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Reducing agricultural losses is an effective way to sustainably increase agricultural output efficiency to meet our present and future needs for food, fiber, fodder, and fuel. Our ever-improving understanding of the ways in which plants respond to stress, biotic and abiotic, has led to the development of innovative sensing technologies for detectin...
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... has since been used extensively in diagnostics to detect diseases through pathogen identification by rapidly synthesizing millions of copies of specific DNA sequences. As shown in Figure 3, the process begins by separating the extracted double-stranded DNA (dsDNA) into two single-stranded DNA (ssDNA) molecules by heating to 95 • C, the temperature is then reduced to 40-65 • C allowing for the binding of the primers at each end of the target ssDNA's region to be amplified [52]. The primers are short pieces of ssDNA which bind specifically to the target DNA sequence by complementary base paring. ...
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The proximal and remote sensing technology has steadily established its enormous potential in agriculture. This technology offers a cluster of benefits in input use efficiency, crop and soil productivity, food quality, and environment protection. An increase in crop production per unit of inputs (like water, fertilizers, seed, and pesticides, etc.)...
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... Thermal sensors measure infrared radiation emitted by plants, which can vary in response to pest feeding, water stress, and disease infection. By detecting changes in plant canopy temperature, thermal sensors enable early detection of pest infestations and facilitate targeted management interventions to mitigate crop damage [89]. Acoustic sensors detect sound emissions produced by pests, such as insect-feeding activity and movement within crop canopies. ...
Among major edible oilseeds, oil palm (Elaeis guineensis Jacq.) stands out as a versatile tropical crop, globally recognized for its high productivity, versatility, and broad range of applications. However, E. guineensis plantations, particularly in tropical regions, face numerous pressures from a wide range of pests, including insects, pathogens, and vertebrate pests. Conventional pest control methods relying mainly on chemicals have raised serious concerns regarding environmental pollution, human health risks, and the development of pesticide resistance in target pests and pathogens. To address these issues, sustainable pest management, comprising integrated pest management strategies, can be augmented with precise agriculture technologies, including remote sensing and GPS-guided equipment for targeted pesticide application, and effective stakeholder engagement. This chapter aims to (1) outline major pest management challenges in E. guineensis plantations; (2) introduce the concepts and principles of precision farming and its application in pest management; (3) discuss the major applications of sensor technology, GPS, and remote sensing for pest monitoring; (4) emphasize the significance of stakeholder collaboration in integrated pest management; and (5) identify aspects that have been least explored in the current context.
... Advances in understanding plant defense mechanisms have led to sensor-based crop health monitoring, enhancing agroecosystem sustainability. For example, methodologies facilitating prompt and precise detection of biotic plant stressors, such as pathogens and pests, allows for the deployment of remedial measures, to mitigate yield losses [4]. The term biogenic volatile organic compounds (BVOCs) encompasses a wide range of organic substances released by vegetation, soils and the oceans into the atmosphere [5,6]. ...
... The objective of the present study was to investigate and optimize the architecture of the molecularly imprinted nanofibrous sensor using a single-step electrospinning process for the 4 selective detection of limonene. More specifically, we utilized PVP and PAA as the fiber and cavity formers, respectively, while integrating multiwalled carbon nanotubes (MWCNT) to enhance conductivity. ...
Detecting volatile organic compounds (VOCs) emitted from different plant species and their organs can provide valuable information about plant health and environmental factors that affect them. For example, limonene emission can be a biomarker to monitor plant health and detect stress. Traditional methods for VOC detection encounter challenges, prompting the proposal of novel approaches. In this study, we proposed integrating electrospinning, molecular imprinting, and conductive nanofibers to fabricate limonene sensors. In detail, polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) served here as fiber and cavity formers, respectively, with multiwalled carbon nanotubes (MWCNT) enhancing conductivity. We developed one‐step monolithic molecularly imprinted fibers, where S(‐)‐limonene was the target molecule using electrospinning technique. The functional cavities were fixed using UV curing method, followed by a target molecule washing. This procedure enabled the creation of recognition sites for limonene within the nanofiber matrix, enhancing sensor performance and streamlining manufacturing. Humidity was crucial for sensor working, with optimal conditions at about 50% RH. The sensors rapidly responded to S(‐)‐limonene, reaching a plateau within 200 seconds. Enhancing fiber density improved sensor performance, resulting in a lower limit of detection (LOD) of 137 ppb. However, excessive fiber density decreased accessibility to active sites, thus reducing sensitivity. Remarkably, the thinnest mat on the fibrous sensors created provided the highest selectivity to limonene
(Selectivity Index: 72%) compared to other VOCs, such as EtOH (used as a solvent in nanofiber development), aromatic compounds (toluene), and two other monoterpenes (α‐pinene and linalool) with similar structure. These findings underscored the potential of the proposed integrated approach for selective VOC detection in applications such as precision agriculture and environmental monitoring.
... The red ratio vegetation index (RVI) produced the highest coefficient of determination (R 2 =0.60) while predicting the nitrogen status of winter wheat in North China. Kashyap and Kumar (2021) ...
Food demands are increasing globally. Various issues such as urbanization, climate change, and desertification increasingly favour crop pests and diseases that limit crop productivity. Elaborating and discussing the pragmatic knowledge and information on recent advances in tools and techniques for crop monitoring developed in recent decades might help agronomists make more informed decisions. This chapter discusses the progress and development of new techniques equipped with recent sensors and platforms such as drones that have revolutionized the way of understanding plant physiology and stresses. It begins with the introduction to various tools available for crop stress estimation, mainly based on optical imaging such as multispectral, thermal, and hyperspectral imaging. An overview of unmanned aerial vehicle (UAV) -based image processing pipeline is presented and shed light on the possible avenues of UAV-based remote sensing for crop health monitoring using machine learning approaches.
... They are unsuitable for disease status monitoring as they involve collecting samples mostly from plants with already clearly visible symptoms of disease; in some cases, it may misrepresent the real status of infections. Besides, molecular and serological methods require detailed sampling procedures, as well as expensive infrastructure (Martinelli et al., 2015;Kashyap & Kumar, 2021). ...
Foliar fungal diseases of small grain cereals are economically among the most important diseases worldwide and in the Baltics. Finding an effective, reliable, and easily accessible method for plant disease diagnosis still presents a challenge. Currently used methods include visual examination of the affected plant, morphological characterization of isolated pathogens and different molecular, and serological methods. All of these methods have important limitations, especially for large-area applications. Hyperspectral imaging is a promising technique to assess fungal diseases of plants, as it is a non-invasive, indirect detection method, where the plant’s responses to the biotic stress are identified as an indicator of the disease. Hyperspectral measurements can reveal a relationship between the spectral reflectance properties of plants and their structural characteristics, pigment concentrations, water level, etc., which are considerably influenced by biotic plant stress. Despite the high accuracy of the information obtained from hyperspectral detectors, the interpretation is still problematic, as it is influenced by various circumstances: noise level, lighting conditions, abiotic stress level, a complex interaction of the genotype and the environment, etc. The application of hyperspectral imaging in everyday farming practice will potentially allow farmers to obtain timely and precise information about the development of diseases and affected areas. This review provides an introduction into issues of hyperspectral imaging and data analysis and explores the published reports of worldwide research on the use of hyperspectral analysis in the detection of foliar fungal diseases of small-grain cereals.
... These preparation techniques have their individual strengths and weaknesses but collectively furnish ample resources for employing ZnO nanoparticles in handling biotic and abiotic stresses. Biotic and abiotic stresses stand as two primary limiting factors for crop growth and yield in agricultural production [28][29][30][31][32]. Biotic stresses encompass various invasions by viruses, bacteria, fungi, and pests, posing significant threats to crop growth [33][34][35][36][37]. Simultaneously, abiotic stresses primarily arise from environmental factors such as drought, high temperatures, low temperatures, salinity, and others, severely impacting plant growth and yield [38][39][40][41][42]. Recent research has underscored the significant potential of ZnO nanoparticles in mitigating biotic and abiotic stress in agriculture [43][44][45][46]. ...
Biotic and abiotic stress factors are pivotal considerations in agriculture due to their potential to cause crop losses, food insecurity, and economic repercussions. Zinc oxide nanoparticles (ZnO nanoparticles) have gained substantial attention from researchers worldwide for their capacity to alleviate the detrimental impacts of both biotic and abiotic stress on plants, concurrently reducing dependence on environmentally harmful chemicals. This article provides an overview of methods for synthesizing ZnO nanoparticles, encompassing physical vapor deposition, ball milling, hydrothermal methods, solvothermal methods, precipitation methods, microwave methods, microbial synthesis, and plant-mediated synthesis. Additionally, it delves into the absorption, translocation, and biotransformation pathways of ZnO nanoparticles within plants. The emphasis lies in elucidating the potential of ZnO nanoparticles to safeguard plants against biotic and abiotic stress, enhance plant performance, and modulate various plant processes. The article also offers a preliminary exploration of the mechanisms underlying plant stress tolerance mediated by ZnO nanoparticles. In conclusion, ZnO nanoparticles present an environmentally friendly and cost-effective strategy for plant stress management, paving the way for the integration of nanotechnology in sustainable agriculture. This opens new possibilities for leveraging nanotechnology to bolster plant resilience against stress in the ever-changing climate conditions, ensuring global food security.
... This thesis is also confirmed by Kashyap et al. [7]. According to the authors, research in this area should focus on monitoring water, nutrients and the environment. ...
... Thermopile sensor data interpolated by the spline method can be used to assess the condition of crops and in particular cucumbers. The small amount of data that have to be send over an existing sensor network, and sufficient accuracy of 85% indicate that using a sensor network with AMG8833 sensors, the recommendations of Kashyap et al. [7] will be fulfilled. According to the guidelines given by the authors, the monitoring of the condition of agricultural crops is an important parameter in the management of agriculture to obtain accurate data leading to sustainability through precision in agriculture. ...
Wireless sensor networks offer theoretical and practical challenges related to their application capabilities. Leaf
temperature is a valuable indicator of the physiological status of plants, corresponding to both biotic and abiotic stressors.
The disadvantage of thermal cameras is that they produce large images, which makes them unsuitable for use in wireless
sensor network systems. The solution to this problem is the use of thermopile sensors. In the present work, a comparative
analysis is made and a suitable method for interpolation of data from a thermopile sensor is selected in the analysis of the
physiological state of cucumbers in a period of drought. It was found that a suitable method for interpolation of data from
a thermopile sensor for the purpose of their scaling is spline interpolation, because when using it there is a minimal
difference in the data from the histograms of the obtained data for the measured temperature of cucumbers compared to
those from a thermal camera. A comparative analysis of the obtained results with those from available literature sources
was made. Recommendations for the practical application of the obtained results are given and guidelines for future
research in the subject area are given.
... Recently, for instance, Perlikowski et al. (2020) Through comprehensive timeseries analytics, including analyses of root architecture, phytohormones, proteome, primary metabolome, and lipidome under progressive stress conditions, integrated features potentially related to a trait for drought-avoidance strategy were demonstrated in Festuca arundinacea. These analytical advancements will facilitate the digitization of data on plant-environment interactions and the monitoring of plant health, leading to advancements in crop breeding, precision agriculture, and smart farming on the path to global food sufficiency (Kashyap and Kumar 2021). ...
Plant’s dynamic phenotypes are shaped by the interactions between the plant and its environment. To advance the study of plants and their environmental interactions, including crop breeding and management, it is crucial to have a comprehensive understanding of plant activities throughout their lifespan in dynamic settings. The plant research community faces the challenge of accurately analyzing a range of traits in an increasing number of plants to aid in adapting to resource-limited situations and low-input agriculture. This chapter explores the evolution of plant phenotyping as a field that draws on various academic disciplines. Technological advancements that enabled the formation of phenotyping centers are discussed, as well as the obstacles that need to be addressed for plant phenotyping to progress further, particularly with regard to data collection consistency and reusability. The emergence of the plant phenotyping community is described as the final step in integrating the community and leveraging synergies.
... Detecting plant stress prior to the onset of visual symptoms is a management approach that can dramatically drive crop yield improvement [32,[58][59][60]. Plants exposed to different stressors can respond by activating a series of complex signaling networks [58]; however, accurately assessing plant stress pre-visually can be challenging when there are multiple sources of stress interacting simultaneously [30]. ...
Root-feeding herbivores present challenges for insect scouting due to the reliance on aboveground visual cues. These challenges intensify in multi-stress environments, where one stressor can mask another. Pre-visual identification of plant stress offers promise in addressing this issue. Hyperspectral data have emerged as a measurement able to identify plant stress before visible symptoms appear. The effectiveness of spectral data to identify belowground stressors using aboveground vegetative measurements, however, remains poorly understood, particularly in multi-stress environments. We investigated the potential of hyperspectral data to detect Western corn rootworm (WCR; Diabrotica virgifera virgirefa) infestations in resistant and susceptible maize genotypes in the presence and absence of drought. Under well-watered conditions, the spectral profiles separated between WCR treatments, but the presence of drought eliminated spectral separation. The foliar spectral profiles separated under drought conditions, irrespective of WCR presence. Spectral data did not classify WCR well; drought was well classified, and the presence of drought further reduced WCR classification accuracy. We found that multiple plant traits were not affected by WCR but were negatively affected by drought. Our study highlights the possibility of detecting WCR and drought stress in maize using hyperspectral data but highlights limitations of the approach for assessing plant health in multi-stress conditions.
... Reducing pest losses is an effective way to increase agricultural production. It is estimated that between 20% and 40% of all crop productivity losses are caused by pests and phytopathogens, respectively [1,2]. On an average, 12.6% worldwide crop losses, which in monetary terms equals to $215.77 billion, has been reported for only the top 20 life-sustaining crops based on the 2010-2013 production figures and prices [3]. ...
Plant proteases are well known for their various industrial applications. Papain, present in papaya latex (Carica papaya) and pineapple bromelain (Ananas comosus), is undoubtedly the most studied and widely used vegetable protease in the food and pharmaceutical industry worldwide. However, its potential as a biopesticide has been little explored. The objective of this study was to evaluate the activity of proteases from Carica papaya latex and peel and crown of Ananas comosus fruits on agricultural pests. To evaluate proteolytic activity on nematodes, extracts, and approximately 50 juveniles of Panagrellus sp. were placed in microtubes. To evaluate the insecticidal effect, larvae and pupae of Tenebrio molitor L. were submerged in active and denatured extracts. Additionally, larvae of T. molitor were fed an artificial diet at doses of 0, 100, 250, and 500 mg/g of wheat bran. The weight and number of dead larvae were recorded, and feeding behavior was evaluated. The proteases of papaya latex and papain caused reduction (p < 0.05) on Panagrellus sp. The extracts showed a toxic effect (p < 0.05) against the larvae of T. molitor. Active papain resulted in the absence of wings in 53.3% of adults from the pupae, and no malformation caused by denatured papain was observed. No mortality was observed in larvae fed an artificial diet. However, there was a strong feed reduction, reduction in the relative rate of consumption, reduction in growth and feed conversion efficiency caused by papaya latex. The results of this study show that plant proteases have the potential for the development of sustainable alternatives for the control of arthropod pests and parasitic nematodes.
... There are four main types of plant pathogens and pests affecting crops, namely bacteria, fungi, viruses and nematodes. These have a major impact on food production worldwide, especially when they affect staple crops, such as rice, wheat, maize and potatoes, on which vulnerable populations are deeply dependent, leading to food insecurity [2]. Additionally, as food demand continues to increase, agricultural production is further threatened by environmental pressures that result from current and predicted climate change scenarios [3]. ...
Crops account for over 80% of the human diet; however, plant diseases and pests are responsible for up to 40% of the loss in food production worldwide, costing approximately EUR 200 billion [...]
