Search Results (223)

Understanding of carrot growth dynamics and ecophysiological functioning in tropical highland environments remains limited, despite the crop’s productive importance in the Colombian Andean region. This study aimed to characterize biomass accumulation and partitioning, as well as the photosynthetic response to radiation, in two carrot (Daucus carota L.) cultivars (Berlicum- and Flakkee-type) grown under high-altitude Andean tropical conditions in Rionegro, Antioquia. To account for field spatial heterogeneity, four beds were used as blocks, and both cultivars were evaluated in parallel under comparable field conditions. Weekly destructive samplings were performed to quantify total dry biomass, shoot biomass, root biomass, leaf number, and leaf area. In addition, the response of net CO₂ assimilation to photosynthetically active radiation was evaluated using a portable gas-exchange system. Total and root biomass were described using logistic models, shoot biomass using a Gaussian model, and the photosynthetic response using an exponential model. Berlicum showed higher biomass accumulation, whereas Flakkee exhibited an earlier response of growth and photosynthetic activity. In both cultivars, the highest functional capacity was concentrated in stage III, coinciding with the strengthening of the storage-root sink. Overall, the results indicate contrasting temporal patterns in biomass partitioning and photosynthetic performance between the two carrot cultivars and provide a useful ecophysiological framework for interpreting crop management and harvest timing under high-altitude Andean tropical conditions. Full article

Rapid urbanization and agricultural expansion in arid regions have profoundly altered carbon cycles and landscape stability. Focusing on the Hexi Corridor, China, this study integrates multi-source geospatial data (1990–2020) to analyze the spatiotemporal evolution and driving factors of land-use carbon emissions (LUCE) and landscape ecological risks (LER). By integrating carbon accounting, LER assessment, bivariate spatial autocorrelation, and the Optimal Parameter Geographic Detector (OPGD), we quantify the intricate relationship between carbon dynamics and landscape integrity. Results indicate a transformative pattern of anthropogenic expansion and natural contraction, with a 2315.49 km² net loss of unused land. Net carbon emissions surged 4.6-fold, while forest and grassland sinks exhibited a significant “lock-in effect” due to fragile ecological foundations. Simultaneously, LER followed an “inverted U-shaped” trajectory; the refined 5 × 5 km grid scale revealed a significant drop in high-risk areas from 44.65% to 10.96% following ecological restoration. Spatial analysis reveals a significant “spatial mismatch” between LUCE and LER, with oases manifesting “high carbon–low risk” clustering. Driver detection confirms a driving asymmetry. LUCE is dominated by anthropogenic factors (nighttime light, q > 0.90), whereas LER is profoundly constrained by natural backgrounds. Future governance must shift toward a collaborative system centered on source-based emission control and precise regional management to synergize low-carbon transition with landscape security. Full article

Monitoring avocado (Persea americana Mill., cv. Semil-34) in tropical mountain landscapes of Cambita, San Cristóbal, Dominican Republic is inherently complex due to the pronounced topographical and climatic heterogeneity that modulates the crop’s ecophysiological responses, specifically vegetative vigor, carbon allocation, and the synchronization of reproductive flushes. This study integrates 5-year (2020–2025) Sentinel-2 time series, ERA5-Land climatic variables (air temperature, total precipitation, and radiation), and geomorphometric covariates to explain variability in yield and fruit quality. Multispectral indices, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Red Edge (NDRE), and Normalized Difference Moisture Index (NDMI), were analyzed using Partial Least Squares Regression (PLSR) to characterize phenological dynamics and rank dominant predictors. The results revealed coherent spectral phenological trajectories; however, a significant inverse relationship was detected between canopy vigor and yield during reproductive phases. High vegetation index values were significantly and negatively associated with lower production (r = −0.58, p < 0.0021), reflecting a potential source–sink imbalance. Topography functioned as a structural filter, regulating root drainage and productive stability across the landscape. While yield variability was partially explainable (R² = 0.38), internal fruit quality, measured as dry matter content, exhibited comparatively high environmental stability. A central contribution of this research lies in identifying the “vigor paradox” in cv. Semil-34 and the suggestion that topography may exert a stronger influence than direct spectral signals under tropical hillside conditions. These findings provide an exploratory framework for anticipating yield and fruit quality through satellite remote sensing or UAVs, supporting site-specific management decisions in mountain agricultural systems. Full article

Accurate estimation of forest soil organic carbon (SOC) is considered critical for understanding terrestrial carbon cycling and supporting climate change mitigation strategies. However, the canopy block, intricate vertical structure of forests, and the constraints of single-source remote sensing data have presented considerable obstacles for estimating forest SOC. This study proposes a forest SOC estimation and uncertainty analysis (ForSOC-UA) framework to enhance forest SOC estimation and quantify its uncertainty in the natural secondary forests of northern China by integrating hyperspectral imagery (ZY-1F), synthetic aperture radar data (Sentinel-1), and environmental covariates (such as topography, vegetation, and soil indices). The performance of traditional machine learning models (RF, SVM, and CNN), geographically weighted regression (GWR), and a geographically weighted random forest (GWRF) model was compared across three different soil depths (0–5 cm, 5–10 cm, and 10–30 cm). The results showed that GWRF consistently outperformed all other models across all soil depth layers, with the highest accuracy achieved using multi-source data (R² = 0.58, RMSE = 27.49 g/kg, rRMSE = 0.31). Analysis of feature importance revealed that soil moisture, terrain characteristics, and Sentinel-1 polarization attributes were the primary predictors, while spectral derivatives in the red and near-infrared bands from ZY-1F also played a significant role for forest SOC estimation. The uncertainty analysis indicated a forest SOC estimation uncertainty of 37.2 g/kg in the 0–5 cm soil layer, with a decreasing trend as depth increased. This pattern is associated with the vertical spatial distribution of the measured forest SOC. This integrated approach effectively captures spatial heterogeneity and nonlinear relationships between feature and forest SOC, while also assessing estimation uncertainty, so providing a robust methodology for predicting forest SOC. The ForSOC-UA framework addresses the uncertainty quantification of SOC estimation at different vertical depths based on machine learning, providing methodological enhancements for the assessment of large-scale forest SOC and the monitoring of carbon sinks within forest ecosystems. Full article

Driven by the goal of carbon neutrality, low-carbon development in township spaces is essential for sustainable urban–rural growth. This paper employs a carbon accounting methodology, taking Fuqiushan Town in the Dongting Lake Ecological Economic Zone as a case study to develop a detailed carbon measurement inventory at the township scale. Using spatial analysis techniques, it synthesizes multi-source data—including land use, agricultural inputs, and population—to estimate emissions from key sources such as crop cultivation, livestock and poultry breeding, industrial production, and residential activities. The study also evaluates the carbon sequestration capacity of sinks such as woodlands and water bodies, enabling the spatial visualization of both carbon emissions and carbon sinks. Key findings include: (1) Fuqiushan Town exhibits a carbon emission profile characterized by “industrial activities as the primary source, supplemented by agriculture, with additional contributions from residential and transportation sectors,” while forested areas and water bodies serve as core carbon sink zones. (2) An innovative multidimensional indicator system for low-carbon development efficiency was established, consisting of the Low-Carbon Development Efficiency Index in Production, the Daily Life Carbon Responsibility Efficiency Index, and the Ecological Carbon Sink Efficiency Index, which together form a Comprehensive Efficiency Index for Low-Carbon Development. (3) Analysis reveals significant spatial coupling relationships and efficiency differentiation patterns among carbon emissions, industrial structure, energy dependence, and ecological background. Based on dominant carbon emission types, low-carbon efficiency thresholds, and spatial factor interactions, the 17 villages and one forest farm in the township are classified into five zones: “Industrial High-Carbon Transition Zone,” “Agricultural Pollution Reduction and Carbon Emission Reduction Synergy Zone,” “Ecological Low-Carbon Conservation Zone,” “Human Settlements Balanced Development Zone,” and “Ecological Core Zone.” Tailored low-carbon spatial planning strategies for material resources are proposed for each zone. These results offer quantitative support and spatially targeted insights for low-carbon spatial planning in ecologically sensitive townships, contributing to the achievement of objectives such as “carbon reduction and sink increase” and “rural revitalization.” Full article

Low-temperature stress during the jointing stage severely disrupts the coordination of the source–flow–sink system in winter wheat. To elucidate the underlying mechanism, three wheat cultivars with different winter habits (Zhenmai 12, Jimai 22, and Shannong 38) were selected and subjected to six temperature levels (−6 °C to 8 °C) and three stress durations (2–6 days). The effects of vascular bundle traits on the transport of photosynthetic products, dry matter distribution, and yield formation were analyzed. The results showed that Zhenmai 12 and Jimai 22 completely ceased photosynthesis under 0 °C and −3 °C, respectively. The leaf vascular bundle area continuously decreased with increasing low-temperature stress, while the proportion of xylem and phloem initially increased by approximately 15% and 10%, respectively, before rapidly decreasing to 65% of the control value. In the stem, the three vascular bundle parameters initially increased by 20%, 25%, and 20%, respectively, before quickly decreasing to 50%. Changes in the vascular bundle structure weakened the transport capacity of assimilates, with dry matter in leaves and stems decreasing by 15–20% and 10%, respectively, while the root dry matter increased by 20–30%. Correlation analysis revealed highly significant relationships (p < 0.001) between vascular bundle parameters and yield components. Principal component and cluster analyses indicate that the area of leaf and stem vascular bundles, maximum net photosynthetic rate, and water use efficiency may be key indicators in explaining the variation in yield. Radar plots further validated this finding, showing that Zhenmai 12 and Jimai 22 are more sensitive to changes in the maximum net photosynthetic rate, while Shannong 38 exhibits a greater sensitivity to changes in water use efficiency. Based on existing research on photosynthetic pathways and dry matter distribution, this study innovatively investigates the potential relationship between material transport and yield formation under low-temperature stress during the jointing stage from the perspective of anatomical structure and functional coupling. The findings provide new insights into understanding the structural impact of low-temperature stress on crop yield formation and offer theoretical support for identifying the structural basis of limited material transport under stress and for developing disaster diagnostic models driven by structural parameters. Full article

Growth-Regulating Factors (GRFs) are plant-specific transcription factors that, together with GRF-Interacting Factors (GIFs) and under post-transcriptional control by miR396, coordinate cell proliferation and expansion to define organ size. This GRF–GIF–miR396 regulatory module holds major agronomic importance, shaping leaf architecture, source–sink relationships, nitrogen-use efficiency (NUE), and stress resilience in crops. Upregulation of specific GRF genes has been shown to enhance leaf width, yield potential, and other important agronomic traits. Synthetic GRF–GIF chimeras have revolutionized regeneration and genome editing in multiple crop species, revealing both successes and species-specific limitations. Expanding GRF/GIF gene families and functional analyses across various crops highlight conserved developmental functions with variable outcomes, including improved drought and salinity tolerance through sustained canopy growth. This review, focused on crop systems, integrates current advances in GRF-regulated leaf development, their contributions to abiotic and biotic stress adaptation, and the emerging utility of GRF–GIF chimeras. Finally, it outlines key challenges and future opportunities for leveraging GRFs in designing climate-resilient, high-efficiency crop ideotypes. Full article

In this study, we dissect the genetic effects of two major rice heading date genes, Heading date 1 (Hd1) and Grain number, plant height, and heading date 7 (Ghd7), in the regulation of six photosynthesis-related traits: the chlorophyll a/b contents, net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO₂ concentration (Ci), and transpiration rate (Tr). Using two sets of near-isogenic lines (Z43 and Z44) derived from a Zhenshan97/Milyang46 cross, functional Hd1 increased the chlorophyll contents but decreased the photosynthesis-related parameters; however, functional Ghd7 consistently inhibited all six traits. More importantly, there is a significant epistatic interaction between them: Hd1 only enhances the photosynthetic capacity under the non-functional background of ghd7 but intensifies its photosynthesis inhibition under the functional background of Ghd7. Transcriptome analysis showed that functional Ghd7 mainly down-regulated the expression of genes related to photosynthesis and chloroplast development, and the inhibitory effect was significantly enhanced in the presence of functional Hd1. GO enrichment analysis further confirmed that the chlorophyll synthesis, photosystem assembly, and electron transfer pathways were downregulated in the bifunctional allele combination. Although Hd1 promotes chlorophyll accumulation, it reduces the actual photosynthetic efficiency, indicating that it has different regulatory paths for chlorophyll synthesis and photosynthetic function. Both physiological and molecular evidence showed that the Hd1-Ghd7 module coordinated the regulation of the heading date and photosynthetic capacity, forming a trade-off relationship between “early heading–high photosynthesis” and “late heading–low photosynthesis”. This study reveals the pleiotropy of genes at the heading stage and provides a theoretical basis for the optimization of the source–sink balance in high-yield rice breeding. Full article

Enhancing rice yield under high-input systems increasingly relies on optimizing physiological processes rather than further increasing external inputs. This study aimed to clarify the physiological basis underlying the yield advantage of super hybrid rice, focusing on photosynthetic capacity and assimilate transport. We compared super hybrid rice (Yliangyou 3218 and Yliangyou 5867) with super conventional rice (Zhendao 11 and Nanjing 9108) under field conditions in 2023–2024. Super hybrid rice consistently outperformed super conventional rice, with grain yield 19.7% higher in 2023 and 23.7% higher in 2024, primarily due to an increased number of spikelets per panicle, and grain yield was also positively correlated with photosynthetic capacity (net photosynthetic rate, stomatal conductance, maximum carboxylation rate, maximum electron transport rate and triose phosphate utilization rate). In 2024, spikelets per panicle and grain yield were also positively associated with phloem soluble sugar and vascular bundle number, indicating that enhanced assimilate transport contributed to higher spikelet formation. These results demonstrate that, compared to super conventional rice, the yield advantage of super hybrid rice is underpinned by coordinated enhancement of photosynthesis and assimilate transport, highlighting the importance of source–sink optimization for further yield improvement. Full article

Background: Peach fruit quality can be compromised by cold storage, a postharvest practice required for long-distance export that can trigger chilling injury and metabolic disturbances affecting sugars, organic acids, and other metabolites. Preharvest practices such as thinning modify source–sink relationships and fruit development, potentially influencing susceptibility to chilling stress. Objectives: This study aimed to determine whether commercial thinning alters fruit susceptibility to cold storage damage and to identify metabolic processes associated with chilling tolerance in two nectarine varieties with contrasting sensitivity, ‘Magique’ (tolerant) and ‘Red Pearl’ (sensitive). Methods: Fruits from thinned (TH) and unthinned (UTH) trees were subjected to cold storage (0 °C, 21 days) followed by ripening, and evaluated for physiological parameters, sugar and organic acid composition by HPLC, and phenylpropanoid-related metabolites by ¹H-NMR. A genome-scale metabolic model was built to model fruit metabolism using COBRApy. Results: Thinning increased fruit size in both varieties. Magique exhibited overall metabolic stability across thinning treatments and cold storage. Red Pearl, in contrast, showed broad metabolic fluctuation in response to external stimuli. Integration of transcriptomic data and metabolic modeling identified quinate-centered reactions as candidate regulatory nodes associated with phenylpropanoid flux during ripening and post-chilling recovery. Conclusions: These findings indicate that modulating quinate metabolism during early ripening may help improve chilling tolerance and highlight the phenylpropanoid pathway as a central metabolic axis modulated by both pre- and postharvest practices, with implications for fruit quality management. Full article

This study elucidates the regulatory mechanisms of girdling on leaf senescence and fruit quality in ‘Jinyan’ kiwifruit, providing a theoretical basis for high-yield and high-quality cultivation. Ten-year-old vines were subjected to single (5 mm, 9 mm) and double (5 mm, 9 mm) girdling treatments at two distinct stages: peak flowering stage (Group A) and 10 days post-anthesis (Group B). Physiological markers, including reactive oxygen species (ROS) and antioxidant enzyme activities, were monitored at 10, 35, and 70 days post-treatment and integrated with fruit quality metrics using Principal Component Analysis (PCA). Physiologically, girdling induced a transient oxidative burst, characterized by increased ROS accumulation proportional to girdling intensity. This triggered a robust antioxidant defense response, where superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activities peaked at 35 days, effectively mitigating oxidative damage (MDA) during the healing phase. Concurrently, metabolic substrates (soluble protein, starch, and sugar) were significantly enriched in leaves. Agronomically, all treatments enhanced fruit yield, single-fruit weight, and soluble solids content (SSC). Notably, double girdling treatments specifically promoted fruit elongation and dry matter accumulation. Comprehensive evaluation identified distinct optimal strategies: while moderate single girdling (A2) was superior during flowering, double girdling (B3, B4) proved most effective post-anthesis. Ultimately, double girdling performed 10 days post-anthesis emerged as the optimal regimen, effectively balancing source-sink relationships to maximize both physiological function and fruit quality. Full article

The constituent elements of source-to-sink systems and their coupling relationships are key controls on the development of sedimentary systems and the spatial distribution of sand bodies. Taking the Paleogene strata in the southern Laizhouwan Sag of the Bohai Bay Basin as a case study, we integrate drilling, logging, core, thin-section, and high-resolution 3D seismic data to quantitatively characterize basement lithology and effective provenance area, drainage-unit subdivision, types and scales of sediment transport pathways, and geometric parameters of depositional fans, within a source-to-sink analytical framework. The results show that: (1) Two distinct provenance types are developed in the southern Laizhouwan Sag, including Proterozoic granitic–gneissic basement and Mesozoic volcanic–clastic basement. These provenance types exhibit pronounced differences in effective source area, vertical relief, and drainage-network configuration across different sequence stages. (2) Two main categories of sediment transport pathways are identified, namely paleo-valleys and fault-controlled troughs. V-shaped, U-shaped, and W-shaped paleo-valleys show systematic morphological transitions along topographic gradients. The width-to-depth ratio of transport channels exerts a significant control on depositional fan scale, with U-shaped valleys exhibiting the highest sediment transport efficiency. Finally, (3) the depositional domain is dominated by near-source fan-delta systems, whose scale shows a strong positive correlation with effective provenance area and transport-channel morphology. Overall, the southern Laizhouwan Sag is characterized by a typical fault-controlled, steep-slope source-to-sink system, in which sedimentary system distribution is jointly governed by effective provenance area, sediment transport pathway geometry, and fault-related slope-break zones. This study provides a quantitative example and methodological reference for source-to-sink system characterization and prediction of favorable sand body distribution in continental rift basins. Full article

Vegetation plays a dual role in the Earth’s climate system: it removes atmospheric CO₂ through photosynthesis while emitting biogenic volatile organic compounds (BVOCs), which can weaken the net carbon sink and contribute to air pollution. To assess the long-term interplay between carbon uptake and BVOC emissions, and to clarify how vegetation characteristics and climate regulate this relationship, we developed a Biogenic Carbon Efficiency Index (BCEI). The BCEI integrates BVOC emissions with gross primary productivity (GPP) to quantify their spatial ratio, thereby capturing the concurrent “source” and “sink” attributes of vegetation. We characterize the spatiotemporal heterogeneity of the BCEI across China and identify its dominant environmental drivers. The BCEI decreases from southeast to northwest, and during 2001–2020 exhibited a declining trend over 78% of the country, with increases mainly in Southwest China and on the Shandong and Liaodong Peninsulas. Driver analyses indicate that variables linked to hydrothermal conditions, including temperature, precipitation, evapotranspiration, and soil moisture, primarily control BCEI variability. Across most regions, the BCEI is negatively correlated with soil moisture and precipitation, positively correlated with evapotranspiration, and shows regionally varying associations with temperature. These findings deepen understanding of vegetation’s dual role as a source and sink and its driving mechanisms, providing a theoretical basis for optimizing regional vegetation management strategies. Full article

Leaves, as the primary “source” organ for photosynthesis, directly influence plant yield. However, it remains unclear whether leaf removal affects Jerusalem artichoke yield by altering rhizosphere nutrient availability. This study evaluated the effects of different leaf removal intensities on tuber yield and rhizosphere nutrient characteristics of Jerusalem artichoke (Helianthus tuberosus L.). Results from two consecutive field experiments demonstrated that removal of the lower leaves (Q2) significantly increased tuber yield in both years, with gains of 93.7% in 2022 and 282% in 2023 compared with the control. Although other leaf removal treatments also showed yield increases, these were not statistically significant. Principal component analysis revealed that rhizosphere soils associated with tubers and taproots contained higher concentrations of ammonium nitrogen, nitrate nitrogen, available phosphorus, and available potassium than bulk soils. Among these nutrients, tuber yield was significantly and positively correlated with available potassium (r = 0.57). These findings indicate that moderate removal of lower leaves enhances rhizosphere nutrient conditions and promotes higher tuber yield in Jerusalem artichoke. Full article

Soluble sugars are the key photo-assimilates in higher plants, playing critical roles in growth, development, and stress regulation. The transport of sugars in plants involves the coordinated action between several sugar transporter families, including the SUT, STP, pGlcT, VGT, TMT, INT, PLT, SFP, and SWEET families. Over recent decades, numerous studies have elucidated the molecular functions of major sugar transporters. Phylogenetic and evolutionary analyses support the conservation of substrate specificity and transport direction, at least to some extent. Structural analyses have provided key insights into the structural–function relationships of important transporters (e.g., OsSWEET2b and AtSTP10), which can be effectively leveraged for artificial intelligence (AI)-enabled protein structure prediction and rational design. Advances in omics technologies now enable low-cost, routine transcriptome profiling and cutting-edge techniques (e.g., single-cell multi-omics and spatiotemporal RNA-seq), providing unprecedented ways to understand how sugar transporters function coordinately at multiple levels. Here, we describe the classification of major sugar transporters in plants and summarize established functional knowledge. We emphasize that recent groundbreaking advances in AI-enabled protein analyses and multi-omics will revolutionize molecular physiology in crops. Specifically, the integration of functional knowledge, AI-based protein analyses, and multi-omics will help unravel the orchestration of different sugar transporters, thereby enhancing our understanding of how sugar transportation and source–sink interactions contribute to crop development, yield formation, and beyond, ultimately boosting carbohydrate transport- related crop improvement. Full article