Agriculture and food have a greater role to play in order to achieve sustainable development goals. Therefore, there is a need to put an end to the effect of pathogens on food quality and safety. Pathogens have been recognized as one of the major factors causing a reduction in profitable food production. The conventional methods of detecting pathogens are time-consuming and expensive for the farmers in rural areas. In view of this, this chapter reviews the biosensors that have been developed for the detection of biological hazards in food and agricultural sectors. This chapter also lays emphasis on the impact of nanotechnology on building a fast, reliable, more sensitive, accessible, user-friendly and easily adaptable technology for illiterate farmers in the rural communities. On the whole, we have addressed the past and most recent biosensors that could ensure the quick delivery of vision 2030 which aims to end hunger and poverty.
- food safety
Biosensor could be defined as an analytical device that produces a quantifiable signal proportional to the concentration of an analyte (i.e., pathogen or its cellular component or toxin molecule). The device comprises a transducer and biologically active elements or materials such as nucleic acids, enzyme, and an antibody that allows detection of an analyte by specific interactions . Biosensors symbolize the end product of a quickly growing field, integrating fundamental and engineering and computer sciences to meet the urgent demands in various areas where its application is required [2–4]. There are different types of biosensors: acoustic, amperometric, electrochemical, optoelectric, calorimetric, potentiometric, immuno and piezoelectric. In this chapter, we report the earlier and recent trends in the usage of biosensors in the identification of pathogens that are responsible for biological hazards in food and agricultural sectors.
2. Traditional methods for pathogen detection in food and agricultural sectors
2.1. Polymerase chain reaction
The discovery and the development of polymerase chain reaction (PCR) have been a boon in the identification and characterization of pathogens [5–7] . PCR employs the following steps: isolation and purification of genomic DNA from plants or food-based pathogens, amplification of the target sequences followed by application of agarose gel electrophoresis for resolving the amplified products, and approximation of their fragment size by comparing with a standard DNA molecular mass marker .
The PCR is a nucleic-acid-based detection method. It is preferable than the other culture dependent techniques in the determination of microbial pathogens. The reasons being rapidity, accuracy, specificity, sensitivity, and the ability to identify small quantities of target nucleic acid in a given sample. It can also detect different pathogens in a single multiplex reaction. In addition, the detection of pathogens is not limited to the laboratory alone. Some portable PCR machines have been made available. The Smart Cycler is an example of portable PCR. It was developed to perform PCR for field identification of
Random amplified polymorphic DNA (RAPD) assays have been carried out on different isolates of
2.2. Culture and colony counting
The culture methods of identifying pathogens from food and agricultural based products involve the morphological and biochemical identification by staining and studying the metabolic profile of the pathogens. These methods require determination of the most suitable media that would favor their growth at different conditions. This may involve pre-enrichment, selective enrichment, biochemical screening, and serological confirmation. The major problems associated with using cultures for identifying pathogens are the high cost of media and the laborious and time-consuming techniques. In addition, they are not feasible for on the spot and real-time or rapid sensoring/identification of threat agents .
2.3. Immunology-based method
The immunological approaches for the detection of pathogens work on the principle of specific affinity between microbial antigens and monoclonal or polyclonal antibodies. They are used for rapid detection and identification of pathogens, including bacteria, viruses, fungus as well as their toxins. This method is very sensitive, rapid, selective and cost-effective. Latex agglutination and enzyme-linked immunosorbent assay (ELISA) are the techniques majorly used in food industry for identification of food pathogens like
2.4. Hand-held immunochromatographic assays (HHIA)
The hand-held immunochromatographic assays (test strips) are normally used for tentative or preliminary identification, both on-site and in laboratories. The test strips consist of nitrocellulose membrane immobilized with specific antibodies followed by a second antibody that is coupled to the colored particle. The liquid sample containing the analyte is then allowed to mix with the antibody-coupled colored particle. The analyte binds to the antibody-coupled particle and this complex migrate by capillary action along the nitrocellulose strip until it meets the immobilized antibody. The interaction produces a visible colored line indicating a positive result and vice versa. This type of assay takes only about 15 min to perform and the result can be read visually without any instruments. Therefore this detection technique is especially suitable for on-site identification. However, HHIA have two major limitations; limitation in the number of biological hazards that can be detected per strip and display of varying sensitivity levels with their respective target agents .
3. Biosensors used for pathogen detection in food and agricultural sector
3.1. Detection of food pathogens
Liébana et al. have developed a quick and simple biosensor based on electrochemical magnet immunosensing with
Majumdar et al. developed an amperometric biosensor which was able to detect
3.2. Detection of animal, poultry, and dairy pathogens
Ellis et al. were able to develop a sensor that could detect breath-derived 500 volatile organic compounds. The analysis helped in identifying Bovine tuberculosis (
Neitzel et al. have developed a biosensor that can detect the presence of mastitis in any milk product . Duarte et al. had also developed a biosensor that couples immune assay with magnetic nanoparticles . Fűtő et al. developed selective amperometric methods that could sense the presence of spoilt and affected milk . The spore-based biosensor is another novel strategy that has been developed to detect the presence of contaminants, including aflatoxins, antibiotics and microbial pathogens in milk. Balhara et al. developed a biosensor that can detect the presence of
3.3. Detection of pathogens in plants
A high-density microelectrode array biosensor was developed by Radke and Alocilja . The biosensor can detect
3.4. Detection of mycotoxins
Carlson et al. developed a fluorometric biosensor to detect and quantify aflatoxins. These toxins are produced by a family of fungi and are commonly found in a variety of agricultural products. The device developed by Carlson et al. operates on the principle of immunoaffinity for specificity and fluorescence for a quantitative assay . Pohanka et al. and Ben Rejeb et al. used Electrochemical (amperometric) antibody-based biosensor to detect the presence of Aflatoxin B1 in spices and olive oil respectively [65, 66]. Wang et al. used an electrochemical (amperometric) antibody/enzyme biosensor to detect Aflatoxin M1 in milk . Asuncion Alonso-Lomillo et al. used an electrochemiluminescent aptamer biosensor to detect the presence of Ochratoxin A in beer and coffee samples . Panini et al. used electrochemical (amperometric) antibody biosensor to detect the presence of zearalenone in corn silage . The presence of deoxynivalenol, T-2, and HT-2 toxins was also detected in cereals and baby food with the help of optical (SPR) antibody biosensor [70, 71].
4. Application of nanotechnology-based sensors in agriculture and food sectors
4.1. Nanomaterial-based sensors for food industry
The food industry as mentioned earlier is continuously challenged by the occurrences of foodborne diseases. WHO in its report for the year (2015) estimated 420,000 deaths occurring every year due to consumption of contaminated food, of which 125,000 deaths are of children under the age of 5, bearing a 40% burden of foodborne diseases . Foodborne disease can be defined as “any disease usually either infectious or toxic in nature, caused by agents that enter the body through ingestion of food.” The causal agents are bacteria, viruses, and protozoa, fungal or bacterial toxins, metal ions, and pesticides. Some of the important pathogenic organisms categorized are
These methods are robust and sensitive as they allow the detection of pathogens by targeting specific nucleic acids or proteins. However, the requirement of an expensive instrument and chemical reagents, experienced personnel, large sample preparation and slow generation time prevent the immediate detection of pathogens thus delaying preventive treatment in patients [75, 76]. Thus, the shift has been to the development of easy to use, rapid and sensitive on the site detection and also stable and portable detecting kits. Nanotechnology has paved way for such developments in the last decade. The versatility of nanomaterials has made possible the development of sensors in the food industry for monitoring the environment and food quality . Some of the advancements in the design and development of nanoparticle-based sensors for food safety are discussed below.
4.1.1. Gold nanoparticle (AuNP)-based sensors
4.1.2. Magnetic nanoparticle (MNP)-based sensors
Magnetic nanoparticle-derived sensors are one of the widely used sensors for detecting and removing food contaminants. The large surface area of MNPs makes them one of the best supports for immobilization of functionalized surface groups thereby improving the loading control and immobilization efficiency . d-mannose functionalized MNPs were used for detecting
4.1.3. Quantum dots (QD)-based sensors
Semiconductor QDs show size-dependent optical and electronic properties making them most suitable for fluorometric-based sensors . The most commonly used are the CdSe quantum dots . The QD-derived fluorescent biosensor was developed for detecting
4.2. Nanomaterial-based biosensors for agriculture
The use of nanobiosensors has been regarded as the more advantageous approach for detecting pathogens in healthcare and food industry as mentioned above. Their rapid and high sensitivity further extends their application in agriculture for disease assessment. Fluorescent silica nanoparticles (FSNP) conjugated with antibodies were successfully used for detecting plant pathogens such as
5. Recommendations and future trends
There is a need to develop biosensors that would be effective and reliable for the routine utilization especially in the area of food and agriculture. Therefore, there is a need to develop biosensor that has the following characteristics in one device: hand-held, and portable, viable cell countability, single button device, easy utilization, accurate strain and species determination, selectivity and short detection time. And most importantly, the biosensor must be inexpensive with simple configuration for access to the illiterate farmers in developing countries.
Because of the useful features of biosensors, their utilization in the bio-monitoring of biological hazards, commonly recorded in agriculture and food sectors has been necessitated. The constant application of pesticides in controlling pathogens has led not only to pathogen resistance but also, bioaccumulation and biomagnification of the chemicals with subsequent health hazards and environmental pollution. Therefore, the demand for biosensors in the market has increased tremendously. Biosensors should be within the reach of food handlers and agro-allied industries to enable them to monitor and determine the presence of pathogens in their food and agricultural products.
The authors are grateful to the Department of Biotechnology (DBT), New Delhi, India, The World Academy of Science (TWAS) for TWAS-DBT post-doctoral given to Dr. Adetunji. FR number: 3240293141.
Conflict of interest
The authors declare no conflict of interest.