Search Results (2,488)

The search for renewable energy sources has driven the desire for knowledge about the energy source of photovoltaic systems and the factors that can influence it. This study applies powerful machine learning techniques to identify the best model for predicting photovoltaic energy generation, using meteorological variables as key inputs. The energy generated data were collected in a photovoltaic plant installed in the city of Pontes e Lacerda, while the meteorological variables were collected from nearby INMET stations. Four different techniques were employed, including SVR (Support Vector Machine), Random Forest, LSTM Neural Network and SARIMAX. The results showed that the Random Forest technique presented the best performance, with calculated values for the coefficient of determination (R²) and Willmott index of 0.909 and 0.972, respectively, standing out for accuracy and efficiency in scenarios where data is available. On the other hand, it was revealed that the model generated by the SARIMAX technique had great potential for applications where there is little data availability, presenting satisfactory estimates. This study highlights the practical applications of machine learning in optimizing photovoltaic power generation plant design and management, including improving energy prediction accuracy, enabling better decision-making, and supporting the expansion of renewable energy sources, especially in areas with scarce data. The findings also reinforce the critical role of meteorological variables in influencing the performance of photovoltaic systems, offering valuable insights for future applications in energy systems planning and operation. Full article

Rapid and accurate identification of maize architecture characteristics is important for understanding both yield potential and crop breeding experiments. Most canopy architecture indicators cannot fully reflect the vertical leaf distribution in field environments. We conducted field experiments on sixty maize cultivars under four planting densities at three different sites, and herein introduce two novel indicators, “kurtosis and skewness,” based on the manually measured leaf area index (LAI) of maize at five different canopy heights. Then, we constructed the LAI, plant height (PH), kurtosis, and skewness estimation models based on unmanned aerial vehicle multispectral, RGB, and laser detecting and ranging data, and further assessed the canopy architecture and estimated yield. The results showed that the fitting coefficient of determination (R²) of cumulative LAI values reached above 0.97, and the R² of the four indicators’ estimation models based on multi-source data were all above 0.79. A high LAI, along with greater kurtosis and skewness, optimal PH levels, and strong stay-green ability, are essential characteristics of high-yield maize. Moreover, the four indicators demonstrated high accuracy in estimating yield, with the R² values based on measured canopy indicators at the four planting densities being 0.792, 0.779, 0.796, and 0.865, respectively. Similarly, the R² values for estimated yield based on estimated canopy indicators were 0.636, 0.688, 0.716, and 0.775, respectively. These findings provide novel insight into maize architecture characteristics that have potential application prospects for efficient estimation of maize yield and the breeding of ideal canopy architecture. Full article

This study aims to investigate the regulatory effect of exogenous melatonin (MT) on the growth and development of cucumbers subjected to salt stress. Using the XinTaiMiCi material and indoor pot culture method, seven treatments were set up: control group (CK), T0 (salt treatment group, 150 mM S + 0 μM MT), T1 (150 mM S + 25 μM MT), T2 (150 mM S + 50 μM MT), T3 (150 mM S + 100 μM MT), T4 (150 mM S + 150 μM MT), and T5 (150 mM S + 200 μM MT). Changes in plant height, stem diameter, leaf area, relative chlorophyll content, antioxidant enzyme activity, reactive oxygen species content, and osmotic adjustment substance content in cucumber seeds and seedlings under different treatments were studied, and a correlation analysis of these indicators was conducted. Meanwhile, the expression of salt stress-related genes was detected in all seven treatment groups. The results showed that, compared to the CK, T0 significantly reduced the hypocotyl length, root length, hypocotyl diameter, root diameter, and fresh and dry weights of cucumber seeds; in the later stage of salt stress treatment, T0 significantly increased the activities of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and malondialdehyde (MDA) and the content of soluble protein in seeds. Additionally, T0 significantly increased the plant height, root length, stem diameter, leaf area, and fresh and dry weights of cucumber seedlings per plant; in the later stage of salt stress treatment, T0 significantly increased the activities of SOD, POD, CAT, and MDA and the content of soluble protein and chlorophyll in leaves. Compared to T0, the application of 50 μmol·L⁻¹ MT under salt stress significantly increased the plant height, stem diameter, root length, leaf area, and fresh and dry weights of cucumber seedlings per plant; significantly increased the activities of SOD, POD, and CAT; decreased the MDA activity; and significantly increased the content of soluble protein and chlorophyll. Under salt stress conditions, the exogenous application of low-concentration melatonin increased the expression levels of salt stress response genes (such as CsSOS, CsNHX, CsHSF, and CsDREB) in cucumber. The germination rate (GR), germination potential (GP), germination index (GI), plant height (PH), root length (RL), leaf area index (LAI), fresh weight (FW), dry weight (DW), soluble protein (SP), relative chlorophyll content (SPAD), POD, CAT, and SOD of cucumber seedlings exhibited significant positive correlations, whereas they were negatively correlated with MDA content. In conclusion, the application of 50 μM MT can effectively alleviate the oxidative and osmotic stress caused by a high-salt environment in cucumber, promote cucumber growth, and improve salt tolerance. Full article

Low plant stands at early crop establishment contribute to yield reduction in legumes. Gap-filling has been suggested as a mechanism to mitigate these losses. There is, however, limited understanding of a yield-compensation mechanism in the cowpea. This study aimed to investigate the mechanism of yield-compensation in some accessions of cowpeas at Minjibir and Shika in Northern Nigeria. The experiment was laid out in a split plot fitted into a randomized complete block design in three replicates. The main plot consisted of four plant densities (33,333; 66,666; 99,999; 133,333 plants ha⁻¹) while the subplots consisted of six cowpea accessions (IT89KD-288, IT93K-452-1, IT99K-537-1-1, IT98K-205-8, IT08K-150-27, and DANILA). Results showed that plant density and environment affected grain yield. Total grain yield increased with increasing plant density and was higher at Minjibir than at Shika. The highest total grain yield of 1793.3 kg ha⁻¹ was observed in the accession DANILA at 99,999 plants ha⁻¹, while the lowest (1100 kg ha⁻¹) was observed in the accession IT98K-205-8 at 33,333 plants ha⁻¹. Leaf area index, stand count at harvest, and intercepted photosynthetically active radiation were positively correlated with total grain yield at both locations, suggesting that these traits could be considered for cowpea improvement. Cowpea growers and breeders could consider the erect (IT93K-452-1 and IT98K-205-8) and semi-erect accessions (IT99K-573-1-1 and IT08K-150-27) for cultivation at 133,333 plants ha⁻¹. Prostrate accessions (IT89KD-288 and DANILA) could be planted at 99,999 plants ha⁻¹ at Minjibir. The accessions IT93K-452-1-1, IT98-205-8, IT99K-573-1-1, and IT08K-150-27 could be considered for cultivation at Shika irrespective of plant density. Full article

This study aimed to evaluate the impact of vineyard cultivation time and the use of metal-based fungicides on the chemical fractions of soil organic matter (SOM) as well as their interactions with Cu, Zn, and Mn in vineyard soils from Southern Brazil with varying histories of fungicide application. Soil samples were collected in 2017 from vineyards aged 35, 37, and 39 years in the Serra Gaúcha region and 13, 19, and 36 years in the Campanha Gaúcha. In each region, samples were also collected from a non-anthropized reference area. In the oldest vineyards, sampling was conducted both within and between the rows of planting. Chemical fractionation of SOM was performed: non-humic substances (nHSs), particulate organic matter (POM), fulvic acid (FA), humic acid (HA), and humin (Hu). Fourier-transform infrared (FTIR) spectra were obtained for the HA, from which the aromaticity index (AI) and relative intensities (RIs) were calculated. In each SOM fraction, total organic carbon and the concentrations of Cu, Zn, and Mn were determined. Changes in land use alter the forms and distribution of soil organic carbon (SOC) and, consequently, of metals. Elemental and spectroscopic analyses of HS revealed that HA in the reference areas (forest and native grassland) was more aliphatic and had higher concentrations of polysaccharides, indicating fractions with a lower degree of stabilization. However, in vineyard areas, HA exhibited greater humification and aromaticity. Increasing cultivation time gradually increased soil carbon content, indicating that viticultural agroecosystems can sequester carbon in the soil over time, reaching levels similar to those observed in the reference areas. When comparing vineyard areas alone, with row collections and inter-row collections, we observed an increase in SOC levels in areas managed with cover crops, demonstrating the importance of conservation management in these areas. When evaluating the distribution of metals in these soils, we could observe the high affinity of Cu for the functional groups of SOM, with FA and HA responsible for the complexation of these elements in the soil. For Zn and Mn, the greatest accumulations were observed in the Hu fraction due to their greater affinity for soil clay minerals. This shows that soil organic matter is a key component in the complexation of metals in soils, reducing their availability and potential toxicity to cultivated plants. Full article

Since 2000, antioxidant research in Chile has shown steady growth, from the chemical sciences to their application in biomedical sciences, functional foods, reproduction, and environmental studies. This study presents a bibliometric analysis of Chilean scientific output in the field of antioxidants from 2000 to 2024, organized into five-year intervals. A total of 3190 research articles indexed in the Web of Science (WoS) database were analyzed. Bibliometric indicators—including Price’s, Bradford’s, and Zipf’s laws—were applied to assess literature growth, authorship concentration, journal dispersion, and keyword evolution. Key findings include (i) high productivity from institutions such as the Universidad de Chile, Pontificia Universidad Católica de Chile, Universidad de Santiago de Chile, and Universidad de Concepción; (ii) the identification of leading authors such as Dr. Antonio Vega-Gálvez, Dr. Guillermo Schmeda-Hirschman, and Dr. Mario J. Simirgiotis; and (iii) the consolidation of three main research areas: biomedical applications (e.g., cancer, cardiovascular, and neurodegenerative diseases), food science and technology (e.g., antioxidant properties, and agro-industrial waste revalorization), and ethnopharmacology (e.g., native plant use). This study made it possible to map the state of the art of antioxidant research in Chile and identify key players and research lines, consolidating a comprehensive vision of scientific development in this field. Full article

Under the “double security” goal of achieving both food security and ecological protection, this study explores the green and low-carbon utilization efficiency of cultivated land (GLCUECL) in the Huaihe River Ecological Economic Belt (HREEB). This study identifies the spatiotemporal evolution characteristics and trends, promoting the green, low-carbon, and sustainable utilization of arable land resources in the HREEB, thus contributing to regional and national food and ecological security. Using a global super-efficiency EBM framework that accounts for undesirable outputs, as well as the GML index, the researchers measured and decomposed the GLCUECL in 25 prefecture-level cities of the HREEB from 2005 to 2021. The Theil index and kernel density estimation were applied to analyze regional disparities and changing developmental traits. Spatial convergence and divergence were assessed using the coefficient of variation and spatial convergence models. Key findings include the following: (1) Over time, the GLCUECL in the HREEB exhibited an overall upward trend and a non-equilibrium characteristic, namely the “East Sea-river-lake Linkage Area (ESLA) > Midwest Inland Rising Area (MIRA) > Huaihe River Ecological Economic Belt (HREEB) > North Huaihai Economic Zone (NHEZ)”. The increase in the GML index of the GLCUECL is mainly attributable to a technical progress change. (2) The overall difference in the GLCUECL tends to decline, which is mainly attributable to the intra-regional differences. (3) The overall kernel density curves for the HREEB and its three sub-regions exhibited a “rightward shift” trend. Except for the expansion and polarization of the absolute difference in the GLCUECL in the NHEZ, the absolute difference in GLCUECL in other regions, such as the HREEB, ESLA, and MIRA, exhibited a decreasing trend. (4) Spatial convergence analysis revealed that only the NHEZ lacks σ-convergence, whereas all regions exhibited β-convergence. Moreover, factors such as rural economic development level, cultivated land resource endowment, agricultural subsidy policy, crop planting structure, and technological input exerted a heterogeneous effect on the change in the GLCUECL. Based on these findings, this study offers recommendations for improving GLCUECL in the HREEB. Our recommendations include the implementation of the concept of green new development, optimization of the institution supply, establishing a regional cooperation mechanism for green and low-carbon utilization of cultivated land, and formulation of differentiated paths for improving the green and low-carbon utilization efficiency of cultivated land according to local conditions. Full article

Accumulation of copper (Cu) in soils devoted to intensive agriculture due to anthropogenic additions is becoming a significant threat to plant productivity. Biological inoculants may play an important role in alleviating toxic effects of heavy metals on plants. The plant-growth-promoting rhizobacteria (PGPR) Bacillus subtilis subsp. spizizenii has demonstrated the ability to reduce harmful impacts of heavy metals on crops. This study aimed to evaluate the suitability of seed inoculation with biofilm produced by this bacterium to mitigate the severity of Cu toxicity on tomato. In the laboratory, first, B. subtilis was cultivated under increased Cu concentrations. Then, germination of inoculated and non-inoculated tomato seeds was tested for Cu concentrations of 0, 50, 100, 150, and 200 ppm. Next, a greenhouse experiment was conducted for four months to assess the effects of both inoculation and excess 150 ppm Cu in the substrate. The studied treatments included control, no inoculation and Cu surplus, inoculation and no Cu surplus, and inoculation plus Cu surplus. In the laboratory, first, the bacterium’s ability to grow in a liquid medium containing Cu was confirmed. Thereafter, we verified that the germination of non-inoculated seeds was negatively affected by Cu, with higher concentrations leading to a more detrimental effect. However, seed inoculation with biofilm mitigated the adverse impact of Cu on germination. Under greenhouse conditions, excess Cu significantly reduced root dry weight, tomato number, and tomato yield compared with the control, whereas shoot dry weight, plant height, leaf area, and soluble solid concentration (Brix index) did not experience significant changes (p < 0.05). However, seed inoculation mitigated the toxic effects of excess Cu, significantly enhancing all the aforementioned plant parameters, except plant height. Seed inoculation also significantly reduced the Cu contents in the fruits of tomato plants growing in the metal contaminated substrate. The biofilm of the B. subtilis strain used demonstrated its effectiveness as a bioinoculant, attenuating the detrimental effects induced by a substrate with excess Cu. Full article

Hippophae rhamnoides subsp. sinensis Rousi has high ecological and medicinal value, and it is an important plant resource unique to the arid regions of Northwest China. Exploring the influence of climate characteristics and soil factors on the composition, diversity, and function of the rhizosphere bacterial community of Chinese seabuckthorn is of great value for developing and popularizing characteristic plant resources in the arid regions of Northwest China. In this study, the rhizosphere soil of 13 Chinese seabuckthorn distribution areas in the northwest of China was taken as the research object, the bacterial community map was constructed based on 16S rRNA gene high-throughput sequencing technology, and the species abundance composition, structural diversity, molecular co-occurrence network, and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt), as well as the function of rhizosphere soil bacterial community, were systematically studied. Combined with Mantel test and redundancy analysis (RDA), the key habitat factors driving the rhizosphere soil bacterial community structure of Chinese seabuckthorn were explored. The results showed that: (1) The number of amplicon sequence variants (ASVs) in rhizosphere soil bacterial community of Chinese seabuckthorn was the highest in S2(3072) and the S12(3637), and the lowest in the S11(1358) and S13(1996). The rhizosphere soil bacterial community was primarily composed of Proteobacteria, Actinobacteriota, and Acidobacteriota. Except for the S6 and S11 habitats, the dominant bacterial genera were mainly Achromobacter, Acidobacter (RB41), and Sphingomonas. (2) The α and β diversity of rhizosphere soil bacterial communities of Chinese seabuckthorn across 13 distribution areas were significantly different. The number of operational taxonomic units (OTUs), Ace index, and Chao 1 index of soil bacterial community in the S12 distribution area are the highest, and they are the lowest in S11 distribution area, with significant differences. The aggregation of soil bacterial communities in the S5 and S10 distribution areas is the highest, while it is the lowest in the S6 and S11 distribution areas. (3) PICRUSt function classification of soil bacteria showed that Metabolism and Genetic Information Processing functions were the strongest across all distribution areas, with S10 exhibiting higher functional capacity than other areas and S11 showing the weakest. (4) Cluster analysis revealed that soil bacteria across the 13 distribution areas were clustered into two groups, with S10 and S12 distribution areas as one group (Group 1) and the remaining 11 distribution areas as another group (Group 2). (5) Redundancy analysis revealed that pH was the key soil environmental factor driving the rhizosphere soil bacterial community α-diversity of Chinese seabuckthorn, followed by altitude (ALT) and soil water content (SWC). In summary, Chinese seabuckthorn prefers neutral to alkaline soils, and environmental factors play an important role in driving bacterial diversity, community structure, functional profiles, and co-occurrence networks in rhizosphere soil of Chinese seabuckthorn. Full article

The objective of the study was to develop and validate a ground-based method using a depth image sensor equipped with depth, visible red, green, blue (RGB), and near-infrared bands to measure the leaf area index (LAI) based on the relative illuminance of foliage only. The method was applied in a Itajii chinkapin (Castanopsis sieboldii (Makino) Hatus. ex T.Yamaz. & Mashiba )forest in Aichi Prefecture, Japan, and validated by comparing estimates with conventional methods (LAI-2200 and fisheye photography). To apply the 5-band sensor to actual forests, a methodology is proposed for matching the color camera and near-infrared camera in units of pixels, along with a method for widening the exposure range through multi-step camera exposure. Based on these advancements, the RGB color band, near-infrared band, and depth band are converted into several physical properties. Employing these properties, each pixel of the canopy image is classified into upper foliage, lower foliage, sky, and non-assimilated parts (stems and branches). Subsequently, the LAI is calculated using the gap-fraction method, which is based on the relative illuminance of the foliage. In comparison with existing indirect LAI estimations, this technique enabled the distinction between upper and lower canopy layers and the exclusion of non-assimilated parts. The findings indicate that the plant area index (PAI) ranged from 2.23 to 3.68 m² m⁻², representing an increase from 33% to 34% compared to the LAI calculated after excluding non-assimilating parts. The findings of this study underscore the necessity of distinguishing non-assimilated components in the estimation of LAI. The PAI estimates derived from the depth image sensor exhibited moderate to strong agreement with the LAI-2200, contingent upon canopy rings (R² = 0.48–0.98), thereby substantiating the reliability of the system’s performance. The developed approaches also permit the evaluation of the distributions of leaves and branches at various heights from the ground surface to the top of the canopy. The novel LAI measurement method developed in this study has the potential to provide precise, reliable foundational data to support research in ecology and hydrology related to complex tree structures. Full article

The urban heat island (UHI) effect has emerged as a growing ecological challenge in compact urban environments. Although urban vegetation plays a vital role in mitigating thermal extremes, its cooling performance varies depending on vegetation type and urban morphological context. This study explores the extent to which compact urban development—quantified using the Mixed-use and Intensive Development (MIXD) index—modulates the cooling responses of different vegetation types in Nanjing, China. A combination of landscape metrics, regression-based interaction models, and XGBoost with SHAP analysis is employed to uncover vegetation-specific and structure-sensitive cooling effects. The results indicate that densely planted trees exhibit reduced cooling effectiveness in compact areas, where spatial clustering and fragmentation tend to intensify UHI effects, particularly during nighttime. In contrast, scattered trees are found to maintain more stable cooling performance across varying degrees of urban compactness, while low-lying vegetation demonstrates limited thermal regulation capacity. Critical thresholds of MIXD (approximately 28 for UHI area and 37 for UHI intensity) are identified, indicating a nonlinear modulation of green space performance. These findings underscore the importance of vegetation structure and spatial configuration in shaping urban microclimates and offer mechanistic insights into plant–environment interactions under conditions of increasing urban density. Full article

Planting patterns and irrigation amounts are key factors affecting maize yield. This study adopted a two-factor experimental design, with planting pattern as the main plot and irrigation amount as the subplot, to investigate the effects of irrigation levels under different planting patterns (including uniform row spacing and alternating wide-narrow row spacing) on spring maize yield and water use efficiency in Xinjiang. Through this approach, the study examined the mechanisms by which planting pattern and irrigation amount influence maize growth, yield formation, and water use efficiency. Experiments conducted at the Agricultural Science Research Institute of the Ninth Division of Xinjiang Production and Construction Corps demonstrated that alternating wide-narrow row spacing combined with moderate irrigation (5400 m³/hm²) significantly optimized maize root distribution, improved water use efficiency, and increased leaf area index and net photosynthetic rate, thereby promoting dry matter accumulation and yield enhancement. In contrast, uniform row spacing under high irrigation levels increased yield but resulted in lower water use efficiency. The study also found that alternating wide-narrow row spacing enhanced maize nutrient absorption from the soil, particularly phosphorus utilization efficiency, by improving canopy structure and root expansion. This pattern exhibited comprehensive advantages in resource utilization, providing a theoretical basis and technical pathway for achieving water-saving and high-yield maize production in arid regions, which holds significant importance for promoting sustainable agricultural development. Full article

Longnan is the largest olive cultivation area in China. The unique microclimates in Longnan make it an ideal testing ground for climate-resilient cultivation strategies with broader applications across similar regions, yet predictive models linking weather to oil quality remain scarce. This study establishes a climate suitability evaluation model for olive cultivation in central Longnan based on meteorological data and olive quality data in the Fotanggou planting base. Four key climatic factors are identified: cumulative sunshine hours during the fruit coloring to ripening period, average temperature during the fruit coloring to harvesting period, number of cloudy and rainy days during the harvesting period, and relative humidity during the fruit setting to fruit enlargement period. Olive oil quality is graded into three levels (Excellent III, Good II, Fair I) based on acidity, linoleic acid, and peroxide value using K-means clustering. A climate suitability index is developed by integrating these factors, with weights determined via principal component analysis. The model is validated against an olive quality report from the Dabao planting base, showing an 80% match rate. From 1991 to 2023, 87.9% of years exhibit suitable or moderately suitable conditions, with 100% of years in the past decade (2014–2023) reaching “Good” or “Excellent” levels. This model provides a scientific basis for evaluating and predicting olive oil quality, supporting sustainable olive industry development in Longnan. This model provides policymakers and farmers with actionable insights to ensure the long-term sustainability of olive industry amid climate uncertainty. Full article

The sustainable utilization of saline water resources represents an effective strategy for alleviating water scarcity in arid regions. However, the mechanisms by which prolonged saline water irrigation influences soil salinization and dryland crop growth are not yet fully understood. This study examined the effects of six irrigation water salinity levels (CK: 0.87 g·L⁻¹, S1: 2 g·L⁻¹, S2: 4 g·L⁻¹, S3: 6 g·L⁻¹, S4: 8 g·L⁻¹, S5: 10 g·L⁻¹) on soil salinization dynamics and jujube growth during a three-year field experiment (2020–2022). The results showed that soil salinity within the 0–1 m profile significantly increased with rising irrigation water salinity and prolonged irrigation duration, with the 0–0.4 m layer accounting for 50.27–74.95% of the total salt accumulation. A distinct unimodal salt distribution was observed in the 0.3–0.6 m soil zone, with the salinity peak shifting downward from 0.4 to 0.5 m over time. Meanwhile, soil pH and sodium adsorption ratio (SAR) increased steadily over the study period. The dominant hydrochemical type shifted from SO₄²⁻-Ca²⁺·Mg²⁺ to Cl⁻-Na⁺·Mg²⁺. Crop performance exhibited a nonlinear response to irrigation salinity levels. Low salinity (2 g·L⁻¹) significantly enhanced plant height, stem diameter, leaf area index (LAI), vitamin C content, and yield, with improvements of up to 12.11%, 3.96%, 16.67%, 16.24%, and 16.52% in the early years. However, prolonged exposure to saline irrigation led to significant declines in both plant growth and water productivity (WP) by 2022. Under high-salinity conditions (S5), yield decreased by 16.75%, while WP declined by more than 30%. To comprehensively evaluate the trade-off between economic effects and soil environment, the entropy weight TOPSIS method was employed to identify S1 as the optimal irrigation treatment for the 2020–2021 period and control (CK) as the optimal treatment for 2022. Through fitting analysis, the optimal irrigation water salinity levels over 3 years were determined to be 2.75 g·L⁻¹, 2.49 g·L⁻¹, and 0.87 g·L⁻¹, respectively. These findings suggest that short-term irrigation of jujube trees with saline water at concentrations ≤ 3 g·L⁻¹ is agronomically feasible. Full article

Excessive nitrogen (N) fertilizer usage in agriculture has prompted the exploration of sustainable strategies to enhance nitrogen use efficiency (NUE) while maintaining crop yield and quality. Processed tomatoes (Solanum lycopersicum L.) were grown for two years (2023 and 2024) following a two-way factorial randomized complete block (RCBD) design, considering three biostimulants and three N regimes as two factors, to assess their morphophysiological, biochemical, anatomical and yield performances. Nitrogen application significantly influenced biomass accumulation, the leaf area index (LAI), nitrogen uptake and yield with notable comparable values between reduced and optimal nitrogen dose, indicating improved nitrogen use efficiency. Biostimulants showed limited effects alone but enhanced plant performance under reduced nitrogen conditions, particularly improving chlorophyll content, crop growth, N uptake, yield and anatomical adaptations. Moreover, compared to 2024, biostimulant application enhanced tomato growth more evidently in 2023 due to environmental variations, likely due to the occurrence of stress conditions. Importantly, biostimulants, together with N regimes, i.e., optimal and reduced doses, showed improved anatomical traits, especially regarding leaf thickness and thickness between the two epidermises, indicating adaptive responses that may support sustained productivity under N-limited conditions. Among the biostimulants used, the processed tomatoes responded better to protein hydrolysate and endophytic N-fixing bacteria than to seaweed extract. These findings suggest that although biostimulants alone were not affected, integrating them with reduced N fertilization provides a viable strategy for optimizing tomato production, conserving resources and minimizing the environmental impact without compromising yield or quality. Full article