Search Results (211)

Peatlands, critical global carbon sinks, are facing increasing threats from climate change-driven heatwaves and droughts. These threats can cause a midday depression in carbon uptake through photosynthetic inhibition. Using high-temporal-resolution solar-induced chlorophyll fluorescence (SIF; ~30 s) and chamber-based CO₂ flux measurements, we investigated the coupling between SIF and gross primary production (GPP) during extreme events (air temperature > 25 °C and vapour pressure deficit > 15 hPa) in a northern peatland. Our results show that SIF tracks GPP closely under non-stress conditions (daily R² = 0.86–0.96). However, during combined heat and drought stress, midday correlations collapsed (Case A: R² = 0.04 on 27 June; Case B: R² = 0.15 and 0.01 on 29 and 30 June, respectively), indicating severe decoupling. Importantly, we discovered legacy effects from multi-day heat exposure: on 26 June, vegetation with prior cumulative stress (Case A) showed weak morning coupling (R² = 0.07), while vegetation without prior stress history (Case B) maintained strong coupling (R² = 0.93). This suggests that cumulative stress alters baseline physiology and can exacerbate midday mismatches; therefore, not just current condition controls photosynthetic regulation. These findings highlight limitations of SIF-based GPP estimation at sub-daily timescales during stress, particularly in heterogeneous peatland systems where canopy composition and physiological responses could vary among plant functional types. Full article

Purple celery (Apium graveolens L.) is a high-value functional vegetable rich in anthocyanins, but achieving a balanced optimization between biomass accumulation and nutritional quality in plant factories remains challenging due to species-specific spectral trade-offs, and current research lacks integrated light recipes that simultaneously optimize photosynthetic efficiency, antioxidant defenses, and functional quality while suppressing nitrate accumulation. This study evaluated five LED treatments over 30 days: white light (CK), monochromatic red (R), and red-to-blue photon flux density ratios of 5:5, 7:3, and 8:2. Red light induced stem elongation but suppressed root development. Conversely, 8R2B delivered the best performance, significantly elevating leaf, petiole, root, and total fresh biomass and increasing total dry weight by 68.8% over CK. It also markedly enhanced chlorophyll a, b, total chlorophyll, and carotenoids, as well as improved PSII quantum yield (YII), photochemical quenching (qP), and electron transport rate (ETR), while reducing non-photochemical heat dissipation (NPQ) by 61.0%, indicating superior light-use efficiency. Furthermore, 8R2B upregulated CAT and POD activities promoted soluble sugars (up 688.4% in leaves), soluble proteins, and ascorbic acid accumulation, yet reduced leaf nitrate by 28.5%. Principal component analysis confirmed 8R2B as the most effective formulation across all growth, photochemical, defense, and quality traits. These findings provide a novel, evidence-based 8:2 red-to-blue LED light recipe for high-yield, high-quality, and commercially viable purple celery production in controlled environment agriculture. Full article

Flooding during the rice (Oryza sativa L.) jointing stage threatens yield stability in regions with concentrated rainfall and limited drainage. However, the extent to which the water regime before flooding modifies rice growth and yield formation remains poorly understood. A pot experiment was conducted over two years to compare controlled irrigation (CI) with conventional flooding irrigation (CF) across three flooding depths and two durations imposed at the jointing stage. Flooding increased tiller number, plant height, and total leaf area, but reduced net photosynthetic rate and grain yield. Yield loss increased with flooding depth and duration. Under corresponding flooding treatments, CI moderated vegetative expansion and maintained a higher net photosynthetic rate, greater root dry matter, and a higher root-to-shoot ratio than CF. Relative to the corresponding non-flooded controls, yield loss ranged from 4.11% to 39.33% under CI and from 5.63% to 52.50% under CF. The lower yield loss under CI was associated with greater effective panicle number, higher seed setting rate, and better maintenance of photosynthetic activity and root biomass. These findings indicate that the water regime before flooding can influence biomass allocation and yield formation during the jointing stage flooding. Controlled irrigation combined with timely drainage may help reduce yield risk in rice systems exposed to temporary flooding. Full article

Solar-induced chlorophyll fluorescence (SIF) provides a direct proxy for vegetation photosynthesis-related information; however, under stress conditions, its relationship with photosynthesis should be interpreted together with absorbed photosynthetically active radiation by chlorophyll (APAR_chl) and non-photochemical quenching (NPQ). This study presents a conceptual design of a compact dual-channel airborne imaging spectrometer for synchronous observation of SIF-related spectral radiance and broadband vegetation-canopy spectral reflectance (BR). A self-collimating shared-optical-path configuration is proposed to reduce the system volume, yielding a simulated optical envelope of 205 × 150 × 120 mm³. Optical simulations predict spectral resolutions better than 0.3 nm over 670–780 nm for the SIF channel and better than 2 nm over 400–780 nm for the BR channel. An asymmetric double Babinet depolarizer is incorporated to reduce polarization-related errors, and the simulated system polarization sensitivity is below 1%. The calculated stray-light ratios of the SIF and BR channels are 0.553% and 0.287%, respectively. LightTools was used to simulate the radiative transfer performance of the instrument under realistic scenes. Furthermore, an end-to-end SIF retrieval simulation was performed to evaluate the retrieval capability of the proposed system. The results indicate that the proposed concept is theoretically feasible and may support future quantitative SIF retrieval and the interpretation of vegetation photosynthetic and stress-related processes. Full article

Microbial inoculants such as Trichoderma have been proposed as sustainable tools to improve seedling quality in coffee nurseries; however, their effectiveness may vary according to formulation and genotype. This study evaluated three treatments: a solid Trichoderma formulation (1 kg m⁻³ of substrate) based on a multispecies consortium (T. harzianum, T. asperellum, and T. viride; 5 × 10⁹ conidia g⁻¹), a liquid formulation of T. harzianum (1 × 10⁸ CFU mL⁻¹; 1 L m⁻³ of substrate), and a non-inoculated control, using three Coffea arabica varieties (Catimor, Marsellesa, and Gran Colombia) under controlled nursery conditions. A linear mixed model was applied, considering variety and inoculant type as fixed effects and replicates as random effects. The results show that the biostimulant response is strongly modulated by the variety × inoculant interaction. The solid formulation was superior in promoting the expansion of the photosynthetic apparatus, increasing leaf area by 24.6%. In turn, the liquid formulation optimized structural vigor, increasing stem diameter by 17.3% and reducing slenderness by 13.1%. Inoculation reduced the lignification index by 10.4%, favoring dynamic vegetative growth. These improvements were integrated into the Dickson Quality Index, which reached values of 0.41–0.70, greatly exceeding the critical threshold of 0.20 for medium- to high-quality seedlings. It is concluded that Trichoderma acts as a physiological compensator that harmonizes plant architecture, although its efficacy depends on specific compatibility with the genotype, which is essential for ensuring the successful establishment of coffee plants under field conditions. Full article

Leaf nitrogen content (LNC) is an important physiological indicator for evaluating citrus nutritional status, photosynthetic capacity, and fertilization demand. However, conventional LNC determination mainly relies on field sampling and laboratory chemical analysis, which are destructive, time-consuming, labor-intensive, and limited in spatial continuity, making them unsuitable for large-scale real-time nitrogen monitoring in complex orchard environments. To achieve rapid and non-destructive estimation of citrus LNC, this study developed a UAV multispectral inversion framework integrating object-based canopy extraction and machine learning models. Field experiments were conducted in a citrus orchard in western Hubei Province, China. Multi-temporal UAV multispectral images were collected from April to October 2025, and ground measurements of citrus LNC were collected simultaneously. First, minimum distance classification (MDC), maximum likelihood classification (MLC), and object-based image analysis (OBIA) were used for land-cover classification of citrus orchard images, and their canopy extraction performance under complex orchard backgrounds was compared. Subsequently, multiple vegetation indices were calculated from the extracted citrus canopy spectra, and sensitive spectral features were selected through correlation analysis. Finally, seven models, including simple linear regression, quadratic regression, partial least squares regression (PLS), back propagation neural network (BP), extreme learning machine (ELM), particle swarm optimization-extreme learning machine (PSO-ELM), and particle swarm optimization-back propagation neural network (PSO-BP), were constructed to systematically evaluate the inversion performance of citrus LNC across the entire growth period. The results showed that: (1) OBIA achieved higher classification accuracy and temporal stability in citrus orchard land-cover classification, with overall accuracy ranging from 68.86% to 85.65% and Kappa coefficients ranging from 0.56 to 0.72, outperforming MDC and MLC. This indicates that OBIA can effectively reduce the interference of bare soil, grass, shadows, and other non-target objects on canopy spectral extraction. (2) The correlations between vegetation indices and LNC varied markedly among different growth stages, suggesting that the spectral response of citrus LNC has strong phenological dependence and that a single vegetation index is insufficient to stably characterize LNC variation across the whole growth period. (3) At the whole-growth-period scale, multi-index fusion models outperformed single-index models, among which EVI, TVI, and MTVI showed relatively strong cross-stage sensitivity. (4) Optimized machine learning models generally outperformed traditional regression models and unoptimized machine learning models. Among them, PSO-BP achieved the best performance, with a validation R² of 0.68 and an RMSE of 1.54 g kg⁻¹, representing an increase in R² of 23.64% compared with the PLS model and 25.93% over the baseline BP model in terms of R². Overall, this study demonstrates that OBIA-based canopy spectral quality improvement combined with PSO-optimized machine learning can effectively improve the stability and reliability of UAV multispectral estimation of citrus LNC under complex orchard backgrounds. The proposed framework provides technical support for citrus nitrogen diagnosis, precision fertilization, and intelligent orchard management. Full article

UK forestry faces increasing drought risk under climate change, raising concerns about the resilience of Sitka spruce, the UK’s dominant commercial conifer. This study assessed whether hyperspectral vegetation indices can detect intraspecific drought responses to support resilience screening. An eight-week controlled drought experiment was conducted on 60 grafted Sitka spruce trees representing six clonal groups from the UK breeding population. Needle-level hyperspectral reflectance was used to derive vegetation indices associated with chlorophyll status, photoprotective pigments, and water content, alongside chlorophyll fluorescence (Fv/Fm). Pigment-based and red-edge indices showed the strongest sensitivity to drought, with ARI1 increasing by up to 1.2 under drought relative to controls, while water-related indices captured later-stage hydraulic decline. Clonal variation was detected in the timing and magnitude of pigment regulation, water loss, and photosynthetic impairment, indicating contrasting drought-response trajectories among clones. These results demonstrate that hyperspectral approaches enable rapid, non-destructive detection of physiologically meaningful drought responses and can support the identification of drought-resilient genotypes for climate-adaptive forest management. Full article

Plant communities in reservoir drawdown zones experience highly altered hydrological regimes, and responses of locally dominant species shape the biodiversity and restoration trajectories of these artificial wetlands. The water-level fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR) is exposed to alternating flooding and drought, which strongly constrains both its vegetation and the biodiversity that depends on it. Cynodon dactylon dominates the herbaceous cover of the TGR WLFZ, but evidence on its stress responses remains fragmented across single-site studies. Following a PRISMA 2020 literature search and screening procedure, we synthesized 169 effect sizes from 12 qualifying experimental studies, covering biomass and morphological traits, photosynthetic gas-exchange parameters, chlorophyll content, and oxidative-stress indicators. Effect sizes were calculated as natural log response ratios (lnRR) and pooled with random-effects models; shallow and deep flooding were compared using subgroup analyses with bootstrap 95% confidence intervals. Flooding effects varied with water depth. Shallow flooding increased total biomass (+47.2%), whereas deep flooding reduced plant height (−46.5%) and root length (−22.3%). Plant height showed significant between-group heterogeneity (Q_between = 5.60, p = 0.045), indicating sensitivity to submergence depth. Flooding also increased malondialdehyde content (MDA) by 31.7%, whereas peroxidase activity (POD), superoxide dismutase activity (SOD), and photosynthetic gas-exchange parameters showed no consistent responses. Drought effects on total biomass, plant height, and total chlorophyll were non-significant, although inference was limited by a few drought-related entries. Deep flooding, therefore, appears to be a stronger constraint than drought for Cynodon dactylon in the TGR WLFZ, mainly through morphological suppression and increased oxidative damage. Given the dominant role of this species in the herbaceous layer, its depth-dependent decline is relevant both for biodiversity conservation in this artificial wetland and for elevation-based restoration planning. Full article

In rocky mountainous regions characterized by shallow, barren soils and water scarcity, non-rainfall water, such as condensation, plays a crucial ecological role in mitigating seasonal drought in forest trees. To enhance the water-use capacity of vegetation, this study utilized a previously developed eco-friendly PVA–CS/SA–Ca²⁺ hydrogel. The primary objective was to elucidate the synergistic mechanisms by which the hydrogel optimizes condensed water utilization and drives the ecophysiological recovery of Pinus tabuliformis and Platycladus orientalis, two keystone afforestation species in northern China. Utilizing a controlled environmental chamber to simulate the condensation and humidification process, the experiment established three treatments: a control group (CK), a pot-sealed group (PS, to isolate soil water absorption), and a hydrogel-amended group (Hydrogel-Root Wrapping, HRW). To comprehensively evaluate the water utilization mechanisms, the amount of condensed water captured by the system was quantified, and hydrogen isotope tracing techniques were employed to precisely track water transport pathways and contribution rates. Concurrently, key physiological parameters were systematically determined, including leaf water potential, stomatal conductance, leaf water content, net photosynthetic rate, and transpiration rate. The results demonstrated the following: (1) the hydrogel significantly enhanced the condensation water capture capacity of the system. The net mass gains of the Pinus tabuliformis and Platycladus orientalis systems under the HRW treatment reached 26.3 g and 32.9 g, respectively, which represented 1.17 and 1.30 times those of the CK treatment, and 1.52 and 1.54 times those of the PS treatment. (2) Isotope tracing confirmed that both tree species possess significant Foliar Water Uptake (FWU) capacity. Following condensation, the δ²H values in the leaves of Platycladus orientalis and Pinus tabuliformis surged to 113.5‰ and 85.3‰, respectively, with stem δ²H values increasing by 31‰ and 22‰ compared to their initial baseline. (3) The introduction of the hydrogel in the HRW treatment provided 11.2% and 10.9% of the stem water supply for Platycladus orientalis and Pinus tabuliformis, respectively, thereby reducing their dependence on soil water by 8.3% and 13.1%. In contrast, there was no significant difference in the fractional contribution of condensation water to stem water between the PS and CK treatments. (4) Regarding physiological responses, the application of the hydrogel material effectively improved the physiological status of the plants. The leaf water potentials of Pinus tabuliformis and Platycladus orientalis increased to −0.15 MPa and −1.32 MPa, respectively. Concurrently, stomatal conductance (3.25 and 3.64 mm·s⁻¹) and leaf water content (58.4% and 67.4%) were significantly higher than those in the other treatments. In summary, the hydrogel can significantly enhance the capture, conversion, and utilization efficiency of condensation water by vegetation, effectively optimizing the water supply dynamics of the system. This provides key theoretical and technical support for ecological afforestation in difficult sites within rocky mountainous areas. Full article

Protein turnover is essential for cellular metabolism, organelle biogenesis, stress adaptation, and ultimately the viability of cells and tissues. Papain-like cysteine proteases (PLCPs) are one of the vital components in protein degradation. PLCPs have been reported to act in senescence-associated proteolysis, but their roles in vegetative growth remain unclear. We identified PtCP1, an AALP-like PLCP in Populus tomentosa, localized to the vacuole and acid-triggered activated. CRISPR/Cas9-generated loss-of-function mutant (d7) showed dwarfism and non-stomatal photosynthetic limitations. On the other hand, the gain-of-function line (EM, deleted ERFNIN domain) exhibited accelerated growth and enhanced photosynthetic parameters. We showed d7 had the accumulation of Rubisco, which was the most important protein in photosynthetic carbon fixation. Transcriptomics revealed dysregulated carbon metabolism in d7. This data supported PtCP1-mediated proteolysis regulated photosynthetic carbon assimilation via altered Rubisco turnover, and then it increased the biomass accumulation during vegetative growth in woody plants. Full article

The increasing frequency of high-temperature episodes associated with climate change poses challenges to crop productivity. Stress priming could help to mitigate these effects, with the capacity to enhance plant resilience through metabolic adjustments and memory mechanisms. We evaluated the efficacy of the Stress Memory Encoder biofertilizer (SME, TIMAC Agro) as a seed treatment to induce heat stress (HS) memory in soybean plants [Glycine max (L.) Merrill]. In Experiment 1, plants with SME (0, 2, and 4 mL kg⁻¹) were exposed to HS (35 °C for 48 h) at V3 and V6 vegetative stages. The 4 mL kg⁻¹ dose at V6 under HS consistently improved photosynthetic traits and reductions in reactive oxygen species and lipid peroxidation. Non-enzymatic antioxidants were detected to this dose at V3. Multivariate analysis revealed patterns consistent with dose-dependent physiological adjustments and potential memory acquisition. In Experiment 2, plants treated with SME were exposed to HS (34 °C for 48 h) consecutively (V3 + V6). The SME-primed plants had a higher expression of transcript factors and genes related to HS. Overall, the findings indicate that SME may act as a priming agent capable of inducing somatic memory and enhancing adaptive responses to HS in soybean. Full article

Agronomic biofortification offers an environmentally friendly way to improve crop nutrition. The biofortification of vegetables with iodine has attracted increasing attention due to its significance for human health. Hydrogen sulphide (H₂S) is a gaseous signalling molecule that affects many physiological and biochemical processes in plants. Lettuce (Lactuca sativa L.) plants were cultivated under controlled greenhouse conditions. Foliar applications of potassium iodate (KIO₃) and hydrogen sulphide (H₂S, supplied by sodium hydrosulphide (NaHS)) were applied separately and together (H₂S + KIO₃). Evaluations included growth parameters, photosynthetic pigments, biochemical metabolites, antioxidant enzyme activities, plant hormone levels, and mineral nutrient contents. All treatments resulted in significant changes in plant growth and physiological traits compared to the control. The combined application resulted in greater responses across several parameters; however, these observations do not demonstrate a causal or mechanistic interaction between the treatments. The combined application increased plant fresh weight by ~42% and leaf area by ~35% compared to the control. Total chlorophyll content approximately doubled (≈100% increase), while SOD, POD, and CAT activities increased by up to ~160%, ~13%, and ~40%, respectively. Proline and sucrose contents increased by approximately 100% and 85%. Hormonal changes included increases in indole-3-acetic acid (~44%) and cytokinins (~55%), and a decrease in abscisic acid (~20%). In addition, several macro- and micronutrients in leaves and roots were affected by the treatments. The combined application of KIO₃ and H₂S was associated with greater responses across several measured parameters than either compound alone; however, these observations do not demonstrate a causal or mechanistic interaction between the two compounds. Furthermore, as the experiment was conducted under non-stress greenhouse conditions, the observed physiological responses should be interpreted as changes in metabolic and regulatory processes rather than direct evidence of enhanced stress tolerance. Overall, the results indicate that foliar application of KIO₃ and H₂S can influence growth and physiological traits of lettuce under controlled conditions. Full article

Artificial lighting is a central and resource-intensive component of controlled environment agriculture, directly regulating plant physiological processes while influencing energy efficiency and production outcomes. Chlorophyll fluorescence analysis, particularly pulse-amplitude-modulated fluorometry, provides a rapid and non-destructive method for assessing plants’ photosynthetic efficiency. However, the extent to which chlorophyll fluorescence reflects plant responses to different light spectra across species remains insufficiently understood. In this study, species-specific photoresponses of leafy vegetables (Amaranthus tricolor, Barbarea verna, Chrysanthemum coronarium, Perilla frutescens) to different light spectra were investigated by integrating chlorophyll fluorescence with growth, antioxidant, and pigment traits. Plants were cultivated under monochromatic red, blue, and combined red–blue light, with additional far-red supplementation. Correlation analysis was performed among growth, antioxidant parameters, pigment contents, and chlorophyll fluorescence parameters. The obtained results show that chlorophyll fluorescence parameters respond selectively, but species-specifically, to applied lighting-spectrum conditions. Relationships between fluorescence indices and physiological traits varied between species, and no single parameter consistently reflected plant performance across all crops. Therefore, to employ chlorophyll fluorescence as a useful proxy for assessing plant responses to lighting spectrum, a species-specific and context-dependent approach is required. Full article

Subalpine grasslands represent highly sensitive ecosystems that are increasingly exposed to climate extremes, yet their long-term disturbance dynamics remain poorly documented. This study investigates climate-driven dieback of subalpine grasslands in Central Europe using a harmonized, multi-decadal satellite time series. We analyzed Landsat (TM, ETM+, OLI, OLI-2) and Sentinel-2 imagery spanning 1984–2024 to detect changes in grassland condition, supported by field-based validation, climatic indices, and geomorphological analysis. Several spectral indices related to non-photosynthetic vegetation were evaluated, with the Normalized Burn Ratio (NBR) providing the best discrimination of dead grassland. In spatially grouped cross-validation, NBR achieved very high accuracy for dead versus non-dead grassland, with AUC = 0.9996, precision = 1.00, recall = 0.82, and F1-score = 0.90 for Sentinel-2, and AUC = 0.9982, precision = 1.00, recall = 0.62, and F1-score = 0.76 for Landsat 9. Retrospective mapping revealed four dieback events since 2000: two short-term episodes with rapid within-season recovery (2000, 2003) and two long-term events characterized by persistent degradation and slow regeneration (2012, late 2018–2019). The largest short-term event, in 2003, affected 42.19 ha of total dieback and 96.95 ha including partially damaged or regenerating grassland. Dieback extent was negatively associated with water balance deficit, strongest for SPEI-12 (ρ = −0.548, p = 0.002), while winter frost under shallow-soil conditions likely contributed to long-term damage in 2012. Geomorphological analysis indicated that elevation, terrain curvature, and, to a lesser extent, wind exposure are the primary controls on dieback susceptibility, highlighting the importance of fine-scale environmental controls. Our results demonstrate the value of long-term, multi-sensor satellite observations for detecting and interpreting climate-driven disturbances in subalpine grasslands and provide a transferable framework to support monitoring and conservation of mountain ecosystems under ongoing climate change. Full article

Nitrogen (N) and phosphorus (P) are essential nutrients that play critical roles in plant physiological processes and the accumulation of N and P in broccoli head was significantly correlated with yield. Therefore, there is a need for a rapid, non-destructive diagnosis of crop status by detecting deficiencies in essential nutrients. This study evaluated the effects of N and P deficiency on field grown broccoli (Brassica oleracea L. var. italica Plenk) using a plant-induced electrical signal (PIES) sensor, in which needle electrodes are inserted into the stem to measure electrical conductivity reflecting plant water and ion status. Four treatments were established, including the control (N100P100) with sufficient N and P supply, N deficiency (N0P100), P deficiency (N100P0), and combined N–P deficiency (N0P0). For sufficient supply, urea and fused phosphate (FP) were applied at rates of 122 kg N ha⁻¹ and 71 kg P ha⁻¹, respectively. Soil, stem, and leaf nutrient contents, growth parameters, and stress related indicators were analyzed and their relationship with PIES values were evaluated. PIES was highest in control (N100P100) and lowest under N–P deficiency (N0P0). Higher PIES values were observed during the vegetative stage, whereas values declined during the reproductive stage, reflecting changes in physiological activity. Growth parameters such as shoot and root weight and stem diameter were generally superior in the control (N100P100) treatment, while leaf calcium (Ca), magnesium (Mg), and potassium (K) concentrations showed no significant differences among treatments. Total N content in leaves was higher in N fertilized treatments (control and P deficiency). Photosynthesis-related parameters, including soil plant analysis development (SPAD), Fv/Fm, and chlorophyll content, were lowest under N–P deficiency, which was reflected in the PIES. Principal component analysis (PCA) showed that the PIES was closely associated with growth and photosynthetic parameters and clearly distinguished N sufficient treatments (control and P deficiency) from N deficient treatments (N0P100, N0P0). Overall, these findings suggest that PIES monitoring can serve as a sensitive physiological indicator of nutrient stress and may be applied as an early diagnostic tool before visible growth inhibition occurs in broccoli cultivation. Full article