Search Results (1,292)

The high pH and heavy metal leaching of argon oxygen decarburization (AOD) slag limit its application in agriculture. Slag carbonation can aid in decreasing slag alkalinity and inhibit heavy metal release; the environmental safety of utilizing carbonated AOD slag (CAS) as a fertilizer remains a topic of significant debate, however. In this work, pakchoi (Brassica chinensis L.) was planted in CAS-fertilized soil to investigate the accumulation and migration behavior of heavy metals in the soil–plant system and perform an associated risk assessment. Our results demonstrated that CAS addition increases Ca, Si, and Cr concentrations but decreases Mg and Fe concentrations in soil leachates. Low rates (0.25–1%) of CAS fertilization facilitate the growth of pakchoi, resulting in the absence of soil contamination and posing no threat to human health. At the optimal slag addition rate of 0.25%, the pakchoi leaf biomass, stem biomass, leaf area, and seedling height increased by 34.2%, 17.2%, 26.3%, and 8.7%, respectively. The accumulation of heavy metals results in diverging characteristics in pakchoi. Cr primarily accumulates in the roots; in comparison, Pb, Cd, Ni, and Hg preferentially accumulate in the leaves. The migration rate of the investigated heavy metals from the soil to pakchoi follows the order of Cr > Cd > Hg > Ni > Pb; in comparison, that from the roots to the leaves follows the order Cd > Ni > Hg > Cr > Pb. Appropriate utilization of CAS as a mineral fertilizer can aid in improving pakchoi yield, achieving sustainable economic benefits, and preventing environmental pollution. Full article

Cowpea (Vigna unguiculata [L.] Walp) is a vital food security crop in sub-Saharan Africa, including Eswatini. The productivity of the crop is low (<600 kg/ha) in the country due to a lack of improved, locally adapted, and farmer-preferred varieties with biotic and abiotic stress tolerance. The objective of the study was to assess the agronomic performance of newly developed elite cowpea mutants to select best-yielding and adapted pure lines for production and genetic improvement in Eswatini. A total of 30 cowpea genotypes, including 24 newly developed advanced mutant lines, their 3 founder parents and 3 local checks, were profiled for major agronomic traits in two selected sites (Lowveld Experiment and Malkerns Research Stations) using a 6 × 5 alpha lattice design with three replications. A combined analysis of variance revealed that the genotype x location interaction effects were significant (p < 0.05) for germination percentage (DG %), days to flowering (DTF), days to maturity (DMT), number of pods per plant (NPP), pod length (PDL), number of seeds per pod (NSP), hundred seed weight (HSW), and grain yield (GYD). Elite mutant genotypes, including NKL9P7, BRR4P11, SHR9P5, and NKL9P7-2 exhibited higher grain yields at 3158.8 kg/ha, 2651.6 kg/ha, 2627.5 kg/ha, and 2255.8 kg/ha in that order. The highest-yielding mutant, NKL9P7, produced 70%, 61%, and 54% more grain yield than the check varieties Mtilane, Black Eye, and Accession 792, respectively. Furthermore, the selected genotypes displayed promising yield components such as better PDL (varying from 13.1 to 26.3 cm), NPP (15.9 to 26.8), and NSP (9.8 to 16.2). Grain yield had significant positive correlations (p < 0.05) with DG %, NSP, and NPP. The principal component analysis (PCA) revealed that 81.5% of the total genotypic variation was attributable to the assessed quantitative traits. Principal component (PC) 1 accounted for 48.6%, while PC 2 and PC 3 contributed 18.9% and 14% of the overall variation, respectively. Key traits correlated with PC1 were NPP with a loading score of 0.91, NSP (0.83), PDL (0.73), GYD (0.68), HSW (0.58), DMT (−0.60), and DTF (−0.43) in a desirable direction. In conclusion, genotypes NKL9P7, BRR4P11, SHR9P5, NKL9P7-2, Bira, SHR3P4, and SHR2P7 were identified as complementary parents with relatively best yields and local adaptation, making them ideal selections for direct production or breeding. The following traits, NPP, NSP, PDL, GYD, and HSW, offered unique opportunities for genotype selection in the cowpea breeding program in Eswatini. Full article

Late sowing and spring low temperatures have a great impact on the growth and maturation of wheat in the rice–wheat rotation region. In order to analyze the impacts of cold stress in February in early spring on yield formation and agronomic traits of wheat on different sowing dates, a controlled pot experiment was performed using the widely promoted and applied spring-type wheat variety Yangmai23 (YM23). The yield of wheat treated with late sowing date II (SDII, 21 November) and overly late sowing date III (SDIII, 9 December) were both lower than that of wheat sown on the suitable date I (SDI, 1 November). The yield of late-sown wheat decreased by 40.82% for SDII and by 66.77% for SDIII, compared with SDI, and these three treatments of wheat all grew under the natural conditions as the control treatments. The plant height, stem diameter of the internode below the ear, flag leaf length and area, and total awn length of the spike, as well as the spike length of late-sown wheat, were all significantly lower than those of wheat in SDI treatment. Early spring low temperatures exacerbated the decline in yield of wheat sown on different dates, to some extent. Despite showing higher net photosynthetic rate, stomatal conductance, and transpiration rate in flag leaves of the SDIII treatment under low-temperature stress than those of the other treatments at anthesis, overly late sowing led to minimal leaf area, shorter plant height, fewer tillers, and smaller ears, ultimately resulting in the lowest yield. Our study suggested that additional focus and some regulation techniques are needed to be studied further to mitigate the combined negative impacts of late sowing and low-temperature stress in early spring on wheat production. Full article

The control of following motion under mesoscale gap flow fields has important applications. The flexible characteristics of the plant, wideband time-varying disturbances caused by the flow field, and requirements of high precision and low overshoot make achieving submicron level accuracy a significant challenge for traditional control methods. This study adopts the control concept of Disturbance Observer Control (DOBC) and uses H_∞ mixed-sensitivity shaping technology to design a Q-filter. Simultaneously, multiple control techniques, such as high-order reference trajectory planning, Proportional-Integral-Derivative (PID) control, low-pass filtering, notch filtering, lead lag correction, and disturbance rejection filtering, are applied to obtain a control system with a high open-loop gain, sufficient phase margin, and stable closed-loop system. Compared to traditional control methods, the new method can increase the open-loop gain by 15 times and the open-loop bandwidth by 8%. We even observed a 150-time increase of the open-loop gain at the peak frequency. Ultimately, the method achieves submicron level accuracy, making important advances in solving the control problem of semiconductor equipment. Full article

Straw mulching is an important strategy for regulating soil moisture, nutrient availability, and thermal conditions in agricultural systems. However, the mechanisms by which the mulching period, thickness, and planting density interact to influence yield formation in wheat–soybean rotation systems remain insufficiently understood. In this study, we systematically examined the combined effects of straw mulching at the seedling and jointing stages of winter wheat, as well as varying mulching thicknesses and soybean planting densities, on soil properties and crop yields through field experiments. The experimental design included straw mulching treatments during the seedling stage (T₁) and the jointing stage (T₂) of winter wheat, with soybean planting densities classified as low (D₁, 1.8 × 10⁵ plants·ha⁻¹) and high (D₂, 3.6 × 10⁵ plants·ha⁻¹). Mulching thicknesses were set at low (S₁, 2830.19 kg·ha⁻¹), medium (S₂, 8490.57 kg·ha⁻¹), and high (S₃, 14,150.95 kg·ha⁻¹), in addition to a no-mulch control (CK) for each treatment. The results demonstrated that (1) straw mulching significantly increased soil water content in the order S₃ > S₂ > S₁ > CK and exerted a temperature-buffering effect. This resulted in increases in soil organic carbon, available phosphorus, and available potassium by 1.88−71.95%, 1.36−165.8%, and 1.92−36.34%, respectively, while decreasing available nitrogen content by 1.42−17.98%. (2) The T₁ treatments increased wheat yields by 1.22% compared to the control, while the T₂ treatments resulted in a 23.83% yield increase. Soybean yields increased by 23.99% under D₁ and by 36.22% under D₂ treatments. (3) Structural equation modeling indicated that straw mulching influenced yields by modifying interactions among soil organic carbon, available nitrogen, available phosphorus, available potassium, bulk density, soil temperature, and soil water content. Wheat yields were primarily regulated by the synergistic effects of soil temperature, water content, and available potassium, whereas soybean yields were determined by the dynamic balance between organic carbon and available potassium. This study provides empirical evidence to inform the optimization of straw return practices in wheat–soybean rotation systems. Full article

Accurate plant species identification in desert grasslands using hyperspectral data is a critical prerequisite for large-scale, high-precision grassland monitoring and management. However, due to prolonged overgrazing and the inherent ecological vulnerability of the environment, sericite–Artemisia desert grassland has experienced significant ecological degradation. Therefore, in this study, we obtained spectral images of the grassland in April 2022 using a Soc710 VP imaging spectrometer (Surface Optics Corporation, San Diego, CA, USA), which were classified into three levels (low, medium, and high) based on the level of participation of Seriphidium transiliense (Poljakov) Poljakov and Ceratocarpus arenarius L. in the community. The optimal index factor (OIF) was employed to synthesize feature band images, which were subsequently used as input for the DeepLabv3p, PSPNet, and UNet deep learning models in order to assess the influence of species participation on classification accuracy. The results indicated that species participation significantly impacted spectral information extraction and model classification performance. Higher participation enhanced the scattering of reflectivity in the canopy structure of S. transiliense, while the light saturation effect of C. arenarius was induced by its short stature. Band combinations—such as Blue, Red Edge, and NIR (BREN) and Red, Red Edge, and NIR (RREN)—exhibited strong capabilities in capturing structural vegetation information. The identification model performances were optimal, with a high level of S. transiliense participation and with DeepLabv3p, PSPNet, and UNet achieving an overall accuracy (OA) of 97.86%, 96.51%, and 98.20%. Among the tested models, UNet exhibited the highest classification accuracy and robustness with small sample datasets, effectively differentiating between S. transiliense, C. arenarius, and bare ground. However, when C. arenarius was the primary target species, the model’s performance declined as its participation levels increased, exhibiting significant omission errors for S. transiliense, whose producer’s accuracy (PA) decreased by 45.91%. The findings of this study provide effective technical means and theoretical support for the identification of plant species and ecological monitoring in sericite–Artemisia desert grasslands. Full article

Bupleurum scorzonerifolium Willd. is a perennial herbaceous plant of the genus Bupleurum in the Apiaceae family. Also known as red Bupleurum, it is mainly distributed in Northeast China, North China and other regions and is a commonly used medicinal plant. It is difficult for the wild plant resources of Bupleurum scorzonerifolium Willd. to meet the market demand. In artificial cultivation, there are problems such as a low yield per plant, low quality, weakened stress resistance and variety degradation. The contents of bioactive components and metabolites in traditional Chinese medicinal materials vary significantly across different growth years. The growth duration directly impacts their quality and clinical efficacy. Therefore, determining the optimal growth period is one of the crucial factors in ensuring the quality of traditional Chinese medicinal materials. In this study, Gas Chromatography–Mass Spectrometry (GC-MS) and High-performance liquid chromatography (HPLC) were comprehensively applied to analyze the metabolically differential substances in different parts of Bupleurum scorzonerifolium Willd. By comparing the compositions and content differences of chemical components in different growth years and different parts, the chemical components with significant differences were accurately screened out. In order to further explore the dynamic change characteristics and internal laws of metabolites, a metabolic network was constructed for a visual analysis and, finally, to see the optimal growth years of Bupleurum scorzonerifolium Willd. This result showed that with the accumulation of the growth cycle, the height, root width, fresh mass and saikosaponins content of Bupleurum scorzonerifolium Willd. increased year by year. Except for sodium and calcium elements in the main shoot, the other elements were significantly reduced. In addition, 59 primary metabolites were identified by GC-MS, with the accumulation of the growth cycle, the contents of organic acids, sugars, alcohols and amino acids gradually decreased, while the contents of alkyl, glycosides and other substances gradually increased. There were 53 positive correlations and 18 negative correlations in the triennial Bupleurum scorzonerifolium Willd. grid, all of which were positively correlated with saikosaponins. Therefore, the triennial Bupleurum scorzonerifolium Willd. was considered to be the suitable growth year. It not only provided a new idea and method for the quality evaluation of Bupleurum scorzonerifolium Willd., but also provided a scientific basis for the quality control of Chinese herbs. Full article

This work deals with the catalytic steam reforming of raw syngas to increase the efficiency of coupling gasification with downstream processes (such as fuel cells and catalytic chemical syntheses) by producing high-temperature, ready-to-use syngas without cooling it for cleaning and conditioning. Such a combination is considered a key point for the future exploitation of syngas produced by steam gasification of biogenic solid fuel. The design and construction of an integrated gasification and gas conditioning system were proposed approximately 20 years ago; however, they still require further in-depth study for practical applications. A 3D model of the freeboard of a pilot-scale, fluidized bed gasification plant equipped with catalytic ceramic candles was used to investigate the optimal operating conditions for in situ syngas upgrading. The global kinetic parameters for methane and tar reforming reactions were determined experimentally. A fluidized bed gasification reactor (~5 kWth) equipped with a 45 cm long segment of a fully commercial filter candle in its freeboard was used for a series of tests at different temperatures. Using a computational fluid dynamics (CFD) description, the relevant parameters for apparent kinetic equations were obtained in the frame of a first-order reaction model to describe the steam reforming of key tar species. As a further step, a CFD model of the freeboard of a 100 kWth gasification plant, equipped with six catalytic ceramic candles, was developed in ANSYS FLUENT^®. The composition of the syngas input into the gasifier freeboard was obtained from experimental results based on the pilot-scale plant. Simulations showed tar catalytic conversions of 80% for toluene and 41% for naphthalene, still insufficient compared to the threshold limits required for operating solid oxide fuel cells (SOFCs). An overly low freeboard temperature level was identified as the bottleneck for enhancing gas catalytic conversions, so further simulations were performed by injecting an auxiliary stream of O₂/steam (50/50 wt.%) through a series of nozzles at different heights. The best simulation results were obtained when the O₂/steam stream was fed entirely at the bottom of the freeboard, achieving temperatures high enough to achieve a tar content below the safe operating conditions for SOFCs, with minimal loss of hydrogen content or LHV in the fuel gas. Full article

Implementing efficient strategies for the circular recovery and reuse of nutrients from wastewaters is mandatory to meet the Green Deal objectives and Sustainable Development Goals. In this context we investigated the use of zeolitic tuff (containing chabazite and phillipsite) in the selective recovery and reuse of N from various anaerobic liquid digestates in view of their implementation in farm-scale treatment plants. We tested the method on three livestock digestates and two municipal organic solid waste digestates. Adsorption isotherms and kinetics were assessed on each digestate, and a large set of parameters, including (i) contact time, (ii) initial NH₄⁺ concentration, (iii) presence of competing ions, (iv) total solids content, and (vi) separation methods (microfiltration and clarification), were considered in the experimental design. Our results showed that the adsorption mechanism can be explained by the Freundlich model (R² up to 0.97), indicating a multilayer and heterogeneous adsorption, while the kinetic of adsorption can be explained by the pseudo-second-order model, indicating chemical adsorption and ion exchange. The efficiency in the removal of NH₄⁺ was indirectly related to the K⁺ and total solids content of the digestate. Maximum NH₄⁺ removal exceeded 90% in MSW-derived digestates and 80% within 60 min in livestock-derived digestates at a 5% solid/liquid ratio. Thermodynamic parameters confirmed favorable and spontaneous adsorption (ΔG up to −7 kJ⋅mol⁻¹). Farm-scale projections estimate a nitrogen recovery potential of 1.2 to 16 kg N⋅day⁻¹, depending on digestate type and process conditions. These findings support the application of natural zeolitic tuffs as a low-cost, chemical-free solution for ammonium recovery, contributing to sustainable agriculture and circular economy objectives. Full article

Substantial boosts in the low-energy nano-oxygenation of incoming process water were achieved at a municipal wastewater treatment plant (WWTP) upstream of activated sludge (AS) aeration lanes on a single-pass basis by means of an electric field nanobubble (NB) generation method (with unit residence times of the order of just 10–15 s). Both ambient air and O₂ cylinders were used as gas sources. In both cases, it was found that the levels of dissolved oxygen (DO) were maintained far higher for much longer than those of conventionally aerated water in the AS lane—and at DO levels in the optimal operational WWTP oxygenation zone of about 2.5–3.5 mg/L. In the AS lanes themselves, there were also excellent conversions to nitrate from nitrite, owing to reactive oxygen species (ROS) and some improvements in BOD and E. coli profiles. Nanobubble-enhanced Dissolved Air Flotation (DAF) was found to be enhanced at shorter times for batch processes: settlement dynamics were slowed slightly initially upon contact with virgin NBs, although the overall time was not particularly affected, owing to faster settlement once the recruitment of micro-particulates took place around the NBs—actually making density-filtering ultimately more facile. The development of machine learning (ML) models predictive of NB populations was carried out in laboratory work with deionised water, in addition to WWTP influent water for a second class of field-oriented ML models based on a more narrow set of more easily and quickly measured data variables in the field, and correlations were found for a more facile prediction of important parameters, such as the NB generation rate and the particular dependent variable that is required to be correlated with the efficient and effective functioning of the nanobubble generator (NBG) for the task at hand—e.g., boosting dissolved oxygen (DO) or shifting Oxidative Reductive Potential (ORP). Full article

The large portion of the eukaryotic genomes was considered non-functional and called the “dark matter” of the genome, now appearing as regulatory hubs coding for RNAs without the potential for making proteins, known as non-coding RNA. Long non-coding RNA (lncRNA) is defined as functional RNA molecules having lengths larger than 200 nucleotides without the potential for coding for proteins. Thousands of lncRNAs are identified in different plants and animals. LncRNAs are characterized by a low abundance, fewer exons than mRNA, tissue-specific expression, and low sequence conservation compared to protein-coding genes (PCGs). LncRNAs, like PCGs, are regulated by promoters and enhancers with characteristic chromatin signatures, DNA methylation, multiple exons, introns, and alternate splicing. LncRNAs interact with DNA, mRNA, microRNA, and proteins, including chromatin/histone modifiers, transcription factors/repressors, epigenetic regulators, spliceosomal, and RNA-binding proteins. Recent observations indicate that lncRNAs code for small peptides, also called micropeptides (<100 amino acids), and are involved in the development and growth of plants, suggesting the bi-functional activities of lncRNAs. LncRNAs have emerged as the major regulators of diverse functions, principally by altering the transcription of target genes. LncRNAs are involved in plant growth, development, immune responses, and various physiological processes. Abiotic, biotic, nutrient, and other environmental stresses alter the expressions of numerous lncRNAs. Understanding the mechanisms of actions of lncRNAs opens up the possibility of improving agronomic traits by manipulating lncRNAs. However, further studies are required in order to find the interactions among the deregulated lncRNAs and validate the findings from high-throughput studies to harness their potential in crop improvement. Full article

The disadvantages of traditional strip fertilization technology for corn planting in China include low fertilizer utilization rates, unstable operation quality, and environmental pollution. Therefore, in this study, a synchronous hole fertilization device for corn planting based on real-time intelligent control is designed, aiming to reduce fertilizer application and increase efficiency through the precise alignment technology of the seed and fertilizer. This device integrates an electric drive precision seeding unit, a slot wheel hole fertilization unit, and a multi-sensor coordinated closed-loop control system. An STM32 single-chip micro-computer is used to dynamically analyze the seed–fertilizer timing signal, and a double closed-loop control strategy (the position loop priority is higher than the speed loop) is used to correct the spatial phase difference between the seed and fertilizer in real time to ensure the precise control of the longitudinal distance (40~70 mm) and the lateral distance (50~80 mm) of the seed and fertilizer. Through the Box–Behnken response surface method, a field multi-factor test was carried out to analyze the mechanism of influence of the implemented forward speed (A), per-hole target fertilizing amount (B), and plant spacing (fertilizer hole interval) (C) on the seed–fertilizer alignment qualification rate (Y₁) and the coefficient of variation in the hole fertilizing amount (Y₂). The results showed that the order of primary and secondary factors affecting Y₁ was A > C > B, and that the order affecting Y₂ was C > B > A; the comprehensive performance of the device was best with the optimal parameter combination of A = 4.2 km/h, B = 4.4 g, and C = 30 cm, with Y₁ as high as 94.024 ± 0.694% and Y₂ as low as 3.147 ± 0.058%, which is significantly better than the traditional strip application method. The device realizes the precise regulation of 2~6 g/hole by optimizing the structural parameters of the outer groove wheel (arc center distance of 25 mm, cross-sectional area of 201.02 mm², effective filling length of 2.73~8.19 mm), which can meet the differentiated agronomic needs of ordinary corn, silage corn, and popcorn. Field verification shows that the device significantly improves the spatial distribution of the concentration of fertilizer, effectively reduces the amount of fertilizer applied, and improves operational stability and reliability in multiple environments. This provides technical support for the regional application of precision agricultural equipment. Full article

In order to elucidate the factors regulating nutrient dynamics in plant–soil interactions across various latitudes within the karst climax community, this study focused on the karst forest climax community in Guizhou Province, Southwest China. We analyzed and compared the differences in carbon, nitrogen, and phosphorus content, as well as stoichiometry, in plant leaves and soils under various growing conditions. Additionally, redundancy analyses were conducted to investigate the stoichiometric correlations between plants and soil. The research findings indicate the following: (1) Leaf carbon content (LCC) and the carbon-to-nitrogen ratio (LCN) exhibit significant differences across various latitudes, with the lowest values observed in high-latitude regions. (2) Soil organic carbon (SOC) and the carbon-to-nitrogen ratio (SCN) also show significant variations across latitudes, with the lowest concentrations found in high-latitude regions and the highest in low-latitude regions. (3) The variability in leaf nutrient element ratios among karst region climax communities is greatest in low-latitude areas. This study found that the carbon content (LCC), nitrogen content (LNC), and carbon-to-nitrogen ratio (LCN) of leaves in karst climax community plants decrease as latitude increases. This suggests that plants regulate the nutrient utilization efficiency of carbon content (LCC), nitrogen content (LNC), and phosphorus content (LPC) in their leaves to maintain the nutrients necessary for their growth and development along the latitudinal gradient. The sensitivity of soil organic carbon (SOC), carbon-to-nitrogen (SCN), and carbon-to-phosphorus (SCP) ratios to latitudinal changes were particularly pronounced in the karst climax community. Additionally, plant leaf stoichiometry was significantly influenced by soil phosphorus content (SPC) in mid- and high-latitude regions, while factors other than soil nitrogen content (SNC) had a more substantial impact on plant leaf stoichiometry in low-latitude areas. The findings of this study are highly significant for guiding nutrient management in karst forest ecosystems and for the restoration of degraded karst forest vegetation. Full article

Driven by the demands of climate change mitigation, many countries have begun large-scale electricity production from variable renewables, such as solar PV and wind power. Electricity production from wind turbines, in particular, strongly depends on local weather conditions and their changes caused by climate change. Thus, for many countries with a high share of wind power generation, such as Germany, two essential questions arise: how will climate change affect electricity production, and how strong will be this impact for different RCPs? To better assess the impact on existing onshore wind turbines, spatially and temporally resolved data on their power generation are required. In order to create such disaggregated data, this study uses a physical simulation model and climate data modified for the RCP 2.6, RCP 4.5, and RCP 8.5 scenarios. To investigate the effects on a significant region with very high wind power generation in Germany, the numerical simulations were carried out on an ensemble of 22 onshore wind turbines with an installed capacity of 65.5 MW in the German Bight. After model validation, the power generation from this turbine ensemble was simulated for the high-wind year 2008 and the low-wind year 2010. The simulation results are presented with a high temporal resolution, and the observed changes are discussed for the applied RCPs. In summary, the resulting wind power generation of the entire plant ensemble decreases with increasing RCP to values of up to nearly 3 GWh for both years. Full article

Leaves are the most ubiquitous plant organs, whose macrostructures exhibit close correlations with environmental factors while simultaneously reflecting inherent genetic and evolutionary patterns. These characteristics render them highly significant for plant taxonomy, ecology, and related disciplines. Therefore, this study presents the first comprehensive evaluation of Malus leaf macrostructures for infraspecific classification. By establishing a trait-screening system, we conducted a numerical taxonomic analysis of leaf phenotypic variation across 73 Malus germplasm (34 species and 39 cultivars). Through ancestor-inclined distribution characteristic analysis, we investigated phylogenetic relationships at both the genus level and infraspecific ranks within Malus. A total of 21 leaf phenotypic traits were selected from 50 candidate traits based on the following criteria: high diversity, abundance, and evenness (D ≥ 0.50, H ≥ 0.80, and E ≥ 0.60); significant intraspecific uniformity and interspecific distinctness ($\overline{CV}$ ≤ 10% and $CV$ ≥ 15%). Notably, the selected traits with low intraspecific variability ($\overline{CV}$ ≤ 10%) exhibit environmental robustness, likely reflecting low phenotypic plasticity of these specific traits under varying conditions. This stability enhances their taxonomic utility. It was found that the highest ancestor-inclined distribution probability reached 90% for 10 traceable cultivars, demonstrating reliable breeding lines. Based on morphological evidence, there was a highly significant correlation between the evolutionary orders of (Sect. Docyniopsis → Sect. Sorbomalus → Sect. Malus) and group/sub-groups (B₁ → B₂ → A). This study demonstrates that phenotypic variation in leaf macrostructures can effectively explore the affinities among Malus germplasm, exhibiting taxonomic significance at the infraspecific level, thereby providing references for variety selection. However, hybrid offspring may exhibit mixed parental characteristics, leading to blurred species boundaries. And convergent evolution may create false homologies, potentially misleading morphology-based taxonomic inferences. The inferred taxonomic relationships present certain limitations that warrant further investigation. Full article