Search Results (1,426)

Nuclear Factor Y, subunit A (NFYA) constitutes a family of transcription factors that play critical roles in plant growth, development and abiotic stress responses. Taxodium hybrid ‘Zhongshanshan’ (T. mucronatum × T. distichum) is a fast-growing tree species with high industrial value and remarkable flooding tolerance. However, the systematic characteristics and abiotic stress response patterns of the ThNFYA gene family remain unclear. In this study, a total of 11 ThNFYA genes were identified. The encoded proteins ranged from 67 to 372 amino acids in length, with predicted molecular weights between 16.84 and 40.12 kDa. Phylogenetic analysis classified plant NFYAs into four clades, with all ThNFYAs falling into clades I and IV. Expression profiling revealed tissue-specific patterns, with six members showing the highest transcript levels in the cambium. Multiple cis-acting elements associated with stress and hormone responses were detected in the promoter regions of ThNFYAs. Most ThNFYAs were differentially regulated under salt, drought, and flooding stresses. Notably, most clade IV members (ThNFYA3, ThNFYA4, and ThNFYA6-ThNFYA8) were downregulated in the wood under partial submergence. This indicates their potential role in modifying wood properties in response to flooding. Co-expression network analysis identified ThNFYA1 and ThNFYA8 as central hub genes in leaves under partial submergence. Overall, these results suggest that the ThNFYA family may serve as candidate regulators of development and stress adaptation in T. hybrid ‘Zhongshanshan’. This study provides valuable insights for further functional verification of ThNFYAs and lays a foundation for marker-assisted breeding of stress-tolerant varieties. Full article

Drought stress severely limits foxtail millet yield and quality, yet current drought-resistance indices are exclusively yield-oriented and ignore grain-filling quality. Our two-year (2024–2025) experiments with 24–48 varieties revealed that yield and blighted grain rate (BGR) are partially decoupled (e.g., Zhangzagu 18: yield 2307 kg/ha, BGR 0.444; Zhonggu 19: yield 1622 kg/ha, BGR 0.280). We therefore constructed the Yield–Quality Synergy Index (YQSI = DYI − BGR), which penalizes varieties with poor grain filling. The YQSI tied for first place with DYI in comprehensive screening performance and achieved the highest inter-annual stability (Spearman ρ = 0.823, Jaccard = 0.438, composite score = 1.261). Sensitivity analysis confirmed robustness of the equal-weight formula across a 4-fold range of quality-penalty weights. Six strongly drought-resistant germplasms with balanced yield and quality were identified. Using UAV multimodal data (RGB, multispectral, and thermal infrared) acquired during grain filling, a Random Forest model predicted a YQSI with overall R² = 0.819 and an F1 score of 0.933 for variety screening. Feature-importance analysis highlighted NDVI, WDRVI, and red-edge texture as key predictors. This study provides a quality-constrained drought-resistance evaluation framework and demonstrates the potential of UAV-based high-throughput phenotyping for foxtail millet breeding. Full article

Hydrothermal variability, rising evaporative demand, and drought extremes increasingly threaten crop production in semi-arid regions, yet their relative contributions to maize yield variability remain unclear. Here, we examined maize yield responses to growing-season climatic conditions in Lyuliang City, North China, during 2005–2024 using yield statistics and ChinaMet climate data. Trend analysis, Pearson correlation, candidate regression models, standardized coefficients, and generalized additive models were used to identify dominant climatic predictors. Maize yield showed no significant temporal trend during the study period (Sen’s slope = 0.01 t ha⁻¹ yr⁻¹, p = 0.58), whereas growing-season potential evapotranspiration tended to increase (2.81 mm yr⁻¹, p = 0.06). Diurnal temperature range declined significantly (−0.04 °C yr⁻¹, p = 0.01), and minimum SPEI also decreased significantly (−0.04 yr⁻¹, p = 0.01), indicating intensified extreme dry conditions. Maize yield was most strongly correlated with aridity index (r = 0.72, p < 0.001) and water deficit (r = 0.72, p < 0.001), suggesting that hydrothermal balance explained yield variability better than precipitation or temperature alone. The highest-ranked regression model included aridity index, growing-season temperature, diurnal temperature range, and minimum SPEI, explaining 70% of interannual yield variation. Aridity index was the strongest positive predictor, whereas diurnal temperature range had a significant negative association with yield. Although extreme dry conditions intensified over time, minimum SPEI was not directly associated with annual yield, implying that drought impacts may depend on drought timing, crop phenology, and management buffering. These findings highlight the importance of maintaining favorable hydrothermal balance and reducing risks from increasing evaporative demand and temperature variability to support climate-resilient maize production in Lyuliang City and climatically similar rain-fed semi-arid regions of North China. Full article

Climate change is placing global agriculture under growing pressure, as plants must withstand extreme environmental conditions such as drought and high salinity, both inducing osmotic and oxidative stress. As part of their survival strategies, plants accumulate protective molecules (osmolytes), including the amino acid proline. For decades, plant biology has largely assumed that high proline accumulation under stress signals strong stress tolerance. However, this review challenges that “proline-centric” perspective. Analyses across a wide range of plant species reveal a more complex picture. Stress-induced proline accumulation is not universal: in some species, proline levels remain relatively unchanged, with other metabolites acting as functional osmolytes, or increase only in response to artificially applied severe stress conditions. Even when proline increases, its absolute concentrations may be too low to contribute significantly to osmotic adjustment. Nevertheless, proline may still be involved in stress tolerance mechanisms through its additional roles, detoxifying reactive oxygen species (ROS), directly stabilising proteins or acting as a stress signalling molecule. Comparative analyses of genetically related taxa with varying degrees of stress tolerance sometimes show negative correlations between proline accumulation and tolerance, with higher proline concentrations measured in the most sensitive genotypes. Overall, the evidence indicates that proline‘s role in plant survival is highly context-dependent and strongly influenced by genetic background and must therefore be evaluated on a case-by-case basis. Distinguishing whether proline acts as an adaptive defence or merely as a biochemical marker of physiological strain under stress is essential for accurately assessing plant stress tolerance. Full article

Aegilops geniculata Roth is a tetraploid wild relative of wheat distributed throughout the Mediterranean Basin, where it grows in a wide range of habitats. Due to its genetic diversity, ecological plasticity and adaptation to Mediterranean ruderal environments, the species has attracted increasing interest as a genetic resource for wheat improvement and as a potential component of sustainable agroecosystems. Beyond use in agriculture, its ecological characteristics also suggest applications in Nature-based Solutions, including revegetation of degraded, low-input, semi-arid ecosystems. This review aims to provide a comprehensive synthesis of current knowledge on the taxonomy, genetics, morphology, distribution, ecology, reproductive biology and conservation of Ae. geniculata. This work is complemented by original experimental data on agronomic traits and an assessment of ex situ conservation efforts. Evidence highlights the species’ value as a source of drought- and stress-adaptive traits for wheat improvement, plus promising cover crop traits (rapid establishment, stable biomass production and flexible germination behavior). Remaining knowledge gaps include population genomics, conservation of undercollected populations and field-scale agronomic performance to better clarify the potential of this species as a cover crop. This work supports further investigation of Ae. geniculata as both a valuable crop wild relative and a promising cover crop for Mediterranean agroecosystems. Full article

Against the backdrop of climate change and compounded by human activities, increasing water scarcity has triggered a series of drought disasters, which have already severely impacted both ecological environments and socioeconomic production. The SWAT model, recognized for its strong portability and superior spatial heterogeneity, has gained widespread acceptance in fields such as hydrology and environmental science, and is extensively applied in hydrological simulation studies across large-scale river basins. Hydrological models of the study area can be constructed in the SWAT model to simulate changes in hydrological variables by conducting spatial discretization, parameter specification, and boundary condition definition. Standardized drought index can effectively reflect the spatiotemporal variations in drought disasters, holding significant importance for clarifying and predicting drought characteristics. This study took the Luanhe River Basin as the research area, constructed a watershed hydrological model based on SWAT, and projected changes in the basin’s hydrological processes for the period 2030–2060. Based on the model’s projected data, we calculated drought indices and extracted drought events for the basin. The results indicate the following: (1) During the simulation period, only 30% of the years in the Luanhe River basin had annual runoff above the long-term average, with a range of 228.18 mm. The range of mean annual runoff across sub-basins was 173.32 mm. Drought and uneven water resource allocation over both spatial and temporal scales coexisted, and this issue is expected to intensify under future climate warming and drying. (2) The mid-reaches of the Luanhe River are more prone to drought compared to the upper reaches for its higher water demand. However, due to a stronger capacity for ecological restoration, droughts there are mostly of low intensity in the mid-reaches. In contrast, the upper reaches experience more periods classified as severe or extreme drought, and the drought events encountered are generally more intense than those in the mid-reaches. (3) The method proposed in this study can screen extreme drought events based on outliers in the characteristic values of drought events. Taking the simulation from this study as an illustration, anomalies in drought event characteristic values suggest a potential basin-scale, prolonged extreme drought event in the Luanhe River Basin from June 2038 to July 2042. Proactive drought prevention policies should be formulated for this period. The findings of this study provide guiding significance and practical value for drought assessment, risk management, and policy application in the Luanhe River Basin. This study methodologically combines hydrological model predictions with drought event responses, providing a novel method for predicting basin-scale drought conditions and issuing early warnings for extreme drought events. Full article

Pines (genus Pinus) are a diverse group of conifers widely distributed across the Northern Hemisphere, comprising more than 110 species worldwide. In Europe, pines are a defining component of forests, occupying environments that range from dry Mediterranean lowlands to high-elevation alpine zones. They support a wide spectrum of ecosystem services, from timber and non-wood products to protection, biodiversity, and cultural values. In this review, we bring together ecological traits, silvicultural practices, and management considerations for ten European pine species. This review examines ten major European pine species, including Scots pine (Pinus sylvestris), maritime pine (P. pinaster), stone pine (P. pinea), Aleppo pine (P. halepensis), black pine (P. nigra), mountain pine (P. mugo), Swiss stone pine (P. cembra), Turkish pine (P. brutia), Bosnian pine (P. heldreichii), and Macedonian pine (P. peuce). Together, these species span a wide range of European environments, with Pinus sylvestris showing the broadest distribution. Despite the extensive literature on pine species, information on their ecological, silvicultural, and management attributes remains fragmented across disciplines. To bridge this gap, this review draws on an expert-curated core of scientific and technical literature complemented by a structured literature search adapted from the PRISMA framework, compiling within a single framework their main ecological and silvicultural characteristics, altitudinal range, growth patterns, stand diversity, and management practices and the principal goods and ecosystem services they provide. The comparative analysis highlighted distinct functional groups among European pines, illustrating contrasting adaptive strategies across environmental gradients, with altitudinal distributions ranging from sea level to 2400 m. Mediterranean species, such as P. halepensis, P. pinaster, and P. brutia, generally showed higher drought and fire adaptation, whereas mountain taxa such as P. cembra, P. mugo, and P. heldreichii displayed greater cold tolerance but increased vulnerability due to restricted climatic niches and slow regeneration. Broadly distributed species, such as P. sylvestris and P. nigra, exhibited intermediate ecological strategies, with responses strongly influenced by regional climatic conditions. By integrating evidence on distribution patterns, functional traits, growth patterns, and management practices, this review provides a comparative framework to support adaptive forest management and informed species selection, helping to safeguard forest functions and their associated benefits under ongoing climate change. Full article

Agriculture is the pillar of Ethiopia’s economy, employing over 80% of the population. However, it remains highly vulnerable to the impacts of climate change. Promoting climate-smart agricultural practices is therefore critical. Quinoa (Chenopodium quinoa Willd.), a highly nutritious pseudo-cereal with broad adaptability and efficient water use, presents a promising alternative crop for Ethiopia’s diverse agro-ecologies. Its tolerance to drought and salinity makes it an ideal candidate for enhancing food and nutritional security under changing climate conditions. Therefore, this study aimed to evaluate the GEI for seed yield and yield-related traits and identify the stable and high-yielding genotypes of quinoa across six agro-ecological locations in Ethiopia—Negelle Arsi, Haramaya, Holeta, Kulumsa, Melkassa, and Ziway—representing three agro-climatic classifications (lowland, midland and highland). Thirteen genotypes were studied using a randomized complete block design (RCBD) with three replications. The G × E interaction main effect revealed significant GEI effects, particularly for plant height, days to maturity, and grain yield. Among the tested genotypes, ‘Brightest Brilliant Rainbow’, ‘Salcedo-INIA-Puno-Peru’, and ‘Multi-Hued’ demonstrated superior performance across multiple environments. Stability analyses were performed using the AMMI, ASV, and GGE biplot approaches. The analyses revealed significant variation among the genotypes for both adaptability and stability. The AMMI results indicated that environmental effects contributed more to yield variability than genotypic or interaction effects. The AMMI model identified four promising genotypes: ‘Salcedo-INIA-Puno-Peru’, ‘Brightest Brilliant Rainbow’, ‘Multi-Hued’, and ‘Bio-bio’. According to the ASV, the most stable genotypes were ‘Amarilla Sacaca’, ‘Amarilla Maranganí’, ‘Bio-bio’, ‘Cherry Vanilla’, ‘Multi-Hued’, and ‘Brightest Brilliant Rainbow’. The GGE biplot identified ‘Brightest Brilliant Rainbow’ and the Holeta location as the most ideal genotype and testing environment, respectively. ‘Multi-Hued’ and ‘Brightest Brilliant Rainbow’ emerged as the winning genotypes in the only defined mega-environment. Notably, ‘Brightest Brilliant Rainbow’ exhibited a high protein content, ranging from 14.8% at Kulumsa to 17.8% at Melkassa. Overall, ‘Brightest Brilliant Rainbow’ and ‘Salcedo-INIA-Puno-Peru’ were identified as high-performing, stable genotypes suitable for cultivation across diverse Ethiopian environments. These findings confirm quinoa’s adaptability to the broader agro-ecologies of Ethiopia and enable selection of stable, widely adapted varieties through the G × E interaction and stability analyses using AMMI, ASV, and a GGE biplot. Full article

This study quantifies same-grid-cell, same-date co-occurrence of low precipitation and low operational wind-power density (WPD) in Southwest China during 1979–2018. Daily precipitation and WRF-derived 10 m wind fields were analyzed on a 271 × 271 grid with 10-, 15-, 20-, and 30-day rolling windows. At each grid cell, rolling precipitation totals and rolling means of the daily operational-WPD index were ranked against a fixed seasonal distribution. Low conditions were defined by $u\le 0.1587$, with sensitivity analyses at $u\le 0.10$ and $u\le 0.20$. Low precipitation represented a sub-monthly meteorological-drought condition. Domain compound frequency declined from 2.207% at 10 days to 1.704% at 30 days. Warm-season frequency was highest at every window, ranging from 2.624% to 2.028%. R3 had the highest compound frequency at the central threshold, whereas R5 had the lowest. Under the 1% regional active-area rule, median compound runs lasted three to five days. Spatial-block intervals changed with block size, so the 40-year record does not support a robust domain-wide trend conclusion. The results provide a 1979–2018 climatology of atmospheric precipitation–WPD co-occurrence. Full article

Sorghum (Sorghum bicolor L. Moench) is a major cereal in water-limited environments. Its C₄ carbon-concentrating pathway suppresses photorespiration and supports comparatively high photosynthetic and water-use efficiency at high temperature, although yield remains sensitive to the timing and intensity of drought. This systematic review critically evaluates how coordinated variation in phenology, canopy development, transpiration regulation, photosynthetic resilience and root-mediated water capture can be phenotyped for sorghum improvement. The review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. Eligible primary studies examined sorghum drought physiology, sensing-based phenotyping, trait retrieval, root-associated water capture, or breeding applications. Following duplicate removal and title, abstract and full-text screening, 45 sorghum-specific studies were included. Owing to substantial heterogeneity in experimental design, drought treatment, sensing platform, target trait, and validation metric, evidence was synthesised narratively rather than by meta-analysis. We compare sorghum studies across Light Detection and Ranging (LiDAR), multi-spectral, hyperspectral, thermal, structural, and fluorescence sensing, with emphasis on reported accuracy, transferability and physiological interpretation. We then examine how PROSAIL (PROSPECT coupled with Scattering by Arbitrarily Inclined Leaves) and SCOPE (Soil Canopy Observation, Photochemistry and Energy Fluxes) can be constrained for sorghum canopies and combined with machine learning. The central contribution is a sorghum-specific framework that distinguishes directly observed or model-retrieved canopy traits from indirect root-function predictions requiring ground validation. The synthesis identifies practical routes for measuring functional stay-green, high-vapour-pressure-deficit responses and post-anthesis water capture, while defining priorities for cross-environment validation and breeding deployment. Full article

Sorghum (Sorghum bicolor [L.] Moench) is a nutritious crop widely adapted to grow in arid and semi-arid agro-ecologies, supporting millions of households, and it has the potential to enhance soil health. However, extreme drought and heat stress conditions curtail its yield potential, requiring global efforts to develop drought-tolerant and agronomically superior cultivars. The objective of this paper was to quantitatively assess the impact of drought stress on sorghum genotypes for agronomic and yield-related traits, based on global breeding efforts for drought-tolerant varieties to guide current and future improvement programmes. The study involved a meta-analysis based on 30 selected research papers published around the world that reported on sorghum agronomic and yield-related traits under non-stress (NS) and drought stress (DS) conditions. Data were extracted for the following vital traits: days to 50% flowering (DTF), days to 50% maturity (DTM), plant height (PH), number of tillers (TN), panicle length (PL), panicle width (PW), shoot biomass (SB), root biomass (RB), root-to-shoot biomass ratio (RS), stay green (SG), and grain yield (GY). The sorghum genotypes reported with drought tolerance exhibited a mean GY value of 3.30 t ha⁻¹, ranging from 0.55 to 8.39 t ha⁻¹ under DS conditions. Under NS conditions, the mean GY was 4.38 t ha⁻¹, with the top genotype scoring a GY of 14.1 t ha⁻¹. Drought reduced TN and GY by 42.12% and 27.18%, followed by PW (25.52%) and SB (22.12%)—in that order. The forest plot analysis revealed that drought had a negative effect on the assessed traits, highlighting the need for developing drought-tolerant cultivars. The highest effect sizes were calculated for TN (−1.83), followed by PW (−1.69), and SB (−1.33), whereas PL (−0.1) had the lowest, suggesting that PW and SB are critical for selection in drought-tolerance breeding. Under DS conditions, GY exhibited positive correlations with RS (r = 0.63), RB (r = 0.50), SB (r = 0.27), DTM (r = 0.26), and SG (r = 0.21). The findings of this study could guide future breeding efforts to develop drought-tolerant sorghum varieties. Full article

The potential for species distribution shifts in response to changing climate and altered fire regimes is a pressing concern across ecosystems. Species responses to climate and disturbance are expressed demographically as changes in survivorship and recruitment across gradients. We examined tree recruitment and radial growth response to climate along a biophysical gradient in a mixed-conifer forest in northern New Mexico, USA, in a watershed spanning from near the lower to upper elevation range for ponderosa pine (Pinus ponderosa var. scopulorum Engelm.) and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco). We compared growth responses with climate variables and stand demographic patterns of the six major tree species present, to track shifts in species community composition and dominance. We found significant changes in species composition between mature trees and seedlings and saplings across Elevation–Aspect groups in several species, indicating incipient community change. Drought stress drove patterns of tree growth and species composition shifts at low elevations, while at higher elevations increased stand density following fire exclusion led to success of shade-tolerant species. Altered growth and demographic trends driven by drought and fire exclusion can serve as the mechanism for changing species distributions and community reorganization across landscape climatic gradients. Full article

Climate-change-induced drought can increase domestic water shortage not only by reducing runoff but also by exposing weaknesses in local sources, reservoirs, and wide-area transfer networks. This study simulates domestic water shortage in the Seomjin River water system, South Korea, using the Korea-Water Evaluation and Planning system (K-WEAP), and proposes an integrated eXtreme Gradient Boosting (XGBoost)–Shapley Additive exPlanations (SHAP) framework to diagnose the explanatory factors of the simulated shortage. Representative drought scenarios were selected from an ensemble of climate projections using a dryness score based on precipitation-related extreme climate indices. K-WEAP was used to simulate shortage for eleven administrative districts, and XGBoost (version 3.2.0) models were trained for districts with sufficient shortage samples. SHAP analysis and shortage-event clustering were then applied to identify dominant explanatory factors and recurrent shortage patterns. The XGBoost models reproduced the simulated shortage rates well, with test R² values exceeding 0.91. Wide-area water supply was the dominant explanatory factor in three inland districts, whereas reservoir supply was more influential in the southern coastal district. The dependence analysis revealed threshold-type responses, in which shortage risk increased sharply once key supply variables fell below district-specific critical ranges. The results indicate that domestic water shortage is governed by district-specific supply pathways and threshold-type system responses rather than by uniform basin-wide drought effects. Full article

Understanding the spatiotemporal dynamics of dominant desert-steppe species under climate change is critical for sustainable management of arid ecosystems. Sophora alopecuroides L., a perennial drought-tolerant leguminous herb with substantial medicinal and forage value, is an important component of these ecosystems. Based on 137 occurrence records and 10 environmental variables, we applied the MaxEnt model and ArcGIS to simulate suitable habitats and range shifts of S. alopecuroides across multiple periods, including the Last Interglacial (LIG), Last Glacial Maximum (LGM), Mid-Holocene (MH), present, and the 2050s and 2070s under four representative concentration pathways (RCP 2.6, 4.5, 6.0, and 8.5). The model showed high predictive performance, with an area under the receiver operating characteristic curve (AUC) greater than 0.9. Temperature annual range (Bio7), elevation, precipitation of the warmest quarter (Bio18), mean temperature of the driest quarter (Bio9), and annual mean temperature (Bio1) were identified as key environmental drivers, indicating that the distribution of this species is mainly shaped by temperature regimes, seasonal water availability, and topography. Under current conditions, the total suitable habitat accounts for 28.9% of China’s territory, closely matching the known distribution. Since the LIG, the total suitable area has fluctuated slightly, being larger during the LIG and LGM, smaller during the MH, and close to the present level thereafter. The distribution centroid remained within the Jinta Basin of the Hexi Corridor, Gansu Province, with only limited displacement from the LIG to the present, suggesting that this area, together with the Tianshan–Junggar Basin margins and the Alxa Plateau–Helan Mountain region, constitute key topographically and climatically inferred potential refugial areas for S. alopecuroides. Future projections indicate that suitable habitat may expand slightly under low-emission scenarios but contract under medium- to high-emission scenarios, with centroid shifts varying among pathways. These findings highlight the potential importance of such bioclimatically inferred putative refugia in maintaining the distribution of dominant dryland herbs and provide a spatially explicit basis for monitoring, germplasm conservation, and adaptive management of S. alopecuroides under ongoing climate change. Full article

The RING-type E3 ubiquitin ligase plays a significant role in plant responses and adaptations to abiotic stresses such as drought. However, few studies have explored the role of E3 ubiquitin ligases in potato drought stress, especially DRIP1. In this study, 172 StHCa genes were identified across the potato genome. These genes were unevenly distributed on twelve chromosomes and divided into six subclades (group I–VI). The molecular weight of potato HCa proteins ranges from 5445.38 to 143,293.69 Da. More than half of them are acidic proteins and most are unstable. There are 161 hydrophilic proteins, and the subcellular localization analysis indicated that they were mainly located in the nucleus. The co-linearity analysis of StHCa genes showed that 172 genes underwent 40 tandem duplications and 28 segmental duplication events. Potato and tomato share a recent common ancestor and exhibit highly similar evolutionary trajectories. Promoter sequence analysis of the StHCa family identified abundant cis-acting elements associated with light signal transduction, hormone responses, plant growth and development, and abiotic stress responses. These results suggest that the StHCa genes may play important regulatory roles in different environmental signals and developmental stages. Expression profiling revealed that StDRIP1 exhibited higher transcript levels in potato roots than in stems and leaves, and its expression was significantly induced by drought stress. Physiological phenotyping demonstrated that StDRIP1-overexpressing (OE) plants displayed reduced root growth compared with wild-type (WT) plants, with decreases in root length, total root area, total root volume, and root vitality. Under 20% PEG-6000-simulated drought stress, the root expression level of StDRIP1 was higher in OE lines than in WT plants. Furthermore, StDRIP1 overexpression suppressed the activities of antioxidant enzymes (POD, CAT, and SOD) and weakened their osmotic adjustment ability by reducing proline (Pro) accumulation. At the late stage of stress treatment (9 h), the SOD, POD, and CAT activities of OE plants were 5.0%, 19.9%, and 25.1% lower than those of WT plants, respectively. These physiological alterations exacerbated oxidative damage, as evidenced by increased malondialdehyde (MDA) content and elevated electrolyte leakage in OE plants. In summary, this study comprehensively characterized the StHCa gene family in potato, providing a valuable theoretical basis for elucidating the functional mechanism of StDRIP1 in modulating drought stress responses. Collectively, StDRIP1 acts as a negative regulator of potato drought tolerance through two primary mechanisms: (1) repressing root growth and weakening root vitality, thereby reducing the water absorption capacity of roots; and (2) diminishing antioxidant enzyme activities and impairing osmotic homeostasis, which further exacerbates oxidative damage under drought stress. Full article