Compiled & shared by-DR. RAJESH KUMAR SINGH, (LIVESTOCK & POULTRY CONSULTANT), JAMSHEDPUR, JHARKHAND,INDIA 9431309542, rajeshsinghvet@gmail.com
Biosensors are devices that can combine a biochemical molecule with a physical signal that can be translated into an indication which are used for Precision livestock farming . Biosensors help carrying out the procedures that are sensitive, selective, rapid, cost effective and portable. These devises are evolving as excellent substitutes for the existing conventional techniques.
Precision livestock farming applies a wide span of technologies, but is including increasingly advanced technologies like microfluidics, sound analysers, image-detection techniques, sweat and salivary sensing, serodiagnosis, and others. Biosensors and wearable technologies are the state of art of dairy health management, and seem to become one of the most impactful and practicable technology in the animal health market. Some of the most used technologies in dairy farms are wearable technologies, like tracking collars, leg tags or rumen boluses. But innovative technologies can also be implanted on animals to detect their sweat constituents, measure body temperature, observe behaviour and movement, detect stress, analyse sound, detect pH, prevent disease, detect analytes and detect presence of viruses and pathogens. Nowadays, a great number of these technologies for producing an accurate health status and disease diagnosis are applicable only for humans, but are being considered for their future use in livestock development and welfare.
Biosensor technology can offer the livestock industry new types of monitoring and measuring devices of which the specificity, sensitivity, reproducibility, speed and ease of use exceed the current technology. Biosensors can be applied to the detection and identification of infectious diseases in livestock, contaminants and toxins in feed, therapeutic drug residues in animal husbandry and oestrus detection.
Advances in engineering research and biomaterials, coupled with the decreasing costs of electronic technologies, have resulted in the emergence of ‘sensing solutions’ and smart computing technologies that include internet and cloud–based connectivity to develop integrated and networked physical devices for data collection and analysis. These systems are equipped to automatically collect data on physiological parameters, farm environment, production measures and behavioural traits.
In the modern world, new diseases that threaten animals’ health emerge every year. There is currently a lack of reliable, cost-effective diagnostic tests for early detection of diseases in farmed livestock animals. Biosensing technologies have the potential to address these problems by developing innovative diagnostic tools for the rapid detection of key health threats within the agri-food livestock sector.
India is the major producer and exporter of milk and milk products. The use of this technology can be beneficial for keeping the nutritional and quality aspects of milk and other food products. This will also reduce packaging costs and there is a potential in carrying out online monitoring of raw materials, trace compounds, vitamins, flavours, additives and contaminants in future.
There are number of areas where the unique capabilities of biosensors might be exploited to meet the requirements of environmental monitoring. Therefore, advances in areas such as multi-pollutant screening could allow these techniques to be more competitive. The present scenario demands for increased range of detectable analytes with portable device structure. Future Trends Therefore, solution to these resulting issues will require further convergence with associated technologies such as biochemistry, polymer chemistry, electronics, micro-fluidics and separation technology. Micro-electro-mechanical systems or MEMS technology is one of the promising areas that may be going to fulfill these demands in future. The technology is an integration of mechanical elements, sensors, acutators and electronics on a common silicon substrate through micro fabrication technology. Biochips and sensor arrays for detection of wide range of hazardous chemical and biological agents can be made out of these MEMS based devices, making it feasible for simultaneous detection of multiple analytes, This also brings the lab-on-chip concept. However, Immobilization and stabilization of bio-molecules on these Nano-devices may be a greater challenge. Some of the works in these areas have already been initiated. Utilization of molecular recognition ability of biomolecules like avidin-biotin or streptavidin-biotin in conjunction with a lithographic technique is being investigated for the micro immobilization of enzymes on silicon wafers for biosensor applications. Immobilization of enzymes on silicon supports has attracted attention in biosensor chip technology and a variety of classical techniques have been proposed. There are interesting possibilities within the field of biosensors. Given the existing advances in biological sciences, coupled with advances in various other scientific and engineering disciplines, it is imminent that many analytical applications will be replaced by biosensors. A fruitful fusion between biological sciences and other disciplines will help to realize the full potential of this technology in the future . There is a big potential for on-line monitoring of raw materials, trace compounds, vitamins, flavours, additives and contaminants. In future, on-line use of biosensors provides feedback control of both the component and microbial levels of these and similar processes by continual on-line monitoring. Quality control in food and dairy industry still relies on human senses such as smell, sight and taste. Quality control of microbial spoilage, oxidative rancidity and fruit ripening by tasting may be replaced by biosensors. Though biosensors are not cheap today but in due course of time due to their wide applications may become cheap. The cost of biosensor depends upon its design for the specific parameter to be analyze and the biological component to be used. Looking to the scope, need, applications and advantages of biosensors in food and dairy industry these are economically viable
Types of biosensors
The classification of biosensors is given below:
The two main elements in a biosensor are a biological recognition element or bioreceptors and a signal transducer. On the basis of these two elements, biosensors are classified. Bioreceptor The bio-receptor is a bio-molecule that recognizes the target analyte and can be divided into three distinct groups: bio-catalytic, bio-affinity and microbe-based systems. o Bio-catalysis- based biosensors depend on the use of pure or crude enzymes to moderate a chemical reaction. Enzyme inhibition is required for a large number of environmental pollutants such as antibiotic/drug residues, aflatoxin M1, pesticides and heavy metals in food system. Such methods require the use of chromogen/fluorogens for measuring the presence of target contaminants in food. This works on the principle of non-competitive enzyme action on inducer resulting in indirect reduction of starch iodine mixture through penicilloic acid. o Bio-affinity based biosensors- These biosensors rely on the use of proteins, DNA or microbial receptor to recognize and bind a particular target.
Microbial biosensors-These biosensors involve application of microorganisms or their spores as biological recognition element. They generally involve the measurement of microbial respiration, or its inhibition by the analyte of interest . The basic requirement of a biosensor is that the biological material should bring the physico-chemical changes in close proximity of a transducer. Thus, immobilization technology has played a major role in this. The biological material is immobilized directly on the transducer or on membranes which can be mounted on the transducer. Immobilization not only helps in forming the required closed proximity between the biomaterial and the transducer but also helps in stabilizing it for reuse. o Immobilization-based biosensors-Some of the widely used immobilization techniques include absorption, entrapment, covalent binding and cross-linking. Novel techniques have been developed for immobilizing viable or non-viable cells through adhesion on a variety of polymeric surfaces including glass, cotton fabric and synthetic polymeric membranes using poly ethyl- enimine (PEI) . Signal transducer A signal transducer is the second essential component of a biosensor. It converts the recognition event into a measurable signal. The transducer can take many forms depending upon the parameters being measured. The most well developed classes of transducers are potentiometric, amperometric, conductometric, optical, acoustic or piezoelectric etc. These utilize various electrochemical responses to measure changes in the electrical properties of the biological recognition element. Based on this, the biosensors are:
Optical biosensors-These employ linear optical phenomena including fluorescence, phosphorescence, polarization, rotation, interference, surface Plasmon resonance (SPR), total internal reflection fluorescence (TIRF). For non-linear phenomena includes second harmonic generation
Application of biosensors for quality assurance of dairy products—————-
Producing high-quality food with a low ecological footprint and high animal well-being is one of the greatest challenges of modern livestock production systems. In order to fulfil these requirements, farmers invest more into their properties, resulting in high-value farms and an increasing necessity to guard, track and monitor all assets with the help of innovations. Those technologies need to seamlessly and proactively integrate to turn the industry into a smart and sustainable one. While the number of connected devices continues to rise simultaneously with the growing demands on the agri-food sector, particularly precision livestock farming requires reliable, affordable, low-power, wide-range network technologies and smart sensors (LoRa and NB-IoT). As those IoT applications play an important role in this use case, leveraging their key characteristics is crucial. The system is thus made up of a small rumen bolus, monitoring various physiological data (temperature, rumen and body activity, pH level), and a cloud-based server application to provide accurate information for daily operations. At the same time, involving multiple types of farms and connected supply chain stakeholders across different regions helps to further develop and deploy the latest innovations required to perform efficient and sustainable livestock farming and animal breeding.
USES OF NANO BIOSENSORS TECHNOLOGY-
• Increase quality analogous to yield, prodictivity, production and reproduction rates;
• Analyse needs of dairy and beef farmers;
• Decrease the occurrence of animal health problems (heat, stress, rumen acidosis; milk fever, etc.), the number of veterinary interventions and antibiotics or hormone treatments;
• Improve farmers’ work-life balance;
• Accurate indoor and outdoor positioning through NB-IoT or LoRa geolocation;
• Provide standard APIs for third party system integration;
• Improve animal welfare by understanding cattle behaviour, rumen contraction detection and animal activity.
Advances in engineering research and biomaterials, coupled with the decreasing costs of electronic technologies, have resulted in the emergence of ‘sensing solutions’ and smart computing technologies that include internet and cloud-based connectivity to develop integrated and networked physical devices for data collection and analysis. These systems are equipped to automatically collect data on physiological parameters, farm environment, production measures and behavioural traits.
Precision livestock farming aims at creating a management system that relies upon autonomous,continuous, real-time monitoring and control of all aspects of livestock management, including reproduction, animal health and welfare, and the environmental impact of livestock production. It is assumed that the direct monitoring of animals will achieve greater control over their health status, which will eventually translate into better animal product quality over longer periods of time. Biosensor technology shall enable accurate and affordable acquisition of data points, while the smart algorithms, coupled with networked farms, shall further decision making and management processes in the animal farms. The primary goal of precision livestock farming is to generate reliable data using biosensors and run it through intelligent software systems to create value for the farmer, the environment, and the animals in the form of improved animal health and welfare, increased productivity and yields and reduced costs while minimising the impact on the environment.While the biosensor technology is available for individual parameters, key advancements in the field are expected to generate robust monitoring systems for a multitude of parameters. Another key challenge currently faced is the slow uptake of these technologies on commercial farms. This has been attributed to the fact that although the precision systems and biosensors generate abundant data, the data is currently not being converted into useful information that could be utilised for the decision-making process in livestock management. Furthermore, the economic benefits of using these advanced systems is set to be demonstrated to individual farmers, who are reluctant to make investments in these systems in the absence of a clear economic benefit.
There is no doubt that advancements in the development of nanobiosensors, combining nanotechnology with highly specific analytic techniques for metabolic biomolecules and surveillance systems for monitoring animal health and welfare will be ubiquitously used to manage livestock farms and prevent disease outbreak. The key challenges that remain to be resolved include harmonisation of methods across various platforms and large-scale implementation of data analysis and sharing technologies.
In the modern world, new diseases that threaten animals’ health emerge every year. There is currently a lack of reliable, cost-effective diagnostic tests for early detection of diseases in farmed livestock animals. Biosensing technologies have the potential to address these problems by developing innovative diagnostic tools for the rapid detection of key health threats within the agri-food livestock sector.
There are numerous factors that affect food production and have an influence on food security
around the world. By 2050, food demand is expected to increase by 70%, and meat production will increase by 50%, making agri-food and livestock key industries for future growth.
Health threats to animal populations can disrupt food supply chains and commerce with potentially long-lasting effects on human health, as well as economic impacts. With novel infectious agents and global pandemic factors on the rise in farmed livestock industries, efficient and timely strategies for monitoring and predicting risks are crucial. With current technology, detecting diseases in the early stage requires time-consuming and expensive laboratory tests. There is a need for detection tools that can predict when an incident is likely to occur and in what population, inform diagnosis and treatment options, and forecast potential impacts on a given population (both human and animal). Furthermore, such technologies must be accurate, affordable and broadly available. Strengthened laboratory and field capabilities are needed to support these capacities. Diagnostic tools provide crucial information to surveillance programs in diverse operational contexts, including networks and reference diagnostic laboratories associated with the World Organization for Animal Health (OIE), the United Nations Food and Agriculture Organization (FAO), and the Canadian Food
Inspection Agency (CFIA). These systems not only integrate the data on individuals and groups; they can also help with the decision-making process by assisting in the early detection of health issues and wellbeing problems in individual animals. These integrated systems will also help in the implementation of corrective measures and improvements in management processes for animal husbandry practices. The biosensor market for the year 2013 was valued at US $11.39 Billion and is expected to increase to US$22.68 Billion by 2020. This growth in the biosensor market and associated applications is attributed to an increase in the demand for point-of-care testing. Furthermore, non-invasive health monitoring is also driving the growth and development of nanotechnology-based biosensors.
The market for point-of-care testing in veterinary diagnostics is expected to increase at acompound annual growth rate (CAGR) of 18%, reaching US$6.71 Billion by 2021. Novel diagnostic tools and disease modelling will enable decision-making and investigate the rapid
diagnosis of epidemic and emerging diseases of farmed animals. The nanotechnology approach in developing biosensing tools offers direct benefits through simpler testing, smaller size, greater accuracy, faster results, and faster responses to key health threats in the farm animal sector.
We have entered a ‘fourth revolution’ in agriculture. This denotes the proliferation of new technologies including the Internet of Things, precision agriculture and mobile apps for disease surveillance.
These technologies shall focus on the non-invasive methodologies to assess animal welfare by
quantifying the stress and metabolic disease biomarkers, welfare assessment based on activity of the animals (monitoring oestrus and lameness detection to maximise animal production) and sensors for temperature and pH sensing (to determine calving alert and rumen function). Furthermore, various non-invasive sensing technologies for early disease detection shall help in saving animals’ lives as well as reducing expenses for the farmers. A combination of these technologies and the use of ‘smart’ husbandry support systems will ensure maximum productivity while improving the wellbeing of farm animals . Non-invasive technologies for the chemical and biological analysis of samples from livestock, food and feed can rapidly provide detailed information to evaluate the safety of various biological samples. Biosensors equipped with robust data collection and integration infrastructure will be able to realise this potential and shall become vital elements in real-time analysis of industrial agriculture. Not only will such systems help in maximising the utilisation of resources for farming; they will also allow for an evaluation of individual and group behaviour of animals. Development of on-site biosensing technologies will enable rapid, cost-effective and meaningful monitoring of dietary inputs, environmental conditions, genetic makeup, performance, metabolism, welfare and physiological state of animals.
1. Biosensing – Taking a systems biology approach
The application of biosensors in animal husbandry and agriculture will increase competitiveness in the ever-changing global economy. The enormous amount of data generated by the continuous monitoring shall generate new knowledge on animals’ health and physiology and is expected to result in the development of technologies that will improve efficiency of animal production, better usage of dietary resources, improved health and welfare of animals through improved animal management, and reduced output of waste per unit of food product, thereby decreasing the impact of animal production systems on the environment.
Taking a systems biology approach to animal productivity and wellbeing is the way forward in animal husbandry, as well as in agriculture. It will also be indicative of future human performance and wellbeing initiatives. Collecting individual animal data as opposed to just ‘herd management’ will be necessary to monitor the wellbeing of individual animals as well as animal groups, and will help in identifying diseased animals sooner so as to provide healthcare and prevent any disease outbreaks. Moving agriculture (animal productivity and wellbeing) on a parallel course with human medicine and social science (human productivity and wellbeing) will enable the determination of multi-parametric data on physiological and environmental factors affecting animal welfare and productivity. This integrated database can be used to implement best farm practices to ensure animal welfare and productivity and to predict animal behaviour.
Biosensing applications for livestock management and welfare will foster productive, value-added partnerships in ways that will lead to social, health, environmental and economic benefits. The approach to develop new solutions ranges from involving molecules to ecosystems, from nanotechnology to big data analysis and management, and from microbes to sheep to human populations. Moreover, real-time monitoring of animal health and assessment will have a direct impact on animal productivity and better utilisation of resources. The future of biosensors lies in utilising the comprehensive knowledge of animal physiology, genetics, environmental sciences and animal nutrition, and integrating this knowledge in a meaningful way will aid in the translation into real commercial and societal benefits.
Biosensors will manifest themselves as indispensable tools in animal husbandry——–
Innovation and development for new approaches
Future developments in biosensors are expected to result in the development of new methodological and technological approaches to measuring dynamic changes in real time, with respect to the changes in physiological state and metabolism (e.g., gastrointestinal flora circulating levels of anabolic and catabolic hormones, immune function, gene expression). This is to better understand the factors influencing animals’ responses, and to develop solutions (e.g.,husbandry practices, technology and associated decision support system) that improve productivity and/or wellbeing of these animals.
Real-time data acquisition and analysis——————-
Monitoring of real-time autonomic responses (e.g., respiration rate, heartrate and heartrate variability, blood pressure, changes in peripheral blood flow) and defence-related reflexes (e.g.,startle) using novel biosensing tools will help to investigate how housing, diet and genotype affect animals’ resiliency to stressors. These sensors will help in the understanding of factors that influence the wellbeing of animals, and in the development of solutions (e.g., husbandry practices, genotype selection) that improve the welfare of livestock and companion animals.
Advances in wearable or imprinted biosensors that are flexible and allow data transfer remotely will be of special significance in this advancing area .
Rapid characterisation of food and feed—————
Biosensors shall be used to develop approaches enabling the rapid, accurate characterisation of
dietary inputs and final products (meat, eggs, milk) in terms of nutrient content (total and bioavailable), anti-nutritional factors and bioactive components, as well as chemical and microbiological contaminants, with the aim of implementing this technology at the level of the commercial feed mill or animal food product processing plant. On the other hand, they would also help in the decision-making process to alter the composition of feed to the animals in case the animal products deviate from the expected nutritional status.
Animal trait analysis and selection of robust breeds—————
Biosensing may also help to select special animal breeds that are robust and resilient to environmental stressors by enabling rapid assessment of the impacts of animal genotype and environmental factors at different life stages. Such assessment would yield critical knowledge to better understand genotype by environment interactions, in order to improve production efficiency and animal wellbeing. The developments in biosensing will also help us better predict and manage the impacts of climate change on animal agriculture over the next several decades.
Enabling planning of energy budgets and reduction of environmental impact———–
The data collected and analysed using biosensors can assist in constructing detailed nutrient, energy and elemental budgets for diverse livestock species at different life stages in response to modulation in diet composition and environmental conditions, allowing precise management and efficient usage of nutrients and minimisation of waste outputs. This will have a direct impact on the efficient management of feed inputs and water resources while reducing the cost of production, wastages and environmental footprint. For example, real-time monitoring of cattle movement can provide information on the quality and quantity of forage, and the ability to determine required changes to the grazing systems. Monitoring variables like the consumption of water can provide insights into feeding behaviour, as well as the interaction between grazing systems management and this behaviour. Quantifying animal water consumption within a grazing environment can help to identify the impact of animal grazing on water quality, as well as land utilisation.
Development of mathematical algorithms for better understanding of complex biological
systems and their interaction with the environment————————–
In the present day and age of big data, the data from animal farms is expected to help in the development of advanced bio-mathematical models that are able to integrate data from the aforementioned scientific research efforts and theoretical understanding of complex biological systems. These models and simulations will allow for an improved quantitative appreciation of the scientific and management aspects of animal agriculture. These will enable the assessment of changes in the system with respect to different production, genetic selection, nutritional and environmental factors. Ultimately, these models will help to identify approaches and strategies to improve the productivity, efficiency and wellbeing of animals and mitigate the potential negative
environmental impacts of livestock production. These models will also provide the basis for the development of the specific algorithms required by a variety of decision support systems.
Current research and development in the field of biosensors for animal health management focusses on innovative non-invasive, wearable sensors equipped with electronic systems for data collection and transmission of data wirelessly. For specific areas where wearable sensors cannot be multiplexed, especially in disease diagnosis, the development of portable hand-held systems with immediate readout of results will enable fast decision-making processes and help in rapid management of animal diseases. For example, non-invasive screening has been applied to the detection of foot-and-mouth disease using hand-held air samplers with electrostatic particle capture. In this case, infectious viruses are captured and subjected to analysis by real-time PCR (polymerase chain reaction). Such biosensors can hasten the process of monitoring, diagnosis and isolation of contaminated livestock in epidemiological contingencies .
On the one hand, in the field, integrated biosensors will enable intensive (frequent and rapid) evaluation of all aspects affecting an animal’s behaviour, genetics and physiology, as well as dynamic changes in metabolism and welfare. On the other hand, they will help manage the production and analysis of the animal’s food composition and help in rapid screening of diseases, which at present cost billions of dollars annually to the livestock industry worldwide. For example, application of nanobiosensors for rapid detection of foot-and-mouth disease in swine has a potential to save costs as well as prevent the spread of infection to the uninfected animals.
Advancements in biosensing technologies is also expected to focus on the use of non-destructive chemical analysis technologies, such as near infrared spectroscopy (NIRS), nuclear magnetic resonance spectroscopy (NMRS) and tunable diode laser absorption spectrometry (TDLAS) for the rapid and detailed evaluation of a biological sample’s chemical composition and safety.
All these exciting technologies need to be developed for seamless performance and validation, before they can be used routinely in research and, ultimately, in a commercial setting. Use of surgically modified animals (e.g., multiple intestinal cannulations, arterials/venous catheters, heart rate telemetry devices) for serial sampling to correlate physiological and metabolic indicators with other variables (e.g., the non-invasive monitoring of behaviour and stress responses, e.g., thermal imaging to assess changes in blood flow). This intensive collection of data from various sensors and complementary analyses will generate a vast magnitude of information, which will need to be effectively collected, compiled, synthesised, securely stored and analysed using a series of advanced statistical, bioinformatics and mathematical modeling approaches. This will require the implementation of a well-integrated and robust data collection, storage and computing infrastructure.
2. Monitoring jaw movement of cattle to know the grazing efficiency—————–
Cattle grazing behaviour requires individual monitoring of cattle based on three important
parameters, including the location of the animal, analysing animal posture and the movement of
the animal, especially movements such as walking and movement of the jaw.Jaw movements define the grazing behaviour of the cattle, and there are three different classes of biosensors that can be used to identify such movements. These include:
Mechanical sensors (pressure sensors), acoustic sensors (microphone) and electromyography sensors
3. Biosensors for breath analysis—————-
Disease diagnosis by identification of volatile organic compounds (VOCs) has long been of
interest to researchers, as it offers a non-invasive methodology. VOCs can be found in the breath,blood, faeces, skin, urine and vaginal fluids of animals as well as humans .These compounds are produced by a number of biochemical reactions, pathogens, and host pathogen interactions and are affected by a number of biological variables such as age, actions, and biochemical pathways .Breath monitoring provides a non-invasive and easy approach to determine the physiological and general health status of animals.
In cattle, analysis of VOCs has been explored to diagnose bovine respiratory disease, bovine tuberculosis , Johne’s diseas, keto acidosis and normal rumen physiology. A rapid, non-invasive identification of foot-and-mouth disease has been performed using air samples collected with a hand-held prototype device equipped with electrostatic particle capture in a microchip chamber of 10-15 μL.
4. Sensors analysing metabolites in perspiration—————–
Most biosensors developed for analysing metabolites in sweat were developed with the purpose of human health monitoring. These have been used to analyse sodium concentration and lactate levels, and converted to portable formats (belt form) to analyse sweat.
5. Analysis of tears for continuous glucose monitoring—————
Metabolites in tears can provide information about the concentration of these metabolites in blood and provide a non-invasive continuous monitoring technique.
6. In vivo implanted biosensor to analyse stress in fish
Fish health is affected by multiple environmental parameters as well as conditions in the fish
farms. Stressors include water pollution and changes in climate. Farm management practices like
stocking density and water exchange can also induce fish stress .
7. Detection of ovulation————-
Progesterone
Breeding forms an integral part of livestock farming. Detection of the ovulation period in cattle is important in order to determine the time window for artificial insemination. Conventional oestrus detection involves ocular inspection of cattle by skilled labour, which is expensive as well as inefficient. Biosensors for ovulation detection have been researched for a long time.
8. Biosensors for animal diseases—————–
Avian influenza virus
Foot-and-mouth disease
Automated Detection of Mastitis
Subclinical ketosis
Detection of porcine reproductive and respiratory syndrome (PRRS) virus
9. Livestock monitoring systems for observing physiological parameters and health of cattle——————–
Jegadeesan et al. have proposed a two-component system. The first component is the monitoring and collection of data on the health parameters of animals in the field, and the second component is the monitoring and acquisition of data on animals from the farms. Animals are subjected to a variety of stress factors during their lives on farms. These include stressors due to changes in temperature, transport across farms, physiological stress due to ill health or improper food intake as well as stress due to restraint.
Reference:On request.
