July , 2021, Volume : 2 Article : 15
Precision Agriculture with Nano-based Biosensors
Author : Kinjal Mondal and Ayush G Jain
ABSTRACT
According to the European Union`s Directorate-General for Internal Policies, precision agriculture is a modern farming approach of measuring and responding to inter and intra-field varying conditions, so that a decision support system can be formed for the whole farm management and a maximum benefit is achieved from the available resources. Advents in nano-based biosensing technology enhance agricultural productivity by its ability to provide better fertilization management, reduced input cost, and environmental safety. Nanobiosensors are also used in the rapid detection of phytopathogens with precise quantification and thereby increasing food safety for the consumers. Since sensor specificity relies heavily on efficient surface functionalization strategy, nanostructural entities provide extreme sensor miniaturization and multiplexing. This article exhibits how nanobiosensors have gradually achieved massive appraisal for rectifying various problems of conventional farming practices and revolutionizing the field of precision agriculture.
Keywords: Precision agriculture, nanobiosensors, surface functionalization, sensor miniaturization, multiplexing
Nano-based research in the current scenario is becoming one of the most captivating and thriving areas of biological science, as the recent breakthroughs in nanotechnology have successfully opened a broad array of biosensing or bioimaging applications. Nanomaterials of dimensions typically between 1 to 100 nm are considered ideal for the analysis of phytopathogens, as they can offer a high surface-to-volume ratio and other unique chemical, optical, and electrical properties, unlike the bulk counterparts. Due to cost-effectiveness, accuracy and rapidity in pathogen detection, nano-based biosensors and their variants have already been appreciated in the field of agriculture as well as medicine.
Nanobiosensors, are constructed as nanoscale analytical devices that quantify analytes of interest combined with the biologically imitative elements through the physical transducer system (Srivastava et al. 2018). They work on the principle that consists of attaching bioanalytes onto the bioreceptor, followed by modulation of physicochemical signals which in later, gets converted into a detectable form by the transducer, and further quantitated as redox changes, by either electrochemically, optically, acoustically, or electronically in the detector. The nanostructures in biosensors act as an intermediate medium between the bioreceptor and transducer system (Fig. 1). The variation in signal transduction due to electrical potential, conductance, impedance, intensity, and viscosity is correlated with the analyte concentration. Nanobiosensors analyze data regarding detection of analytes (glucose, urea, pesticides, etc.) and inquisition of metabolites, microorganisms and pathogens in real-time.
Nanoparticle-based sensors: types and functioning
The increasing demand for detecting food contaminants and different types of analytes at low concentrations with high specificity has encouraged the technique of using nanoparticles in biosensing. From the ancient days, experiments and detection of plant diseases are carried out indirectly with the existing imaging technologies like thermographic and hyperspectral imaging systems. But due to notable problems, such as non-specificity of pathogenic strains and sensitivity to environmental changes, conventional approaches become obsolete. On the other hand, advances in nanotechnology have led to wide-ranging successful applications. These are nanobiosensors for monitoring soil conditions (e.g. moisture, soil pH); detection of food borne contaminants and supervision of environmental conditions at the farm; nanocapsules for smart and precise delivery of pesticides, herbicides, fertilizers and vaccines and nanoparticles for quick delivery of growth hormones as well as novel gene segments to plant genome in a controlled manner (Omanović and Maksimović, 2016).
With conventional transduction technologies, the commercially available biosensor molecules used to require huge time in detection, while the nanoscale biosensors are designed to reduce the detection time and to detect the number of analytes present in each sample. Nanoparticles having a greater amount of surface area exposure are spontaneously chosen by the scientists as ideal catalysts for chemical reactions and biocompatibility (Malekzad et al., 2017). According to the biorecognition mechanism, working of biosensor molecules is based on either biocatalytic or bioaffinity-based approach. In biocatalytic system, the bioreceptor (enzyme, whole cell, tissue, etc.) recognizes the analyte and catalyzes a chemical reaction leading to complete exhaustion of the analytic, while in bioaffinity system, the bioreceptor (e.g., antibody or aptamer) typically binds to the analyte and an equilibrium is usually reached (Malekzad et al., 2017). This article emphasizes the construction and functioning of some popular nanobiosensors (e.g., metalloid-based nanobiosensors, quantum dots, array-based nanobiosensors etc.) in the context of precision agriculture.
a) Metalloid-based nanobiosensors
Inorganic compounds like Ag, Au, Si and several metal oxides which look chemically inert in their macroscale form, are often used as nanoparticles to improve sensing tactics along with reliable quantification of different bioanalytes of specific relevance to plant diseases (Kwak et al., 2017). Nanoparticles are employed here to promote immobilization of bioreceptors and appropriate bioreactions. Characteristic sensor responses are carefully monitored by recording the differences in the refractive index and surface-enhanced optical properties, due to localized surface plasmon resonance (LSPR) of nanoparticles (Sugawa et al., 2015). Mostly, the nanoparticles used for biosensing practices are hazardous for human health and carry risks of lung as well as skin diseases. Therefore, metalloid-based nanobiosensors are recommended to use skillfully in judicious manner. Table 1 has shown a list of achievements by metalloid-based nanobiosensors, along with corresponding working principles.
Table 1. Metalloid-based nanobiosensors and their implication
|
Target |
Agricultural importance |
Sensor component |
Detection mechanism |
|
Pseudomonas syringae |
Rod-shaped, Gram-negative bacterium causes bacterial canker on almond trees and produces tabtoxin and phaseolotoxin. |
Au NPa-ssDNA |
Electrochemistry |
|
Bacillus thuringiensis |
Gram-positive, soil-dwelling bacterium, commonly used as a biological pesticide (delta-endotoxins are processed and subjected to kill insects that eat them). Also used in transgenic crop production against mostly lepidopteran and dipteran insects. |
Pt NP-IgGb |
MALDI-TOF MSc |
|
Ralstonia solanacearum |
Aerobic non-spore-forming, Gram-negative, soil-borne bacterium causes bacterial wilts of tomato, pepper, eggplant, and Irish potato. |
Au NP-ssDNA |
Colorimetry |
|
Xanthomonas campestris |
Gram-negative bacterium causes "black rot" in cruciferous vegetables and bacterial wilt in turfgrass. |
Si NP-Rubpy-IgG
|
Fluorescence |
|
Afflatoxins |
Poisonous carcinogens and mutagens, produced by soil-borne molds such as Aspergillus flavus and Aspergillus parasiticus which decay vegetation, hay, and grains. |
Ag NRc |
SERS |
Note: aNanoparticle, b Immunoglobin G, c Matrix assisted laser desorption, Source: Li et al., 2020
b) Quantum dots: optical biosensor
Quantum dots (QDs) are semi-conducting optical nanobiosensors, working on the basis of luminescence for detection of several phytopathogenic fungal and bacterial strains associated with various plant diseases (Wang et al., 2016). Carbon or silica being environmentally benign elements are mostly preferred than Pb, Zn, Cd and Hg to design QDs (Pramanik et al., 2018). Due to ultra-small size (1–10 nm), excellent photostability and broad absorption spectra, QDs can easily be excited to all colors even by a single excitation light source (Warad et al., 2004), which make them visible in living systems too (Li et al., 2020). When excitation occurs, electrons at ground state within a quantum dot, occupies an energy level and becomes excited to emit photons, which trigger emission of light (Srivastava et al. 2018). Since, QDs show the inverse relationship between its size and emission wavelength, the larger QDs produce blue light while the smallest one produces red light (Malekzad et al. 2017) as shown in Fig. 2. Apart from inherent fluorescence enhancement or quenching mechanism, QD biosensors have also found to work by fluorescence resonance energy transfer (FRET) technique (Srivastava et al., 2018). Here, the proximity of the donors (i.e., QDs) to acceptors (e.g., gold nanoparticles, carbon nanodots etc.) promotes an energy transfer, which ultimately impacts on quenched fluorescence intensity. In addition, optical biosensors may also work on the principle of colorimetry, SPR (surface plasmon resonance), and SERS (surface enhanced Raman scattering) spectroscopy for rapid detection of a wide range of analytes including fungi, bacteria, virus, toxins, antibodies, drugs etc. (Srivastava et al. 2018).
c) Array-based nanobiosensor
The array-based sensor assemblies made of several chromophores or synthetic nanomaterials are one of the most accepted models in state-of-the-art nanobiosensors in the context of multiplexing and isolating different analytes. Unlike the chemical sensors, the array-based sensors are often called “electronic nose” (e-nose), as they use electronic transducers instead (Li et al., 2020). This method can be used to differentiate mixtures of similar analytes, with its cross-reactivity and molecular fingerprinting properties. A sensor array comprised of different recognition elements with different affinities to analytes. Therefore, different patterns of analytes are generated based on analytes with different binding affinities for the sensor array. The fingerprints of each analyte are further processed through multivariate analysis. The clusters of analytes in a data matrix show successful classification when the dimensions are reduced as shown in Fig. 3. As a multiplexed gas sensor used in plant stress events from pathogen infection, pest invasion, to physical wounding, e-noses made from metal oxide or conductive polymer coatings have gained many conveniences (Mahmud et al., 2018). Recently, a smartphone-integrated VOC sensing system utilizing plasmonic nanoparticles has been developed to distinguish various abiotic stresses (mechanical damages, drought, and nutritional deficiency) as well as biotic stresses by using volatile organic compounds (VOCs), which are released by diseased plant body (Li et al., 2020). Pyruvic acid, glyphosate, acetic acid and citrinin are the typical examples of VOCs, specifically found in the plant cell, pesticides, microbes, and food products, respectively. The profiling of plants for volatile chemical biomarkers is an important indirect method of detecting plant diseases. Research in the future should focus on improving sampling protocols so that no concentration of VOCs will be determinant prior to data analysis.
Applications in precision agriculture
Nanobiosensor-aided precision agriculture, making use of computers, global satellite positioning systems and remote sensing devices sets long-desired goal to maximize crop productivity by reducing the input of fertilizers, pesticides, herbicides, etc. through proper monitoring of the environmental variables and applying necessary action. Among the metallic nanostructures, gold-based biosensors are mostly used in food quality assessment, packaging and identification of toxic elements in living system. For example, GO/DexP-AuNPs (Graphene oxide/phenoxy-derivatized dextran nanoparticles) are designed to detect concanavalin A, which is a plant-derived lectin and binding with plasma membrane receptors hinders cell proliferation (Huang et al., 2013). Ochratoxin A (produced by Aspergillus and Penicillium species) causing food contamination, is detected by gold nanoparticles enhanced surface plasmon resonance technique (Evtugyn et al., 2013). The carcinogenic nitrile pollutant is detected by using silver nanobiosensors containing hyper-branched polyethylene mine (Chen et al., 2018). FRET-based QDs have been developed to detect witches’ broom disease of lime caused by Phytoplasma aurantifolia. Zn-SeQD immobilized acetyl cholinesterase also shows potentials for detection of organophosphate pesticides using graphene-chitosan nanocomposite modified electrode (Duhan et al., 2017). In addition, a huge number of specific antibody or aptamer based nanobiosensors are promisingly employed now a days in detection of insecticides like triazophos, carbofuran, malathion etc.
Conclusion
The development of biomolecular recognition and quantification approaches by modern analytical sensor elements in combination with optics, electrochemistry, spectroscopy and quantum physics at nanoscale is one the most promising advances in biotechnology for plant disease detection. Precision agriculture with the aid of nanoparticle-based biosensing practices now being merely accessible to farmers even at field conditions encourages quick detection and determination of infections caused by phytopathogens, as well as several abiotic stresses. Although multiplex detection sometimes causes notable issues of cross-reactivity, researchers are very much optimistic to achieve sustainability in agriculture as well as food processing industry by using modified versions of nanodiagnostic tools in the coming future.
References
Chen, B.B., Liu, M.L., Zhan, L., Li, C.M and Huang, C.Z (2018). Terbium (III) modified fluorescent carbon dots for highly selective and sensitive ratiometry of stringent. Analytical chemistry, 90(6): 4003-4009.
Duhan, J.S., Kumar, R., Kumar, N., Kaur, P., Nehra, K and Duhan, S (2017). Nanotechnology: The new perspective in precision agriculture. Biotechnology Reports, 15: 11-23.
Evtugyn, G., Porfireva, A., Stepanova, V., Kutyreva, M., Gataulina, A., Ulakhovich, N., Evtugyn, V and Hianik, T (2013). Impedimetric aptasensor for ochratoxin a determination based on Au nanoparticles stabilized with hyper-branched polymer. Sensors, 13(12): 16129-16145
Huang, C.F., Yao, G.H., Liang, R.P., Qiu, J.D (2013). Graphene oxide and dextran capped gold nanoparticles-based surface plasmon resonance sensor for sensitive detection of concanavalin A. Biosens Bioelectron, 50: 305–310.
Kwak, S.Y., Wong, M.H., Lew, T.T.S., Bisker, G., Lee, M.A., Kaplan, A., Dong, J., Liu, A.T., Koman, V.B., Sinclair, R., Catherine Hamann, C and Strano, M.S (2017). Nanosensor technology applied to living plant systems. Annual Review of Analytical Chemistry, 10: 113-140.
Li, Z., Yu, T., Paul, R., Fan, J., Yang, Y and Wei, Q (2020). Agricultural nanodiagnostics for plant diseases: recent advances and challenges. Nanoscale Advances, 2(8): 3083-3094.
Mahmud, M.M, Constantino, N., Seok, C., Yamaner, F.Y., Dean, R.A and Oralkan, O (2018). A CMUT-based electronic nose for real-time monitoring of volatiles emitted by plants: preliminary results. In: IEEE SENSORS (pp. 1-4). IEEE.
Malekzad, H., Zangabad, P.S., Mirshekari, H., Karimi, M and Hamblin, M.R (2017). Noble metal nanoparticles in biosensors: recent studies and applications. Nanotechnology reviews, 6(3): 301-329.
Omanović-Mikličanina, E and Maksimović, M (2016). Nanosensors applications in agriculture and food industry. Bull Chem Technol Bosnia Herzegovina, 47: 59-70.
Pramanik, S., Hill, S.K.E., Zhi, B., Hudson-Smith, N.V., Wu, J.J., White, J.N., McIntire, E.A., Kondeti, V.S.S.K., Amani, L. Lee, A.L., Bruggeman, P.J., Kortshagen, U.R., Haynes, C.L. (2018). Comparative toxicity assessment of novel Si quantum dots and their traditional Cd-based counterparts using bacteria models Shewanella oneidensis and Bacillus subtilis. Environmental Science: Nano, 5(8): 1890-1901.
Srivastava, A.K., Dev, A and Karmakar, S (2018). Nanosensors and nanobiosensors in food and agriculture. Environmental Chemistry Letters, 16(1): 161-182.
Sugawa, K, Tahara, H, Yamashita, A, Otsuki, J, Sagara, T, Harumoto, T and Yanagida, S (2015). Refractive index susceptibility of the plasmonic palladium nanoparticle: potential as the third plasmonic sensing material. Acs Nano, 9(2): 1895-1904.
Thibodeaux, L.K., Burnett, K.G. and Burnett, L.E., (2009). Energy metabolism and metabolic depression during exercise in Callinectes sapidus, the Atlantic blue crab: effects of the bacterial pathogen Vibrio campbellii. Journal of Experimental Biology, 212(21), pp.3428-3439.
Ting-Lan, ZENG, Yang-Fang, Y.E., Chang-Kao, M.U., Kai, WANG, Rong-Hua, L.I. and Chun-Lin, WANG, (2016). Gut microbiota and metabolic phenotype of Portunustrituberculatus. Chinese Journal of Analytical Chemistry, 44(12), pp.1867-1873
Vaseeharan, BARP and Ramasamy, P., 2(003). Control of pathogenic Vibrio spp. by Bacillus subtilis BT23, a possible probiotic treatment for black tiger shrimp Penaeus monodon. Letters in applied microbiology, 36(2), pp.83-87.
Wang, X, Sun, G, Li, N and Chen, P (2016). Quantum dots derived from two-dimensional materials and their applications for catalysis and energy. Chemical Society Reviews, 45(8): 2239-2262.
Wang, Y.B., (2007). Effect of probiotics on growth performance and digestive enzyme activity of the shrimp Penaeus vannamei. Aquaculture, 269(1-4), pp.259-264.
Warad, H.C., Ghosh, S.C., Thanachayanont, C., Dutta, J and Hilborn, J.G (2004). Highly luminescent manganese doped ZnS quantum dots for biological labeling. In: Proceedings of international conference on smart materials (SMARTMAT-04), Chiang Mai, Thailand.
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