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14 pages, 4352 KB  
Article
Potato-Based Cropping Systems Improve Soil Quality by Increasing the Content of Available Nutrients and Aggregate Structure
by Wei Zhou, Wen-Wen Song, Chun-Lian Jin, Feng-Jun Yan, Yi-Hong Kuang, Zhen-Dong Chen, Hao-Tian Yao, Yong Chen and You-Feng Tao
Agriculture 2026, 16(4), 435; https://doi.org/10.3390/agriculture16040435 - 13 Feb 2026
Abstract
Crop rotation plays a critical role in enhancing cropping intensity and ensuring food security. To evaluate its long-term effects on soil quality, a fixed-site field experiment established in 2014 including four cropping systems—winter fallow–rice (Oryza sativa L.) (FR), potato (Solanum tuberosum [...] Read more.
Crop rotation plays a critical role in enhancing cropping intensity and ensuring food security. To evaluate its long-term effects on soil quality, a fixed-site field experiment established in 2014 including four cropping systems—winter fallow–rice (Oryza sativa L.) (FR), potato (Solanum tuberosum L.) –maize (Zea mays L.) (PM), potato–rice (PR), and potato–rice → rapeseed (Brassica napus L.) –rice (RRPR)—was conducted. A minimum data set (MDS) was screened from 21 soil indicators via principal component analysis (PCA), and the soil quality index (SQI) was calculated by integrating membership functions and indicator weights to comprehensively evaluate the impact of different patterns on soil quality. Results showed that paddy–upland rotations (PR and RRPR) significantly improved soil physical properties, increasing soil moisture content, porosity, and macro-aggregate proportion by 2.27–10.17%, while reducing bulk density by 10.32–13.38%, compared to FR and PM. PR and RRPR rotations also increased total nitrogen (TN), available phosphorus (AP), and available potassium contents (AK) by 5.19–114.00% (p < 0.01). PM rotation notably enhanced available nutrients, with NH4+-N, AP, and AK rising by 3.65–243.50% (p < 0.05), compared to FR. The MDS-based SQI, comprising NH4+-N, AP, mean weight diameter, and soil porosity, showed a highly significant positive correlation with the total data set-based SQI (p < 0.0001). PM exhibited the highest and most stable SQI, exceeding other systems by 8.15–19.30%, while PR and RRPR increased SQI by 9.04–10.30%, compared to FR. In conclusion, potato-based cropping systems enhance soil quality by improving soil structure and increasing nutrient content and availability. The results of this study provide a theoretical basis for nutrient management and sustainable production in cropping systems. Full article
(This article belongs to the Special Issue Soil Health Solutions for Sustainable Agriculture)
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12 pages, 6921 KB  
Article
Appropriate Soil Thickness Can Improve Growth of Machine-Transplanted Seedlings in Factory Seedling Raising Mode
by Lu Zhou, Yu Zhou, Xingchen Chen, Jiamin Liu, Dingyi Wang, Yukun Huang, Yue Wang and Yuan Hu
Agronomy 2026, 16(4), 440; https://doi.org/10.3390/agronomy16040440 - 13 Feb 2026
Viewed by 50
Abstract
The aim of this study was to investigate the impact of soil thickness on seedling growth in rice machine transplanting. Zhongzu 53 was selected as the test variety, and three different soil thickness treatments were applied: 0 cm (CK), 0.5 cm (T1), and [...] Read more.
The aim of this study was to investigate the impact of soil thickness on seedling growth in rice machine transplanting. Zhongzu 53 was selected as the test variety, and three different soil thickness treatments were applied: 0 cm (CK), 0.5 cm (T1), and 1 cm (T2). The emergence rate, plant height, root length, leaf age, number of green leaves, total root length, projected area, root surface area, and total root volume were measured. The results demonstrated that, compared with the CK treatment, the seedling emergence rate of the T1 treatment increased significantly by 68.6%, while no significant difference was observed in the emergence rate between the T1 and T2 treatments. The plant height, root length, and leaf age of the T1 treatment were significantly higher than those of both the CK and T2 treatments. In terms of root morphological indicators, the total root length, total root projected area, and number of root tips in the T1 treatment were significantly greater than those in the CK and T2 treatments. Correlation analysis revealed that the seedling emergence rate was extremely significantly positively correlated with the total root number (p < 0.01) and significantly positively correlated with the number of white roots, number of root tips, and total root length (p < 0.05). Grey correlation analysis indicated that the total root number had the highest correlation degree with the seedling emergence rate. Principal component analysis (PCA) results showed that the cumulative contribution rate of PCA1 and PCA2 reached 67.5%. Membership function analysis revealed that the T1 treatment had the highest average membership value, whereas the CK treatment exhibited the poorest performance. In conclusion, an appropriate cover soil thickness can effectively improve the growth performance of mechanically transplanted rice seedlings. Full article
(This article belongs to the Topic Crop Ecophysiology: From Lab to Field, 2nd Volume)
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17 pages, 819 KB  
Article
Integrating Agronomic Traits and Physiological Responses for Drought Resistance Screening in Wheat Germplasms
by Wenwen Cui, Yan Jin, Baoyuan Zhou, Liang Chen, Jiajing Song and Quanhao Song
Plants 2026, 15(4), 576; https://doi.org/10.3390/plants15040576 - 12 Feb 2026
Viewed by 73
Abstract
Drought stress is a critical limiting factor for wheat yield. Wild relatives of wheat have proven to be valuable genetic resources for desirable traits. This study aimed to conduct a comparative analysis of agronomic traits, photosynthetic physiological parameters, and antioxidant components among 26 [...] Read more.
Drought stress is a critical limiting factor for wheat yield. Wild relatives of wheat have proven to be valuable genetic resources for desirable traits. This study aimed to conduct a comparative analysis of agronomic traits, photosynthetic physiological parameters, and antioxidant components among 26 heterogermplasm wheat cultivars under well-watered (WW) and water-stressed (WS) conditions over two consecutive years. The results revealed that all nine agronomic traits were adversely affected under WS conditions. Four agronomic traits were selected based on the drought-resistance coefficient (DC < 0.8) and heritability (H2 < 0.7) to calculate the membership function value of drought resistance (MFVD), including flag leaf area (FLA), tiller number (TN), grain yield per plant (GYPP), and biomass per plant (BMPP). All wheat genotypes clustered into three groups based on their mean value of MFVD in two years. Under drought stress, wheat germplasms classified within the high MFVD group demonstrate significantly enhanced drought adaptability, as evidenced by superior photosynthetic performance with elevated photosynthesis rate (Pn), the actual photochemical quantum efficiency of photosystem II (ΦPSII), and the electron transfer rate (ETR), increased chlorophyll retention (higher SPAD values), strengthened antioxidant enzyme activities, and reduced stomatal limitation. Correlation analyses further reveal that MFVD exhibits significant positive correlations with Pn, ΦPSII, ETR, SPAD, and key antioxidant enzymes, while displaying a significant negative correlation with stomatal limitation value (Ls). These consistent physiological and biochemical patterns corroborate that the constituent agronomic traits—tiller number (TN), flag leaf area (FLA), biomass per plant (BMPP), and grain yield per plant (GYPP)—serve as robust and integrated phenotypic indicators for comprehensively evaluating drought resistance in wheat germplasm. Among the evaluated lines, lines 6, 15, 17, 21, and 22 exhibited significantly higher levels of drought resistance. These results highlight the presence of genetic variability among heterogermplasm wheat cultivars, which can be harnessed in breeding programs to develop drought-tolerant wheat varieties. Full article
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18 pages, 3592 KB  
Article
Vibration-Based Mechanical Fault Diagnosis of On-Load Tap Changers Using Fuzzy Set Theory
by Zhaoyu Qin, Feng Lin, Xiaoyi Cheng, Sasa Kong and Qingxiang Hu
Appl. Sci. 2026, 16(4), 1766; https://doi.org/10.3390/app16041766 - 11 Feb 2026
Viewed by 136
Abstract
On-load tap changers (OLTCs) are critical components of power transformers. In recent years, condition monitoring technologies for OLTCs based on vibration signals have attracted increasing research interest. However, practical applications still face several challenges, including background noise interference, insufficient characterization of transient signals, [...] Read more.
On-load tap changers (OLTCs) are critical components of power transformers. In recent years, condition monitoring technologies for OLTCs based on vibration signals have attracted increasing research interest. However, practical applications still face several challenges, including background noise interference, insufficient characterization of transient signals, signal complexity, difficulty in detecting subtle anomalies, and ambiguous associations between fault modes and signal features. To address these issues, this paper proposes an OLTC acoustic fingerprint feature recognition method based on multidimensional phase-space trajectory analysis. First, an OLTC fault simulation platform was established, in which typical mechanical faults—such as fastener loosening, contact wear, and insufficient spring energy storage—were physically simulated. Corresponding vibration signals were then acquired under different operating conditions. Considering the independence of vibration characteristics at different locations of the distribution transformer, a blind source separation method based on endpoint detection was employed to separate OLTC vibration signals from the operational noise of the transformer body. Given the nonlinear and chaotic characteristics of OLTC vibration signals, phase-space reconstruction was introduced for signal analysis. Based on the reconstructed phase space, characteristic patterns and geometric feature parameters corresponding to different mechanical states of the OLTC were extracted. Furthermore, a two-dimensional membership function was constructed using the phase-space trajectories, and fuzzy inference based on predefined fuzzy rules was applied to compute representative feature parameters. A feature parameter database was subsequently established to enable OLTC condition identification. Experimental results demonstrate that the proposed diagnostic model can effectively classify and identify OLTC fault conditions using vibration signals, achieving an average classification accuracy exceeding 91.25%. The proposed method provides an effective non-intrusive approach for online monitoring and mechanical fault diagnosis of OLTCs without interrupting normal transformer operation. Full article
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15 pages, 1144 KB  
Article
Interannual Variation in Key Quality Constituents in Shiqian Taicha Manufactured as Green and Black Tea (2021–2023)
by Yuan Zhang, Xiubing Gao and Can Guo
Appl. Sci. 2026, 16(3), 1614; https://doi.org/10.3390/app16031614 - 5 Feb 2026
Viewed by 132
Abstract
Shiqian Taicha (Camellia sinensis) is a local tea cultivar originating from Shiqian County and Guizhou (China) that is suitable for both green and black tea. The year-on-year manufacturing conditions, which affect chemical quality, were elucidated through the analysis of 78 green [...] Read more.
Shiqian Taicha (Camellia sinensis) is a local tea cultivar originating from Shiqian County and Guizhou (China) that is suitable for both green and black tea. The year-on-year manufacturing conditions, which affect chemical quality, were elucidated through the analysis of 78 green tea and 38 black tea commercial batches manufactured in 2021–2023. The batches were manufactured by the same process, but these naturally varied in raw-leaf status and factory parameters. The moisture content, water-soluble extract, free amino acids, tea polyphenols, caffeine, gallic acid, total ash, total catechins and individual catechins were predicted using a calibrated near-infrared (NIR) spectroscopy model and membership function evaluation, which integrated multiple indices to produce an overall quality score for each year and tea type. The amino acids of green tea peaked in the year 2022, (with 4.55%) whereas the polyphenols (which refers to carbon-based molecules) was in the year 2021, (with 24.22%), and the total catechins was in the year 2021, (with 16.71%); due to these observations, the ratio of phenol-to-amino was high in the year 2021, with (10.09); while the year 2022 had a lower ratio with (3.41). Although there were fewer differences from region to region with black tea, 2022 was better in terms of moisture control, amino acids retention and composite score with a value of 0.585. The assessment of the membership function indicated that 2022 was the most ideal tea production year for green tea (0.506) as well as black tea (0.477), with 2021 tea (0.486) and 2023 tea (0.488) following next based on type. The data presents quantitatively stable fixation and moisture/fermentation management targets to improve Shiqian Taicha value and consistency. Full article
(This article belongs to the Section Agricultural Science and Technology)
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36 pages, 2942 KB  
Article
Can a Rural Collective Property Rights System Reform Narrow Income Gaps? An Effect Evaluation and Mechanism Identification Based on Multi-Period DID
by Xuyang Shao, Yihao Tian and Dan He
Land 2026, 15(2), 243; https://doi.org/10.3390/land15020243 - 30 Jan 2026
Viewed by 278
Abstract
For a long time, low efficiency in the transfer of rural collective land use rights and the ambiguous attribution of collective land property rights have not only restricted the mobility of rural labor factors but have also hindered the release of vitality in [...] Read more.
For a long time, low efficiency in the transfer of rural collective land use rights and the ambiguous attribution of collective land property rights have not only restricted the mobility of rural labor factors but have also hindered the release of vitality in the rural collective economy. This has resulted in lagging growth in the income that rural residents obtain from collective economic factors, contributing to the persistent widening of the urban/rural income gap. As an important institutional innovation to address these issues, the effects of the reform of the rural collective property rights system urgently need to be clarified. The reform of the rural collective property rights system constitutes a major initiative in the transformation of the rural land system. Centered on asset verification and valuation, as well as the demarcation of membership rights and the restructuring towards a shareholding cooperative system, it aims to establish a collective property rights regime characterized by clearly defined ownership and fully functional entitlements. This study takes the national pilot reform of rural collective property rights launched in 2016 as a quasi-natural policy experiment, systematically examining the impact of this pilot policy on the internal income gap within households and its spillover effects on the urban–rural income gap. Based on microdata from the China Household Finance Survey (CHFS) and the China Longitudinal Night Light Data Set (PANDA-China), this study constructs a five-period balanced panel dataset covering 2304 rural households across 25 provinces. A relative exploitation index based on the Kawani index is constructed, and empirical analysis is conducted using a combination of multi-period difference-in-differences (Multi-period DID), discrete binary models, and propensity score matching-difference-in-differences (PSM-DID) models. The results show that: First, the pilot reform significantly reduced the level of income inequality within rural areas in the pilot regions, and its policy benefits further generated positive spillovers via market-driven factor allocation mechanisms, effectively bridging the urban–rural income gap. Second, institutional reforms activated the potential of rural non-agricultural economic factors, establishing new channels for a two-way flow of urban and rural factors, becoming an important path to achieve the goal of common prosperity. Third, the policy effects exhibited significant heterogeneity, specifically manifested in the attributes of major grain-producing regions, initial household income levels, and the human capital characteristics of household heads having significant moderating effects on reform outcomes. This study not only provides theoretical support and empirical evidence for deepening rural property rights reforms under the new rural revitalization strategy, but it also reveals the driving role of institutional innovation in factor mobility, thereby influencing the transmission mechanism of income distribution patterns. This finding offers a China-based solution for developing countries to address the imbalance in urban–rural development and the widening income gap. Full article
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19 pages, 4708 KB  
Article
Integrated Physiological and Transcriptomic Analyses Reveal the Mechanism of Salt Acclimation-Induced Salinity Tolerance in Tomato Seedlings
by Nuo Fan, Ruiqing Li, Huixin Liu, Ke Zhang, Guan Pang, Xiaoying Liu, Lifei Yang, Jin Sun and Yu Wang
Horticulturae 2026, 12(2), 159; https://doi.org/10.3390/horticulturae12020159 - 30 Jan 2026
Viewed by 108
Abstract
Although salt acclimation is a recognized strategy for improving crop salt tolerance, its specific role in tomato (Solanum lycopersicum L.) remains unclear. This study investigated the effects of salt acclimation on enhancing salt tolerance in tomato seedlings through physiological and transcriptomic analyses. [...] Read more.
Although salt acclimation is a recognized strategy for improving crop salt tolerance, its specific role in tomato (Solanum lycopersicum L.) remains unclear. This study investigated the effects of salt acclimation on enhancing salt tolerance in tomato seedlings through physiological and transcriptomic analyses. Here, we found that T3 acclimation treatment (irrigation with 14 mL of 7.5 g L−1 NaCl solution per plant) effectively conferred enhanced salt tolerance in tomato seedlings, with plant height, stem diameter, leaf area, chlorophyll content, net photosynthetic rate, and soluble protein content increasing by 4.52, 5.13, 3.16, 10.78, 11.85, and 25.96%, respectively, compared with the control. T3 treatment also reduced oxidative damage and ionic stress, as evidenced by reduced electrolyte leakage, lower malondialdehyde content, and a decreased root Na+/K+ ratio, while simultaneously boosting antioxidant enzyme activities. Membership function analysis confirmed T3 as the optimal treatment, with a 9 d duration consistently benefiting multiple cultivars. Transcriptomic analysis revealed that salt acclimation upregulated genes associated with phenylpropanoid biosynthesis, lignin catabolic process, and peroxidase activity, suggesting that these pathways might mediate acclimation-induced salt tolerance through promoting lignin biosynthesis to reduce Na+/K+ ratio and enhancing reactive oxygen species’ scavenging capacity to maintain cellular homeostasis. Our results indicate that tomato seedlings acclimated with 14 mL of 7.5 g L−1 NaCl solution per plant for 9 d significantly improves salt tolerance through coordinated physiological adjustments and transcriptional reprogramming. Full article
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21 pages, 3803 KB  
Article
A System-Oriented Framework for Reliability Assessment of Crowdsourced Geospatial Data Using Unsupervised Learning
by Hussein Hamid Hassan, Rahim Ali Abbaspour and Alireza Chehreghan
Systems 2026, 14(2), 129; https://doi.org/10.3390/systems14020129 - 27 Jan 2026
Viewed by 306
Abstract
Crowdsourced geospatial platforms constitute complex socio-technical systems in which data quality and reliability emerge from collective user behavior rather than centralized control. This study proposes a system-oriented, unsupervised machine learning framework to assess the reliability of crowdsourced building data using only intrinsic indicators. [...] Read more.
Crowdsourced geospatial platforms constitute complex socio-technical systems in which data quality and reliability emerge from collective user behavior rather than centralized control. This study proposes a system-oriented, unsupervised machine learning framework to assess the reliability of crowdsourced building data using only intrinsic indicators. The framework is demonstrated through a large-scale analysis of OpenStreetMap building polygons in Tehran. Six intrinsic indicators—reflecting contributor activity, temporal dynamics, semantic instability, and geometric evolution—were normalized using fuzzy membership functions and objectively weighted based on their discriminative influence within a K-means clustering process. Five reliability classes were identified, ranging from very low to very high reliability. The resulting classification exhibited strong internal validity (average silhouette coefficient = 0.58) and pronounced spatial coherence (Global Moran’s I = 0.85, p < 0.001). This approach eliminates dependence on authoritative reference datasets, enabling scalable, reproducible, and feature-level reliability assessment in open geospatial systems. The framework provides a transferable methodological foundation for trust-aware analysis and decision-making in participatory and data-intensive systems. Full article
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23 pages, 7022 KB  
Article
Robust H Fault-Tolerant Control with Mixed Time-Varying Delays
by Jinxia Wu, Yahui Geng and Juan Wang
Actuators 2026, 15(2), 73; https://doi.org/10.3390/act15020073 - 25 Jan 2026
Viewed by 295
Abstract
This paper investigates the robust fault-tolerant control (FTC) problem for interval type-2 fuzzy systems (IT2FS) with simultaneous time-varying input and state delays. In order to more comprehensively capture system uncertainties, an Interval Type-2 (IT2) fuzzy model is constructed, which, compared to the conventional [...] Read more.
This paper investigates the robust fault-tolerant control (FTC) problem for interval type-2 fuzzy systems (IT2FS) with simultaneous time-varying input and state delays. In order to more comprehensively capture system uncertainties, an Interval Type-2 (IT2) fuzzy model is constructed, which, compared to the conventional Interval Type-1 model, better captures the uncertainty information of the system. A premise-mismatched fault-tolerant controller is designed to ensure system stability in the presence of actuator faults, while providing greater flexibility in the selection of membership functions. In the stability analysis, a novel Lyapunov–Krasovskii functional is formulated, incorporating membership-dependent matrices and delay-product terms, leading to sufficient conditions for closed-loop stability based on linear matrix inequalities (LMIs). A numerical simulation and a practical physical model are used, respectively, to illustrate the effectiveness of the proposed method. Comparative experiments further reveal the impact of input delays and actuator faults on closed-loop performance, verifying the effectiveness and robustness of the designed controller, as well as the superiority of interval type-2 over interval type-1. Full article
(This article belongs to the Section Control Systems)
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18 pages, 586 KB  
Article
Performance of Twelve Apple Cultivars Grafted onto SH40 Dwarf Interstock: Comprehensive Fruit Quality Evaluation and Selection of Adapted Varieties in Lingwu, Ningxia
by Zhikai Zhang, Yu Wang, Wenyan Ma, Jiayi Zhai, Xuelian Huang, Wenjing Xue, Jun Zhou, Jing Wang, Xin Zhang, Binbin Si, Lan Luo and Wendi Xu
Agriculture 2026, 16(3), 303; https://doi.org/10.3390/agriculture16030303 - 25 Jan 2026
Viewed by 265
Abstract
This study evaluated the fruit quality of 12 apple cultivars grafted onto the cold-resistant dwarfing interstock SH40 in the arid region of Lingwu, Ningxia, to identify well-adapted varieties for local production. A total of 21 indicators were measured, encompassing three major aspects: external [...] Read more.
This study evaluated the fruit quality of 12 apple cultivars grafted onto the cold-resistant dwarfing interstock SH40 in the arid region of Lingwu, Ningxia, to identify well-adapted varieties for local production. A total of 21 indicators were measured, encompassing three major aspects: external quality (e.g., fruit size, shape index, peel color), internal flavor (e.g., soluble solids, soluble sugars, titratable acids, vitamin C content), and textural attributes (e.g., hardness, crispness, chewiness), and data were analyzed using principal component analysis and membership function methodology. The cultivars exhibited distinct quality profiles under identical management: ‘Red General’ performed well in fruit size, weight, and sugar–acid balance; ‘Yanfu 6’ showed the highest firmness and crispness; ‘Shengli’ had the greatest soluble solids content; and ‘Granny Smith’ was richest in vitamin C. Four principal components were extracted, explaining 80.06% of the total variance and simplifying the quality evaluation system. Based on the comprehensive membership function scores, ‘Red General’, ‘White Winter Pearmain’, and ‘Huashuo’ ranked highest in overall fruit quality. In conclusion, these three cultivars perform excellently on SH40 and are recommended for promotion, whereas ‘Red Delicious’ is not recommended due to poor performance. These findings offer a practical reference for selecting apple cultivars paired with SH40 in similar arid regions. Full article
(This article belongs to the Special Issue Fruit Quality Formation and Regulation in Fruit Trees)
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35 pages, 1361 KB  
Article
A Fuzzy-SNA Computational Framework for Quantifying Intimate Relationship Stability and Social Network Threats
by Ning Wang and Xiangzhi Kong
Symmetry 2026, 18(1), 201; https://doi.org/10.3390/sym18010201 - 21 Jan 2026
Viewed by 170
Abstract
Intimate relationship stability is fundamental to human wellbeing, yet its quantitative assessment faces dual challenges: the inherent subjectivity of psychological constructs and the complexity of social ecosystems. Symmetry, as a fundamental structural feature of social interaction, plays a pivotal role in shaping relational [...] Read more.
Intimate relationship stability is fundamental to human wellbeing, yet its quantitative assessment faces dual challenges: the inherent subjectivity of psychological constructs and the complexity of social ecosystems. Symmetry, as a fundamental structural feature of social interaction, plays a pivotal role in shaping relational dynamics. To address these limitations, this study proposes an innovative computational framework that integrates Fuzzy Set Theory with Social Network Analysis (SNA). The framework consists of two complementary components: (1) a psychologically grounded fuzzy assessment model that employs differentiated membership functions to transform discrete subjective ratings into continuous and interpretable relationship quality indices and (2) an enhanced Fuzzy C-Means (FCM) threat detection model that utilizes Weighted Mahalanobis Distance to accurately identify and cluster potential interference sources within social networks. Empirical validation using a simulated dataset—comprising typical characteristic samples from 10 couples—demonstrates that the proposed framework not only generates interpretable relationship diagnostics by correcting biases associated with traditional averaging methods, but also achieves high precision in threat identification. The results indicate that stable relationships exhibit greater symmetry in partner interactions, whereas threatened nodes display structural and behavioural asymmetry. This study establishes a rigorous mathematical paradigm—“Subjective Fuzzification → Multidimensional Feature Engineering → Intelligent Clustering”—for relationship science, thereby advancing the field from descriptive analysis toward data-driven, quantitative evaluation and laying a foundation for systematic assessment of relational health. Full article
(This article belongs to the Section Mathematics)
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25 pages, 2562 KB  
Article
Mathematically Grounded Neuro-Fuzzy Control of IoT-Enabled Irrigation Systems
by Nikolay Hinov, Reni Kabakchieva, Daniela Gotseva and Plamen Stanchev
Mathematics 2026, 14(2), 314; https://doi.org/10.3390/math14020314 - 16 Jan 2026
Viewed by 233
Abstract
This paper develops a mathematically grounded neuro-fuzzy control framework for IoT-enabled irrigation systems in precision agriculture. A discrete-time, physically motivated model of soil moisture is formulated to capture the nonlinear water dynamics driven by evapotranspiration, irrigation, and drainage in the crop root zone. [...] Read more.
This paper develops a mathematically grounded neuro-fuzzy control framework for IoT-enabled irrigation systems in precision agriculture. A discrete-time, physically motivated model of soil moisture is formulated to capture the nonlinear water dynamics driven by evapotranspiration, irrigation, and drainage in the crop root zone. A Mamdani-type fuzzy controller is designed to approximate the optimal irrigation strategy, and an equivalent Takagi–Sugeno (TS) representation is derived, enabling a rigorous stability analysis based on Input-to-State Stability (ISS) theory and Linear Matrix Inequalities (LMIs). Online parameter estimation is performed using a Recursive Least Squares (RLS) algorithm applied to real IoT field data collected from a drip-irrigated orchard. To enhance prediction accuracy and long-term adaptability, the fuzzy controller is augmented with lightweight artificial neural network (ANN) modules for evapotranspiration estimation and slow adaptation of membership-function parameters. This work provides one of the first mathematically certified neuro-fuzzy irrigation controllers integrating ANN-based estimation with Input-to-State Stability (ISS) and LMI-based stability guarantees. Under mild Lipschitz continuity and boundedness assumptions, the resulting neuro-fuzzy closed-loop system is proven to be uniformly ultimately bounded. Experimental validation in an operational IoT setup demonstrates accurate soil-moisture regulation, with a tracking error below 2%, and approximately 28% reduction in water consumption compared to fixed-schedule irrigation. The proposed framework is validated on a real IoT deployment and positioned relative to existing intelligent irrigation approaches. Full article
(This article belongs to the Special Issue Advances in Fuzzy Logic and Artificial Neural Networks, 2nd Edition)
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27 pages, 8058 KB  
Article
Quality Evaluation and Antioxidant Activity of Cultivated Gentiana siphonantha: An Ethnic Medicine from the Tibetan Plateau
by Jiamin Li, Liyan Zang, Xiaoming Song, Zixuan Liu, Hongmei Li and Jing Sun
Molecules 2026, 31(2), 312; https://doi.org/10.3390/molecules31020312 - 16 Jan 2026
Viewed by 320
Abstract
Gentiana species are widely used in traditional and modern medicine, and Gentiana siphonantha is an important medicinal representative. To evaluate the quality characteristics of cultivated G. siphonantha roots, the accumulation patterns of iridoid glycosides and antioxidant activities across different cultivation ages and harvest [...] Read more.
Gentiana species are widely used in traditional and modern medicine, and Gentiana siphonantha is an important medicinal representative. To evaluate the quality characteristics of cultivated G. siphonantha roots, the accumulation patterns of iridoid glycosides and antioxidant activities across different cultivation ages and harvest months were investigated. Five major iridoid glycosides were quantified, and antioxidant capacity was assessed through DPPH, ABTS, and FRAP assays. Quality was subsequently multidimensionally evaluated using principal component analysis (PCA), orthogonal partial least squares–discriminant analysis (OPLS-DA), membership function analysis, and entropy weight–TOPSIS analysis, and the relationship between iridoid glycoside content and antioxidant activity was analyzed. Results showed that 3-year-old cultivated roots had the highest total iridoid glycoside content (134.60 mg·g−1 DW), indicating the optimal cultivation age. Peak glycoside accumulation occurred in 4-year-old plants harvested in June–July, identifying this period as the optimal harvest time, as supported by multivariate statistical and comprehensive evaluation. Antioxidant activity increased with cultivation age, with samples collected in June or August showing higher capacities, and it was positively correlated with total iridoid glycoside content, particularly with FRAP (p < 0.05). In conclusion, cultivated G. siphonantha exhibits stable quality and favorable antioxidant activity, providing a basis for standardized cultivation, quality evaluation, and rational utilization. Full article
(This article belongs to the Section Analytical Chemistry)
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18 pages, 1144 KB  
Article
Hypersector-Based Method for Real-Time Classification of Wind Turbine Blade Defects
by Lesia Dubchak, Bohdan Rusyn, Carsten Wolff, Tomasz Ciszewski, Anatoliy Sachenko and Yevgeniy Bodyanskiy
Energies 2026, 19(2), 442; https://doi.org/10.3390/en19020442 - 16 Jan 2026
Viewed by 225
Abstract
This paper presents a novel hypersector-based method with Fuzzy Learning Vector Quantization (FLVQ) for the real-time classification of wind turbine blade defects using data acquired by unmanned aerial vehicles (UAVs). Unlike conventional prototype-based FLVQ approaches that rely on Euclidean distance in the feature [...] Read more.
This paper presents a novel hypersector-based method with Fuzzy Learning Vector Quantization (FLVQ) for the real-time classification of wind turbine blade defects using data acquired by unmanned aerial vehicles (UAVs). Unlike conventional prototype-based FLVQ approaches that rely on Euclidean distance in the feature space, the proposed method models each defect class as a hypersector on an n-dimensional hypersphere, where class boundaries are defined by angular similarity and fuzzy membership transitions. This geometric reinterpretation of FLVQ constitutes the core innovation of the study, enabling improved class separability, robustness to noise, and enhanced interpretability under uncertain operating conditions. Feature vectors extracted via the pre-trained SqueezeNet convolutional network are normalized onto the hypersphere, forming compact directional clusters that serve as the geometric foundation of the FLVQ classifier. A fuzzy softmax membership function and an adaptive prototype-updating mechanism are introduced to handle class overlap and improve learning stability. Experimental validation on a custom dataset of 900 UAV-acquired images achieved 95% classification accuracy on test data and 98.3% on an independent dataset, with an average F1-score of 0.91. Comparative analysis with the classical FLVQ prototype demonstrated superior performance and noise robustness. Owing to its low computational complexity and transparent geometric decision structure, the developed model is well-suited for real-time deployment on UAV embedded systems. Furthermore, the proposed hypersector FLVQ framework is generic and can be extended to other renewable-energy diagnostic tasks, including solar and hydropower asset monitoring, contributing to enhanced energy security and sustainability. Full article
(This article belongs to the Special Issue Modeling, Control and Optimization of Wind Power Systems)
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19 pages, 2766 KB  
Article
Regulatory Effects of Exogenous Trehalose on the Growth and Photosynthetic Characteristics of Celery (Apium graveolens L.) Under Salt Stress
by Yanqiang Gao, Liangmei Zhang, Wenjing Rui, Miao Zhang, Zixiao Liang, Kaiguo Pu, Youlin Chang, Yongwei Ma, Jingwen Huo, Jiongjie Zhang, Jing Li and Jianming Xie
Plants 2026, 15(2), 212; https://doi.org/10.3390/plants15020212 - 9 Jan 2026
Viewed by 257
Abstract
Salinity has been recognized as one of the major environmental stresses that restrict the growth and quality of celery (Apium graveolens L.). Therefore, this study investigates the impact of different NaCl concentrations on celery growth and photosynthetic characteristics, as well as the [...] Read more.
Salinity has been recognized as one of the major environmental stresses that restrict the growth and quality of celery (Apium graveolens L.). Therefore, this study investigates the impact of different NaCl concentrations on celery growth and photosynthetic characteristics, as well as the potential regulatory role of exogenous trehalose application in mitigating the stress-induced effects. The results indicated that an increase in NaCl concentration from 50 to 200 mM markedly inhibited the growth of celery plants compared to that under control conditions. The application of different concentrations of trehalose mitigated the inhibitory effects of salt stress (100 mM NaCl) on celery growth and photosynthesis. Among the different trehalose treatments, T3 (10 mM trehalose) exhibited the most significant effects, increasing the aboveground biomass, belowground biomass, plant height, chlorophyll a, chlorophyll b, total chlorophyll, and net photosynthetic rate compared to that of salt stress alone, respectively. Furthermore, trehalose treatments enhanced the various fluorescence parameters, including the maximum efficiency of PSII photochemistry (Fv/Fm), coefficient of photochemical quenching (qP), fluorescence intensity, and photosynthetic performance index (PIabs) under salt stress. Meanwhile, trehalose reduced intercellular carbon dioxide concentration, excess excitation energy (1-qP)/NPQ, heat dissipation per unit area (DIo/CSm), and energy dissipated per reaction center (DIo/RC). Additionally, the results of principal component analysis (PCA) and membership function comprehensive evaluation indicate that an appropriate concentration of trehalose positively alleviates the salnitiy-induced effects in celery. Overall, the T3 demonstrated the most promising effects on mitigating the effects of salt stress by decreasing the excess excitation energy of PSII in celery leaves through the heat dissipation pathway. This reduction lowers the excitation pressure on the reaction centers, enhances the activity of PSII reaction centers per unit cross-section, and improves photosynthesis activity, thereby improving the growth of celery plants under salt stress. Full article
(This article belongs to the Section Plant Response to Abiotic Stress and Climate Change)
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