Drought is a natural phenomenon that occurs when water is not available. This water can be in the form of rain, running rivers, dammed waters, or groundwater. Whenever drought hits a region, we can see that it detrimentally affects plant growth, which in turn has an adverse effect on yield. Drought-affected areas are essentially disturbed in homeostasis, which interferes with crucial physiological and biochemical functions. Key impacts of stress on crops and plants due to drought include diminished cell turgor, stomatal closure, and suppressed photosynthetic activities due to restricted CO₂ uptake. Drought stops the uptake of the nutrients and produces a hormonal imbalance, which is the reason for increased levels of Abscisic Acid (ABA) (Reinelt et al., 2023; Tian et al., 2025). Drought also has the tendency to increase Reactive Oxygen Species (ROS), which causes oxidative damage. Various researchers have found that all of the aforementioned phenomena caused by drought (whether recent or ongoing) will disrupt biomass production, hinder reproductive processes, and cause substantial yield declines. However, it has been found that, over time, plants have also evolved to counteract the effects of drought, including through morphological alterations such as increased root-to-shoot ratio, osmotic regulation through the buildup of compatible solutes, such as proline and glycine betaine (Ozturk et al., 2021; Chachar et al., 2025) and the activation of drought-responsive genetic pathways that enhance tolerance.

Waterlogging and flooding are critical environmental stressors that interfere with vital physiological and metabolic activities in plants. When soils become saturated with water, air is expelled from soil pores, creating oxygen-deficient conditions (hypoxia or anoxia) that severely impair aerobic respiration in the root zone (Zahra et al., 2021). This lack of oxygen compromises mitochondrial Adenosine Triphosphate Production (ATP), thereby disrupting energy-dependent processes such as nutrient and ion transport. Prolonged anaerobic conditions may result in stunted root development (hypoplasia), the formation of air-filled cavities in roots (aerenchyma), and, in severe scenarios, root tissue death (necrosis) (Teoh et al., 2022). Furthermore, researchers have mentioned that saturation also alters the soil’s redox balance, which influences the solubility of essential nutrients. This, in turn, typically causes deficits in the nitrogen, phosphorus, and potassium absorption, while at the very same time increasing the consolidation of potentially toxic elements such as manganese and iron. Toxic effects due to ethanol, methane and lactic acid can also be seen in such scenarios as these are byproducts of the flooded soils. The buildup of ethylene causes various aging-related symptoms that are readily seen in the leaves of crops and plants. Initially, yellowing of the leaves is one symptom; however, shedding and shoot elongation can also be observed (Gu et al., 2021). However, with the advancements in findings on this subject over time, it has also been concluded that species tolerance, growth stage, flood duration, and soil characteristics also play a critical role.

Salinity stress is a critical abiotic factor that significantly affects a plant’s growth, development, and productivity by interfering with key physiological, biochemical, and molecular functions (Sahito et al., 2024). Elevated levels of soluble salts, particularly sodium chloride (NaCl) decrease the soil’s water potential in the rhizosphere. This leads to osmotic stress, which impedes root water uptake even when soil moisture is present. This osmotic stress disrupts cellular turgor, limits cell elongation, and ultimately restricts overall plant development. Concurrently, ionic stress occurs when excess sodium (Na⁺) and chloride (Cl⁻) ions accumulate in plant tissues, disrupting enzymatic processes, destabilizing cell membranes, and impairing metabolic pathways (Shaikh et al., 2022; Yuan et al., 2024). Various researchers have mentioned that an increased concentration of sodium in the soil has the tendency to disrupt the digestion of important nutrients. These nutrients include potassium (K⁺), calcium (Ca²⁺), and magnesium (Mg²⁺). This imbalance of nutrients in crops and plants can result in deficiencies. However if we take a closer look at the cellular level, we will find out that an increase in salinity also tends to activate oxidative stress ROS, which results in lipid membrane degradation, protein malfunction, and genetic material damage. Some obvious signs of an increase in salinity include chlorosis, necrosis, premature leaf drop, and reduced overall biomass. However, the literature tells us that the severity of the aforementioned stress is also dependent on the tolerance of a species to the stressed environment, its growth stage, the type of salt accumulated in the soil, its concentration per square meter, and the duration of exposure. Overall, it is observed that salinity-induced stress on crops and plants has more significant effects in arid regions, sometimes becoming a major obstacle to the food security of people dependent on indigenous farming techniques (Ehtaiwesh, 2022).

Temperature extremes encompassing heat, cold, and frost are significant stressors that detrimentally affect the physiological, biochemical, and molecular functions of plants, ultimately limiting their growth, development, and productivity. Heat stress occurs when ambient temperatures exceed the optimal range for a specific plant species, leading to impaired photosynthesis through destabilization of the photosystem. Heat stress compromises membrane fluidity, elevates respiration rates, and disrupts protein folding mechanisms, which collectively reduce carbon assimilation and disturb metabolic homeostasis (Saddhe et al., 2021). To counteract thermal damage, plants activate protective responses such as producing Heat Shock Proteins (HSPs), which aid in stabilizing and refolding damaged proteins. In contrast, cold and frost stress occur when temperatures drop below a plant’s tolerance limit, causing membrane rigidity, disruption of the cytoskeleton, and formation of extracellular ice. These lead to cellular dehydration and mechanical injury. Frost damage worsens when ice crystals form intracellularly, rupturing cells and causing permanent tissue damage. Cold stress has been observed to abolish and slow down the metabolism of the vegetation, affecting very critical stages of crops and plants, such as germination, flowering, and fruit development. Various researchers have shown that both increase and decrease in temperature activate oxidative stress. This is done through the accumulation of ROS, which in turn leads to damaging the crops and plants at the cellular level. Over time, however, some plant species have developed the capacity to lessen these effects by incorporating cryoprotectants, such as antifreeze proteins and osmolytes. However the exact effect of the severity of fluctuating temperature-based stress on vegetation whether high or low, is mainly determined by the growth stage, duration, and intensity of exposure. This can sometimes severely impair crop productivity and resilience (Ding and Yang, 2022).

Moderate light stress, which includes low light levels (reduced photon flux), excessive light (high irradiance), and ultraviolet radiation, represents a stressor that disrupts a plant’s photosynthesis. In low-light scenarios, the limited supply of Photosynthetically Active Radiation (PAR) hampers chlorophyll’s ability to absorb photons, thereby diminishing electron transport, lowering ATP and Nicotinamide Adenine Dinucleotide Phosphate (NADPH) production, and constraining carbon fixation via the Calvin cycle. These effects lead to reduced plant growth and biomass (Roeber et al., 2021). Conversely, high light exposure causes excessive excitation of chlorophyll, leading to photoinhibition. This energy surplus promotes the generation of ROS, which cause oxidative damage to thylakoid membranes, proteins, and nucleic acids. It is observed that Ultraviolet B (UV-B) radiation exacerbates stress in plant cells. This occurs due to Deoxyribonucleic Acid (DNA) damage, protein cross-linking, lipid peroxidation, and disruption of hormone signaling pathways. However, with the passage of time plants have developed a protective mechanism to counteract this effect. This includes Non-Photochemical Quenching (NPQ), activation of the xanthophyll cycle, and increased activity of antioxidant enzymes such as Superoxide Dismutase (SOD), Catalase (CAT), and Ascorbate Peroxidase (APX), along with the accumulation of Ultra Violet (UV)-screening secondary metabolites such as flavonoids (Yang et al., 2019). However it has been observed that the effects of stress due to light exposure vary greatly depending on the presence of a specific photoreceptor, developmental stage and exposure duration.

Nutrient imbalances, arising from either deficiencies or toxicities, are significant stress factors that interfere with essential physiological activities, suppress plant growth, and lower agricultural productivity. The inadequate availability of vital macronutrients (e.g. nitrogen, phosphorus and potassium) or micronutrients (e.g. iron, zinc and boron) can disrupt primary metabolic pathways such as photosynthesis, respiration, and protein synthesis (Abbas et al., 2021). Deficiency symptoms commonly include chlorosis, necrosis, reduced meristem activity, and impaired reproductive development. Conversely, nutrient toxicity occurs when element concentrations exceed optimal thresholds, causing ionic imbalances, membrane disintegration, and oxidative damage due to the overproduction of ROS. Excesses of toxic elements such as manganese, aluminum, or sodium tend to block or disrupt the enzymatic functionality, assimilation of nutrients and osmotic regulation. Therefore, nutrient deficiency stress ultimately lessens cellular homeostasis, alters hormonal signaling, and heightens susceptibility to pests and environmental stress (Kumari et al., 2022). These issues are often intensified by suboptimal soil conditions, such as nutrient-poor soils, incorrect pH levels, salinity, or overfertilization. Effective nutrient management through soil analysis, customized fertilization plans, and comprehensive fertility practices is essential for maintaining nutrient balance and supporting sustainable crop production. In Table 1 , we have summarized the effects caused by both the deficiencies and toxicities arising from the lack of various essential nutrients in crops and plants.

Soil compaction is a stress that impairs plant physiological processes and reduces crop yields by altering the physical integrity of the soil. It leads to increased bulk density and decreased porosity, which restricts root expansion, slows down seedling emergence, and obstructs the movement and absorption of water, air, and essential nutrients. Reduced oxygen availability results in hypoxic stress, which can disrupt the respiratory system in roots. This, in turn, has a direct weakening effect on microbial activity, which is essential for effective nutrient cycling (Shaheb et al., 2021). Additionally, compacted soils exhibit limited water infiltration and drainage, which promotes surface runoff, exacerbates erosion, and increases crop susceptibility to moisture extremes such as drought and waterlogging. In compacted soil conditions, it is common to observe the formation of a dense subsoil layer, due to which roots can lose their ability to penetrate and reach the moisture and nutrient reserves that are deep within the soil (Jamali et al., 2021). The primary causes of compaction include anthropogenic activities such as the use of heavy machinery, frequent tillage, and overgrazing. To address the negative effects of soil compaction, strategies such as implementing controlled traffic farming, adopting reduced tillage practices, incorporating cover crops, and utilizing deep-rooted plant species can improve soil structure and promote greater ecosystem resilience.

Heavy metal toxicity is a critical stressor that negatively impacts the physiological and molecular functioning of plants and crops. Harmful metals such as cadmium (Cd), lead (Pb), arsenic (As), and mercury (Hg) frequently enter the soil through human-driven activities, including industrial waste release, mining operations, and the excessive application of agricultural chemicals. These metals are notable for their environmental persistence and pronounced ability to bioaccumulate in plant tissues (Ghuge et al., 2023). Once taken up by roots, heavy metals interfere with cellular homeostasis by disrupting nutrient transport mechanisms, altering enzyme activities, and compromising membrane stability. At the intracellular level, heavy metal stress provokes the excessive generation of ROS, resulting in oxidative damage that targets lipids, proteins, and nucleic acids. These disruptions negatively affect vital physiological processes such as photosynthesis, mitochondrial respiration, and hormonal signaling, especially pathways regulated by ABA and ethylene. Additionally, heavy metal exposure influences the expression of the genes related to metal sequestration, antioxidative responses, and detoxification systems, including the synthesis of phytochelatins and metallothioneins (Ali and Gill, 2022). Collectively, these effects lead to inhibited growth, developmental anomalies, and reduced agricultural productivity, while posing serious risks to food safety and ecological health.

Soil pH imbalance is a stressor that negatively influences plant physiological functions and diminishes crop yields. When the pH strays from the optimal range of 5.5 to 7.5, typical for the majority of crops, nutrient solubility and uptake are impaired, leading to inefficient ion transport and disturbances in vital metabolic pathways. However the proliferation of cells and growth of crop and plant roots is severely hampered in acidic soils (pH < 5.5), due to the presence of aluminum (Al³⁺) and manganese (Mn²⁺). On the other hand, alkaline conditions (pH > 7.5) limit the availability of essential micronutrients such as iron (Fe²⁺), zinc (Zn²⁺), and copper (Cu²⁺), often resulting in visible symptoms of nutrient stress, such as interveinal chlorosis and reduced photosynthetic performance (Tsai and Schmidt, 2021). Additionally, soil acidity has been observed to affect microbial activities that are beneficial to the plants by disturbing their movement in the rhizosphere. This ultimately hinders the plant’s ability to better and more precise nitrogen fixation and organic matter decomposition. The effectiveness of agrochemicals also decreases under such conditions. Therefore researchers have used techniques to adjust the pH of soil using agricultural lime (CaCO₃) or elemental sulfur (S), which have been found to be vital for restoring soil health, nutrient dynamics, and crop tolerance to pH-related stress (Gao et al., 2025).

Aerodynamic stress resulting from both excessive and limited wind exposure can significantly disrupt a plant’s architecture. Strong winds impose mechanical stress, leading to structural damage such as stem lodging, leaf fragmentation, and heightened water loss due to accelerated transpiration via stomatal and cuticular surfaces. These effects are exacerbated under drought conditions when elevated evapotranspiration surpasses a plant’s water uptake capacity, triggering cellular dehydration and oxidative stress. Inconsistent wind patterns can also compromise floral structure and hinder anemophilous pollination, reducing reproductive efficiency and crop yield (Das and Biswas, 2022). Prolonged wind exposure may induce thigmomorphogenic responses, including reduced internode length and altered distribution of biomass. Conversely, minimal wind activity especially in enclosed agricultural environments such as greenhouses limits convective air movement, thereby impairing thermal regulation and gas exchange. This, in turn, promotes microenvironments with high humidity and depleted CO₂ levels, and such conditions encourage fungal pathogen outbreaks and suppress photosynthetic efficiency. For the aforementioned reasons, effective wind management, such as the use of shelterbelts or engineered ventilation systems is essential to maintaining optimal growing conditions that can alleviate wind-related stress (Müller et al., 2023).

Airborne pollution is a stressor that disrupts plant physiological homeostasis, interferes with metabolic functions, and undermines overall crop productivity. Major atmospheric pollutants include tropospheric ozone (O₃), sulfur dioxide (SO₂), nitrogen oxides (NO_x), and particulate matter 2.5 (PM2.5), which are predominantly taken up via stomatal pathways, initiating extensive biochemical disturbances in plant tissues. Ozone exposure enhances the generation of ROS, which compromise cellular structures by damaging lipid membranes, denaturing proteins, and fragmenting nucleic acids, thereby impairing photosynthetic capacity and accelerating leaf senescence (Jimenez-Montenegro et al., 2021). SO₂ and NO_x undergo apoplastic transformations through oxidation and hydration reactions, leading to intracellular acidification and suppression of vital enzymatic processes. The accumulation of particulates on leaf surfaces obstructs light absorption, disrupts stomatal regulation, and interferes with cuticular water loss. Persistent exposure to these pollutants destabilizes the redox equilibrium, downregulates carbon assimilation, and impairs source-to-sink translocation, ultimately reducing biomass and yield (Bui et al., 2022). Additionally, long-term pollution exposure weakens Systemic Acquired Resistance (SAR), increasing vulnerability to pathogens and environmental stress. Effective pollutant mitigation is essential for preserving the stability and resilience of agroecosystems.

Radiation-induced stress adversely affects plant physiological functions, growth, and productivity. Types of ionizing radiation such as gamma rays, X-rays, and UV light can cause significant cellular damage and interfere with essential biochemical processes. Exposure to high-energy radiation often results in DNA strand breaks and mutations that impair mitotic activity, leading to stunted growth and diminished reproductive capacity. UV-B radiation, in particular, has been observed to intensify the production of ROS, which in turn causes oxidative damage. This damage includes membrane lipid peroxidation, protein degradation, and chloroplast dysfunction (Jan et al., 2022). These effects reduce photosynthetic efficiency and disturb overall metabolic stability. Radiation also affects membrane integrity and disturbs hormonal signaling pathways, further complicating plant development and morphological patterns. Sensitive plant species may exhibit symptoms such as chlorosis, necrosis, or irregular growth forms. Findings from different research groups suggest that although low radiation levels can sometimes activate stress adaptation mechanisms. However, prolonged or intense radiation exposure that surpasses the inherent protective capacity of plants can lead to significant physiological damage. To counteract these adverse effects, strategic interventions such as the use of UV-blocking films and the development of radiation-resistant crop varieties through breeding are crucial for enhancing crop resilience under radiation-induced stress (Katiyar et al., 2022).

The mechanical stress arising from the use of agricultural machinery and its related activities has the capacity to sometimes negatively impact plant structural integrity, physiological function, and soil quality. Ultimately, these factors contribute to compromising crop yield. It is a well-researched fact that the continual use of heavy equipment related to agricultural activities, such as tractors, plows, and harvesters, can result in the significant compaction of loose soil, reducing the microporosity that in turn reduces water infiltration and hinders proper oxygen availability to roots (Kouhen et al., 2023). These alterations hinder root respiration, restrict elongation, and impair the uptake of essential water and nutrients. Moreover, direct mechanical interference with plant organs during field operations often inflicts physical damage, including stem bending, leaf abrasion, and detachment of reproductive structures. The occurrence of these injuries reduces the effective photosynthetic surface and, in turn, disrupts assimilate allocation, ultimately risking the plant’s ability to produce a good yield. In addition, mechanical trauma can activate stress response pathways, notably through increased ethylene synthesis and ROS accumulation, which can trigger premature aging and abnormal growth responses (Cho and Nam, 2024). To alleviate these effects, practices such as Controlled Traffic Farming (CTF), low-impact machinery, and precision mechanization are vital for preserving soil structure and mitigating mechanical stress.

With the invention and frequent use of 5G and 6G communication technologies in almost all areas of life to achieve the Internet of Things (IoT) and the Industrial Internet of Things (IIoT). Where Radio-frequency (RF) and Electromagnetic (EM) waves are used as sources of communication. These communication sources are within the non-ionizing spectrum of 30 kHz to 300 GHz. However, these non-ionizing ranges are now increasingly acknowledged by the scientific community as a critical stressor that influences both plant physiological homeostasis and molecular regulation. Ongoing exposure to RF sources including mobile networks, wireless communication infrastructure, and telemetry systems, has been correlated with subtle yet detrimental effects on plant biology (Kaur et al., 2021). These effects encompass alterations in membrane properties, including changes in fluidity, ion channel modulation, and disruptions to membrane potential gradients. Additionally, it is observed that the use of RF hinders the functions of crops and plant cells and their viability. This is because RF can activate oxidative stress, which is driven by the excessive generation of ROS. ROS is responsible for cell damage, lipid peroxidation, protein destabilization, and DNA fragmentation. According to findings from different research groups, reductions in seed germination rates, photosystem impairment, and decreased biomass accumulation have been highlighted. Hormonal signaling pathways, particularly those involving ABA and auxins, may also be dysregulated. Phenotypically, plants may exhibit reduced leaf area, shortened internodes, and altered chlorophyll content (Halgamuge, 2017; Tran et al., 2023).

Pathogen stress arising from fungi, bacteria, viruses, and nematodes represents a major biotic constraint that disrupts plant physiological processes, compromises cellular stability, and leads to significant yield losses. Fungal species such as Fusarium spp, Botrytis cinerea, and Phytophthora infestans infiltrate plant tissues by enzymatically degrading protective barriers such as the cuticle and cell wall, causing vascular occlusion, tissue necrosis, and impaired photosynthetic efficiency (Gorshkov and Tsers, 2022). Bacterial pathogens, including Xanthomonas and Pseudomonas spp, gain access through natural openings in plants or through physical damage, releasing effectors and cell wall-degrading enzymes that compromise membrane integrity and trigger hypersensitive responses, manifesting as chlorosis, wilting, and cell lysis. Viral pathogens, often transmitted by phloem-feeding insects, hijack host translational mechanisms to proliferate, leading to widespread symptoms such as mosaic patterns, stunted development, and organ malformations. Nematodes such as Meloidogyne spp, induce root galls that disrupt water and nutrient uptake (Desaint et al., 2021). These biotic agents often act in unison, exacerbating plant stress. Effective mitigation requires an integrated approach combining molecular diagnostics, resistant genotypes, biological control, and site-specific agronomic strategies.

Insects and arthropods represent biotic stresses that disrupt plant physiological equilibrium, damage cellular components, and markedly decrease agricultural productivity. Key herbivorous groups, including Hemiptera (e.g., aphids, whiteflies), Thysanoptera (thrips), Lepidopteran larvae (caterpillars), and Acari (mites) employ diverse feeding mechanisms such as foliar consumption, phloem and xylem sap withdrawal via stylet insertion, and tissue injury associated with oviposition (Guedes et al., 2022). Chewing insects compromise foliar architecture and impair vascular function, thereby reducing photosynthetic efficiency and structural stability. In contrast, piercing-sucking species breach the epidermal and vascular layers, disrupting nutrient and water transport and often serving as efficient vectors for viral, bacterial, and phytoplasmal infections. Arthropod saliva frequently contains bioactive effectors that interfere with plant hormonal signaling pathways, particularly Jasmonic Acid (JA), Salicylic Acid (SA), and ethylene. This results in suppressed defense mechanisms (Jafir et al., 2023). Herbivory further induces oxidative stress through the accumulation of ROS, causing lipid peroxidation, protein degradation, and loss of membrane integrity. Symptoms include chlorosis, necrosis, impaired growth, and yield decline. Robust Integrated Pest Management (IPM) strategies involving resistant cultivars, biological control agents, and targeted agrochemical interventions are essential to mitigate these effects and ensure crop resilience.

The crops and plants that we grow have to compete with a variety of vegetation that is considered parasitic in nature. It can be easily observed on a daily basis that these parasitic plants have evolved with the passage of time in such a way. Now they are much better adapted to various stressors and have an exceptional ability to create vigorous biomass and reproduce copiously. Thus, the plants and crops that we cultivate to fulfill our food requirements and many other needs are under constant pressure to obtain essential resources, including PAR, soil moisture, and vital nutrients. This competitive imbalance disrupts photosynthetic carbon assimilation, limits nutrient acquisition, and constrains root development (Ronay et al., 2021). Furthermore, allelopathic weed species release chemical compounds into the rhizosphere that interfere with plant signaling, inhibit seedling establishment, and restrict root elongation through toxic effects. Dense weed infestations also modify the microenvironment by increasing relative humidity and altering canopy structure, thereby enhancing the risk of disease outbreaks and arthropod pest infestations. Collectively, these stressors can hinder the photosynthetic processes, delay developmental stages, and ultimately lead to significantly reduced crop yields (Horvath et al., 2023). Addressing these impacts requires Integrated Weed Management (IWM), which includes the strategic use of herbicides, crop diversification, selection of competitive cultivars, and site-specific agronomic interventions to sustain agroecosystem functionality and optimize resource efficiency.

Parasitic plants such as Striga and Cuscuta utilize highly specialized biotrophic mechanisms that impose a substantial physiological and metabolic burden on their host plants. Striga species infiltrate the host root cortex and form haustorial interfaces with xylem vessels that enable the extraction of water, essential minerals, and photoassimilates. This parasitic interaction disrupts transpiration dynamics and ionic equilibrium, and interferes with the translocation of carbon metabolites within the plant system (Zagorchev et al., 2021). Striga infestation leads to hormonal dysregulation, particularly in ABA signaling and strigolactone synthesis. This is accompanied by a decline in photosynthetic performance due to chlorophyll degradation and downregulation of Ribulose-1,5 bisphosphate carboxylase/oxygenase (Rubisco) activity. Cuscuta species, which lack functional roots and chlorophyll, attach to aboveground organs that tap into both the xylem and the phloem, disrupting source-to-sink relationships and altering hormonal networks, especially those involving auxins and cytokinins. Both parasitic genera provoke oxidative stress, which is characterized by increased ROS, membrane lipid peroxidation, and loss of cellular stability (Albanova et al., 2023). Control strategies include integrated management approaches involving resistance genes, pre-emergence herbicidal treatments, and modulation of rhizospheric microbial communities.

Stress arising from interactions with animals including rodents, birds, livestock, and wild herbivores constitutes a major biotic constraint on the sustainability of agroecosystems and crop yield potential. Rodents cause significant damage both below and above ground by consuming seeds and vegetative organs, leading to reduced germination and impaired early plant growth (Kuka et al., 2022). Granivorous birds commonly feed on reproductive structures, resulting in grain loss and mechanical injury to inflorescences, thereby disrupting assimilate partitioning and impairing source-to-sink dynamics. Unregulated livestock access also causes extensive physical damage through trampling, leaf removal, and root exposure, which adversely affects photosynthetic capacity, turgor pressure regulation, and plant recovery potential. Wild animals and various primates inflict additional stress by stripping foliage, abrading bark, and feeding on fruits, intensifying physiological disruption (LaMalfa et al., 2021). These injuries increase ROS levels and interfere with hormone signaling, resulting in increased vulnerability to pathogen infections. Effective management requires integrated strategies involving exclusion structures, deterrents, and ecological landscape design.

Anthropogenic stress arising from unsustainable agricultural practices such as overexploitation of resources, improper handling of crops, monocultural farming, and suboptimal landscape configuration severely hampers plants’ physiological processes and threatens the sustainability of agroecosystems. Overharvesting interrupts developmental progression by removing vital vegetative and reproductive tissues, thereby limiting meristem function and regeneration. Mishandling during sowing, transplantation, or harvesting inflicts physical trauma, disrupts vascular continuity, and increases vulnerability to pathogenic infiltration (Demirdogen et al., 2023). Monoculture systems, with minimal genetic variability and repetitive cropping, lead to rapid soil nutrient depletion, destabilization of rhizosphere microbial communities, and a heightened risk of pest and pathogen epidemics. Additionally, poorly designed landscapes, characterized by inadequate spacing, inefficient irrigation, and a lack of crop rotation, intensify interspecific competition for essential resources such as PAR, water, and nutrients (Hernández-Ochoa et al., 2022). Collectively, these stressors impair hormonal signaling pathways, reduce photosynthetic capacity, and disrupt source-to-sink dynamics, leading to decreased biomass accumulation and diminished yield. Implementing adaptive and ecologically sound management strategies is critical to counteracting these compounded stresses and is also helpful in enhancing resilience.

Leaf water potential (Ψ_leaf) quantifies the total potential energy of water within leaf tissues and is a key determinant of water movement through the plant’s hydraulic continuum. The Pressure Chamber Method, a widely recognized destructive approach, provides accurate measurements of Ψ_leaf in both field and experimental settings. The method involves excising a mature, physiologically active leaf or shoot, ideally during midday when water stress is typically at its peak and securing it in an airtight pressure chamber, with the severed end extending through a tightly sealed gasket (Rodriguez-Dominguez et al., 2022). Compressed nitrogen is gradually introduced to increase the chamber’s pressure, effectively countering the negative pressure (tension) in the xylem. When the sap emerges at the cut surface, the internal tension is balanced by the external pressure, which is recorded in megapascals (MPa) and that reading corresponds to the leaf’s water potential. More negative values of Ψ_leaf indicate higher levels of water stress and reduced water availability to the plant. This method yields high-resolution quantitative data that are critical for optimizing irrigation schedules, assessing drought resilience, and modeling plant physiological responses to environmental stress. The formula to calculate leaf water potential is Ψ_Leaf = Ψ _s + Ψ _p where Ψ _s is the solute potential and Ψ _p is the pressure potential (Ding et al., 2021). A simplified process flow is illustrated in Figure 5a , while a basic setup of the equipment to perform the aforementioned task is shown in Figure 5b .

RWC is an important physiological metric for assessing the water status of plant tissues under various environmental conditions, particularly drought. RWC reliably reflects the extent of water retention within plant cells and indicates the plant’s ability to maintain turgor pressure, which is crucial for sustaining metabolic activities and supporting cell expansion during stress (Rashid et al., 2022). The assessment of RWC involves three main stages: (i) the Sampling Phase, in which mature, healthy leaves are harvested from a consistent nodal position across plants to ensure uniformity. Immediately after collection, the Fresh Weight (FW) is recorded to capture the leaf’s current water content. (ii) the rehydration phase, during which the samples are immersed in deionized water and kept in darkness at room temperature (approximately 22°C to 25°C) for 4 to 6 hours, allowing the leaves to fully rehydrate and reach maximum turgor. After rehydration, surface moisture is gently removed, and the Turgid Weight (TW) is measured. (iii) the drying phase, during which the leaves are dried in an oven at 70°C for 24 to 48 hours to achieve a constant weight, known as the Dry Weight (DW), which represents their solid biomass (Ilyas et al., 2021). The formula to calculate the RWC is RWC (%) = [(FW − DW)/(TW − DW)] × 100. This calculation provides an accurate measure of tissue water deficit. High RWC values are associated with better water retention and stress tolerance, whereas low values indicate dehydration and increased vulnerability. RWC is widely used in ecological and physiological research and plays a vital role in breeding programs focused on improving stress resistance.

Quantifying proline and other compatible osmolytes is a pivotal technique used for analyzing plant physiological responses to stress conditions such as drought, high salinity, and temperature fluctuations. These adverse conditions disrupt cellular homeostasis, triggering the upregulation and accumulation of low-molecular-weight osmolytes such as proline, glycine betaine, and soluble sugars. That plays an essential role in osmotic adjustment, and membrane and protein stabilization, with the mitigation of oxidative stress through ROS scavenging (Spormann et al., 2023). The standard procedure for proline determination involves homogenizing fresh leaf tissue in 3% sulfosalicylic acid, followed by centrifugation to obtain a clear supernatant. This extract is then reacted with an acid ninhydrin solution (prepared using 1.25 g ninhydrin in a mixture of glacial acetic acid and phosphoric acid) and incubated at 100°C for 60 minutes to facilitate chromophore formation. Once cooled, the mixture is extracted with toluene, and the absorbance of the resulting colored complex is measured using a UV spectrophotometer. The concentration of proline can then be observed in comparison to the calibration curve of L-proline standards (Zdunek-Zastocka et al., 2021). However, researchers have also mentioned that other types of related osmolytes, that are equally important, can be analyzed by using distinct, specific colorimetric assays, which consist of the phenol sulfuric acid method for sugar evaluation, and also incorporate more progressive state-of-the-art techniques into existing approaches, such as High Performance Liquid Chromatography (HPLC). We can conclude that the described analytical approach is crucial for understanding stress tolerance mechanisms and is also helpful in identifying stress-resilient genotypes in crop improvement programs.

The MDA and Lipid Peroxidation (LPO) assay is a vital biochemical method for determining the extent of oxidative damage to plant cell membranes caused by stress, especially under conditions such as drought, salinity, and extreme temperatures. LPO is a key marker of oxidative stress, triggered by ROS attacking polyunsaturated fatty acids in membrane structures. This leads to the formation of MDA, a reactive aldehyde and widely accepted biomarker of oxidative damage (Shahid et al., 2022). MDA quantification is most commonly carried out using the Thiobarbituric Acid Reactive Substances (TBARS) assay. In this protocol, the users will homogenize the tissues from a fresh plant; the part of the plant that can be used is the leaves. In this process the leaves are homogenized in 0.1% to 1% trichloroacetic acid (TCA). This homogenization helps in the precipitation of proteins, which makes extracting soluble metabolites possible. After centrifugation, the supernatant is mixed with thiobarbituric acid (TBA) and dissolved in 20% TCA. The reaction mixture is incubated at 95°C for 30 to 60 minutes, which helps in promoting the formation of a pink-colored MDA-TBA complex. After cooling, absorbance is measured at 532 nm using a spectrophotometer, with a correction at 600 nm to account for background interference (Wang et al., 2022). MDA content is then determined with the help of either a standard curve or by using a molar extinction coefficient. This assay is essential for investigating lipid peroxidation and screening plant genotypes for oxidative stress resilience.

Antioxidant enzyme activity assays, specifically targeting SOD, CAT, and POD, are essential biochemical methods for characterizing plant responses to oxidative stress triggered by stress conditions such as drought, salinity, and temperature extremes. These enzymes play a key role in the enzymatic antioxidant defense mechanism by neutralizing ROS generated during stress-induced metabolic dysfunction (Kavian et al., 2022). Typically, in this process, plant tissues, most commonly leaves, are homogenized in an ice-cold extraction medium, such as potassium phosphate buffer (pH 7.0), supplemented with protective additives such as Ethylenediaminetetraacetic Acid (EDTA) and 1% Polyvinylpyrrolidone (PVP) to inhibit phenolic interference and preserve enzymatic integrity. The homogenate is then centrifuged at 12,000 to 15,000 × g for 15 to 20 minutes at 4°C to collect a clear enzyme-containing supernatant. SOD activity is measured by its ability to inhibit the photoreduction of nitroblue tetrazolium (NBT), with absorbance monitored at 560 nm. CAT activity is evaluated by tracking the reduction in absorbance at 240 nm as hydrogen peroxide is decomposed enzymatically. POD activity is quantified by observing the oxidation of guaiacol in the presence of hydrogen peroxide, and measuring it at 470 nm (Osei et al., 2022). These spectrophotometric evaluations offer precise indicators of a plant’s oxidative defense status and are indispensable in stress physiology and genotype selection programs.

It has been observed that whenever a plant or a crop is affected by a factor that has the ability to induce stress in vegetation, such as drought, salinity, intense light exposure, and extreme temperatures, it may be necessary to extract the chlorophyll and pigments for analysis to evaluate the efficiency of the photosynthetic process in plants. This allows for determining whether the plant is performing optimally and whether a good yield can still be obtained or if some kind of countermeasures are required to put the crop or the plant back on track to achieve a sufficient yield. Plants under environmental stress have disrupted pigment biosynthesis and accelerated chlorophyll degradation. This hinders the ability of the plant to use the captured light and perform the process of photosynthesis efficiently. Quantitative analysis of chlorophyll a, chlorophyll b, and auxiliary pigments such as carotenoids provides a dependable indicator of photosynthetic competence and stress-induced deterioration (Berhe et al., 2024). The standard method involves grinding freshly collected leaf tissues in an appropriate organic solvent, which is commonly 80% acetone, absolute ethanol, or Dimethyl Sulfoxide (DMSO). This process is done under dim light to avoid pigment degradation. The extract is then centrifuged at 10,000 to 15,000 × g for 10 to 15 minutes to yield a pigment-rich supernatant, which is used for spectrophotometric assessment. The users will then take absorbance readings at specific wavelengths of 663 nm for chlorophyll a, 645 nm for chlorophyll b, and 470 nm for carotenoids. Then, the pigment concentrations can be determined by using standardized equations, such as those developed by Arnon or Lichtenthaler. Once the calculations are obtained, the results are analyzed and expressed in relation to the fresh weight of the plant tissue (Saini et al., 2022).A reduction in pigment levels signifies oxidative damage, disruption of chloroplast function, and metabolic imbalance, underscoring the value of this assay in stress diagnostics and crop improvement programs.

Protein and Ribonucleic Acid (RNA) extraction are fundamental molecular techniques that are very crucial for characterizing the functional responses of plants to stressors at the transcriptomic and proteomic levels. RNA is commonly extracted using phenol-chloroform-based methods such as the Total RNA Isolation Reagent (TRIzol) or commercial silica-based spin column kits. To ensure high-quality RNA that may be suitable for downstream applications, Deoxyribonuclease I (DNase I) treatment is applied to remove any contaminating genomic DNA. Quantitative Real-Time Polymerase Chain Reaction (qPCR) is utilized to evaluate the expression levels of critical stress-responsive genes in plants. These include genes that encode antioxidant enzymes such as SOD and CAT, HSPs, and transcription factors such as DREB and WRKY (named after the SPF1 protein cloned from sweet potato). All of these play vital roles in defending against environmental stresses such as drought, salinity, cold, and pathogen invasion (Khurshid et al., 2021). To get a better view of gene expression, RNA sequencing offers high-throughput analysis that has the capability of detecting genome-wide transcriptomic changes, which in turn makes it possible to reveal the regulatory networks associated with stress adaptation. Recovery of stress-inducible proteins is only possible under denaturing or native conditions. These proteins are subsequently characterized using electrophoretic techniques such as Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), immunodetection via western blotting, or more sophisticated proteomic approaches including Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) (Wang et al., 2024). As discussed, these analyses can expose crucial information about the post-translational modification, enzyme activity modulation, and signal transduction pathways that are triggered by environmental stimuli. The accuracy and reliability of both RNA- and protein-based investigations depend on rigorously optimized extraction protocols that preserve biomolecule integrity, inhibit enzymatic degradation, and avoid contamination. Thus, it can be concluded that, taken together, transcriptomic and proteomic methodologies can provide a comprehensive molecular framework. This framework can be used for the understanding of plant stress responses, which can in turn play a pivotal role in guiding the development of genetically enhanced, stress-tolerant crop varieties.

Ion content analysis, notably the precise measurement of Na⁺ and K⁺ levels, is an essential physiological technique for assessing how plants respond to and adapt to saline stress conditions. This is because an immense amount of salinity in the soil will normally result in higher Na⁺ content in plant tissues. This, in turn, damages the normal ionic balance of a crop/plant, and prohibits K⁺ uptake. If these abnormalities occur due to severe salinity, they will hinder key cellular functions including enzymatic activity, protein synthesis, and membrane potential regulation (Kumar et al., 2021). For analysis, plant tissues such as leaves, stems, or roots are carefully collected and thoroughly washed to remove surface salts, oven-dried to achieve constant weight, and finely pulverized. The powdered material undergoes acid digestion using concentrated nitric acid or a nitric-perchloric acid mixture under controlled conditions to extract ionic constituents. These digests are then appropriately diluted and analyzed using techniques such as flame photometry, Atomic Absorption Spectrophotometry (AAS), or Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) for precise ion quantification (Singhal and Singh, 2024). Based on the preceding discussion on salinity, it can be concluded that the Na⁺/K⁺ ratio in the examined soil serves as a reliable physiological marker for assessing salinity tolerance. A lower Na⁺/K⁺ ratio indicates effective ion selectivity, efficient osmotic regulation, and the preservation of cellular ion balance under saline conditions.

Histochemical staining is a highly specialized cytochemical technique that can be utilized for the in situ detection of stress-induced biochemical alterations in plant tissues. This technique provides detailed resolution at both the cellular and subcellular levels. It employs chromogenic or fluorogenic reagents to identify molecular markers related to oxidative injury, enzyme activity, or cell viability under stress conditions. Diaminobenzidine (DAB) is used to detect Hydrogen Peroxide (H₂O₂) by producing a localized brown precipitate, whereas NBT reacts with superoxide anions to form a blue formazan deposit. Both serve as spatial indicators of ROS presence (Yadav et al., 2021). As part of this method the users first select the appropriate plant or crop samples necessary to perform the aforementioned histochemical staining process such as leaves and roots. These parts are carefully detached and infiltrated under an artificially created vacuum in the presence of a selected staining reagent. Once this step is completed, the extracted and processed plant part will be incubated with the staining reagent in the absence of light at a precisely controlled temperature to ensure that efficient reaction kinetics are achieved. Following staining, the tissues are cleared using ethanol or acetic acid, with glycerol solution used to eliminate the chlorophyll and improve visualization (De Palma and Fett-Neto, 2024). The stained sections are then analyzed using light or fluorescence microscopy to enable a semi-quantitative evaluation of oxidative stress patterns and spatial mapping of plant defense responses.

Estimating dry weight or biomass is a critical physiological technique employed to evaluate plant growth responses and assess the extent of stress-induced effects under both abiotic and biotic challenges. To perform these measurements, a specific process is used that includes obtaining plant parts such as leaves, stems, roots, and, in some site-specific cases, the entire plant. Once these samples are collected, they are carefully cleaned to prevent any kind of external debris from contaminating them. Then, the samples are gently bottled to ensure that residual moisture on their surface can be properly eliminated (Qu et al., 2021). These samples are then oven-dried at a regulated temperature, generally between 65°C and 80°C, for 48 to 72 hours or until a constant weight is achieved, ensuring complete dehydration. After drying, the samples are accurately weighed using a sensitive analytical balance to determine the dry biomass, which reflects the plant’s total organic matter excluding water content. Crops or plants may exhibit signs of impaired photosynthetic activity, altered metabolic pathways, and restricted cellular proliferation (Chandrasekaran, 2022). Once a farmer or lab analyst detects any impairment, dry weight analysis can provide a reliable and integrative metric for evaluating stress tolerance and genotypic variation in plant physiological and agronomic studies.

Chlorophyll fluorescence imaging is a precise, non-destructive method used to evaluate photosynthetic performance and detect early stress indicators in plants at a high spatial resolution. This technique is based on the idea that a small amount of light absorbed by Photosystem II (PSII) is re-emitted as fluorescence. Variations in this signal reflect the plant’s physiological state regarding photosynthesis (Moustaka and Moustakas, 2023). Under optimal conditions, the absorbed energy is largely utilized for photochemical processes. However, exposure to environmental stresses such as drought, salinity, temperature extremes, or nutrient deficiencies reduces the efficiency of electron transport in PSII, leading to increased fluorescence output. Utilizing the Pulse Amplitude Modulated (PAM) fluorometry combined with advanced imaging systems, researchers can measure parameters such as maximum quantum yield (Fv/Fm), effective quantum yield (ΦPSII), and NPQ, which reflect declines in PSII efficiency and indicate photoinhibition under stressed conditions. This approach has the capability to enable high-throughput, real-time phenotyping along with precise spatial mapping of photosynthetic stress responses. This ultimately makes it an essential tool for accessing plant physiology and stress diagnostics, bringing the users closer to achieving precision agriculture (Park et al., 2024). A formal blueprint of the explained process is provided in Figure 6 , so that readers can better understand the schematic and implement it further if needed.

Imaging technologies, including Red Green and Blue (RGB) cameras, multispectral imaging, and thermal imaging (thermography), play a crucial role in identifying stress in crops and plants. Integrating these imaging systems with drones and satellites within the scope of Wireless Sensor Networks (WSNs) effectively achieves this objective, enabling comprehensive stress detection in agricultural environments. RGB imaging captures visual patterns and color variations in foliage, which often reflect nutrient deficiencies or the presence of a disease. Multispectral systems gather data across different spectral bands, enabling the assessment of plant health through indices such as the Normalized Difference Vegetation Index (NDVI). Thermal imaging, whether deployed via satellite or drone, tracks variations in canopy temperature, offering insights into heat stress or impaired transpiration resulting from drought conditions. Additionally, Light Detection and Ranging (LiDAR) provides a three-dimensional view of the canopy structure, enhancing stress assessment capabilities. Collectively, these non-invasive tools support real-time observation, early diagnosis of stress symptoms, and precision agriculture strategies, thereby improving crop health management and boosting productivity across varying environmental conditions. In the subsection of this part of the review, readers will find technical details of these non-destructive imaging stress assessment methods. Figure 7 provides a basic layout that is aimed at stress detection using non-destructive techniques such as LiDAR, hyperspectral imaging, and thermography to complement the discussion in sections 4.2.2.1, 4.2.2.2 and 4.2.2.3.

Gas exchange analysis is a vital physiological technique for accurately assessing plant responses to abiotic stress. It measures real-time gas fluxes associated with photosynthesis and transpiration. This approach employs advanced Infrared Gas Analyzers (IRGAs) paired with controlled cuvette systems to monitor essential parameters, including net CO₂ assimilation, stomatal conductance, transpiration rate, and intercellular CO₂ concentration. Under environmental stressors such as drought, salinity, extreme temperatures, or nutrient limitations, plants undergo shifts in stomatal regulation and metabolic activities, resulting in noticeable declines in carbon assimilation and alterations in transpiration dynamics (Pflüger et al., 2024). From the literature, we have observed that the aforementioned stresses can reduce a plant’s ability to signal a reduction in gas exchange efficiency and this specific property can be detected much earlier than any visible symptom appears. Therefore, it can be concluded that the non-destructive gas exchange profiling can have a crucial role in evaluating PSII function and determining water use efficiency. This approach offers users (farmers or field analysts) valuable insight into plant stress responses and helps them make informed decisions regarding genotype screening, agronomic strategy development, and environmental stress modeling within precision agriculture frameworks (Abdelhakim et al., 2021).

Chlorophyll content measurement is a widely adopted, non-destructive technique for assessing the physiological state of plants, especially when under stress. One of the most commonly utilized instruments for this purpose is the SPAD meter, which determines relative chlorophyll levels by measuring the differential transmission of red (650 nm) and NIR (940 nm) light through the leaf. As chlorophyll pigments absorb red light efficiently while allowing NIR light to pass through, the SPAD device generates an index value indicative of chlorophyll concentration (Mielcarek et al., 2018). When plants experience abiotic or biotic stress such as drought, salinity, nutrient deficiency, or pathogen attack, chlorophyll biosynthesis is often suppressed, leading to reduced SPAD values that can signal stress before any visible symptoms appear. This rapid, on-site diagnostic tool supports precision agriculture by enabling real-time tracking of photosynthetic efficiency and the early identification of physiological disruptions (Ojoatre, 2016). Its ease of use, portability, and capacity for high-throughput data collection make it essential for large-scale phenotyping, agronomic evaluations, and plant stress studies.

Electrical Impedance Tomography (EIT) is an advanced and non-invasive imaging technique that farmers can utilize to assess the physiological stress of crops and plants. This method examines the internal distribution of electrical conductivity within plant tissues. The aforementioned process entails the precise arrangement of electrodes around plant structures, most commonly stems or leaves, through which low-amplitude alternating currents are systematically applied. A trained individual captures the resulting voltage measurements obtained from multiple electrode pairings at the periphery. The readings obtained are processed using inverse computational techniques, and the reason to do so is to reconstruct a high-resolution image capable of capturing spatial impedance variations (Corona-Lopez et al., 2019). Different research groups have focused on the fact that stress conditions, including drought, nutrient deficiencies, and pathogen attacks, alter physiological parameters such as water content, membrane stability, and ion movement, all of which are reflected in the impedance data. Thus, the EIT methodology is ideally suited for the continuous assessment of plant stress over extended periods. Additionally, some have noted that when this technology is integrated with WSNs, EIT enables scalable, on-site diagnostics across extensive agricultural systems, advancing precision agriculture by supporting the early detection and timely management of latent stress responses in crops (Basak and Wahid, 2022).

Over time supervised ML techniques, especially classification models, have become a core component of agricultural data analysis. Their effectiveness has been demonstrated by researchers and practitioners worldwide, consistently delivering valuable and beneficial outcomes. These models primarily offer critical solutions that can distinguish whether a crop or a plant is healthy or experiencing some form of stress that is hindering its growth. These models rely on labeled datasets, where class labels such as “stressed” or “healthy” are predefined, enabling the algorithm to learn discriminative patterns and establish predictive relationships between input features and output classes. The growing accessibility of high-resolution data from remote sensing platforms including multispectral, hyperspectral, and thermal imaging along with field physiological measurements, has significantly enhanced the accuracy, robustness, and scalability of these classification systems across diverse agricultural scenarios (Navrozidis et al., 2022).

Supervised classification methods such as SVMs, RF, DTs, and k-NN have collectively established a fundamental analytical foundation for the data-driven evaluation of plant and crop stress. Their integration with sensor technologies, UAV-based data acquisition, and cloud-enabled agricultural platforms supports the accurate, scalable, and real-time detection of stress in crops. This facilitates informed, proactive decision making, and efficient resource utilization, which promotes the progression of precision agriculture toward more sustainable and resilient food production systems. Table 4 presents several real-world applications of ML models across a variety of crop types, aimed at achieving effective stress assessment.

Supervised ML regression models provide a technically advanced and scalable framework for quantifying stress severity in crops and plants, playing a pivotal role in precision agriculture. These models are trained on labeled datasets in which continuous output variables representing measurable indicators of stress severity, such as the extent of chlorosis, leaf water potential, and deviations in canopy temperature, are linked with a wide array of input features. These features are extracted from diverse data sources, including multispectral and hyperspectral imagery captured by UAVs, thermal imaging systems, soil moisture probes, and weather-related parameters (Asaari et al., 2022). The primary objective of supervised regression is to construct a functional mapping that can effectively capture and predict the severity of biotic or abiotic stress impacting plant health by representing a high-dimensional vector comprising environmental and physiological variables. Among the various regression algorithms used for this application, Simple Linear Regression (SLR), Random Forest Regression (RFR), Gradient Boosting Machines (GBMs), and Extreme Gradient Boosting (XGBoost) are particularly noteworthy, each offering unique modeling structures, learning strategies, and levels of predictive performance.

These supervised regression models collectively provide a solid foundation for predictive analytics in agricultural stress monitoring. When combined with UAV-based imaging systems, ground-level sensor networks, and cloud-edge computing infrastructure, they enable precise spatial and temporal predictions of crop stress severity. This capability supports key precision agriculture strategies, including site-specific irrigation, efficient pesticide application, and the early detection of plant health issues. The choice of an appropriate algorithm is typically influenced by the balance between model transparency, computational efficiency, and the complexity of feature-target relationships. Within modern agronomic decision support systems, these regression approaches serve as the core of scalable, data-driven solutions aimed at promoting sustainable crop production and optimizing yields under varying environmental and biological stress conditions. Table 5 presents a comparative analysis of the previously discussed supervised ML algorithms, along with their reported performance metrics as documented in various research studies.

Clustering techniques play a vital role in agriculture by detecting crop and plant stress through the identification of natural groupings within unlabeled data. These unsupervised learning methods evaluate patterns of features such as spectral reflectance, thermal data, and vegetation indices to differentiate stressed plants from healthy ones. Algorithms such as k-means, hierarchical clustering, and Density Based Spatial Clustering of Applications with Noise (DBSCAN) effectively group plant populations based on physiological characteristics, enabling the timely detection of stress factors such as nutrient shortages, water stress, and disease. Offering spatially detailed insights without requiring labeled inputs, clustering aids in implementing precise interventions and strengthens decision-making processes to enhance crop health and overall agricultural productivity.

The performance of unsupervised clustering algorithms can be significantly enhanced through the use of dimensionality reduction techniques such as PCA and t-Distributed Stochastic Neighbor Embedding (t-SNE) (Zhu et al., 2021; Dutağaci, 2023). These approaches simplify complex, high-dimensional sensor data such as multispectral or hyperspectral imagery, leading to improved clustering precision and more intuitive visual interpretation. In agricultural practice, the clustered outputs can be mapped geospatially to identify spatial stress patterns within fields, enabling precision interventions such as site-specific irrigation, targeted pesticide application, or soil treatment. Additionally, by integrating these clustering methods with edge computing platforms, real-time analysis can be performed directly on UAVs or sensor nodes, delivering immediate, field-level insights and decision support. As agricultural data continues to expand in both scale and complexity, unsupervised clustering provides a flexible, scalable, and label-free solution for extracting meaningful insights from raw sensor inputs, thereby supporting sustainable and data-informed farming strategies tailored to the dynamic variability of crop conditions. Table 6 presents a comparative analysis of the previously discussed unsupervised ML algorithms, along with their reported performance metrics as documented in various research studies.