Current Issue : October-December Volume : 2026 Issue Number : 4 Articles : 5 Articles
Agricultural by-products such as apricot kernel shells (AKS) and walnut shells (WS) constitute a substantial portion of global food waste generated by processing industries. The shell composition has potential for sustainable industrial applications that align with circular economy goals. Microbial communities present on AKS and WS surfaces, or those introduced during postharvest handling and storage, may pose significant contamination. Monitoring microbial quality should be considered before repurposing as raw ingredients for cosmetic and food-related applications. Kyrgyzstan is a key Central Asian country for the natural agroforestry of walnuts and apricot agroforestry with integrated co-agriculture practices. We investigated the microbial communities associated with AKS and WS collected from Kyrgyzstan over three harvest years (2022–2024), using comparative samples from German supermarkets and an online platform. To assess microbial load, taxonomic diversity, and functional potential of the detected microorganisms on the shell surfaces, culture-dependent total viable count analysis and culture-independent shotgun metagenomic sequencing were employed. Harvest-dependent variations in microbial load were observed, with Proteobacteria dominant on WS, including Pantoea agglomerans and Xanthomonas arboricola. In contrast, AKS samples were dominated by the phylum Firmicutes, particularly Weissella confusa and Weissella cibaria. Three-month storage of shells at 20°C with 50% relative humidity led to noticeable changes in fungal diversity....
This study investigated the effects of different straw return practices—no-tillage with straw mulching (SM), shallow tillage with straw incorporation (SS), and deep tillage with straw incorporation (DS)—on the content and structural characteristics of soil water-soluble organic carbon (WSOC) under a maize–soybean rotation in the black soil region in the Northeast of China. Compared with SM, SS and DS increased WSOC content by 39.0% and 28.8% in the 0~20 cm layer (p < 0.05), and by 28.4% and 8.5% in the 20–40 cm layer, respectively. Deep tillage combined with straw return reduced the WSOC/SOC ratio. The DS treatment exhibited the highest levels under maize straw incorporation, while SM treatment showed the highest levels under soybean straw incorporation. Spectral indices in both maize and soybean seasons—including the fluorescence index (FI, ranging from 1.53 to 1.57 in the maize season and from 1.53 to 1.67 in the soybean season), biological index (BIX, ranging from 0.84 to 1.79 in the maize season and from 0.61 to 0.74 in the soybean season), and humification index (HIX, ranging from 0.51 to 0.79 in the maize season and from 0.84 to 0.97 in the soybean season)—collectively indicated that WSOC predominantly consisted of microbially processed organic matter with a low degree of humification. PARAFAC modeling resolved two fluorescent components in maize season: C1 (humic acid-like substances, accounting for 34.8–54.9%) and C2 (Tryptophan-like substance, accounting for 45.1–65.2%), and two components in the soybean season: C1 (humiclike substances, 51.0–53.7%), and C2 (Fulvic acid-like substance 46.3–49.0%). Overall, deep straw return promotes soil humification but increases the structural complexity of WSOC. This systematic investigation provides mechanistic insights into how straw return practices regulate the quantity and quality of labile carbon pools in agricultural ecosystems over time....
This study proposes an intelligent spraying vehicle speed control system integrating realtime canopy density detection with a fuzzy PID control algorithm. Utilizing LiDARacquired 3D point cloud data for canopy density calculation, the system dynamically adjusts PID parameters through fuzzy logic to achieve coordinated optimization of vehicle speed and spray volume. Based on the designed canopy density prediction model, a MATLAB/Simulink co-simulation framework integrating canopy perception with vehicle dynamics was established. Simulation results based on the MATLAB/Simulink platform demonstrate that the fuzzy PID controller achieves superior performance compared to conventional PID control. While maintaining a tracking accuracy of ±0.15 m/s, the proposed controller reduces speed overshoot by 5.8 percentage points. The developed control system ensures optimal speed tracking under varying canopy conditions, providing an extensible technical framework for intelligent sprayer vehicles....
Albic soils are a typical problematic soil type distributed worldwide. These soils are characterized by a thin humus layer, low organic matter content, nutrient insufficiency, and weak microbial activity. Therefore, microbial-based approaches hold great potential for the amelioration of Albic soils. This review synthesizes microbial characteristics, influencing factors, amelioration mechanisms, and related technical efficacy of Albic soils. Microbial communities of Albic soils exhibit distinct regional characteristics, with Acidobacteriota and Proteobacteria dominating the bacterial community. Reasonable agricultural management practices—including deep plowing and subsoil mixing, combined organic fertilization and straw return—can increase microbial biomass by 62–248% and enhance enzyme activities by 12–303%, ultimately increasing crop yield by 1.5–13%. Such practices drive fertility enhancement and ecological functional improvement in Albic soils. Inoculation with functional microbes (e.g., Arbuscular Mycorrhizal Fungi, Trichoderma) alleviates Albic soil acidification by 1.1–3.8%, activates recalcitrant nutrients, and accelerates Soil Organic Matter (SOM) decomposition. Through extracellular polymeric substance secretion, such inoculation promotes aggregate formation, improving soil permeability and structural stability. However, challenges remain for current research, including difficult microbial agent colonization, unstable amelioration effects, and a lack of long-term field studies. Future research should utilize bio-omics technologies, artificial intelligence, and big data technologies to analyze microbial functions and regulate soil quality for cultivated land improvement and sustainable agriculture development....
The impact of warmer droplets on cold leaves in sprinkler anti-frost is a case of agricultural engineering involving multiphysics. This study models the leaf as an elastic body of finite thickness, incorporates the temperature field, and establishes a fluid–solid–thermal multiphysics coupling model. The effects of droplet velocity, droplet diameter, and initial temperature are analyzed accordingly. The results show that the higher the Weber number (We) of the droplet, the higher the droplet spreading coefficient and the leaf stress. The maximum spreading coefficient and maximum leaf strain atWe of 1583.1 are 1.58 and 4.75 times those atWe of 1055.4, respectively. There is a gradual decrease in the leaf deformation, a very rapid process, a cycle of about 10% of the spreading time. The temperature at the impact point on the leaf surface increased with the droplet’s initial temperature but could be influenced by an air bubble trapped at the droplet’s bottom. The modeling and analysis of the dynamics of droplet impact on plant leaves enabled a better understanding of the mechanisms of sprinkler frost protection....
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