Search Results (8,108)

The electromagnetic induction (EMI) and frequency domain reflectometry (FDR) sensors, which measure the soil apparent electrical conductivity (ECa) in situ, have emerged as efficient and rapid tools for the indirect assessment of soil salinity, conventionally determined by the electrical conductivity of the saturated soil paste extract (ECe). However, the limitations of applying a single soil sensor and the ECa dependence on multiple soil properties, such as soil moisture and texture, can hinder the interpretation of ECe, whereas selecting the most appropriate set of sensors is challenging. To address these issues, this study explored the prediction ability of a noninvasive EM38-MK2 (EMI) and a capacitance dielectric WET-2 probe (FDR) in assessing topsoil salinity and texture within 0–30 cm depth across diverse soil and land-use conditions in Laconia, Greece. To this aim, multiple linear regression models of laboratory-estimated ECe and soil texture were constructed by the in situ measurements of EM38-MK2 and WET-2, and their performances were individually evaluated using statistical metrics. As was shown, in heterogeneous soils with sufficient wetness and high salinity levels, both sensors produced models with high adjusted coefficients of determination (adj. R² > 0.82) and low root mean square error (RMSE) and mean absolute error (MAE), indicating strong model fit and reliable estimations of topsoil salinity. For the EM38-MK2, model accuracy improved when clay was included in the regression, while for the WET-2, the soil pore water electrical conductivity (ECp) was the most accurate predictor. The drying soil surface was the greatest constraint to both sensors’ predictive performances, whereas in non-saline soils, the silt and sand were moderately assessed by the EM38-MK2 readings (0.49 < adj. R² < 0.51). The results revealed that a complementary use of the contemporary EM38-MK2 and the low-cost WET-2 could provide an enhanced interpretation of the soil properties in the topsoil without the need for additional data acquisition, although more dense soil measurements are recommended. Full article

High-precision automated detection of metal welding defects is critical to ensuring structural safety and reliability in modern manufacturing. However, existing methods often struggle with insufficient fine-grained feature retention, low efficiency in multi-scale information fusion, and vulnerability to complex background interference, resulting in low detection accuracy. This work addresses the limitations by introducing the DEIM-SFA, a novel detection framework designed for automated visual inspection in industrial machine vision sensors. The model introduces a novel structure-aware dynamic convolution (SPD-Conv), effectively focusing on the fine-grained structure of defects while suppressing background noise interference; an innovative multi-scale dynamic fusion pyramid (FTPN) architecture is designed to achieve efficient and adaptive aggregation of feature information from different receptive fields, ensuring consistent detection of multi-scale targets; combined with a lightweight and efficient multi-scale attention module (EMA), this further enhances the model’s ability to locate salient regions in complex scenarios. The network is evaluated on a self-built welding defect dataset. Experimental results show that DEIM-SFA achieves a 3.9% improvement in mAP50 compared to the baseline model, mAP75 by 4.3%, mAP50–95 by 3.7%, and Recall by 1.4%. The model exhibits consistently significant superiority in detection accuracy across targets of various sizes, while maintaining well-balanced model complexity and inference efficiency, comprehensively surpassing existing state-of-the-art (SOTA) methods. Full article

The deep integration of artificial intelligence (AI) is a core driver for digitalization and intelligence in agricultural and food engineering, boosting production efficiency, resource optimization, and product quality. This review systematically analyzes AI’s application scenarios, technical pathways, and challenges across the agricultural value chain. It aims to develop a structured taxonomy of AI-driven technical application mechanisms in agriculture, highlighting their roles in optimizing core agricultural processes. A systematic literature review was conducted using reputable databases, including Google Scholar, IEEE Xplore, ScienceDirect, Web of Science, SpringerLink, and Scopus, focusing on peer-reviewed articles from the last decade. Findings show that AI-enhanced techniques improve product quality and safety inspection efficiency. However, challenges like multi-source data synchronization barriers, high intelligent equipment costs, and model adaptability limitations in complex agricultural environments remain. This review contributes to the field by providing a unified framework for understanding AI applications in agri-food engineering, identifying key research gaps, and highlighting pathways for sustainable technology adoption that can benefit diverse agricultural stakeholders. Full article

Continued population growth demands a significant increase in agricultural production to ensure food security. However, agricultural output is limited by environmental crises and the negative impacts of open-field farm practices. As an alternative, vertical farming techniques, such as aeroponics, can be utilized to optimize the use of resources. However, the uneven size and distribution of spray droplets in aeroponics, issues that affect root development and nutrient delivery, continue to be problematic in spray performance analysis. In aeroponics, nutrient solutions are delivered to plant roots through pressurized nozzles, and the effectiveness of this delivery depends on the spray characteristics. Variations in flow rates directly affect droplet size, density, and coverage, which in turn influence nutrient uptake and crop growth. In this study, the flow rate was adjusted (3, 4.5, and 6 L/min) to quantitatively analyze spray performance using water-sensitive paper (WSP) as a deposit collector via a quick assessment method. Subsequently, image-processing techniques such as threshold segmentation and morphological operations were applied to isolate individual spray droplets on the WSP images. This technique enabled the quantification of the droplet’s coverage area, size, density, and uniformity to effectively evaluate spray performance. One-way ANOVA indicated that all the spray parameters varied significantly with respect to the flow rate (p < 0.05): For example, the average diameters of the droplets increased from 0.73 mm at 3 L/min to 1.29 mm at 6 L/min. The droplets’ densities decreased from 85.53 drops/cm² to 30.00 drops/cm² across the same flow range. The average uniformity index improved from 30.53 to 15.95 as the flow rate increased. These results indicate that the application of WSP is an effective and scalable approach for analyzing spray performance in aeroponics, as WSP can be rapidly digitized with simple tools, such as a cell phone camera, avoiding the limitations of flatbed scanners or specialized imaging systems. Full article

The use of saline water (low-quality water) in irrigation is a reality in many regions, especially in areas where fresh water is scarce, like semi-arid regions. However, it is important to adopt strategies to minimize the damage caused by salt stress to plants. The use of soil conditioners can help improve soil structure and water retention capacity, reducing salinity effects. The objective was to analyze the potential of a soil conditioner (hydrogel) as a mitigator of salty stress by irrigation with saline water in ornamental sunflower. Two sunflower cycles were carried out in a protected environment with a factorial 4 × 4 consisting of four doses of hydrogel polymer (0.0, 0.5, 1.0, and 1.5 g kg⁻¹) and four different levels of irrigation with saline water (0.5, 2.0, 3.5, and 5.0 dS m⁻¹). Plant biomass and physiological parameters, such as chlorophyll fluorescence measurements and gas exchange parameters, stomatal conductance, transpiration, and photosynthesis, were evaluated. Ornamental sunflower showed better performance with a saline water of 0.5 dS m⁻¹ without the use of hydrogel. At higher salinity levels, with a hydrogel dose of 1.5 g kg⁻¹, the sunflower achieved favorable performance, promoting gains in some gas exchange variables in plants irrigated with saline water at 3.5 dS m⁻¹ and in fluorescence-related variables within the range of 2.0 to 3.5 dS m⁻¹. This positive effect of hydrogel indicates its potential as a mitigating strategy against the adverse effects of salinity, contributing to the maintenance of plant vigor and physiological functionality in saline environments. Full article

Biomass pellets are widely used for combustion but can also serve as sustainable feedstocks for pyrolysis. This study examined wood (WP), palm-pruning (PP), reed (RD), and daphne (DP) pellets. We present a compact framework linking composition (proximate/ultimate and lignocellulosic fractions) with TG/DTG, FTIR, TGA-derived indices (CPI, D_dev, R_w), T_pmax and R_av to predict product selectivity and temperature ranges. TG/DTG showed the following sequence: hemicellulose (≈200–315 °C) first, cellulose (≈315–400 °C) with a sharp maximum, and lignin ≈200–600 °C. Low-ash WP and DP had sharper, higher peaks, favoring concentrated devolatilization and condensables. Mineral-rich PP and RD began earlier and showed depressed peaks from AAEM catalysis, shifting toward gases and ash-richer chars. Composition shaped these patterns: higher cellulose increased R_av and CPI; links to T_pmax were moderated by ash. Lignin strengthened a high-T shoulder, while hemicellulose promoted early deacetylation (RD’s 1730 cm⁻¹ acetyl C=O) and release of CO₂ and acids. Correlations (|r| ≥ 0.70) supported these links: VM with total (m_∞) and second stage mass loss; cellulose with R_av and CPI (T_pmax moderated by ash); lignin and O/C with T_f and last stage mass loss; ash negatively with T_i, T_pmax, and m_∞. The obtained results guide the sustainable valorization of biomass pellets by selecting temperatures for liquids, H₂/CO-rich gases or low-ash aromatic chars. Full article

Livestock and poultry genetic resources form the cornerstone of elite population breeding, new breed development, and global food security. The yak (Bos mutus), endemic to the Qinghai–Tibet Plateau, is indispensable for maintaining regional biodiversity and ecological stability. The Datong yak—China’s first nationally recognized cultivated yak breed and the world’s inaugural domesticated yak variety—plays a pivotal role in enhancing yak production performance, mitigating grassland–livestock conflicts, and restoring degraded grasslands. This study aimed to provide a scientific basis for the conservation and sustainable utilization of yak genetic resources by comprehensively evaluating the genetic resource value of Datong yaks. We employed the market price method, opportunity cost method, and shadow engineering method to assess four value dimensions—aligned with the Food and Agriculture Organization (FAO) livestock genetic resource value framework and adapted to China’s yak production context: direct use value (DUV), indirect use value (IUV), potential use value (PUV), and conservation value (CV). Data were collected through expert consultations, semi-structured interviews, and questionnaire surveys in Datong County (Qinghai Province, the core production area of Datong yaks) between August and September 2024, with the widely distributed Qinghai Plateau yak serving as the control breed. Based on a recent market survey, the total genetic resource value of Datong yaks in China was estimated at CNY 2.505 billion in 2024, highlighting the increasing economic and strategic significance of yak genetic resources. Among the four value dimensions, PUV accounted for the largest share (65.67%), driven by superior production performance, market price premiums, and reduced feeding costs. DUV contributed 20.72%, reflecting the value of biological assets and beef products; IUV represented 7.10%, primarily associated with grassland conservation benefits; and CV constituted 6.51%, encompassing costs for genetic resource preservation and cultural heritage contributions. These results underscore the substantial potential of Datong yak genetic resources, particularly given their unique adaptation to high-altitude environments and their critical role in supporting local livelihoods and ecological stability. Future research should focus on expanding breeding programs and genetic conservation, optimizing industrial and value chains, and strengthening genetic improvement initiatives to promote ecological security and sustainable development of the yak industry on the Qinghai–Tibet Plateau. Full article

In this study, a driving test was conducted using a small-tracked forestry tractor with a scale of 1/11 in the shape of an actual tractor to assess safety under dynamic conditions. The driving conditions resulting in lateral overturning were derived. Additionally, an angular velocity sensor was used to analyze the variation in roll angular velocity with driving conditions. Driving condition variables comprised obstacle height, ground slope angle, and driving speed. Obstacle height had five levels between 0 and 40 mm in 10 mm intervals, and ground slope angle had 11 levels at 5° intervals from 0° to 50°. Driving speed had three levels: 0.07, 0.11, and 0.13 m/s. The ground slope angle resulting in lateral overturning in the driving scenario was lower than that in non-driving under all conditions. Roll angular velocity increased as obstacle height and tractor driving speed increased. However, ground slope angle did not significantly affect angular velocity. Roll angular velocity at the moment of lateral overturning was about 90 deg/s regardless of driving conditions. A certain critical angular velocity was found to induce lateral overturning, and adjusting the driving method such as reducing driving speed and making turns when the roll angular velocity of the tractor approached the critical value improved safety. However, the quantitative results from the small tractor cannot be directly applied to full-size tractors. Although numerical values may differ, this study focused on capturing the overall trends in lateral overturning considering various driving conditions. Future studies can improve the practical applicability of these findings by determining the critical angular velocity of various full-size tractors. Full article

To solve the problems of large root damage and incomplete seedling blocks (SBs) in rice machine transplanting, this study numerically optimized the root blanket-cutting device for rice blanket seedling cutting and throwing transplanters based on the discrete element method (DEM) and multi-body dynamics (MBD) coupling method. A longitudinal sliding cutter (LSC)–substrate–root interaction model was established. Based on the simulation tests of Center Composite Design and response surface analysis, the sliding angle and cutter shaft speed of the LSCs arranged at the circumferential angles (CAs) of 0°, 30°, and 60° were optimized. The simulation results indicated that the LSC arrangement CA significantly affected the cutting performance, with the optimal configuration achieved at a CA of 60°. Under the optimal parameters (sliding angle of 57°, cutter shaft speed of 65.3 r/min), the average deviation between the simulated and physical tests was less than 11%, and the reliability of the parameters was verified. A seedling needle–substrate–root interaction model was established. The Box–Behnken Design method was applied to conduct simulation tests and response surface optimization, focusing on the picking angle, needle width, and rotary gearbox speed. The simulation results showed that the picking angle was the key influencing factor. Under the optimal parameters (picking angle of 20°, seedling needle width of 15 mm, rotary gearbox speed of 209 r/min), the average deviation between the simulated and physical tests was less than 10%, which met the design requirements. This study provides a new solution for reducing root injury, improving SB integrity, and reducing energy consumption in rice transplanting, and provides theoretical and technical references for optimizing transplanting machinery structure and selecting working parameters. Full article

Alternative housing systems for laying hens, such as the aviary, promote the expression of dustbathing behavior by providing substrate materials to improve their welfare. However, extensive litter areas in aviaries can lead to reduced air quality and increased incidence of diseases, making them unsuitable for deployment in new large cage aviary unit (LCAU) systems in China. Dust baths have advantages in terms of continuous availability, but their design lacks unified standards. This study explored the effects of different areas, shapes (circular and square), and substrate depths (1 cm, 5 cm, 9 cm) of dust baths on dustbathing behavior in LCAU systems by recording digital video. Each LCAU system was initially populated with 305 Jingfen No. 2 laying hens at 50 days of age. The dust baths were initially placed on the bottommost tier at 66 days of age. The results showed that after approximately 3 weeks of adaptation to dustbathing, the average daily proportion of dustbathing hens within the flock stabilized at approximately 10%. A 50 cm diameter circular dust bath could accommodate their dustbathing requirements. Increasing the number of circular dust baths to 2 did not significantly affect the daily proportion of dustbathing hens. Both the circular dust bath and a 5 cm depth substrate resulted in better expression of the hens’ side rubbing behavior and the lower frequency of tossing behavior. Full article

In Northeast Brazil, climatic factors and technology synergistically enhance melon productivity and fruit quality. However, the region requires further research on the efficient use of water resources, particularly in determining the crop coefficient (Kc), which comprises the evaporation coefficient (Ke) and the transpiration coefficient (Kcb). Air temperature affects crop growth and development, altering the spectral response and the Kcb. However, the direct influence of air temperature on Kcb and spectral response remains underemphasized. This study employed unmanned aerial vehicle (UAV) with RGB and Red-Green-NIR sensors imagery to extract biophysical parameters for improved water management in melon cultivation in semiarid northern Bahia. Field experiments were conducted during two distinct periods: warm (October–December 2019) and cool (June–August 2020). The ‘Gladial’ and ‘Cantaloupe’ cultivars exhibited higher Kcb values during the warm season (2.753–3.450 and 3.087–3.856, respectively) and lower during the cool season (0.815–0.993 and 1.118–1.317). NDVI-based estimates of Kcb showed strong correlations with field data (r > 0.80), confirming its predictive potential. The results demonstrate that UAV-derived NDVI enables reliable estimation of melon Kcb across seasons, supporting its application for evapotranspiration modeling and precision irrigation in the Brazilian semiarid context. Full article

Chiral amines are vital structural motifs in pharmaceuticals and agrochemicals, where enantiomeric purity governs bioactivity and environmental behavior. We identified a novel (R)-selective amine transaminase (MwoAT) from Mycobacterium sp. via genome mining, which exhibits activity toward the synthesis of the chiral amine (R)-1-methyl-3-phenylpropylamine. The enzyme displayed optimal activity at pH 7.0 and 40 °C, with high thermostability and solvent tolerance. Using an AlphaFold3-guided semi-rational engineering strategy integrating molecular docking, alanine scanning, and saturation mutagenesis, residue L175 was pinpointed as critical for substrate binding. The resulting L175G variant exhibited a 2.1-fold increase in catalytic efficiency (k_cat/K_m) and improved thermal stability. Applied to the asymmetric synthesis of (R)-1-methyl-3-phenylpropylamine—a precursor for the antihypertensive drug dilevalol and potential scaffold for crop protection agents—the mutant achieved 26.4% conversion with ≥99.9% ee. The enzyme also accepted several ketones relevant to agrochemical synthesis, underscoring its versatility. This work delivers an engineered biocatalyst for sustainable chiral amine production and demonstrates an AI-assisted protein engineering framework applicable to both medicinal and agricultural chemistry. Full article

Conventional ridging and mulching machines struggle to perform effectively in yellow sand substrates due to their loose texture, high collapsibility, and strong fluidity, which compromise ridge stability and operational quality. To address these challenges, this study proposes the development of an integrated rotary tillage, ridging, and film-mulching machine specifically designed to meet the agronomic requirements of tomato cultivation in greenhouse environments with yellow sand substrate. Based on theoretical analysis and parameter calculations, a soil transportation model was established, and the key structural parameters—such as blade arrangement and helical shaft geometry—were determined. A discrete element method (DEM) simulation was employed to construct a contact model for the yellow sand–slag mixed substrate. A combination of single-factor experiments and Box–Behnken response surface methodology was used to investigate the effects of forward speed, shaft rotational speed, and tillage depth on ridge stability and operational performance. The simulation results indicated that a forward speed of 0.82 m·s⁻¹, shaft speed of 260 rpm, and tillage depth of 150 mm yielded the highest ridge stability, with an average of 95.7%. Field trials demonstrated that the ridge top width, base width, height, and spacing were 598.6 mm, 802.3 mm, 202.4 mm, and 1002.8 mm, respectively, with an average ridge stability of 94.3%, differing by only 1.4 percentage points from the simulated results. However, a quantitative traction/energy comparison with conventional equipment was not collected in this study, and we report this as a limitation. The energy consumption is estimated based on power usage and effective field capacity (EFC) under similar operating conditions. Soil firmness reached 152.1 kPa, fully satisfying the agronomic requirements for tomato cultivation. The proposed machine significantly improves operational adaptability and ridge stability in yellow sand substrate conditions, providing robust equipment support for efficient greenhouse farming. Full article

Against the backdrop of global agricultural transformation, rural China faces the critical challenge of reconciling economic development with environmental conservation and social well-being. This study, grounded in the rural revitalization strategy, investigates the internal mechanisms, level measurement, and sustainable development paths of rural industrial integration based on the “Triple Integration of Production, Livelihood and Ecology” (PLE) philosophy. Firstly, we discussed the suitability and the mechanisms of this philosophy on China’s rural industrial integration. Secondly, based on a textual corpus extracted from academic journals and policy documents, we employed an LDA topic model to cluster the themes and construct an evaluation indicator system comprising 29 indicators. Then, utilizing data from the China Statistical Yearbook and the China Rural Statistical Yearbook (2013–2022), we measured the level of China’s rural industrial integration using the entropy method. The composite integration index displays a continuous upward trend over 2013–2022, accelerating markedly after the 2015 stimulus policy, yet a temporary erosion of “production–livelihood–ecology” synergy occurred in 2020 owing to an exogenous shock. Lastly, combining the system dynamics model, we simulated over the period 2023–2030 the three sustainable development scenarios: green ecological development priority, livelihood standard development priority and production level development priority. Research has shown that (1) the “Triple Synergy of Production, Livelihood and Ecology” philosophy and China’s rural industrial integration are endogenously unified, and they form a two-way mutual mechanism with the common goal of sustainable development. (2) China’s rural industrial integration under this philosophy is characterized by production-dominated development and driven mainly by processing innovation and service investment, but can be constrained by ecological fragility and external shocks. (3) System dynamics simulations reveal that the production-development priority scenario (Scenario 3) is the most effective pathway, suggesting that the production system is a vital engine driving the sustainable development of China’s rural industrial integration, with digitalization and technological innovation significantly improving integration efficiency. In the future, efforts should focus on transitioning towards a people-centered model by restructuring cooperative equity for farmer ownership, building community-based digital commons to bridge capability gaps, and creating market mechanisms to monetize and reward conservation practices. Full article

Accurate leaf area measurement is essential for plant growth monitoring and ecological research; however, it is often challenged by perspective distortion and color inconsistencies resulting from variations in shooting conditions and plant status. To address these issues, this study proposes a visual and semi-automatic measurement system. The system utilizes Hough transform-based perspective transformation to correct perspective distortions and incorporates manually sampled points to obtain prior color information, effectively mitigating color inconsistency. Based on this prior knowledge, the level-set function is automatically initialized. The leaf extraction is achieved through level-set curve evolution that minimizes an energy function derived from a multivariate Gaussian distribution model, and the evolution process allows visual monitoring of the leaf extraction progress. Experimental results demonstrate robust performance under diverse conditions: the standard deviation remains below 1 cm², the relative error is under 1%, the coefficient of variation is less than 3%, and processing time is under 10 s for most images. Compared to the traditional labor-intensive and time-consuming manual photocopy-weighing approach, as well as OpenPheno (which lacks parameter adjustability) and ImageJ 1.54g (whose results are highly operator-dependent), the proposed system provides a more flexible, controllable, and robust semi-automatic solution. It significantly reduces operational barriers while enhancing measurement stability, demonstrating considerable practical application value. Full article