Search Results (2,119)

The canopy temperature of winter jujube serves as a direct indicator of plant water status and transpiration efficiency, making its accurate prediction a critical prerequisite for effective water management and optimized growth conditions in greenhouse environments. This study developed a data-driven model to forecast canopy temperature. The model serially integrates a Long Short-Term Memory (LSTM) network and a Random Forest (RF) algorithm, leveraging their complementary strengths in capturing temporal dependencies and robust nonlinear fitting. A three-stage framework comprising temporal feature extraction, multi-source feature fusion, and direct prediction was implemented to enable reliable nowcasting. Data acquisition and preprocessing were tailored to the greenhouse environment, involving multi-sensor data and thermal imagery processed with Robust Principal Component Analysis (RPCA) for dimensionality reduction. Key environmental variables were selected through Spearman correlation analysis. Experimental results demonstrated that the proposed LSTM–RF model achieved superior performance, with a determination coefficient (R²) of 0.974, mean absolute error (MAE) of 0.844 °C, and root mean square error (RMSE) of 1.155 °C, outperforming benchmark models including standalone LSTM, RF, Transformer, and TimesNet. SHAP (SHapley Additive exPlanations)-based interpretability analysis further quantified the influence of key factors, including the “thermodynamic state of air” driver group and latent temporal features, offering actionable insights for irrigation management. The model establishes a reliable, interpretable foundation for real-time water stress monitoring and precision irrigation control in protected winter jujube production systems. Full article

Drought stress and insecticide exposure are two significant environmental factors that can impact the physiology and behaviour of aphids, a major agricultural pest. An understanding of the mechanisms of green peach aphids’ response to insecticides under drought stress is a critical area of research that needs urgent attention. In view of this, we conducted this study to determine the impact of drought and insecticides on the activity of detoxification enzymes in green peach aphid. A 2 × 2 × 3 factorial experiment involving two levels of water treatments (drought and no drought), two levels of aphids infestation (aphids and no aphids), and three levels of pesticides applications (thiacloprid, flonicamid and no pesticide) was conducted. The treatments were arranged in a randomized complete block design with three replications. The results showed that there was a significant (p < 0.01) interaction effect of drought × insecticides on the green peach aphid performance under drought or no drought conditions. Generally, the highest aphids host acceptance, survival rate, colonization success, and average daily reproduction under drought and well-watered conditions occurred on flonicamid-treated plants, whereas thiacloprid-treated plants had the least. However, the thiacloprid-treated plants had higher photosynthetic rate, water use efficiency, lower stomatal conductance, and decreased transpiration rate. Moreover, flonicamid treatment increased the accumulation of glutathione–S-transferase, acetylcholinesterase, butyrylcholinesterase, 1-napthyle acetate, and 1-napthyle butyrate activities in aphids, compared to the thiacloprid treatments. The thiacloprid pesticide, which demonstrated higher efficacy against green peach aphid, can be used in areas where green peach aphids and drought stress are major concerns. Full article

Hyperspectral imaging (HSI) is a noncontact camera-based technique that enables deep learning models to learn various plant conditions by detecting light reflectance under illumination. In this study, we investigated the effects of four light sources—halogen (HAL), incandescent (INC), fluorescent (FLU), and light-emitting diodes (LED)—on the quality of spectral images and the vase life (VL) of cut roses, which are vulnerable to abiotic stresses. Cut roses ‘All For Love’ and ‘White Beauty’ were used to compare cultivar-specific visible reflectance characteristics associated with contrasting petal pigmentation. HSI was performed at four time points, yielding 640 images per light source from 40 cut roses. The results revealed that the light source strongly affected both the image quality (mAP@0.5 60–80%) and VL (0–3 d) of cut roses. The HAL lamp produced high-quality spectral images across wavelengths (WL) ranging from 480 to 900 nm and yielded the highest object detection performance (ODP), reaching mAP@0.5 of 85% in ‘All For Love’ and 83% in ‘White Beauty’ with the YOLOv11x models. However, it increased petal temperature by 2.7–3 °C, thereby stimulating leaf transpiration and consequently shortening the VL of the flowers by 1–2.5 d. In contrast, INC produced unclear images with low spectral signals throughout the WL and consequently resulted in lower ODP, with mAP@0.5 of 74% and 69% in ‘All For Love’ and ‘White Beauty’, respectively. The INC only slightly increased petal temperature (1.2–1.3 °C) and shortened the VL by 1 d in the both cultivars. Although FLU and LED had only minor effects on petal temperature and VL, these illuminations generated transient spectral peaks in the WL range of 480–620 nm, resulting in decreased ODP (mAP@0.5 60–75%). Our results revealed that HAL provided reliable, high-quality spectral image data and high object detection accuracy, but simultaneously had negative effects on flower quality. Our findings suggest an alternative two-phase approach for illumination applications that uses HAL during the initial exploration of spectra corresponding to specific symptoms of interest, followed by LED for routine plant monitoring. Optimizing illumination in HSI will improve the accuracy of deep learning-based prediction and thereby contribute to the development of an automated quality sorting system that is urgently required in the cut flower industry. Full article

Drought events intensified by climate change severely compromise the physiological stability and productivity of Coffea arabica, particularly in rainfed systems, underscoring the need to identify cultivars with greater functional resilience. This study evaluated the physiological, nutritional and biochemical responses of seedlings from ten cultivars subjected to adequate irrigation (AW), severe water deficit (SWD) and rehydration (RI). Water potential, gas exchange, oxidative stress markers, stomatal traits and foliar macro- and micronutrients were quantified. Most cultivars exhibited pronounced reductions in the pre-dawn leaf water potential (Ψ_pd), photosynthesis (A), stomatal conductance (g_s) and transpiration (E), together with increases in oxidative stress indicators under SWD. In contrast, Obatá amarillo, Castillo, and Arará maintained greater hydraulic stability, more efficient stomatal regulation, higher water-use efficiency, and lower oxidative stress, accompanied by a more effective post-stress recovery after RI. Regarding nutrient dynamics, Geisha, Castillo, and Arará showed higher K⁺ accumulation, while Catimor bolo presented elevated Ca²⁺, P, and Fe²⁺ contents, elements associated with metabolic reactivation and structural recovery after stress. Geisha and Marsellesa displayed an adaptive, recovery-driven resilience strategy following drought stress. Overall, the findings identify Obatá amarillo, Castillo, and Arará as the most drought-tolerant cultivars, highlighting their potential relevance for breeding programs aimed at improving drought resilience in coffee. Full article

Biochar is recognized for its ability to improve the chemical, physical, and biological properties of soil, thereby enhancing crop productivity. However, the effects of biochar on photosynthetic and transpiration traits in rice crop–soil systems, particularly through the lens of on-site data subjected to Box–Cox transformation, remain insufficiently explored. To address this, a two-factor randomized block design experiment was conducted using the rice cultivar Nangeng 9108 at the Agricultural Meteorology Experimental Station of Nanjing University of Information Science and Technology over the 2022–2023 principle phenophases. This study investigated changes in leaf stomatal conductance, photosynthetic, transpiration, and water-use efficiency (WUE) parameters under combined applications of biochar (0, 15, and 30 t/ha) and nitrogen fertilizer (0, 180, 225, and 300 kg/ha). Application of the Box–Cox transformation substantially improved data normality and variance homogeneity, enabling the development of a robust predictive model linking net photosynthetic rate to environmental factors. A two-way ANOVA further revealed that both the high nitrogen (300 kg/ha) with high biochar (30 t/ha) treatment and the conventional nitrogen (225 kg/ha) with moderate biochar (15 t/ha) treatment significantly enhanced rice photosynthetic and transpiration performance. Of particular note, the N225B15 treatment, which showed a net photosynthetic rate increase from 9.52% to 19.01%, and transpiration rate increase from 11.49% to 28.43%, is recommended as an optimal fertilization strategy for sustainable rice production. These results underscore the synergistic role of moderate biochar and nitrogen inputs in improving key physiological traits of rice, supporting higher crop yields. Full article

Silicon (Si) application is recognized for its beneficial roles in crop growth. This study examines the effects of two forms: zeolite and sodium metasilicate (SMS), on rice under hydroponic (EP I) and soil (EP II) conditions. Four treatments were used at the early stage of rice: 4 ppm and 2 ppm of Si from zeolite, 4 ppm of Si from SMS, and a control. In EP I, only 4 ppm of SMS significantly improved root traits: total root length (36%), surface area (34%), root volume (23%), tips (46%), and forks (34%) by day seven compared to the control. Zeolite-based Si had minimal effects, except on the average diameter. However, in EP II, all Si forms enhanced root traits: total root length (50–73%), surface area (51–58%), average diameter (32–50%), root volume (54–72%), tips (29–68%) and increased shoot and root dry weights by 19–24% and 79–106%, respectively, compared to the control. In EP II, starting from the first and fifth day of treatment, the Si applied groups showed a significant increase in photosynthetic traits and vegetative indices, respectively. On the last day of treatment, particularly for 2 ppm of Si zeolite, the electron transport rate increased by 5 times, the apparent transpiration by 3 times, total conductance and stomatal conductance by around 50%, normalized difference vegetative index by 6–8%, and photochemical reflectance index by 14–33%. These results suggest that the effectiveness of Si is highly dependent on the growth medium and the type of Si, with soil enabling better Si availability, uptake, and physiological response compared to hydroponics. The superior performance of zeolite in EP II indicates its potential as a slow-release Si source that enhances root development and photosynthetic efficiency over time. Thus, it is concluded that zeolite has more potential in soil, and soluble silicon sources should be selected in hydroponics. Full article

Oats (Avena sativa L.) are a staple grain and forage crop with substantial market demand. In China, they are the second most-imported forage grass, only after alfalfa (Medicago sativa L.). Enhancing the salt tolerance of oats to facilitate their cultivation in saline areas can thereby increase forage yield and promote the utilization of saline land, which constitutes an important reserve land resource in China. This study aimed to identify the bacterial strain Bacillus sp. LrM2 (hereafter referred to as strain LrM2) to determine its precise species-level classification and evaluate its effects on oat photosynthesis and growth under salt stress through indoor pot experiments. The results indicated that strain LrM2, capable of urease production and citrate utilization, was identified as Bacillus mojavensis. The strain LrM2 had a positive effect on shoot and root growth of oats under 100 mM NaCl stress conditions. Strain LrM2 inoculation modulated osmotic stress in oats under 100 mM NaCl stress by significantly increasing soluble sugar and decreasing proline content in leaves. It inhibited Na⁺ uptake and promoted K⁺ absorption in the roots, thereby reducing Na⁺ translocation to the leaves and mitigating ionic toxicity. Inoculation with strain LrM2 significantly increased photosynthetic pigment content (chlorophyll a, carotenoids), improved gas exchange parameters (stomatal conductance, transpiration rate, net rate of photosynthesis), enhanced PSII photochemical efficiency (maximum quantum yield, coefficient of photochemical quenching, actual photosynthetic efficiency of PSII, electron transfer rate), and reduced the quantum yield of non-regulated energy dissipation. These improvements, coupled with increased relative water content and instantaneous water use efficiency, thereby collectively enhanced the overall photosynthetic performance. In conclusion, strain LrM2 represents a promising bio-resource for mitigating salt stress and promoting growth in oats, with direct applications for developing novel biofertilizers and sustainable agricultural strategies. Full article

Legume green manure incorporation offers a potential pathway for sustainable cropping in arid irrigated areas. This study aimed to determine whether water and nitrogen inputs could be concurrently reduced without compromising maize productivity under this practice. A two-year field experiment (2024–2025) was conducted using a split-plot design with three irrigation levels (I1: 4045, I2: 3240, I3: 2430 m³·ha⁻¹) and three nitrogen rates (N1: 360, N2: 288, N3: 216 kg·ha⁻¹). Compared with conventional management (I1N1), 20% co-reduction in water and nitrogen (I2N2) maintained stable leaf area index (LAI), net photosynthetic rate (P_n), transpiration rate (T_r), DM, and GY, while significantly increasing water use efficiency (WUE) by 7.6% and nitrogen use efficiency for grain yield (NUtEg) by 11.7%. Excessive water reduction (I3) or nitrogen reduction (N3) significantly inhibited growth and reduced yield (p < 0.05). Soil water content under I2N2 did not differ significantly from I1N1 in the 0–110 cm profile, and soil total nitrogen remained higher at silking.) Structural equation model (SEM) revealed SWC and STN indirectly affected P_n and T_r via regulating LAI and SPAD (path coefficients: 0.48–0.62), which drove DM accumulation and determined GY (R² = 0.81). These short-term results suggest that moderate water-nitrogen reduction with green manure can sustain yield while improving resource efficiency, offering a promising practice for arid irrigated maize systems, though longer-term validation is needed. Full article

Fresh fruits are inherently prone to postharvest deterioration due to loss of moisture, respiration, mechanical damage, and microbial decay, making quality preservation a persistent challenge across fresh fruit supply chains. While conventional plastic packaging offers barrier protection and cost-efficiency, its environmental footprint, particularly poor biodegradability and increasing incidence of plastic waste necessitates a transition toward more sustainable alternatives. Among these, the use of edible coatings, primarily based on natural biopolymers, have emerged as a versatile strategy capable of modulating transpiration, gas exchange, microbial activity, and sensory quality while addressing environmental concerns. Unlike biodegradable plastic films, edible coatings directly interface with the fruit surface and offer multifunctional roles extending beyond passive protection. This review synthesizes recent advances in edible coatings for fresh fruits, with emphasis on material classes, functional performance, optimization strategies, and analytical evaluation methods. Key findings indicate that polysaccharide-based coatings provide adequate gas permeability but limited moisture resistance, while nanocomposite and multi-component systems enhance water-vapor barrier performance without compromising respiration compatibility. Incorporation of bioactive agents such as essential oils, nanoparticles, and plant extracts further extends shelf life through antimicrobial and antioxidant mechanisms, though formulation trade-offs and sensory constraints persist. The review also highlights critical limitations, including variability in barrier and mechanical properties, challenges in industrial-scale application, insufficient long-term validation under commercial cold-chain conditions, and regulatory uncertainty for active formulations. Future research priorities are identified, including mechanistic transport–physiology integration, standardized performance metrics, scalable application technologies, and life-cycle-informed material design. Addressing these gaps is essential for transitioning edible coatings from experimental sustainability concepts to robust, function-driven solutions for fresh-fruit preservation. Full article

The response of cocoa (Theobroma cacao L.) to low oxygen availability in the soil and the possibility of recovery after stress relief are associated with the plasticity capacity of each genotype; however, studies evaluating the influence of rootstock on stress response are scarce. Thus, in the northern region of the state of Espírito Santo, municipality of São Mateus, the physiological, biochemical, and anatomical responses and recovery capacity of cocoa PS-1319 grafted onto the rootstocks TSH-1188, Cepec-2002, Pará, Esfip-02, and SJ-02 were evaluated under flooded conditions. The plants were subjected to flooding for 60 days, and their recovery capacity was assessed after this period. The gas exchange, relative chlorophyll content, stem and leaf anatomy, photosynthetic pigments, and carbohydrates were evaluated. All genotypes showed reductions in net photosynthetic assimilation, stomatal conductance, and transpiration rate in the flooded environment compared to the non-flooded environment. All pigments were degraded, with average values of Chl a, Chl b, total Chl, and total carotenoids of 9.33, 10.418, 19.75, and 590.75 μg.mL⁻¹ in the non-flooded environment and 6.43, 7.69, 14.12, and 500.33 μg.mL⁻¹ in the flooded environment. The rootstocks Cepec-2002 and Esfip-02 showed the highest carotenoid accumulation, with 585.78 and 650.47 μg.mL⁻¹, respectively, when compared to SJ-02 (474.03 μg.mL⁻¹), Pará (491.58 μg.mL⁻¹), and TSH-1188 (525.86 491.58 μg.mL⁻¹). The Pará rootstock did not show differences in stomatal density between environments, with values of 32.25 in flooding, 34.83 in non-flooding, and 31.61 in recovery. During flooding, lenticels formed in all rootstocks. After recovery, all rootstocks normalized their gas exchange, carbohydrate levels, and anatomy, showing that the root system was able to re-establish its functions, making these rootstocks suitable for areas at risk of flooding. Full article

Global warming is increasingly constraining plant productivity by altering the photosynthetic energy balance and leaf thermoregulation. Under high light and elevated temperatures, absorption of energy in excess (AEE) by photosystem II disrupts photosynthetic electron transport, oxygen evolution, and CO₂ assimilation, often accompanied by reduced foliar transpiration. These conditions promote photoinhibition, as reflected by a decrease in maximal photosynthetic efficiency (Fv/Fm), an increase in non-photochemical quenching (NPQ), and photooxidative stress associated with enhanced reactive oxygen species (ROS) production. In addition to environmental heat stress, AEE influences foliar temperature through internal energy partitioning, including regulated dissipation of AEE as heat and changes in transpirational cooling. The relative contributions of NPQ, photochemistry, and transpiration to leaf temperature regulation are strongly context dependent and vary with light intensity, temperature changes, and water availability. Under global warming, rising background temperatures and increased vapor pressure deficit may constrain transpirational cooling and alter the balance between non-photochemical and photochemical energy dissipation and usage, respectively. In this review, we synthesize current knowledge on AEE handling, photoinhibition, NPQ and other quenching processes, and on transpiration cooling, and discuss a conceptual framework in which sustained imbalance among these processes under global warming conditions could amplify foliar heat stress and increase the risk of cellular damage. Rather than proposing new physiological mechanisms, this work integrates existing evidence across molecular, leaf, and ecosystem scales to highlight potential feedbacks relevant to plant performance under future climate prediction scenarios. Full article

Cassava plants’ response to waterlogging must be monitored in an accurate and timely manner to mitigate the adverse effects of waterlogging stress. Under waterlogging conditions, root hypoxia reduces water uptake and stomatal closure limits transpiration, which often results in increased leaf temperature due to reduced evaporative cooling. However, how this relationship changes in cassava leaves under waterlogged conditions remains poorly understood. This study hypothesized that more negative ΔT values reflect enhanced transpirational cooling, which is a key determinant of superior physiological performance under waterlogging stress among cassava genotypes. Two cassava cultivars were subjected to twelve days of waterlogging. Results revealed a significant decrease in photosynthetic rate (p < 0.001), stomatal conductance (p < 0.001), and transpiration rate (p < 0.001), as well as an increase in leaf temperature (p < 0.001) and ΔT (p < 0.001), reflecting impaired stomatal regulation and reduced evaporative cooling. Strong negative correlations between ΔT and photosynthetic parameters (Pn (p < 0.001, r = −0.91), gs (p < 0.001, r = −0.91), and E (p < 0.001, r = −0.87)) were observed, presenting ΔT as a reliable, nondestructive indicator of cassava’s physiological responses under hypoxic conditions. Findings indicate that maintaining cooler canopies may contribute to waterlogging-tolerant cassava genotypes, and that ΔT can act as a screening parameter for waterlogging-tolerant genotypes. However, further studies with contrasting genotypes and additional parameters are recommended for validation. Full article

Heat stress caused a stagnation in the growth and development of Passiflora edulis Sims. To investigate the effects of high-temperature stress, this study subjected P. edulis to 40 °C treatment for different durations; the changes in chlorophyll content, chlorophyll fluorescence parameters, photosynthetic parameters, transcriptome profiles, and photosynthesis-related genes of P. edulis under high-temperature stress were analyzed. The results showed that after 5 h of heat stress, the chlorophyll content of the leaves decreased by 31%, variable fluorescence/maximum fluorescence (Fv/Fm) decreased by 26.91%, photochemical performance index (PI_abs) by 99.28%, comprehensive performance index (PI_total) by 94.20%, light energy absorbed per unit area (ABS/CSm) by 13.56%, light energy captured per unit area (TRo/CSm) by 17.90% and quantum yield of electron transfer per unit area (ETo/CSm) by 92.61%. The net photosynthetic rate (Pn), transpiration rate (Tr) and stomatal conductance (Gs) decreased by 47%, 41% and 38%, respectively, while intercellular CO₂ concentration (Ci) increased by 1.34 times. Transcriptome sequencing results of P. edulis under heat stress identified 2336 differentially expressed genes (DEGs), which were significantly enriched in pathways including chloroplast function and plant hormone signal transduction. GO enrichment analysis demonstrated that DEGs were significantly enriched in terms related to catalytic activity and chloroplast components. Concurrently, KEGG pathway analysis revealed that carbon fixation in photosynthetic organisms was among the key pathways showing significant enrichment of these DEGs. The expression levels of photosynthesis-related genes, including PePSAE, PeMADs, PebHLH, PeFAR1, PePSBS, PePnsB4, PebZIP and PeC2H2, exhibited a significant increase after 3 h of high-temperature stress and rapidly declined following 5 h. These findings lay a foundation for further research on the high-temperature stress response mechanism and photosynthetic regulation of heat tolerance in P. edulis. Full article

The Hailiutu River Basin in northern China represents a semi-arid area where groundwater-dependent ecosystems (GDEs) play a critical role in maintaining regional vegetation structure and ecological stability. This study investigated the spatiotemporal dynamics of GDEs and their relationship with water conditions using trend analysis, partial correlation, and Random Forest models over the period of 2002–2022. The results show that vegetation activity (NDVI) increased at a rate of 0.0052/yr in GDEs. Precipitation exhibited a basin-wide upward trend of 0.735 mm/yr, while SPEI increased at 0.0207/yr. In contrast, groundwater storage declined markedly at −11.19 mm/yr, highlighting a persistent reduction in water availability that poses a significant risk to the stability of GDEs. Both partial correlation analysis and the random forest model consistently showed strong ecohydrological interactions between vegetation and groundwater. Vegetation dynamics are primarily driven by groundwater availability, especially in groundwater-dependent ecosystems. Conversely, groundwater variations are most strongly influenced by vegetation. The results indicate that precipitation and the standardized precipitation–evapotranspiration index (SPEI) are the primary positive drivers of interannual NDVI variability, whereas groundwater plays a critical role in sustaining GDEs. Field observations of key species confirm the dependence of GDEs on groundwater, and vegetation dynamics are regulated by climate and groundwater; however, ongoing groundwater decline may threaten ecosystem stability. These findings demonstrate that vegetation transpiration exerts the dominant influence on groundwater variations, while groundwater simultaneously constrains vegetation growth, particularly in areas where declining groundwater storage anomalies (GWSAs) coincide with reduced NDVI. The results emphasize that continuous groundwater depletion threatens vegetation–groundwater sustainability, highlighting the need for balanced groundwater and vegetation management in arid regions. Full article

Introduction: Traditional approaches to discover teleconnections and quantify uncertainty, such as global sensitivity analysis, Monte Carlo experiments, decomposition analysis, etc., are computationally intractable for large-scale process-based Coupled Human and Natural Systems (CHANS) models. This study hypothesizes that machine-learned emulator models provide “computationally efficient” algorithms for discovering teleconnections and quantifying uncertainty within and across dynamically evolving human and natural systems. Objectives: This study aims to harness machine-learned emulator models to discover the relative contributions of internal- versus external-to-the-lake teleconnected processes driving the emergence of Harmful Algal Blooms (HABs) and trophic regime shifts. Three objectives are pursued: (1) build emulators; (2); quantify uncertainty and (3) identify teleconnections. Methods: Six machine-learned emulator models are trained on ~3.8 million observations for ~52 features derived from 332 scenarios simulated in an integrated process-based CHANS model that predicts water quality in Missisquoi Bay of Lake Champlain under alternate hydro-climatic and nutrient management scenarios for the 2001–2047 timeframe. The regression random forest (RRF), regression LightGBM (RLGBM) and regression XGBoost (RXGB) models predict the average surface mean of ChlA. Further, the classifier random forest (CRF), classifier LightGBM (CLGBM) and classifier XGBoost (CXGB) predict four trophic states of Missisquoi Bay. Relative importance and partial dependence plots are derived from all six emulator models to quantify relative uncertainty and importance of external-to-the-lake (climatic, hydrological, nutrient management) and internal-to-the-lake (P and N sediment release) drivers of HABs. Results: RXGB (R² = 96%, 48 features) outperforms RLGBM (R² = 95%, 37 features) and RRF (R² = 93%, 20 features) in predicting the average surface mean of ChlA. CLGBM (F1 = 96.15, 4 features) outperforms CXGB (F1 = 95.66, 48 features) and CRF (F1 = 93.06, 23 features) in predicting four trophic states. We discovered that predictor variables representing snow, evaporation and transpiration dynamics teleconnect hydro-climatic processes occurring in terrestrial watersheds with the biogeochemical processes occurring in the freshwater lakes. Conclusions: The proposed approach to discover teleconnections and quantify uncertainty through machine-learned emulator models can be scaled up in different watersheds and lakes for informing integrated water governance processes. Full article