Search Results (197)

The objective of this study is to analyze spatial entropy flows that reveal the directional dynamics of climate change—patterns that remain obscured in traditional statistical analyses. This approach enables the identification of pathways for “climate information transport”, highlights associations with atmospheric circulation types, and allows for the localization of both sources and “informational voids”—regions where entropy is dissipated. The analytical framework is grounded in a quantitative assessment of long-term climate variability across Europe over the period 1901–2010, utilizing Shannon entropy as a measure of atmospheric system uncertainty and variability. The underlying assumption is that the variability of temperature and precipitation reflects the inherently dynamic character of climate as a nonlinear system prone to fluctuations. The study focuses on calculating entropy estimated within a 70-year moving window for each calendar month, using bivariate distributions of temperature and precipitation modeled with copula functions. Marginal distributions were selected based on the Akaike Information Criterion (AIC). To improve the accuracy of the estimation, a block bootstrap resampling technique was applied, along with numerical integration to compute the Shannon entropy values at each of the 4165 grid points with a spatial resolution of 0.5° × 0.5°. The results indicate that entropy and its derivative are complementary indicators of atmospheric system instability—entropy proving effective in long-term diagnostics, while its derivative provides insight into the short-term forecasting of abrupt changes. A lag analysis and Spearman rank correlation between entropy values and their potential supported the investigation of how circulation variability influences the occurrence of extreme precipitation events. Particularly noteworthy is the temporal derivative of entropy, which revealed strong nonlinear relationships between local dynamic conditions and climatic extremes. A spatial analysis of the information entropy field was also conducted, revealing distinct structures with varying degrees of climatic complexity on a continental scale. This field appears to be clearly structured, reflecting not only the directional patterns of change but also the potential sources of meteorological fluctuations. A field-theory-based spatial classification allows for the identification of transitional regions—areas with heightened susceptibility to shifts in local dynamics—as well as entropy source and sink regions. The study is embedded within the Fokker–Planck formalism, wherein the change in the stochastic distribution characterizes the rate of entropy production. In this context, regions of positive divergence are interpreted as active generators of variability, while sink regions function as stabilizing zones that dampen fluctuations. Full article

This study introduces a theoretical and computational framework for modeling acoustic wave propagation in defective concrete, with applications to non-destructive testing and structural health monitoring. The formulation is based on a coupled system of evolutionary hyperbolic equations, where internal defects are explicitly represented as localized energetic sources or sinks. A key contribution is the definition of a coercivity coefficient, which quantifies the energetic effect of defects and enables their classification as stabilizing, neutral, or dissipative. The model establishes a rigorous relationship between defect morphology, spatial distribution, and the global energetic stability of the material. Numerical simulations performed with an explicit finite-difference time-domain scheme confirm the theoretical predictions: the normalized total energy remains above $95\%$ for stabilizing defects (${\mu }_i>0$), decreases by about $10\%$ for quasi-neutral cases (${\mu }_i\approx 0$), and drops below $50\%$ within $200\mathsf{\mu }\mathrm{s}$ for dissipative defects (${\mu }_i<0$). The proposed approach reproduces the attenuation and phase behavior of classical Biot-type and Kelvin–Voigt models with deviations below $5\%$ while providing a richer energetic interpretation of local defect dynamics. Although primarily theoretical, this study establishes a physically consistent and quantitatively validated framework that supports the development of predictive ultrasonic indicators for the energetic classification of defects in concrete structures. Full article

Forest and grassland fire behavior prediction is increasingly critical under climate change, as rising fire frequency and intensity threaten ecosystems and human societies worldwide. This paper reviews the status and future development trends of wildfire behavior modeling and prediction technologies. It provides a comprehensive overview of the evolution of models from empirical to physical and then to data-driven approaches, emphasizing the integration of multidisciplinary techniques such as machine learning and deep learning. While conventional physical models offer mechanistic insights, recent advancements in data-driven models have enabled the analysis of big data to uncover intricate nonlinear relationships. We underscore the necessity of integrating multiple models via complementary, weighted fusion and hybrid methods to bolster robustness across diverse situations. Ultimately, we advocate for the creation of intelligent forecast systems that leverage data from space, air and ground sources to provide multifaceted fire behavior predictions in regions and globally. Such systems would more effectively transform fire management from a reactive approach to a proactive strategy, thereby safeguarding global forest carbon sinks and promoting sustainable development in the years to come. By offering forward-looking insights and highlighting the importance of multidisciplinary approaches, this review serves as a valuable resource for researchers, practitioners, and policymakers, supporting informed decision-making and fostering interdisciplinary collaboration. Full article

Under refined management, high-yield cotton fields are approaching their maximum output. However, how to break this yield upper limit, specifically the source–sink relationship is still inadequately researched. This experiment was conducted to explore the interaction mechanism between yield formation and source–sink parameters (photosynthesis, nitrogen content, canopy structure and dry matter accumulation and distribution). The treatments consisted of a no cutting source and sink treatment (CK), cutting 1/2 leaves per plant (1/2L) and cutting 1/2 bolls per plant (1/2B) at the initial flowering stage (IFS), the flower and boll stage (FABS), and the full boll stage (FBS). The results showed that 1/2L treatment minimized yield losses to 2.3–5.9% by enhancing photosynthetic compensation, with FBS-1/2L showing the smallest reduction (2.3–2.9%) due to higher leaf N content and SPAD values, whereas, the 1/2B treatments resulted in significant yield losses attributable to fewer bolls, especially the FBS-1/2B treatments, which reduced yields by 35.7–41.9%, with a compensatory rate of only 8.1–14.3%. It is noteworthy that the compensation rates of IFS-1/2B and FABS-1/2B could reach 26.7–32.3% and 18.7–23.8% of their yields due to the higher leaf N content. In a word, the source damage can be buffered by physiological compensation, while the sink loss leads to yield collapse due to the irreversibility of reproductive development. Thus, the core regulator of high-yield cotton fields was sink strength. Accordingly, optimizing the sink quality was performed through moderate boll thinning at the IFS, enhancing water and fertilizer supply at the FABS and strengthening sink organ protection at the FBS in order to realize a breakthrough in yield limit. Full article

Biodiversity conservation has been identified as an important climate change mitigation tool. Healthy ecosystems act as natural carbon sinks while also strengthening resilience, making them essential for climate change adaptation. Climate change effects have led to various negative impacts, including biodiversity loss and food insecurity. The loss of forest biodiversity threatens vital wild fruits and vegetables that sustain rural communities, disrupting natural food sources and constituting a form of social injustice for poor, vulnerable, and previously marginalised groups in rural and semi-urban communities. Therefore, this study aimed to investigate the relationship between previous biodiversity conservation outcomes, ecosystem services, highly utilised wild vegetables and fruits, food and nutritional security, climate change effects, and climate resilience. We identified gaps in African biodiversity conservation and developed a conceptual framework to highlight integral principles required for the effective biodiversity conservation of wild forests in Africa. The integral principles are active community engagement, a strong network of stakeholders, sustainable plant resources management practices, legal reforms, and the creation of awareness through various platforms. Conservation policies should prioritise African indigenous wild, drought-tolerant vegetables and fruits that serve as an interface between food and medicine; play various roles in human survival in the form of ecosystem services; and act as carbon sinks to ensure a food-secure future with reduced climate change effects. The African indigenous community’s efforts in biodiversity conservation engagements are key to successful outcomes. Full article

This study investigated the effects of light intensity regulation on yield and energy efficiency during potato pre-basic seed propagation in plant factories. Using virus-free ‘Favorita’ potato seedlings as experimental material, gradient light intensities (200, 300, and 400 μmol·m²·s⁻¹) were applied at four developmental stages: the seedling stage (SS), tuber formation stage (TFS), tuber growth stage (TGS), and harvest stage (HS), to explore the physiological mechanisms of stage-specific light intensity regulation and energy utilization efficiency. The results revealed that: (1) The per-plant tuber yield of the high yield group reached 72.91 g (T59 treatment), representing a 25% increase compared to the medium yield group and a 168% increase compared to the low yield group. Additionally, the high yield group exhibited superior leaf area, photosynthetic rate, and accumulation of sucrose and starch. (2) The impact of light intensity on tuber development exhibited stage specificity: low light intensity (200 μmol·m⁻²·s⁻¹) during TFS promoted early tuber initiation, while a high light intensity (400 μmol·m⁻²·s⁻¹) enhanced tuber formation efficiency. Increasing the light intensity during TGS facilitated the accumulation of sucrose and starch in tubers. (3) Energy use efficiency (EUE) increased significantly with yield, with the high yield group reaching 3.2 g MJ⁻¹, representing 52% and 88% improvements over the medium yield (2.1 g MJ⁻¹) and low yield (1.7 g MJ⁻¹) groups, respectively. A “stage-specific precision light supplementation” strategy was proposed, involving moderate light reduction (200 μmol·m⁻²·s⁻¹) during TFS and light enhancement (300 μmol·m⁻²·s⁻¹) during TGS to coordinate source-sink relationships and optimize carbohydrate metabolism. This study provides a theoretical basis for efficient potato production in plant factories. Full article

Rice (Oryza sativa L.) plays a pivotal role in the Brazilian economy, serving as a staple food for more than half of the world’s population and thereby contributing to global food security. Projections of future climate change scenarios indicate an increase in extreme weather events. Among climate variables that impact the development and productivity of irrigated rice, solar radiation is one of the most important in defining productive potential. Understanding the risks imposed on agricultural production by the occurrence of days with reduced luminosity availability is crucial for guiding adequate responses that mitigate the negative impacts of climate variability. Therefore, this study aimed to investigate the effect of shade on the metabolism and productivity of irrigated rice plants, with a specific focus on the synthesis of photosynthetic pigments, carbohydrate accumulation, invertase activity, and the nutritional status and grain yield of rice. For this, the study was conducted on the field rice cultivars IRGA 424 RI, BRS PAMPA, and BRS PAMPEIRA, which were subjected to 35% shading using black nylon netting installed when the plants reached the reproductive stage (R0). The restriction was maintained until the R4 stage, and later, from the R4 stage until the R9 stage. After the imposition of treatments, evaluations took place at the phenological stages R2, R4, R6, and R8. In shaded plants, a higher content of photosynthetic pigments and a lower accumulation of carbohydrates were observed, which was reflected in an increase in the activity of invertase enzymes. These conditions were able to potentiate effects on the nutritional status of the plants, in addition to reducing productivity and 1000-grain weight and increasing spikelet sterility, due to changes in the source–sink relationship, with effects more pronounced in cultivars BRS PAMPA and BRS PAMPEIRA during the R4–R9 period. Full article

There is a lack of systematic research on the comprehensive regulatory effects of urea and organic fertilizer application on soil quality and cotton yield in summer direct-seeded cotton fields in the Yangtze River Basin. Additionally, there is a redundancy of indicators in the cotton field soil quality evaluation system and a lack of reports on constructing a minimum dataset to evaluate the soil quality status of cotton fields. We aim to accurately and efficiently evaluate soil quality in cotton fields and screen nitrogen application measures that synergistically improve soil quality, cotton yield, and nitrogen fertilizer utilization efficiency. Taking the summer live broadcast cotton field in Jiangxi Province as the research object, four treatments, including CK without nitrogen application, CF with conventional nitrogen application, N1 with nitrogen reduction, and N2 with nitrogen reduction and organic fertilizer application, were set up for three consecutive years from 2022 to 2024. A total of 15 physical, chemical, and biological indicators of the 0–20 cm plow layer soil were measured in each treatment. A minimum dataset model was constructed to evaluate and verify the soil quality status of different nitrogen application treatments and to explore the physiological mechanisms of nitrogen application on yield performance and stability from the perspectives of cotton source–sink relationship, nitrogen use efficiency, and soil quality. The minimum dataset for soil quality evaluation in cotton fields consisted of five indicators: soil bulk density, moisture content, total nitrogen, organic carbon, and carbon-to-nitrogen ratio, with a simplification rate of 66.67% for the evaluation indicators. The soil quality index calculated based on the minimum dataset (MDS) was significantly positively correlated with the soil quality index of the total dataset (TDS) (R² = 0.904, p < 0.05). The model validation parameters RMSE was 0.0733, nRMSE was 13.8561%, and the d value was 0.9529, all indicating that the model simulation effect had reached a good level or above. The order of soil quality index based on MDS and TDS for CK, CF, N1, and N2 treatments was CK < N1 < CF < N2. The soil quality index of N2 treatment under MDS significantly increased by 16.70% and 26.16% compared to CF and N1 treatments, respectively. Compared with CF treatment, N2 treatment significantly increased nitrogen fertilizer partial productivity by 27.97%, 31.06%, and 21.77%, respectively, over a three-year period while maintaining the same biomass, yield level, yield stability, and yield sustainability. Meanwhile, N1 treatment had the risk of significantly reducing both boll density and seed cotton yield. Compared with N1 treatment, N2 treatment could significantly increase the biomass of reproductive organs during the flower and boll stage by 23.62~24.75% and the boll opening stage by 12.39~15.44%, respectively, laying a material foundation for the improvement in yield and yield stability. Under CF treatment, the cotton field soil showed a high degree of soil physical property barriers, while the N2 treatment reduced soil barriers in indicators such as bulk density, soil organic carbon content, and soil carbon-to-nitrogen ratio by 0.04, 0.04, 0.08, and 0.02, respectively, compared to CF treatment. In summary, the minimum dataset (MDS) retained only 33.3% of the original indicators while maintaining high accuracy, demonstrating the model’s efficiency. After reducing nitrogen by 20%, applying 10% total nitrogen organic fertilizer could substantially improve cotton biomass, cotton yield performance, yield stability, and nitrogen partial productivity while maintaining soil quality levels. This study also assessed yield stability and sustainability, not just productivity alone. The comprehensive nitrogen fertilizer management (reducing N + organic fertilizer) under the experimental conditions has high practical applicability in the intensive agricultural system in southern China. Full article

To achieve regional sustainable development, the low-carbon transformation of agriculture is essential, as it serves both as a significant carbon source and as a potential carbon sink. This study calculated the agricultural carbon emissions in Liaocheng from 2010 to 2022 by analyzing processes including crop cultivation, animal husbandry, and agricultural input. Additionally, a simulation model of the water–energy–food–carbon nexus (WEFC-Nexus) for Liaocheng’s agricultural production process was developed. Using Vensim PLE 10.0.0 software, this study constructed a WEFC-Nexus model encompassing four major subsystems: economic development, agricultural production, agricultural inputs, and water use. The model explored four policy scenarios: business-as-usual scenario (S1), ideal agricultural development (S2), strengthening agricultural investment (S3), and reducing agricultural input costs (S4). It also forecast the trends in carbon emissions and primary sector GDP under these different scenarios from 2023 to 2030. The conclusions were as follows: (1) Total agricultural carbon emissions exhibited a three-phase trajectory, namely, “rapid growth (2010–2014)–sharp decline (2015–2020)–gradual rebound (2021–2022)”, with sectoral contributions ranked as livestock farming (50%) > agricultural inputs (27%) > crop cultivation (23%). (2) The carbon emissions per unit of primary sector GDP (CEAG) for S2, S3, and S4 decreased by 8.86%, 5.79%, and 7.72%, respectively, compared to S1. The relationship between the carbon emissions under the four scenarios is S3 > S1 > S2 > S4. The relationship between the four scenarios in the primary sector GDP is S3 > S2 > S4 > S1. S2 can both control carbon emissions and achieve growth in primary industry output. Policy recommendations emphasize reducing chemical fertilizer use, optimizing livestock management, enhancing agricultural technology efficiency, and adjusting agricultural structures to balance economic development with environmental sustainability. Full article

This study used Xinxin 2 (Juglans regia L. ‘Xinxin2’), a major cultivated walnut variety in Xinjiang, China, to clarify the response and adaptation mechanisms of the anatomical structures of walnut related to source–sink–flow under altered source–sink relationships. We anatomically observed the leaves, fruit stalks, and fruit of bearing branches by artificially adjusting the leaf-to-fruit ratio (LFR). The LFR substantially affected the leaf structure and thickness of the fruit-bearing branches obtained via girdled (p < 0.05). The results of the analysis of the leaf anatomy revealed that a low LFR impeded leaf growth and internal structural development while accelerating senescence, whereas a high LFR promoted leaf growth and delayed senescence. The same trend was observed for the phloem area (PA) of the fruit stalk with the increase in fruit load when the number of leaves on the fruit branch was the same. The maximum PA was reached when the number of fruits was high (except for 4L:3F). This indicates that the micro-anatomical structure of the fruit stalk is more developed under the treatment of a higher number of pinnate compound leaves and fruit level of LFRs. The cells of the 1L:3F and 2L:3F were considerably smaller in the green peel and kernel of the fruit on the branches obtained via girdled than those of 5L:1F plants (p < 0.05). No significant difference was found in the number of cells per unit area or the cross-sectional area of cells in the pericarp and kernel of the fruit under LFRs (p > 0.05); however, a large difference was noted in the microanatomical structure of the pericarp and kernel of fruit. Changes in the structural adaptation characteristics of walnut leaves (source), fruit stalk (flow), and fruit (sink) are related to source–sink regulation. A change in the LFR affects the carbohydrate synthesis in the leaves (source), transport in fruit stalks (flow), and the carbohydrate reception in fruits (sink). Full article

Non-structural carbohydrates (NSCs), the main substrates and energy carriers of plants, play an important role in mediating the source-sink balance of carbon (C). However, the trade-offs in the allocation of NSCs remain unclear at critical stages of fruit development. In this study, we evaluated the dynamic and allometric partitioning characteristics of NSCs at the key stage of fruit development in Camellia oleifera. The seed NSCs pool was the highest in the middle stage of rapid fruit expansion, and an inverted “V” shape appeared from July to September and peaked in August. Notably, although the NSC pool of twigs was the smallest and did not change significantly at each stage, the starch pool was the largest. Significant correlations existed between the NSC content of different organs in C. oleifera in the early stage of slow development and the middle stage of rapid fruit expansion. In particular, NSC components, both of the twigs in the early stage and of the twigs and seeds in the middle stage, showed significant allometric partitioning relationships. In summary, seeds are the main carbon sink for fruit development trade-offs of C. oleifera, and twigs may play an important role in transferring C to seeds at the early and middle stages of fruit development. In the future, attention should be paid to controlling the factors affecting the balance of plant C during the rapid fruit expansion period to ensure high yield. Full article

This study reviews and synthesizes published data to estimate the net carbon flux associated with the complete potato production process. It identifies the key components that contribute to this flux and explores potential mitigation strategies, including both cultivation and post-harvest storage. Data were compiled from field-scale studies (primarily using eddy covariance) and life cycle assessment studies. The results indicate that potato production can act as a carbon sink or a carbon source, depending on the production scenario. In Scenario 1, which represents the worst-case scenario, potato production acts as a carbon source, with a carbon flux of 13,874.816 kg CO₂ eq ha⁻¹ season⁻¹. In contrast, in Scenario 2, the best-case scenario, potato production acts a carbon sink with a carbon flux of −12,830.567 kg CO₂ eq ha⁻¹ season⁻¹. Similarly, in Scenario 3, which is the average scenario, potato production acts as a carbon sink, though a minor one, with a carbon flux of −90.703 kg CO₂ eq ha⁻¹ season⁻¹. Notably, the growing phase has the most significant impact on potato production’s overall carbon flux, as it is the period in which the highest levels of carbon sequestration and emissions occur. Fertilization is the primary carbon source among all potato production operations, averaging 1219.225 kg CO₂ eq ha⁻¹ season⁻¹. Optimizing farming practices, including fertilization, irrigation, tillage methods, and cultivar selection, are essential to enhance carbon sequestration and reduce greenhouse gas emissions. Additionally, further research through controlled experiments is recommended to deepen the understanding of the relationships between various farming factors and carbon flux, ultimately supporting more sustainable potato production practices. Full article

Sugar beet is a nitrogen (N)-sensitive crop, and its N regulation and utilization are critical for enhancing productivity. Sugar beet seedlings at the two-true-leaf-pair stage were hydroponically grown in an artificial climate chamber. Leaves and roots from three seedlings per treatment were sampled at 10, 20, 25, and 30 days after exposure to N treatments (N5: 5 mmol/L, N10: 10 mmol/L, N15: 15 mmol/L, and N20: 20 mmol/L) to assess the effects of N supply level on growth, photosynthesis, and carbon and nitrogen metabolism. The results revealed a time-dependent dynamics in beet biomass accumulation, with N20 inducing chlorosis and necrosis symptoms by 10 days post-treatment (DPT), resulting in the lowest biomass. While N15 significantly promoted root biomass by 30 DPT, showing a 23.70% (root dry weight, RDW) increase over N20; chlorophyll content and gas exchange parameters-net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr) exhibited significant N dependence, with N15 maintaining high chlorophyll level (0.78 mg/g) and photosynthetic rate (220.33 μmol/(m²·s). Nitrogen assimilation, as indicated by glutamine synthetase and glutamate synthetase activity (GS and GOGAT), was stronger under N15, promoting amino acid synthesis and root growth, whereas N20 inhibited enzyme activity. Carbon metabolism analysis revealed that N15-driven sucrose synthesis significantly increased root sucrose content, sucrose phosphate synthase and sucrose synthase activity (SPS and SS), optimizing source–sink allocation. Correlation analysis showed a positive relationship between leaf and root biomass (r = 0.91), and root sucrose content was positively correlated with GOGAT activity (r = 0.90), emphasizing the synergistic regulation of C/N metabolism. On the contrary, N20 led to disrupted C/N metabolic homeostasis, inhibited enzyme activity, and C/N distribution. These results indicated that the photosynthetic output, enzyme efficiency, and sucrose distribution were coordinated by nitrogen optimization, and the growth of sugar beet seedlings was optimized. Full article

With the increasing consumer demand for healthy and natural foods, strawberries have emerged as one of the most popular small berries globally. Consequently, careful investigation of the relationship between leaf photosynthetic activity (source strength) and fruit development (sink strength) during strawberry growth provides important insights for maximizing the production potential of this crop. This objective necessitates accurate strawberry organ segmentation. Recently, advancements in deep learning (DL) have driven the development of numerous semantic segmentation models that have performed effectively on benchmark datasets. Nevertheless, their small-organ plant segmentation efficacy remains insufficiently explored. Consequently, this study evaluates eight representative point-based semantic segmentation models for the strawberry organ segmentation task: PointNet++, PointMetaBase, Point Transformer V2, Swin3D, KPConv, RandLA-Net, PointCNN, and Sparse UNet. The employed dataset comprises two components: the open-source LAST-Straw strawberry dataset and a custom Japanese strawberry dataset. Strawberry point cloud organs were categorized into four classes: leaf, stem, flower, and berry. The sparse convolution-based Sparse UNet achieved the highest mean intersection over union of 81.3, followed by the PointMetaBase model at 80.7. This study provides insights into the strengths and limitations of existing architectures, assisting researchers and practitioners in selecting appropriate models for strawberry organ segmentation tasks. Full article

The high demands of corn (Zea mays L.) grain production coupled with water quality goals and phosphorus (P) conservation pose a great challenge to farmers and society and necessitate improved P utilization efficiency (PUtE: grain yield per mass total P (TP) content). The objective of this study was to evaluate PUtE among six Pioneer corn hybrids released over a span of 75 years. Corn was grown in a sand culture hydroponics system that eliminated confounding plant–soil interactions and root architecture and allowed for precise control of nutrient availability. Four P concentration levels (4, 7, 10, and 12 mg P L⁻¹) were applied to hybrids released in 1936, 1942, 1946, 1952, 2008, and 2011. Nutrients other than P were applied at sufficient levels. Shoots and roots were harvested at maturity (R6) and biomass and P concentration determined. Results showed that total biomass did not differ among hybrids, but partitioning of biomass varied with hybrid. Grain yield varied between hybrids, but there was no trend with the year of release. Grain P content was negatively correlated with stem P content (R² = 0.89). PUtE differed between the most recently released hybrids (2008 and 2011) whereas older hybrids had intermediate and similar PUtE. Grain yield was not solely determined by TP in the plant, but was strongly influenced by biomass and P partitioning, which was manifested as relative differences in PUtE between hybrids. While the PUtE did not necessarily change as a function of the breeding period, there were differences between hybrids. The findings highlight the critical role of the source–sink relationship in determining PUtE and grain yield. Full article