Agriculture

44 pages, 5672 KB

Open AccessArticle

Digitalizing Sustainability Assessment in Agriculture: The SUSTIN-OLIVA Indicator-Based Application for Tunisian Olive Farming Systems Under Agroecological Transition

by Saida Elfkih, Amel ElKadri, Olfa Boussaadia, Houda Sahnoun, Aymen Laabidi, Ghayth Ghozzi, Sana Bouazza, Ahmed Charfi, Oussema Charfi and Idalina Sardinha

Agriculture 2026, 16(17), 1912; https://doi.org/10.3390/agriculture16171912 - 3 Sep 2026

Abstract

With the shift in Tunisian olive growing toward more intensive models, significant sustainability concerns have emerged. Aware of the need for reliable and operational tools to support agricultural policies under climate and socioeconomic pressures, we address a digitalized methodological framework for measuring and [...] Read more.

With the shift in Tunisian olive growing toward more intensive models, significant sustainability concerns have emerged. Aware of the need for reliable and operational tools to support agricultural policies under climate and socioeconomic pressures, we address a digitalized methodological framework for measuring and assessing the sustainability of olive farming systems that are undergoing an agroecological transition. The main contribution lies in the development of the SUSTIN-OLIVA digital indicator-based application, designed as a decision-support tool to enhance the accessibility, scalability, and operationalization of sustainability assessment within a holistic approach that integrates environmental, economic, and socio-territorial indicators tailored to Tunisian olive agroecosystems. The methodology was tested on 61 Tunisian olive farms in two agroecological zones undergoing transition, using face-to-face surveys conducted between April and May 2026 with a structured questionnaire. Principal Component Analysis (PCA) was applied as an exploratory approach to examine the relationships, contribution patterns, and internal structure of the proposed sustainability indicators. The results indicated that, among the 28 indicators considered, 23 made substantial contributions to the main patterns of variation identified by the PCA in the studied context. These findings demonstrate the feasibility and operational applicability of the SUSTIN-OLIVA framework across heterogeneous olive farms and provide insights into differences in sustainability performance and indicator interactions. The framework also enables the identification of under-addressed sustainability dimensions, supporting more targeted interventions and context-specific decision-making. Overall, this work advances digitalized sustainability assessment by linking a holistic indicator framework with an operational digital decision-support tool, thereby supporting adaptive governance in the Mediterranean olive sector. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

27 pages, 12087 KB

Open AccessArticle

YOLOv11n-SWAQ: A Lightweight Adaptive Compression Method for Agricultural Images

by Kaixuan Zhao, Yue Zhang, Yinan Chen and Jiangtao Ji

Agriculture 2026, 16(17), 1911; https://doi.org/10.3390/agriculture16171911 - 3 Sep 2026

Abstract

Agricultural pest and disease images often lose diagnostically important textures during transmission and storage, while conventional codecs struggle to balance high compression ratios and information fidelity. This study proposes YOLOv11n-SWAQ, a lightweight adaptive compression framework integrating shared feature encoding and critical-region-aware quantization. The [...] Read more.

Agricultural pest and disease images often lose diagnostically important textures during transmission and storage, while conventional codecs struggle to balance high compression ratios and information fidelity. This study proposes YOLOv11n-SWAQ, a lightweight adaptive compression framework integrating shared feature encoding and critical-region-aware quantization. The YOLOv11n backbone and feature fusion network are reused as a shared encoder to reduce redundant feature extraction. A lightweight window-based attention module enhances lesion boundaries, insect contours, and local textures. Detection boxes and attention weights are combined to construct a three-level quantization map for background, ordinary critical, and high-importance texture regions, while a hyperprior entropy model improves latent probability estimation. At an actual complete-stream bitrate of approximately 0.31 bpp, the proposed method achieved an ROI-PSNR of 36.970 dB and an ROI-MS-SSIM of 0.9652. Compared with the YOLOv11n+CAE cascaded baseline, the reconstruction error in complex-texture regions decreased by 4.8%, indicating preferential bitrate allocation to diagnostically important regions. The proposed method achieved an end-to-end processing time of 13.44 ms, representing an average reduction of approximately 72% compared with representative advanced learned image compression models. Overall, YOLOv11n-SWAQ provides a favorable trade-off between critical-region fidelity and computational efficiency for high-ratio agricultural image compression, with its principal advantage lying in lightweight task-oriented processing rather than a large absolute gain in global reconstruction quality. Full article

(This article belongs to the Special Issue Advanced Image Collection, Processing, and Analysis in Crop Management—2nd Edition)

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28 pages, 32600 KB

Open AccessArticle

Three-Dimensional Open-Path Sequencing for Robotic Tea-Shoot Plucking via Hierarchical Ant Colony Optimization and Endpoint Coordination

by Decheng Liu, Baijuan Wang, Pengfei Wang, Zhi Zhang and Yongguang Hu

Agriculture 2026, 16(17), 1910; https://doi.org/10.3390/agriculture16171910 - 3 Sep 2026

Abstract

Efficient three-dimensional (3D) open-path sequencing is important for robotic selective plucking because harvestable tea shoots are irregularly distributed in canopy space. This study formulates tea-shoot plucking as an open-path sequencing problem over preparatory plucking points and proposes a hierarchical ant colony optimization framework [...] Read more.

Efficient three-dimensional (3D) open-path sequencing is important for robotic selective plucking because harvestable tea shoots are irregularly distributed in canopy space. This study formulates tea-shoot plucking as an open-path sequencing problem over preparatory plucking points and proposes a hierarchical ant colony optimization framework with endpoint-aware traversal-direction coordination. Preparatory points are decomposed into local operating regions, within which routes are optimized using ant colony optimization and 3-opt refinement. Centroid-level ant colony optimization then determines the cluster visiting order, followed by dynamic programming to select the traversal direction of each local route according to endpoint-to-endpoint connection costs. Across eleven simulated scenarios, including an unstructured Global-random control, the proposed method achieved the shortest mean route length in ten scenarios. In the Large-scale scenario, it achieved a mean route length of 13.973 ± 0.184 m, which was 10.5% and 2.9% lower than those obtained by global ant colony optimization and greedy insertion, respectively. On five real tea-field point-cloud datasets, the proposed method reduced mean route length by 0.57–3.15% relative to greedy insertion, with statistically significant improvements in four datasets. A preliminary CoppeliaSim assessment further showed that the optimized visiting sequence could be geometrically connected using smoothed local transfer trajectories. Overall, the proposed framework improves sequence-level route quality and computational efficiency for clustered 3D tea-shoot distributions, while its field-level operational benefits remain to be established through closed-loop robotic validation. Full article

(This article belongs to the Section Agricultural Technology)

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26 pages, 868 KB

Open AccessArticle

Metabolic and Physiological Associations with LMD-Based Enteric CH₄ Concentration in Early Lactation Dairy Cows: A Multivariate Approach with Parity-Specific Insights

by Justina Krištolaitytė, Karina Džermeikaitė, Samanta Grigė, Akvilė Girdauskaitė, Greta Šertvytytė, Gabija Lembovičiūtė, Arūnas Rutkauskas and Ramūnas Antanaitis

Agriculture 2026, 16(17), 1909; https://doi.org/10.3390/agriculture16171909 - 3 Sep 2026

Abstract

Understanding cow-level factors associated with enteric methane (CH₄) is important for precision-based methane mitigation in dairy systems. This study evaluated associations between laser methane detector (LMD)-based CH₄ concentration, relative CH₄ concentration-based indices, biochemical markers, sensor-derived variables, and milk traits [...] Read more.

Understanding cow-level factors associated with enteric methane (CH₄) is important for precision-based methane mitigation in dairy systems. This study evaluated associations between laser methane detector (LMD)-based CH₄ concentration, relative CH₄ concentration-based indices, biochemical markers, sensor-derived variables, and milk traits in clinically healthy Holstein cows, with an emphasis on parity. Ninety-one cows within 100 days in milk (DIM) were examined: 46 primiparous and 45 multiparous cows. Methane concentration was measured using a portable LMD. Data were evaluated using parity comparisons, principal component analysis (PCA), DIM-adjusted multiple linear regression with parity interaction terms, and DIM-adjusted partial correlation analyses with Benjamini–Hochberg false discovery rate (FDR) correction. Mean CH₄ concentration did not differ between primiparous and multiparous cows (370.83 vs. 361.16 ppm; p = 0.765), despite higher estimated group-level dry matter intake (DMI; +11.2%) and milk yield (+23.1%) in multiparous cows. The milk-yield-adjusted CH₄ concentration index was higher in primiparous cows (11.26 vs. 8.91 ppm CH₄/kg milk; p = 0.022). In the primary PCA-based regression model, the energy metabolism/lipid mobilisation component showed a positive but non-significant association with CH₄ concentration (p = 0.077), while the overall model’s explanatory capacity was limited (R² = 0.105; adjusted R² = 0.018). Exploratory DIM-adjusted subgroup analyses identified associations involving non-esterified fatty acids (NEFA), triglycerides, serum iron, and milk lactose that remained significant after FDR correction. However, formal predictor × parity interaction analyses did not confirm effect modification by parity. These findings suggest that LMD-based CH₄ concentration is best interpreted within a broader metabolic, behavioural, and production context and warrants validation in larger longitudinal studies. Full article

(This article belongs to the Special Issue Effects of Feed on Methane Emissions and Microbial Activity in the Rumen of Ruminants)

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20 pages, 3984 KB

Open AccessArticle

Environmental Drivers and Spatial Suitability of Erosion Control Measures in the Black Soil Region of Northeast China

by Zheng Chen, Yan Xu, Huarui Gong, Yitao Zhang, Jiaxu Fu, Lei Zhang and Jing Li

Agriculture 2026, 16(17), 1908; https://doi.org/10.3390/agriculture16171908 - 3 Sep 2026

Abstract

Sloping farmland erosion in cold-region black soil zones threatens global agriculture, yet regional-scale quantitative evidence on the erosion mitigation performance and spatial suitability of control measures remains lacking. This study integrated 959 field observation datasets from 132 peer-reviewed publications, and used meta-analysis and [...] Read more.

Sloping farmland erosion in cold-region black soil zones threatens global agriculture, yet regional-scale quantitative evidence on the erosion mitigation performance and spatial suitability of control measures remains lacking. This study integrated 959 field observation datasets from 132 peer-reviewed publications, and used meta-analysis and Boosted Regression Tree (BRT) models to evaluate tillage, biological, engineering, and combined conservation measures in Northeast China. Results showed that all measures significantly reduced erosion, achieving an average runoff reduction of 73.2% and sediment reduction of 83.6%. Specifically, engineering measures showed the highest runoff reduction, while combined measures achieved more than 95% sediment reduction. Machine learning revealed that runoff reduction was primarily regulated by precipitation, whereas sediment reduction was mainly controlled by soil clay content and bulk density. Spatially, tillage, biological, and engineering measures showed the highest suitability in continuous cultivated plains, plain–hill transition zones, and low hilly and gully regions, respectively. This study moves erosion-control assessment beyond comparisons of average runoff and sediment reduction rates toward environmentally matched spatial allocation, providing a basis for targeted black soil conservation and resilient grain production in cold-region agricultural landscapes. Full article

(This article belongs to the Special Issue Soil Erosion Mechanisms and Water Conservation Processes in Farmland)

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29 pages, 13001 KB

Open AccessArticle

Design and Testing of a Gravity-Constrained Fertilizer Guide Tube for Stable Fertilizer Cluster Movement

by Xinhe Shan, Jianjun Dong, Bingxin Yan, Liwei Li, Yanxin Yin, Qingzhen Zhu, Chunhong Dong and Guangwei Wu

Agriculture 2026, 16(17), 1907; https://doi.org/10.3390/agriculture16171907 - 3 Sep 2026

Abstract

Fertilizer clusters tend to lose their agglomerated state upon ground contact, which reduces fertilizer use efficiency. To address this, we designed a gravity-constrained fertilizer guide tube. Based on the principle of minimum friction, we designed a trapezoidal groove. By analyzing the motion of [...] Read more.

Fertilizer clusters tend to lose their agglomerated state upon ground contact, which reduces fertilizer use efficiency. To address this, we designed a gravity-constrained fertilizer guide tube. Based on the principle of minimum friction, we designed a trapezoidal groove. By analyzing the motion of the fertilizer as it dropped and contacted the ground, we identified the key factors affecting hole formation such as the fertilizer guiding angle, groove angle, and forward velocity. We used the discrete element method to determine the optimal combination of parameters: with a fertilizer guiding angle of 60°, a groove angle of 80°, and a forward velocity of 6 km/h, the average hole length was 87.6 mm, the coefficient of variation of hole length was 6.51%, and the coefficient of variation of hole spacing was 1.76%. Bench test results indicated that under conditions of a target fertilizer dosage per hole of 6.0 g, a forward velocity of 4–10 km/h, and a target hole spacing of 0.20–0.30 m, the fertilizer clusters consistently maintained their agglomerated state during descent. Field test results showed that under conditions of a target fertilizer dosage per hole of 2.0–8.0 g, a forward velocity of 4–10 km/h, and a target hole spacing of 0.20–0.30 m, the average hole length ranged from 94.5 to 223.0 mm, with a coefficient of variation of hole length of 7.17–11.16% and a coefficient of variation of hole spacing of 2.95–6.06%. Although hole formation performance was somewhat reduced in the field, the fertilizer in each hole remained in an aggregated state and was distributed uniformly. The collision between the fertilizer and the soil was the key factor affecting hole formation. The results of this study can provide insights and references for the design and optimization of fertilizer-hole-applied discharge devices. Full article

(This article belongs to the Section Agricultural Technology)

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27 pages, 3882 KB

Open AccessReview

Bionic Thermodynamic Model of the Stomatal System of a Plant Leaf: Energy Transformation and CO₂ Metabolism

by Tomas Ūksas and Simona Paulikienė

Agriculture 2026, 16(17), 1906; https://doi.org/10.3390/agriculture16171906 - 3 Sep 2026

Abstract

The mechanisms of plant leaf gas exchange and their relationship to energy transformation remain insufficiently studied quantitatively, limiting the assessment of CO₂ gas exchange processes. In this work, the stomatal system of a plant leaf is analyzed as a micro-, macro-, or [...] Read more.

The mechanisms of plant leaf gas exchange and their relationship to energy transformation remain insufficiently studied quantitatively, limiting the assessment of CO₂ gas exchange processes. In this work, the stomatal system of a plant leaf is analyzed as a micro-, macro-, or nanoscale thermodynamic system, applying modeling based on bionic principles. An idealized thermodynamic cycle is constructed, allowing for the assessment of the conversion of thermal energy into mechanical work. The theoretical upper limit of the thermal efficiency coefficient is estimated at η_t ≈ 0.003, and the mechanical energy flux, at a temperature difference of approximately 1 °C between the leaf and the ambient temperature, reaches up to 0.6 W/m², i.e., about 0.3% of the solar radiation flux absorbed by the leaf. The results obtained show that even with low efficiency, this energy transformation is sufficient to influence the intensity of gas exchange. Based on the model, the plant’s CO₂ sorption potential, depending on canopy area, was also estimated. It is concluded that the stomatal system of a plant leaf can be interpreted as a theoretical bionic energy transformation model, suitable for the analysis of CO₂ exchange processes and the development of bionic micro-, macro-, or nanoscale systems. Full article

(This article belongs to the Special Issue Mass and Energy Fluxes over Agricultural Ecosystems)

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30 pages, 4626 KB

Open AccessArticle

Nectar or Nemesis? The Asymmetric Impact of the Digital Economy on China’s Urban–Rural Income Gap

by Yi Shi, Huangxin Chen, Xi Wang, Su Lin and Tao Zhang

Agriculture 2026, 16(17), 1905; https://doi.org/10.3390/agriculture16171905 - 3 Sep 2026

Abstract

Common prosperity places the distributional consequences of digitalization at the center of China’s current development agenda. This study develops a two-level analytical framework linking macro-level structures to household income positions. The empirical analysis combines a prefecture-level panel for 2009–2022 with the China Family [...] Read more.

Common prosperity places the distributional consequences of digitalization at the center of China’s current development agenda. This study develops a two-level analytical framework linking macro-level structures to household income positions. The empirical analysis combines a prefecture-level panel for 2009–2022 with the China Family Panel Studies to examine how city-level digital development relates to the urban–rural income gap. City-level estimates indicate that more advanced digital economies are associated with a wider urban–rural income gap during the sample period. The mechanism estimates are consistent with possible channels involving skill-biased technological progress and unequal digital access and absorptive capacity. Moderation tests indicate that interaction between an “enabling government” and an “efficient market” can mitigate this widening trend. Evidence from the Broadband China pilot further suggests that infrastructure expansion without complementary institutions may intensify polarization, highlighting the limits of policy intervention. At the micro level, digital participation exhibits an inclusive yet asymmetric pattern. Internet use is associated with lower income-based relative deprivation in both groups, with a slightly larger estimated reduction among urban households. Taken together, the evidence points to a distributional tension between digital expansion and equity and supports policies that pair connectivity with stronger capabilities and inclusive institutions. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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17 pages, 3096 KB

Open AccessArticle

Selenium Biofortification of Popcorn Maize Microgreens by Nutri-Priming and Foliar Application

by Zoican Eugen Cătălin, Dario Iljkić, Ivana Varga, Jurica Jović, Miro Stošić, Boris Ravnjak and Monika Tkalec Kojić

Agriculture 2026, 16(17), 1904; https://doi.org/10.3390/agriculture16171904 - 3 Sep 2026

Abstract

Selenium (Se) biofortification may improve the nutritional value of microgreens, but its effect depends on the chemical form and application method. This study evaluated selenium applied as selenate or selenite through seed nutri-priming, foliar application, or their combination on the growth, biomass, mineral [...] Read more.

Selenium (Se) biofortification may improve the nutritional value of microgreens, but its effect depends on the chemical form and application method. This study evaluated selenium applied as selenate or selenite through seed nutri-priming, foliar application, or their combination on the growth, biomass, mineral composition, and estimated selenium intake of popcorn maize microgreens. Roots and aboveground tissues were analyzed separately to assess the potential use of both plant parts as sources of nutritionally valuable biomass. Seeds were treated with 40 µmol Se L⁻¹, and microgreens were harvested nine days after sowing. Selenium treatments significantly affected plant growth, fresh biomass, and the concentrations of P, Mn, Fe, Cu, Zn, and Se. Seed nutri-priming with selenite produced the best growth response, with the highest total plant length of 48.5 cm and the highest total fresh mass of 1.31 g per plant. The greatest selenium accumulation was obtained with seed nutri-priming using selenate combined with foliar application, reaching 890.90 µg kg⁻¹ d. m. in roots and 1389.80 µg kg⁻¹ d. m. in leaves. This treatment also resulted in the highest estimated daily intake (EDI), with 1.95 µg day⁻¹ from leaves and 1.25 µg day⁻¹ from roots. In contrast, the lowest EDI values were recorded after hydropriming followed by foliar selenate application, with 0.05 µg day⁻¹ in the leaves and 0.09 µg day⁻¹ in the roots. In general, selenite seed nutri-priming was more suitable for improving growth and biomass, whereas combined selenate application was the most effective strategy for selenium enrichment. The results also indicate that both roots and aboveground tissues may have potential value, although the use of root biomass requires further assessment of selenium bioavailability, safety, and suitability for food applications. Full article

(This article belongs to the Special Issue Advanced and Integrated Approaches for Nutritional, Chemical, and Quality Profiling of Vegetables)

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19 pages, 1742 KB

Open AccessArticle

Does Small-Scale Spatial Heterogeneity Influence Carbon Dioxide Emissions from Agricultural Sandy Soil? A Case Study

by Eszter Tóth, Imre Cseresnyés, Márton Dencső and Marianna Magyar

Agriculture 2026, 16(17), 1903; https://doi.org/10.3390/agriculture16171903 - 3 Sep 2026

Abstract

The sequestration and release of carbon in soil is a crucial aspect of agricultural production studies, involving numerous small-plot trials and modelling processes. Small-scale heterogeneity in soil properties can influence measured carbon dioxide (CO₂) fluxes. This study aimed (i) to compare [...] Read more.

The sequestration and release of carbon in soil is a crucial aspect of agricultural production studies, involving numerous small-plot trials and modelling processes. Small-scale heterogeneity in soil properties can influence measured carbon dioxide (CO₂) fluxes. This study aimed (i) to compare CO₂ emission from two neighbouring sandy soil plots managed with identical agricultural practices; (ii) to identify the key factors influencing soil CO₂ emissions; and (iii) to examine the effect of soil water content (SWC) and soil temperature (Ts) on the results. Two plots located approximately 30 m apart and differing in terms of their humus depths and contents were selected for investigation. Continuous SWC and Ts measurements were taken. Portable devices were used to determine CO₂ emissions, penetration resistance (PR) and vegetation cover. The humus layer in plot A was 55 cm thicker than in plot B, while the soil organic carbon (SOC) content was 18% and 163% higher in the 0–30 cm and 30–90 cm soil layers, respectively. Vegetation cover was nearly twice as high in plot A, and the mean soil CO₂ emissions were 36% higher than those measured in plot B. SWC showed an opposite trend, with plot B exhibiting values that were 9.7% and 17.7% higher than those of plot A in both the top and deepest soil layers, respectively. These findings emphasize the importance of including small-scale spatial heterogeneity when parameterizing or interpreting biogeochemical models, particularly when model inputs are based on limited soil measurements from specific locations. Full article

(This article belongs to the Special Issue Soil Carbon Enhancement for Sustainable Climate-Smart Agriculture)

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25 pages, 10586 KB

Open AccessArticle

Device and Algorithm Co-Design for Precise Monitoring of Matsumurasca onukii Trap-Capture Dynamics in Field Environments

by Shi-Lei Zhu, Shao-Ping Chen, Yan Shi, Jia-Xiong Chen, Zhi-Peng Li, Rong-Zhou Qiu and Jian Zhao

Agriculture 2026, 16(17), 1902; https://doi.org/10.3390/agriculture16171902 - 2 Sep 2026

Abstract

Precise monitoring of Matsumurasca onukii is essential for data-driven integrated pest management (IPM), yet existing automated monitoring systems are often limited by unstable outdoor illumination, morphological degradation of trapped insects, and target occlusions, resulting in reduced detection accuracy. To address these challenges, an [...] Read more.

Precise monitoring of Matsumurasca onukii is essential for data-driven integrated pest management (IPM), yet existing automated monitoring systems are often limited by unstable outdoor illumination, morphological degradation of trapped insects, and target occlusions, resulting in reduced detection accuracy. To address these challenges, an automated Internet of Things (IoT)-based tea pest monitoring system was developed through the coordinated design of an intelligent monitoring device and an enhanced detection model. The monitoring device employed an active mechanical decoupling mechanism to acquire images in a standardized optical chamber, while the detection model was designed to address detection difficulties associated with post-capture morphological degradation. In addition, a spatiotemporal correction procedure was introduced to improve counting reliability. Field trapping comparisons showed higher observed capture density for the IMD than for the standard and resized controls, with mean paired differences of 0.225 (95% CI, 0.109–0.380) and 0.275 (95% CI, 0.169–0.412) individuals/cm⁻², respectively, while RVBE-YOLO achieved an F1 score of 92.90%. Year-round deployment of three IMDs at one research site in 2025 showed close correspondence between system-generated and expert-derived daily counts (R² > 0.99; RMSE = 0.17–0.63) and captured clear seasonal variation in daily M. onukii trap captures. These results indicate that the proposed system can provide reliable and continuous records of M. onukii captures under the evaluated field conditions, supporting long-term automated pest monitoring in tea plantations. Full article

(This article belongs to the Section Agricultural Technology)

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20 pages, 8781 KB

Open AccessArticle

Comparative Evaluation of Three Temporary Immersion System Bioreactors for Improved In Vitro Propagation and Terpene Production in Myrtus communis L.

by Waed Tarraf, Anna De Carlo, Francesca Ieri, Gabriele Cencetti and Carla Benelli

Agriculture 2026, 16(17), 1901; https://doi.org/10.3390/agriculture16171901 - 2 Sep 2026

Abstract

Myrtus communis L. is an aromatic and medicinal plant commonly used in the pharmaceutical, food, and cosmetic industries for its bioactive compounds. Temporary immersion systems (TISs) are an efficient and cost-effective in vitro propagation method for enhancing biomass and secondary metabolite production under [...] Read more.

Myrtus communis L. is an aromatic and medicinal plant commonly used in the pharmaceutical, food, and cosmetic industries for its bioactive compounds. Temporary immersion systems (TISs) are an efficient and cost-effective in vitro propagation method for enhancing biomass and secondary metabolite production under controlled conditions. This study aimed to compare the effect of three different TIS bioreactors (SETIS™, Plantform™, and ElecTIS) and a conventional semisolid culture on relative growth rate (RGR), photosynthetic pigments, stomatal function and terpene content. The results showed that all bioreactors increased biomass production, with the highest RGR achieved in ElecTIS (7.1) after 28 days of culture. SETIS^TM induced 80% rooting and better stomatal density and functionality, resulting in a 98% survival rate of plants in acclimatization. Moreover, chlorophylls and carotenoids were significantly enhanced during rooting, particularly in SETIS™ and Plantform™. GC-MS analysis identified 14 volatile compounds, with myrtenyl acetate, linalool, and α-pinene as the dominant constituents. Rooted shoots cultured in Plantform™ and SETIS™ accumulated the highest terpene concentrations (341.5 and 326.4 μg g⁻¹ FW, respectively), which exceeded those of semisolid cultures. These findings demonstrate that TIS bioreactors, particularly SETIS™, represent a promising tool for the efficient production of biomass and terpenes, depending on the selection of the appropriate culture conditions, bioreactor type, and plant development stage. Full article

(This article belongs to the Special Issue Medicinal and Aromatic Crops: Cultivation, Quality, Processing, Application)

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20 pages, 2150 KB

Open AccessReview

From Soil Amendment to Fruit Quality: Evidence and Uncertainties in Organic Amendment-Driven Regulation of the Rhizosphere Microbiome in Fruit Tree Systems

by Zhenqing Xia, Zhuo Yan, Xinmei Ji, Yaqin Wu, Yusheng Li, Hehe Cheng, Xumin Wang, Chao Zhang, Da Zhang and Long Chen

Agriculture 2026, 16(17), 1900; https://doi.org/10.3390/agriculture16171900 - 2 Sep 2026

Abstract

Excessive chemical fertilization causes orchard soil degradation and fruit quality decline. Organic amendments serve dual functions in nutrient supply and ecological restoration. Yet the causal pathway through which they modulate fruit quality via the rhizosphere microbiome remains poorly understood. This review proposes a [...] Read more.

Excessive chemical fertilization causes orchard soil degradation and fruit quality decline. Organic amendments serve dual functions in nutrient supply and ecological restoration. Yet the causal pathway through which they modulate fruit quality via the rhizosphere microbiome remains poorly understood. This review proposes a cascade framework: “soil amendment → microbiome restructuring → root response → quality formation.” Regulatory evidence at each step is synthesized across organic amendment types. Results indicate that evidence for improvements in soil organic matter and aggregate stability is relatively well established. Shifts in microbial community composition are widely confirmed, yet their associations with soil functions remain predominantly correlative. The causal chain from microbiome to fruit quality has been validated in only a few cases; most underlying mechanisms remain hypothetical. These effects are modulated by tree species, rootstock, soil type, climate, and application regime, and are accompanied by risks of pathogen introduction and heavy metal accumulation. Priority research directions are proposed, including nutrient-matched controls, isotope tracing, re-inoculation of synthetic microbial communities, and multi-site long-term field trials. These directions aim to provide a scientific basis for reducing chemical fertilizer use while enhancing production efficiency in orchards. Full article

(This article belongs to the Section Crop Production)

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26 pages, 1007 KB

Open AccessArticle

Solanaceous-Vegetable Price Volatility and Producer Operating Income in China: Evidence from Three Production-Side Response Indicators

by Yuhao Lu and Fantao Kong

Agriculture 2026, 16(17), 1899; https://doi.org/10.3390/agriculture16171899 - 2 Sep 2026

Abstract

Solanaceous vegetables are fresh and perishable, are marketed in concentrated periods, and require production decisions to be made in advance; consequently, fluctuations in the price path can alter producers’ cash-flow arrangements, input schedules, and risk exposure. Using a balanced panel of 31 provincial-level [...] Read more.

Solanaceous vegetables are fresh and perishable, are marketed in concentrated periods, and require production decisions to be made in advance; consequently, fluctuations in the price path can alter producers’ cash-flow arrangements, input schedules, and risk exposure. Using a balanced panel of 31 provincial-level regions in China from 2014 to 2025, this study matches monthly prices of tomatoes, eggplants, and green peppers with annual vegetable operating income, variable costs per unit area, and provincial production conditions. Province and year two-way fixed effects are employed to examine the conditional associations between within-province price volatility and production-side outcomes. The price-volatility indicator aggregates annual crop-specific volatility, and its measurement stability is assessed using seasonal adjustment, the CV measure, the return-volatility measure, fixed base-period weights, and lagged production weights. The results show that higher price volatility is associated with weaker vegetable operating-income conditions and greater variable-cost pressure; supplementary analyses include production structure and investment, as well as risk exposure and response pressure, as exploratory outcomes. Lagged, threshold, and spatial tests further reveal the intertemporal linkages, regime differences, and regional clustering of price risk. At the provincial annual level, this study distinguishes changes in average prices from price uncertainty. It examines the economic manifestations of market risk through operating income and production-side adjustment. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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9 pages, 425 KB

Open AccessTechnical Note

Detection of Canola GMO Events Using Pentaplex Droplet Digital PCR

by Tigst Demeke, Monika Eng and Michelle Holigroski

Agriculture 2026, 16(17), 1898; https://doi.org/10.3390/agriculture16171898 - 2 Sep 2026

Abstract

Efficient detection and quantification of GMO events is necessary due to international regulatory requirements. Digital PCR (dPCR) has been widely used for detection and quantification of GMOs. The objective of this study was to detect and quantify canola GMO events using pentaplex droplet [...] Read more.

Efficient detection and quantification of GMO events is necessary due to international regulatory requirements. Digital PCR (dPCR) has been widely used for detection and quantification of GMOs. The objective of this study was to detect and quantify canola GMO events using pentaplex droplet digital PCR (ddPCR) and a six-colour droplet reader. The first pentaplex qualitative ddPCR assay included three element-specific (CaMV P35S, Tnos and tE9) and two event-specific (DP73496 and MON94100) targets, and the assay was used to detect 15 canola GMO events. The second pentaplex event-specific ddPCR assay was designed for the detection and quantification of five GMO events that can be found in commercially grown canola cultivars (DP73496, GT73, RF3, MS8 and MON88302). A total of 15 canola GMO events were detected at the 0.1% level using the first pentaplex qualitative ddPCR. Specific GMO events were also detected at 0.01 and 0.05% levels. Five major canola GMO events were detected and quantified using the second event-specific pentaplex ddPCR. DNA samples spiked at 0.1, 0.5 and 1% were successfully quantified using the event-specific pentaplex ddPCR. DNA concentrations of 0.01 and 0.05% were detected with the event-specific pentaplex ddPCR. The two developed pentaplex ddPCR assays will help facilitate efficient screening and quantification of canola GMO events. Full article

(This article belongs to the Special Issue Detection Methods for Genome-Edited (GE) Crops and Commercialized Genetically Modified (GM) Crops)

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24 pages, 13951 KB

Open AccessArticle

Flowering-Stage Heat Stress in Xinjiang Jujube Orchards: Spatiotemporal Evolution, Integrated Risk Assessment, and Multi-Scale Drivers

by Wenyue Hai, Jianghua Zheng, Chunrong Ji, Lei Wang, Nigela Tuerxun, Jianhao Li and Hong Fan

Agriculture 2026, 16(17), 1897; https://doi.org/10.3390/agriculture16171897 - 2 Sep 2026

Abstract

Jujube is an important economic fruit tree in China, with Xinjiang being the largest production region, where flowering-stage heat stress threatens yield stability. Assessing heat risk in jujube orchards requires consideration of crop-specific phenological sensitivity and heat injury thresholds. Therefore, this study developed [...] Read more.

Jujube is an important economic fruit tree in China, with Xinjiang being the largest production region, where flowering-stage heat stress threatens yield stability. Assessing heat risk in jujube orchards requires consideration of crop-specific phenological sensitivity and heat injury thresholds. Therefore, this study developed a Heat Injury Accumulating Index for jujube (HIS_j) to assess flowering-stage heat injury by integrating temperature–humidity stress and phenological sensitivity. A Hazard–Vulnerability–Exposure framework combined with Landsat image was applied for spatial heat risk assessment, atmospheric circulation analysis and interpretable machine learning were integrated to identify the drivers of hazard and vulnerability. Results show that HIS_j exhibited pronounced spatial heterogeneity and a distinct spatial dipole-like pattern, with higher values mainly concentrated in the oasis regions of eastern and southern Xinjiang, and an approximately six-year oscillation across most regions. High risk areas were mainly concentrated in Turpan, Yizhou District, and southern Bazhou, whereas Aksu, Kashgar, and most of Hotan were predominantly characterized by moderate-risk conditions. Climatic heat hazard and integrated orchard-scale risk were not spatially equivalent, with some intensively managed orchard areas exhibiting comparatively lower risk despite relatively strong meteorological heat stress. Variations in HIS_j were associated with the Western Pacific Subtropical High, Eurasian zonal circulation, and the India–Burma trough. NDVI was used as an observational proxy for orchard vegetation condition to characterize vegetation-based vulnerability. NDVI showed nonlinear associations with hydrothermal conditions and elevation, with threshold-like responses around 0.10–0.15 cm³/cm³ for soil moisture and around 800 m for elevation. The relatively weak and non-monotonic SHAP contribution of HIS_j to NDVI suggests that the association between meteorological heat stress and orchard vegetation conditions may vary with local environmental conditions. These findings provide a spatially explicit basis for understanding flowering-stage heat risk and supporting targeted adaptation in arid oasis jujube orchards. Full article

(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)

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20 pages, 3457 KB

Open AccessArticle

Rice Cultivation Duration Is Associated with Changes in Potential CO₂ Production, Q₁₀, Enzyme Activity, and Microbial Diversity in Saline–Alkali Soils

by Minghui Wang, Fanbing Xu, Xinyuan Ma, Liming Tian, Caixia Lv, Xiwen Zhang, Yuanbo Xie, Xiao Yao, Ziming Guo and Dan Zhang

Agriculture 2026, 16(17), 1896; https://doi.org/10.3390/agriculture16171896 - 2 Sep 2026

Abstract

Saline–alkali soils are important reserve resources for agricultural production. In western Jilin Province, China, large areas of saline–alkali land have been reclaimed as paddy fields; however, their carbon cycling responses to long-term rice cultivation and warming remain unclear. Using a space-for-time chronosequence approach, [...] Read more.

Saline–alkali soils are important reserve resources for agricultural production. In western Jilin Province, China, large areas of saline–alkali land have been reclaimed as paddy fields; however, their carbon cycling responses to long-term rice cultivation and warming remain unclear. Using a space-for-time chronosequence approach, a laboratory incubation experiment was conducted at 15 °C and 25 °C using soils collected from two soil layers (0–20 and 20–40 cm) in fields with 2, 5, 10, and 12 years of rice cultivation, together with an uncultivated reference field (CK). The results showed that cumulative potential soil carbon dioxide (CO₂) production was generally higher in cultivated soils than in CK, peaking at 5 years under 15 °C and at 10 years under 25 °C. It subsequently declined in the 10- and 12-year treatments at 15 °C and decreased slightly at 12 years at 25 °C. Soils with longer rice cultivation histories generally exhibited relatively high apparent temperature sensitivity (Q₁₀) at several stages of incubation, particularly in the 0–20 cm soil layer. Hydrolytic enzyme activities generally increased along the rice cultivation chronosequence, whereas polyphenol oxidase activity showed an overall declining trend, reflecting differences in potential enzymatic capacity for carbon transformation among cultivation duration treatments. Bacterial and fungal alpha diversity was generally higher in cultivated soils, particularly from the 5-year stage onward, and they also differed significantly among rice cultivation duration groups in both soil layers, although the fungal pattern in the 20–40 cm layer was partly influenced by heterogeneous within-group dispersion. Partial least squares path modeling showed that enzyme activity was strongly associated with cumulative potential soil CO₂ production at 25 °C and Q₁₀. These findings indicate that potential SOC mineralization across the rice cultivation chronosequence showed clear temperature-dependent patterns. This study provides insights into carbon cycling and its temperature response in reclaimed saline–alkali paddy soils and may inform their sustainable management under changing temperature conditions. Full article

(This article belongs to the Section Agricultural Soils)

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30 pages, 5359 KB

Open AccessArticle

An Improved Transformer-KAN Model for Soybean Mapping Based on Multi-Temporal Remote Sensing Data

by Chulin Pan, Jiachen Ju, Hongpeng Guo, Yufeng Jiang and Shuang Xu

Agriculture 2026, 16(17), 1895; https://doi.org/10.3390/agriculture16171895 - 1 Sep 2026

Abstract

Accurate and transferable soybean mapping is essential for agricultural monitoring and area verification, yet conventional Transformer models can be limited in modeling complex nonlinear phenological relationships and maintaining training stability. This study proposes an improved Transformer-KAN model for multi-temporal Sentinel-2 data. Temporal positional [...] Read more.

Accurate and transferable soybean mapping is essential for agricultural monitoring and area verification, yet conventional Transformer models can be limited in modeling complex nonlinear phenological relationships and maintaining training stability. This study proposes an improved Transformer-KAN model for multi-temporal Sentinel-2 data. Temporal positional encoding, multi-head self-attention with relative positional bias, and a Pre-LayerNorm residual structure are introduced to strengthen phenological sequence modeling, while FastKAN replaces the conventional MLP-based feed-forward network to enhance nonlinear feature representation. The model was trained using 2023 samples from Hailun City and directly evaluated in Bozhou, McLean, and Cass without retraining or fine-tuning. Cross-year transferability was further evaluated by applying the Hailun-trained model to data from Bozhou and McLean from 2021 to 2025. The proposed model achieved overall accuracies of 0.975, 0.983, 0.958, and 0.966 in Hailun, Bozhou, McLean, and Cass, respectively, with corresponding Kappa coefficients of 0.895, 0.887, 0.883, and 0.916. Complexity analysis showed that Transformer-KAN required 0.8142 M parameters and 1.1967 M FLOPs, with an average inference time of 3.0191 ms per sample, compared with 0.6130 M parameters, 0.7971 M FLOPs, and 1.4009 ms per sample for the conventional Transformer, indicating that the improved feature representation was accompanied by increased computational complexity. Cross-year classification performance remained generally high from 2021 to 2025, although interannual variations were observed due to differences in crop growth conditions, phenological timing, and image acquisition quality. Discrepancies between remote-sensing-derived and officially reported soybean areas were mainly related to differences in statistical definitions and residual classification uncertainties, rather than model transferability. Overall, Transformer-KAN provides accurate and transferable soybean mapping and can serve as a spatially explicit complement to official agricultural statistics. Full article

(This article belongs to the Topic Object Detection and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

4 pages, 277 KB

Open AccessEditorial

Multiple Soil Health Assessment Methods for Changing Agricultural Environment

by Irina Gabriela Cara, Iuliana Motrescu and Gerard Jităreanu

Agriculture 2026, 16(17), 1894; https://doi.org/10.3390/agriculture16171894 - 1 Sep 2026

Abstract

Soil is the foundation of resilient agricultural systems, yet its assessment remains a complex challenge due to its inherent variability across scales and management systems [...] Full article

(This article belongs to the Special Issue Multiple Soil Health Assessment Methods for Changing Agricultural Environment)

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