values to estimate risk characterisation ratios, which are very useful for communicating with risk managers and the general public and for prioritising actions to be taken in terms of research, risk assessment or risk management. The chapter presents the progress made in recent years.

Chemicals in food can pose a risk to human health. The Codex Alimentarius Commission (CAC) provides a global framework for the risk management of these chemicals, from setting maximum residue limits for veterinary drugs and pesticide residues in food to maximum levels (MLs) for contaminants in foods. Codex standards are based on science provided by independent scientific bodies from FAO and WHO. This chapter outlines the work of Codex on food chemical risk management with a focus on contaminants in food. It discusses how its standards relate to food trade and WTO agreements, the legal basis of its standards, its working procedures and the scientific basis for standards, considerations other than science and future challenges.

Toxicokinetic modeling is critical for accurately assessing human health risks associated with chemical residues ingested through food. This chapter highlights recent advancements in toxicokinetic modeling, emphasizing physiologically based toxicokinetic (PBTK) models that predict internal doses more realistically. Such models incorporate detailed physiological parameters, enzyme activities, and organ-specific dynamics across different life stages, from infancy to adulthood. Innovations include generic PBTK models adaptable to numerous chemicals and sophisticated computational tools, such as quantitative structure-activity relationship (QSAR) models, machine learning, and Bayesian inference, which significantly enhance predictive power and address population variability. The chapter describes the shift toward next-generation risk assessment (NGRA), utilizing high-throughput in vitro data and in vitro-to-in vivo extrapolation (IVIVE) methods to minimize reliance on animal testing. Incorporating these advanced toxicokinetic modeling approaches into regulatory practices provides robust, human-centric risk evaluations, enabling more effective public health protection measures against foodborne chemical exposure.

Flame retardants are commonly utilized in consumer products to impede or slow down the spread of fire. However, many of these chemicals have emerged as a significant source of contamination in the environment and the food chain. The persistence, bioaccumulation, and potential toxicity of flame retardants—such as polybrominated diphenyl ethers (PBDEs), chlorinated flame retardants (CFRs), and organophosphorus flame retardants (OPFRs)—pose considerable public health concerns. Recent advancements in detecting flame retardant residues in food have centred on the development of highly sensitive analytical techniques, regulatory frameworks, and innovative methods for trace detection. This chapter provides a review of current research and showcases recent breakthroughs in the field, with a specific focus on analytical methodologies for the detection of flame-retardant residues in food.

The chapter on computational toxicology tools provides a basic exploration of their roles in evaluating chemicals in food. Some of these chemicals may pose health risks necessitating rigorous safety assessments. Computational tools may support these assessments by swiftly screening chemicals based on their structural properties, predicting their toxicity, and integrating various data sources. Key platforms such as the OECD QSAR Toolbox, along with other publicly and commercially available tools, facilitate safety and hazard assessments and aid in regulatory compliance. Yet, despite their benefits in reducing animal testing, accelerating assessments, and enhancing transparency, these tools encounter challenges related to data quality and predictive accuracy. The author advocates for a synergistic approach that combines computational predictions with experimental data to bolster safety and hazard assessments, highlights emerging tools, and provides information to aid in selecting appropriate ones based on specific endpoints and regulatory requirements, thereby ensuring that advancements in food safety align with technological innovations and regulatory standards.

Food control of pyrrolizidine alkaloids (PAs) is currently in the spotlight of human health risk assessment due to their widespread presence in our daily diet. Within the last years, food alerts about concerning levels of these alkaloids in food have notably increased, due in part to improvements in their control. The EU regulation of PAs in certain foods is quite recent and has already undergone several updates. Therefore, increasing progress in the assessment of these compounds is needed to ensure food safety and comply with regulatory requirements. This chapter provides a comprehensive overview of PAs, including their contamination pathways, current regulation and evolution of their food alerts, highlighting the main contaminated products as far as they are currently known. Likewise, it gathers relevant analytical strategies for the assessment of PAs in food (2018-2024). Information about how food processing can influence the content and stability of these alkaloids is also included.

Thermal processing contaminants, including acrylamide (AA), heterocyclic amines (HCAs), and polycyclic aromatic hydrocarbons (PAHs), are carcinogenic compounds formed during high-temperature cooking processes such as frying, grilling, and roasting. AA primarily develops in carbohydrate-rich foods, whereas HCAs and PAHs are prevalent in protein- and fat-rich foods like meat, fish, and oils. Controlling these contaminants is challenging as they typically form during the final stages of food preparation. This chapter investigates the formation mechanisms, precursors, and conditions leading to AA, HCAs, and PAHs in foods, alongside strategies for their mitigation. It also evaluates dietary exposure levels across various countries, with a case study on the Republic of Korea, including associated risk characterization outcomes. Finally, it outlines effective management strategies to reduce the presence of these harmful compounds in food preparation and processing.

The environmental impact of macroplastics in the sea and soil has become a global problem, resulting in their entry into the food chain. Macroplastics become microplastics and nanoplastics over time through abrasion and degradation mechanisms. Current analytical measurements show that micro- and nanoplastics accumulate in the environment via the air and water and enter the food chain. Micro- and nanoplastics therefore have a long-term impact on the environment and biodiversity. The oral bioavailability of microplastics (> 1.5 µm) is low due to membrane barriers. In contrast, small microplastics (< 1.5 µM) and nanoplastics could probably be orally bioavailable due to their small size and ability to cross biomembranes. A potential health risk form nanoparticles can be considered relevant. Therefore, research on the oral bioavailability of nanoplastics as well as studies on molecular mechanisms of action in the organism and exposure data are needed to assess possible health risks.

The chapter focuses on the analytical applications of chromatography within the domain of food contaminant analysis. Gas chromatography (GC) is one of the most popular techniques for detecting volatile and semi-volatile food contaminants. One of the most significant developments in this area is multidimensional GC, which employs columns with varying polarities to enhance separation and peak capacity, particularly for compounds that elute within similar temperature ranges. High Performance Liquid Chromatography (HPLC), especially in combination with mass spectrometry, broadens the scope of analytes that can be analyzed by chromatographic methods to non-volatile and very polar ones. The main advances in this area include the introduction of UHPLC systems in combination with small particle columns, as well as multidimensional methods. In spite of its simplicity, thin-layer chromatography can also be useful in the analysis of food contaminants. Finally, supercritical fluid chromatography (SFC) enjoys a renaissance in many areas, including food analysis.

A sensor is defined as a single device that is founded on chemical and physical principles including electrochemistry, fluorescence, thermal, surface plasmon resonance, piezo, reflectometry, chemo and bioluminescence, and optics. More specifically, the term chemical sensor refers or describes a small appliance that is capable to deliver instantaneous information about the chemicals (e.g. concentration, identification) and other compounds present in either the food sample or food system. These sensors can be deployed throughout the different steps during the manufacturing, storage, and transport of foods. This chapter offers the readers with a summary of some of the sensors applied by the food industry to measure and monitor issues related with food contamination and spoilage, with emphasis in the application of electrochemical sensors.

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants (POP) that can accumulate in food systems. This chapter examines their sources, detection, and mitigation strategies in food. Sources include environmental contamination through soil, water, and air, as well as animal feed, and migration from food contact materials. Analyzing these substances at the required levels is complex due to the diversity of PFAS and food matrices, analytical limitations, and contamination risks. Furthermore, it remains challenging to obtain monitoring data for exposure assessment and to comply with current European regulations. Mitigation strategies for agriculture include soil amendments and phytoremediation, while animal exposure can be reduced through improved practices. Case studies highlight regional variation in PFAS contamination and variation concerning the impact food processing may have on these substances. This stresses the need for more sensitive analytical methods, extended regulations, reduced exposure risk and innovative remediation approaches to address PFAS contamination more effectively.

This chapter provides a comprehensive overview of the presence, sources, risks, and detection methods of heavy metals (HMs) in food. It focuses on toxic elements such as lead, mercury, cadmium, and arsenic, which pose significant health risks even at low concentrations. The chapter explores the mechanisms of HM uptake and bioaccumulation in plants and animals, and highlights global contamination trends, particularly in fish and fresh produce. Risk assessment frameworks, regulatory standards, and toxicological evaluations by international bodies are discussed, with emphasis on the shift toward New Approach Methodologies such as in vitro, in silico, and AI-assisted tools. Advanced analytical techniques, especially X-ray fluorescence, are detailed for detecting and quantifying of HMs in food. A case study on turmeric adulteration with lead chromate illustrates the public health implications of economically motivated fraud. The chapter concludes by emphasizing the need for rapid, cost-effective screening tools and the integration of artificial intelligence.

The increasing presence of chemicals in food and the environment raises significant public health concerns, as chronic exposure to residues or contaminants like pesticides, heavy metals, and persistent organic pollutants (POPs) can lead to adverse health effects, even at low levels. Effect biomarkers, which indicate biological changes in response to exposure, are essential tools for assessing health risks associated with these contaminants. Unlike exposure biomarkers that detect chemical presence, effect biomarkers provide insights into biological responses, helping understanding toxicological mechanisms. This review discusses the use of effect biomarkers in food safety and environmental health, examining types, their relevance in studies, and advancements in detection techniques such as metabolomics. Two case studies are explored, highlighting varied applications and nuances in using effect biomarkers in food safety and environmental health. Finally, the review addresses the challenges and future directions for integrating effect biomarkers into regulatory science to improve chemical risk assessments and management strategies.

The intake of chemical substances through food is a critical component of the chemical exposome as food is a considerable source of chemicals and the perfect vehicle for daily and continuous exposure. Traditional dietary exposure assessment methods are still essential tools for understanding and managing risks related to the presence of chemical contaminants in food. Usual methods for collecting food consumption data are labour-intensive, time-consuming and costly and are still prone to both random and systematic errors. Analysing food contaminants is a complex task that presents ongoing challenges, as the field continually evolves, and new contaminants emerge. Dietary exposure models are still mostly based on a deterministic approach, inadequate methods for dealing with left-censored data and focused on single contaminants. The rapid acceleration of technological advancements has become a defining feature of the modern era, fundamentally transforming various aspects of human life, including the methodologies for dietary exposure assessments.

Tropane alkaloids (TAs) are known to be present in certain plants but can contaminate crops that enter the food chain, leading to severe toxic effects in humans. This has prompted the European Union to set legal limits for atropine and scopolamine, the most common TAs, in various foods. However, the Rapid Alert System for Food and Feed still reports instances of TAs exceeding these limits in the EU. Climate change may further exacerbate the spread of invasive plants containing TAs, increasing their presence in plant-based foods. This chapter aims to compile information on the health hazards posed by TAs, review studies documenting food contamination, and assess the primary methods for determining these compounds and potential decontamination techniques. Further research is essential to develop new methods for preventing contamination and removing high levels of TAs, as well as for investigating the toxicity of their metabolites.

JECFA is an international scientific expert committee administered jointly by the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) (FAO, 2024). It has been meeting since 1956, to evaluate initially the safety of food additives. Currently, the Committee evaluates the safety of chemicals in foods including food additives, contaminants, naturally occurring toxicants and residues of veterinary drugs in food [FAO, 2024]. The evaluations of contaminants can result in Health Based Guidance Values (HBGVs), such as TDIs, and estimates of exposure to contaminants and toxins for various populations worldwide. The results are usually reported to the Codex Committee of Contaminants in Foods (CCCF). The CCCF uses that information to decide about food safety standards for contaminants in food, to be included in the General Standard for Contaminants and Toxins in Food and Feed (CODEX STAN CXS 193/1995).

Exposure assessment is the third step in food safety risk assessment, in which the dietary intake of chemical substances is estimated. The health risk of that intake is then evaluated in the risk characterization, where intake is compared with a Health Based Guidance Value. When the dietary intake is equal to or below the HBGV, there is no health concern. To estimate dietary intake, the exposure assessor needs consumption quantities of the foods and the concentration of substances in these foods. A HBGV of the substance is needed for the risk characterization. Data on exposure and HBGVs come from public sources, or from studies of the national food safety authorities. A closer look into existing assessments reveals that various issues exist, that complicate exposure assessment calculations and its interpretation. In this chapter, many of these issues are identified and addressed; some solutions and recommendations are included at the end.

Chemical risk assessment is moving towards non-animal approaches that rely on the mechanistic understanding of toxicity. In this respect, the adverse outcome pathway (AOP) framework is a promising tool to capture chemical-agnostic mechanistic understanding of toxicological processes. AOPs link a molecular initiating event to a specific adverse outcome via a series of key events and key event relationships. Sharing common key features to the AOP framework, the aggregate exposure pathway (AEP) framework is a complementing tool to systematically collect chemical-specific exposure information from the source to the site of action via key exposure states and key transitional relationships. Integrating exposure and toxicological knowledge into combined AEP-AOP constructs can facilitate prediction of chemical-induced toxicity and enable risk-based decision making. The current chapter focuses on the structure, development, assessment, and applications of the AOP and AEP frameworks, illustrated by a case-study on the hepatotoxicity of the metabolites and environmental residues of pesticides.

Improving sheep system sustainability is of key importance to producers, processors, retailers and government, yet balancing interdependent and opposing environmental, economic and social factors is a Herculean task. Mixed farming systems provide an option for improving all three facets of sustainability, although negative trade-offs must be minimized. A variety of opportunities exist for integrating sheep grazing enterprises into other systems, including arable rotations, viniculture, silvopasture, cattle, goat and agrivoltaics. The principal benefit of mixed systems is to diversify outputs per unit of land. Although yields of individual products may sometimes be less than in single-output systems, this is outweighed by greater combined yields, and in many mixed systems, lamb performance remains equal to that of sheep-only systems. From an environmental perspective, integrating sheep into other systems may also confer benefits for nutrient cycling, resource use, soil health, carbon sequestration, greenhouse gas emissions, biodiversity and sheep health.

The quality of the product for consumers is a strong driver for ensuring market share, maintaining sales and guaranteeing sustainability of sheep meat production systems. Meat product quality is driven by eating experience and nutritional benefits. Decisions made on-farm can influence age at slaughter, carcass composition and meat nutrient composition and thereby, impact the intrinsic properties of meat that define the quality. Research has shifted to consider intrinsic attributes of meat such as the intramuscular fat content to ensure tenderness but also the fatty acid profile for nutritional quality. There is increasing research identifying alternative forage species that can be grazed by lambs to enhance not only the balance of nutrient provided to the animal to increase utilisation and nutrient capture but, to also alter the intramuscular fat content of the meat and produce a more favorable nutritional profile.

This chapter describes advances in understanding and optimizing gastrointestinal (GI) microbiome in sheep. The chapter focuses on the assembly and development of the rumen microbiome and modulation at early ages. The rumen microbiome of sheep is shaped in early life by deterministic factors (including host genetics and diet) and stochastic factors (including colonization timing). Certain interventions, including dietary strategies, transplants and probiotics can influence microbial composition. The chapter then focuses on rumen microbiome and productivity. The rumen microbiome is crucial in shaping sheep productivity, as it has a strong influence on meat and milk quality, growth, feed efficiency, resistant to diseases and methane emissions. Current research shows strong correlations between microbiomes and productivity traits. Future trends on optimizing the GI microbiome are also given.

This chapter provides a review of advances in understanding and optimising sheep wool quality. It begins with a review of the microstructure of wool fibres that determine key wool properties and summarises fibre quality criteria and performance characteristics used in the industry. There are then discussions of how specific wool fibre quality characteristics affect the performance of wool fabrics, covering: wool fibre diameter (fibre fineness) and coefficient of variation (CV); fibre length; fibre crimp, strength and elasticity; colour, whiteness, lustre, handle and comfort. Finally, the chapter reviews research on key factors affecting wool quality including: sheep breed, quality variance within a wool fleece, the use of genetic technologies and the role of environmental factors.

Sheep production is a long-standing agricultural practice across the world, but the impact of our food production systems on the environment is receiving increasing attention, in particular with regards to climate change. To preserve the industry for future generations, sheep production systems must improve practices to reduce environmental impacts while considering socio-economic factors. This book chapter aims to provide an exploration of sustainability issues in sheep farming, summarising a key measurement method (LCA) while exploring challenges and prospects for improvement. Sustainability issues and what a sustainable sheep industry requires are discussed, alongside factors that limit application of LCA to sheep systems. This includes inherent uncertainty in modelling, for example variation in input data and methodology choices. A summary of recent LCA results is given and the impact of making these measurements on assessment of different mitigation strategies is discussed. The chapter concludes with reflections on the requirements for future research.

"One Health" issues affecting small ruminant production are important in both commercial businesses and smallholder farming communities throughout the world. Human food production from small ruminants needs to be integrated with food production from other livestock and from vegetable and cereal crops; and with the environment. This integration is important at regional, national and global levels, whereby ‘One Health’ benefits and trade-offs may be possible. Current levels of efficiency of conversion of finite environmental resources to food for human consumption by small ruminants around the world are currently woefully inadequate to meet ‘One Health’ human and environmental needs. Advances in livestock nutrition, husbandry and disease management are essential with regards to the United Nations 2030 agenda for sustainable development.

Good flock management is integral to sheep farming. An important aspect of this is optimising ewe lifetime production by reducing wastage (premature culling and ewe mortality). The consequences of reduced lifetime production include financial and environmental impacts, poor flock welfare, and, damage to the reputation of the industry. This chapter begins by defining ewe wastage and summarising what happens on sheep farms globally. We compare this with industry targets and discuss technology that can be used to gather information. We briefly look at common diseases that affect ewe longevity. This leads into a section on ewe nutritional requirements and how to assess ewe condition, with a major focus on ewe body condition score (BCS) at key production points (mating, scanning, lambing, 8-weeks post-lambing and weaning). We finish with a case study summarising how data collection and analysis, using the electronic tagging technology, has a positive impact on flock production.

Sheep play an essential role in the rural economy for food production, cultural heritage and landscape. Despite being generally less frequently kept in the types of confinement systems that cause the greatest public concern, sheep are not free from welfare compromise. In recent years, Precision Livestock Farming (PLF) has been increasingly adopted by most of the livestock industries, but not the sheep sector, due partly to costs and lack of training. This is despite the welfare advantages that could be achieved using PLF. This chapter presents the main health and welfare challenges faced by sheep, and the current and future PLF and digital technologies that can help address them. It also presents a case study – the TechCare project, that addresses the use of PLF to improve small ruminant welfare management. We conclude on how technology can help to improve health and welfare.

This chapter reviews key issues in the design and implementation of disease surveillance systems in sheep populations. It assesses different types of surveillance and flock health objectives, data sources, testing and sampling techniques. The chapter also reviews sampling strategies, including epidemiological variables, as well as information dissemination.

Sheep farming contributes to the world economy by producing wool, meat and dairy products and is an integral part of the agricultural sector. Sheep provide important ecosystem services, but their methane emissions can contribute to environmental problems. Transformations in social and consumer attitudes towards lamb and dairy products reflect changes in taste and a growing awareness of the health, environmental and ethical aspects of food choices. Increasing demand for more sustainable and ethically produced products encourages practices prioritising animal welfare, ecological protection and responsible management of natural resources. Emerging trends suggest that the future of the sheep meat and dairy industry lies in a harmonious balance between satisfying consumer preferences, taking into account environmental considerations and ensuring the welfare of the animals involved in the production process.

This chapter highlights ways of thinking holistically about grass and forage. Getting the system right has huge implications for the sustainability of the sheep sector, in terms of health, production, economics, environmental impact and social cohesion. This chapter focuses on seven elements that drive effective grazing systems. The reasons why each area is important, how it can be optimized and ways to engage farmers with tools and guidance will be discussed. Farmer case studies are used to highlight what these areas can mean in terms of profitability, health and welfare and environmental impact.

Like other livestock sectors, sheep production faces the challenge of improving sustainability. After considering the various dimensions of sustainability, this chapter reviews different ways this might be achieved. Firstly, it considers the potential for increasing the number of pasture species and broader diversity of species mixtures towards achieving sustainability goals. Secondly, it assesses how the potential benefits of pasture composition can be optimized by appropriate grazing management, including spatial effects and animal grazing patterns. Finally, it considers the relationship between forages and animal health and draws some conclusions about how sheep production can contribute to the achievement of sustainability.

Since the banning of antibiotic use in animal feeds in 2006 there has been much interest in supplementary feed additives to support animal production, efficiency and health. Furthermore, these supplements may offer the opportunity for reductions in enteric methane production. This chapter reviews a number of these additives and their benefits for sheep in particular, including prebiotics, probiotics, plant extracts, macroalgae, alkaloids, flavonoids and chemical additives. The different types of supplements within these categories are also outlined, such as yeast cultures and essential oils and their potential mode of action.

The survival of the newborn lamb is a crucial component of successful sheep farming. Lambs are more likely to die on the first few days after birth than at any other time and much research has been directed to addressing why this occurs and how it can be prevented. Lamb deaths can be attributed to due to a failure to transition successfully from in utero to independent life, congenital malformation, infection, predation or accident. Factors influencing the risks of the different causes of mortality include: the nutrition of the ewe during pregnancy, the number of lambs she is carrying, her genetics (and those of her lamb), her age and the number of previous pregnancies, and how the lambing and postnatal environment is managed. In this Chapter these different risks are reviewed and how they impact on the developing ewe and lamb relationship and ensure adequate colostrum intake in the lamb.

Sheep production plays an important role in supplying high-quality protein for human consumption and contributes significantly to the global economy. To ensure the sustainability and competitiveness of this sector, animal breeding stands as a vital pillar for continuous and cumulative improvements. Over recent decades, sheep breeding programs have undergone significant advancements and evolved to address current challenges in agriculture and food security. These developments, including genetic selection, advancements in genetic technologies, and a deeper understanding of the genetic architecture of both production and non-production traits, have played a vital role in sheep breeding programmes. They have enabled substantial genetic gains and contributed to the development of more productive, efficient, and resilient sheep breeds that can meet the evolving industry, social and market demands. This chapter provides a review of genetic aspects related to productive, reproductive, health, and emerging sustainability traits in sheep such as resilience, feed efficiency and methane emissions.

This chapter reviews the challenge posed by gastrointestinal nematode (GIN) infections in sheep. It sets out the growing problem of anthelmintic resistance (AR) to anthelmintic (AH) drugs conventionally used for GIN control. After reviewing the use of targeted treatments to slow the development of anthelmintic resistance, the chapter goes on to discuss alternative approaches such as the use of refugia. It also addresses other complementary interventions: selective breeding and grazing management, nutritional supplementation and bioactive plants, vaccination and biological control. The chapter concludes by emphasizing the need for more holistic and integrated practices to offset the issue of AR and effectively control GIN infection.

In this chapter the authors review the use of precision technologies in pasture-based systems as a mean to achieve these sustainability goals. There is a particular focus on Ireland, given that it has a predominantly grassland-based production system. The chapter reviews traditional measurement systems, the range of precision technologies, data processing and decision support systems. It also reviews applications such as virtual fencing and dairy herd management.

The call for downsizing livestock production to reduce negative environmental impacts will result in a further reduction in (permanent) grasslands in NW-Europe. This might hamper the provision of important ecosystem services (ES) by grasslands. In this study, ecosystem services of different types of grasslands are compared to arable land. It is shown that, particularly permanent grasslands score better than arable land on important ES’s, such as: soil quality, water regulation, GHG-emissions, water quality and biodiversity. On the contrary, food production is higher from one hectare of arable land than from one hectare of grassland. In such a comparison, land use types are considered as ‘permanent/stable’ situations. However, large temporal effects in greenhouse gas emissions and nitrate leaching are likely when grasslands are converted to arable land. It is essential that temporal and interconnected agro- and socio-economic effects of interventions are taken into account if changes in food systems are envisaged.

The objective of this chapter is to integrate the knowledge of feed quality assessment with that of grassland science to optimize nutrient fluxes in the plant-animal system. Although animal performance is the most accurate answer to define appropriate feed quality, in vitro laboratory methods are often used to evaluate feed quality by feed composition, digestibility or degradability of defined groups of substances. This is possible because of the standard laboratory conditions, the small amount of sample required, and the ability to analyze multiple samples simultaneously. The estimation of the energy value of forages is becoming increasingly important and the digestibility of organic matter plays an important role in determining the energy value of forages. High milk yields are possible and justifiable if the animals can be supplied with energy and nutrients to meet their performance requirements, a major part of which comes from forage intake.

Grassland farming has continued to support the lifestyle and growth of New Zealand since the first shipments of frozen products to Britain in 1882. Its importance remains relevant to the wealth of New Zealand, as a major trading nation in high quality dairy, sheep meat and deer products, with a relatively low environmental footprint, from a unique year-round use of grasslands. Research has increased efficiency, reduced emissions to water and air and improved animal health and wellbeing. Developments in animal and plant genetics have supported improvements in efficiency, reduced use of artificial chemicals such as fertiliser, anthelmintics, and pesticides, and increased productivity. Grassland production is in decline threatening the ability of pastures and forages to support future potential productivity gains in animal breeding. Developing solutions for both mitigation of grassland farming impacts and adaptation to future climate change needs to continue to ensure progress.

This chapter explores the potential of narrow-leaved plantain (ribgrass, Plantago lanceolata L.) to perform a range of roles in promoting more sustainable pasture-based livestock systems. The chapter begins by looking more broadly at the challenge of nitrogen losses from grazed pastures. This provides a context for first introducing plantain as a forage source. The chapter then explores recent research on the ways plantain affects nitrogen leaching. This functionality provides a way of mitigating nitrogen losses to air and water in intensive pasture-based livestock systems that is relatively simple to implement. This chapter summarises this and other uses of modern forage plantain and identifies scope for research relating to management for persistence, effects on animal health and milk composition and a better understanding of the biochemical mechanisms behind nitrogen cycle effects.

Many different techniques are available to observe and quantify ecosystem functions and services provided by grasslands. Measurements need to be analysed and integrated to translate data into management recommendations for adoption in sustainable grassland management. Here, we provide an overview of techniques available to collect data about grasslands. Different spatio-temporal scales require different modes of data collection to capture grassland dynamics. Examples are provided, e.g., how high temporal resolution measurements of greenhouse gas exchange are used to quantify soil carbon sequestration and detect trade-offs between C sequestration and N2O losses; how image analyses help in restoration projects; how remote sensing is used to improve grassland farming; and how models help predicting biomass production and long-term carbon sequestration rates. The benefits of FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing as well as strengths and weaknesses of techniques are addressed, management options outlined and gaps in knowledge identified.

The escalating demand for food, driven by population growth and urbanization, threatens global agricultural systems. Traditional agricultural policies emphasizing specialization and intensification often degrade ecosystems and heighten pollution risks. In response, sustainable intensification of existing cropland has emerged, yet the potential of grasslands to provide crucial ecosystem services is often overlooked. This chapter advocates for effective grassland management to harness its potential in offering regulating services, carbon sequestration, and biodiversity support. Challenges such as land-use change and intensification threaten grassland resilience. Integrating grasslands into mixed farming systems offers practical solutions, promoting synergies between crop cultivation and livestock rearing for sustainability. Ley systems within cropping practices further enhance food security and ecological resilience. Despite adoption hurdles, strategic grassland management remains pivotal for fostering global agricultural sustainability. This chapter underscores the necessity for concerted efforts in research, policy formulation, and management strategies aimed at optimizing grassland capacities and enhancing agricultural resilience.

The evolution of Homo as habitual consumers of inside- (marrow, brains) and outside-bone (meat, liver, fat) nutrients within grassland ecosystems, coupled with the infrequency of cardiometabolic diseases in modern hunter-gatherer communities, suggests that ancestral-type diets (although variable) offer insights into what constitutes suitable nutrition. The Neolithic era, characterized by a settled human lifestyle, brought dietary shifts based on crop and livestock agriculture. While presenting novel feeding possibilities, cereal-dominated diets often led to malnutrition, partially mitigated by secondary animal source foods (e.g. dairy). Technological advancements in industrializing societies brought widespread availability of animal-source foods, improving nutrition. However, industrialized diets eventually contributed to so-called ‘diseases of modernity’, potentially triggered by the gradual incorporation of refined starches, sugars, oils, and heavily processed foods. The certainty of evidence linking unprocessed red meat and whole-fat dairy to the emergence of such diseases is low, challenging prevailing dietary paradigms and emphasizing the need for nuanced reconsideration of the role of grassland-derived foods in public health.

This chapter provides a coherent, integrated overview of grasslands in Europe, addressing: (i) their current status and use, (ii) the ecosystem services they provide, (iii) the major drivers and trends affecting them, and (iv) promising innovations and research directions. These are illustrated by a case study from the project Grazing4AgroEcology that shows how innovative farmers, researchers and other stakeholders are now jointly exploring new approaches. Throughout the chapter, we advance the central argument that grassland systems can, if appropriately managed and supported, simultaneously deliver nutritious food and multiple ecosystem services, thereby contributing to resilient agricultural futures in Europe.

Grassland ecosystems are vital in global carbon cycling, biodiversity conservation, and agricultural productivity. As ecosystems typically bordering arid or semiarid zones, they are particularly vulnerable to the impacts of climate change, which will alter key environmental drivers such as temperature or precipitation regimes. This chapter outlines the anticipated impacts of climate change on grasslands, focusing on plant productivity and composition. It then discusses the methods and techniques used to determine the impact of climate change on grassland dynamics, highlighting the potential for shifts in phenology, species composition, and ecosystem functioning. Methods such as soil sampling, remote sensing, or ecosystem flux measurements are outlined. Challenges in predicting and mitigating the impacts of climate change are also discussed, emphasising the importance of researching adaptation strategies to enhance grassland resilience.

This chapter describes the diversity of data available about grasslands, and how such data may be analysed and fuel a variety of tools in order to support grassland management decisions at farm and territory scales, with a focus on EU countries. Specific attention is then drawn to the case of semi-natural grasslands that are more difficult to document but that are of high strategic importance. Based on different examples, the potential of combining different types of data and different tools is discussed, as well as the importance of multi-stakeholder networks.

How does grazing affect milk quality and fatty acid (FA) composition? Grazing animals can select, prefer green leaves and have fresh herbage diets rich in poly-unsaturated fatty acids (PUFA). The environment and farm management affect herbage allowance and grazing time. Milk from grazing-based production systems contains less saturated FA and more n-3 PUFA than with indoor feeding. The occurrence of natural trans-11 FA in milk predominates with grazing, whereas intensive feeding practices enhance trans-10 FA with possible negative health effects. Concentrates and starch-rich fodders affect rumen retention time and alter rumen biohydrogenation pathways. As some forbs reduce biohydrogenation, grassland species diversity may improve PUFA transfer efficiency from feed to milk. Trends in animal genetics and increased herd size, TMR feeding and automated milking systems cause reduction of grazing in Europe, which can increase saturated and trans-10 milk FA concentrations and reduce naturally occurring fat-soluble vitamins and antioxidants in dairy products.

The use of MSS, also known as herbal leys, has increasingly been recognised as a viable alternative in temperate grass-based agricultural systems to enhance forage yield, quality, and ecosystem health. By integrating complementary grass, legume, and herb species into the sward mix, these systems offer enhanced resource-use efficiency, reduced dependency on inorganic N fertilisers, and improved resilience to environmental stressors. Unlike traditional monocultures, MSS leverage the concept of functional diversity, typically utilising four to eight species that interact to maximise productivity. This diversity enables improved nutrient cycling, reduced weed growth, increased soil organic matter, and enhanced carbon sequestration, all of which contribute to ecosystem stability. This chapter outlines the principles, benefits, and practical management strategies of MSS and highlights their importance in creating sustainable and resilient agricultural systems that meet both agronomic and environmental goals.

The aim of this book has been to bring together the best available knowledge on temperate grasslands and to frame this knowledge in such a way that is useful to those who manage, advise on, study and make policy for these systems. The individual chapters of the book describe different scales going from plant physiology and soil processes through animal nutrition and product quality to landscape-scale management. They illustrate a strikingly consistent message: temperate grasslands are multifunctional systems whose potential is incompletely realized unless farm management, technology, research and policies are aligned to support multiple objectives simultaneously. This concluding chapter highlights the cross-cutting insights that have emerged from the preceding chapters, provides practical recommendations for practitioners and policymakers, and sets out overarching priorities for a research agenda to accelerate the transition to resilient, productive, sustainable, and biodiversity-rich temperate grasslands.

This chapter explores advances in grazing management. First, grassland dry matter production is described, followed by a section on grass measurement adoption. Grazing infrastructure is then discussed. Next, grass growth prediction is highlighted, as well as grass swards and alternative sward species. A section on grazing management influences on grass quality is also included. Grass breeding applications are covered next, followed by sections on grass variety selection indices, sward persistence, and climate adaptation.

The term "weed" is both relative and subjective, defined contextually and in relation to human activities. In this chapter, we discuss weeds in different grassland types, ranging from cultivated feed crops in arable land (leys) to natural multispecies grasslands. As agricultural systems transition from monocultures to more diverse natural ecosystems, the perception of what constitutes a weed may shift. In the current framework of complex human societies driving significant environmental changes, questions arise regarding whether weeds are always detrimental or if they can potentially offer solutions as well. We review different management practices to prevent weed proliferation, e.g. Nature-based Solutions (NbS) that, in contrast to conventional agriculture, include the role of biodiversity in suppressing weeds. To sustainably manage grasslands, we should address both the opportunities and threats posed by weeds. Challenges and solutions are discussed in the framework of a case study in Catalonia.

In this chapter, the authors describe the biology of the Epichloë-grass association, the secondary metabolites that are linked to the bioactivity, control of invertebrate pests, occurrence of mammalian toxicity globally, toxic responses in terms of animal productivity, health and welfare, utilisation of Epichloë strain variation in commerce, along with flow-on effects to animal product quality and food safety. There is a particular focus on the most well-studied, mutualistic tall fescue and perennial ryegrass endophyte associations due to their significant economic impacts and prospects to advance future sustainable grassland farming.

Expansion of the ingredient portfolio is crucial for sustainable aquaculture, as it ensures that the supply of feed ingredients aligns with future aquafeed demand. Industrial hemp grain and its co-products are plant-based materials known for their high-quality and easily digestible protein, healthy fats, and appropriate micronutrients required for the optimal growth and development of fish and shellfish. Hemp protein is rich in edestin (globulin), albumin, and sulfur-containing amino acids, while the oil is characteristically rich in linoleic acid (18:2n-6) and α-linolenic acid (18:3n-3). Despite these benefits, hemp is not without challenges. It contains notable anti-nutritional factors and is high in fiber. Furthermore, the presence of psychoactive Δ9-tetrahydrocannabinol (Δ9-THC) and its possible accumulation in flesh remain a subject of investigation. Nevertheless, research has demonstrated that hempseed cake/meal and oil may be effectively incorporated into fish diets, serving as sustainable alternative feed ingredients for aquatic animals.

Polycyclic aromatic hydrocarbon (PAH) pollution poses potential risks to human health, soil, and microbial biodiversity, presenting challenges for sustainable development. PAH pollution is mostly attributed to anthropogenic sources, such as domestic and industrial runoff or emissions, influenced by weathering processes, posing a challenge to transportation, fate, and distribution, with most of the available treatment methods being costly and environmentally unfriendly. This review discusses emerging technologies for remediating soil polluted with PAH and their contamination routes, techniques for their identification and tracking, persistence and bioaccumulation in the soil, and risks to and effects on human health and soil health. This review also discusses recent developments in the management of soil contamination with PAH and its challenges. This review suggests that nanoremediation methodologies enhance soil remediation by increasing microbial functionality and biodegrading contaminants. This eco-friendly and sustainable method addresses soil pollution with PAH, enhances the cleanup process, and minimizes environmental impact.

Soil pollution has become a major concern in China, driven by rapid industrialization and urbanization, posing a substantial threat to agroecosystems and human health. Approximately 16.1% of surveyed soil sites in China, including one-fifth of its farmland, is polluted, primarily with heavy metals and metalloids, leading to serious implications for food safety and public health. This issue of soil pollution is particularly severe in southern China. In response, the Chinese government has launched initiatives such as the "Soil Pollution Prevention and Control Action Plan" and various remediation projects to combat this problem. This chapter examines the extent of agricultural soil contamination in China, focusing on the widespread presence of pollutants like heavy metals, organic pollutants and emerging contaminants such as microplastics, and exploring ongoing efforts to implement sustainable agricultural practices, which may offer broader implications for global soil remediation and agricultural sustainability efforts.

Remediation of soils contaminated with heavy metals and metalloids should give priority to risk minimisation by reduction of their bioavailable fraction that poses actual risk. This may be achieved in certain situations, and within a reasonable timespan, using immobilisation/phytostabilization strategies, i.e., locking contaminants in the root zone, using plants, soils amendments, and rhizosphere microorganisms, lowering their bioavailability. The choice of proper soil amendments, eventually waste-derived organic and inorganic materials, is of pivotal importance to immobilize the contaminants. Non-edible crops may be used, with means for their biomass valorisation, and the selection of soil-quality indicators, to evaluate environmental risk reduction and the increase in soil health, are very important in this strategy. The objective of this chapter is to describe the importance of immobilisation/phytostabilisation and recent advances that may contribute to its use, not only in mining and industrial soils, but also in agricultural and peri-urban soils.

Phytoextraction is the use of plants to remove heavy metal contaminants from agricultural soil and keeping the contaminants inside their own tissues. If the metal accumulator plants, particularly those called hyperaccumulator plants, that can accumulate relatively large quantities of the heavy metals in the above-ground parts such as the leaves and stems, then these tissues could be harvested and moved off the site of contamination for disposal or further processing. Ideally, the plants selected for the phytoextraction purpose can be cultivated for intercropping and are compatible with the crops of interest in the same field with polluted soil. In this chapter, selected studies were discussed regarding their impacts on Cd and Cu phytoextraction research that have emerged from the major contemporary research trends including the strategies to enhance phytoextraction of Cd and Cu contaminants from agricultural and viticultural soils.

Soil contamination, stemming from both anthropogenic and natural origins, remains a critical environmental and public health concern. This contamination spectrum is diverse, encompassing inorganic elements like heavy metal(loid)s—lead, mercury, arsenic—and organic compounds such as pesticide residues and petroleum byproducts. The consequences of such contamination range from compromised soil health to severe health implications in humans. With emerging contaminants like PFAS, microplastics, and endocrine disruptors adding to the challenge, there's an urgent need for sophisticated detection and analysis methodologies. This review emphasizes the role of analytical tools, notably spectroscopy and mass spectrometry, in comprehensively addressing soil contamination. Techniques like atomic absorption Spectroscopy (AAS), Fourier-transform infrared (FTIR) and nuclear magnetic resonance (NMR) provide molecular-level clarity, while mass spectrometry elucidates intricate elemental and structural facets. Complementing these are imaging technologies, namely X-ray Fluorescence (XRF) and Hyperspectral Imaging (HSI), which afford both micro and macro environmental assessments.

Treated wastewater (TWW) has become recently a valuable and significant resource for crop production in irrigated agriculture. Use of TWW for irrigation includes benefits (e.g., conservation of nutrients), yet it also poses notable risks to crop production, soil ecosystem, the environment and human health. This review discusses risks arising from using TWW that include elevation of soil water osmotic pressure, addition of toxic ions and organic contaminants to the soil, deterioration of soil physical and hydraulic properties, hazard of surface and ground water contamination by dissolved organic matter, epidemiological threats to humans and animals, and increased abundance and diversity of antibiotic resistant bacteria and genes. Current knowledge highlights the importance of recognizing and elucidating the processes by which irrigation with TWW may lead to contamination of the soil ecosystem and the necessity to develop possible management practices that could mitigate these hazards and enhance the sustainability of TWW irrigation.

Agricultural soils can be contaminated with range of pollutants, including heavy metal(loid)s, petroleum hydrocarbons (PHCs), pesticides, and microplastic. Among them, PHCs are associated with oil handling, nearby mining operations, used tires, surface runoff, and agrochemicals. Bioremediation such as microbial degradation or phytoremediation can breakdown these PHCs. However, active microorganisms often require additional support, such as additives that can boost their degradation efficiency. Many additives have been known for a long time. Certain mineral-based additives, both in their raw and modified forms, have been the focus of much research by numerous researchers. These additives have the potential to be used directly in agricultural soil. This chapter will discuss clay mineral-based additives that can be biostimulator for the bioremediation of hydrocarbons in agricultural soil.

This chapter explores the challenges and solutions to trace element contaminants in agricultural soils. Trace elements are naturally occurring environmental components but human activities have significantly altered their distribution, leading to contamination across various environmental compartments. Contamination of agricultural soils with trace elements is a concern because they can persist in the soil and potentially be transferred to food crops and humans. While certain trace elements, like copper and zinc, are essential for the growth and development of plants and animals, others, like cadmium, lead and arsenic, don't have beneficial metabolic functions. Both types can be harmful to humans if exposure occurs at concentrations exceeding the maximum tolerable intake levels. Various remediation strategies can reduce their bioavailability in agricultural soils. Additionally, regulatory standards for trace element concentrations in soil or agricultural products could play a strong and indirect role in controlling their environmental impact.

Contaminants associated with agriculture is a major concern for environmental health, food safety, and sustainable farming. The contamination, stemming from diverse sources like industrial pollution, use of biosolids, secondary treated water, waste mismanagement, overuse of agrochemicals, and accidental spills, poses serious risks to natural ecosystem. The focus of the chapter is on the latest methods that improve our ability to detect, measure, and reduce these contamination risks. These methods include comprehensive evaluations of multiple contaminants and a holistic risk assessment approach. This approach is in line with the World Health Organization's One Health initiative, which emphasise the interconnectedness of humans, animals, plants, and their environment. The chapter aims to provide a thorough understanding of the risks associated with soil contamination and its far-reaching effects. It also seeks to guide sustainable land use, safe food production, ecosystem protection, and human health safeguarding.

When the EU Soil Observatory stated that 61% of EU soils are in an unhealthy state, contamination was one of the main reasons. Common contaminants include persistent organic pollutants, drug and veterinary product residues, microplastics, and residues from excessive fertilizer or pesticide application. This chapter focusses on organic amendments in agricultural soils that have the potential to immobilize toxic trace elements and support the biodegradation of organic pollutants, by immobilizing and supporting microbiological degraders. The most commonly used organic amendments are compost, biochar and chitosan. The chapter reviews new developments in remediation treatments based on chemical modifications of classic amendments and/or the combination of different amendments. Complex contaminant mixtures require novel developments of tailor-made amendment combinations.

This chapter focuses on per- and poly-fluoroalkyl substances (PFAS) as contaminants in agricultural soils. It begins by highlighting key PFAS characteristics followed by PFAS environmental entry modes and fate in agricultural fields. The chapter includes sections on human and ecological exposure routes and health risks from agriculture. This is then followed by plausible mitigation strategies and strategies to keep PFAS-impacted farms viable while minimizing PFAS impacts to our food system, including techniques in PFAS identification, tracking, remediation, and mitigation.

• Discusses the range of silvopastoral systems
• Considers the role of silvopastoral systems in delivering key ecosystem services
• Reviews the benefits of integrating livestock production with tree crops