Search Results (10,377)

Efficient pest control in orchards is crucial for preserving crop quality and maximizing yield. A key factor in optimizing automated variable-rate spraying is accurate tree canopy size estimation, which helps reduce pesticide overuse while minimizing environmental and health risks. This study evaluates the performance of two advanced convolutional neural networks, PP-LiteSeg and fully convolutional networks (FCNs), for segmenting tree canopies of varying sizes—small, medium, and large—using short-term dense-connection networks (STDC1 and STDC2) as backbones. A dataset of 305 field-collected images was used for model training and evaluation. The results show that FCNs with STDC backbones outperform PP-LiteSeg, delivering superior semantic segmentation accuracy and background classification. The STDC1-based model excels in precision variable-rate spraying, achieving an Intersection-over-Union of up to 0.75, Recall of 0.85, and Precision of approximately 0.85. Meanwhile, the STDC2-based model demonstrates greater optimization stability and faster convergence, making it more suitable for resource-constrained environments. Notably, the STDC2-based model significantly enhances canopy-background differentiation, achieving a background classification Recall of 0.9942. In contrast, PP-LiteSeg struggles with small canopy detection, leading to reduced segmentation accuracy. These findings highlight the potential of FCNs with STDC backbones for automated apple tree canopy recognition, advancing precision agriculture and promoting sustainable pesticide application through improved variable-rate spraying strategies. Full article

European plum production is affected by mostly harm Monilinia spp., causing full pathogen brown-rot infections. The plums are the susceptible to the Monilinia fructigena pathogen, which is the most common in Europe. This study aims to analyze the gene expression profiles and signaling pathways of the European plum, cv. Victoria, inoculated with the M. fructigena pathogen at 24, 48, and 72 h post inoculation. By transcriptome sequencing, the number of differentially expressed genes (DEGs) increased over time, with the highest number at 72 hpi, showing the tendency to involve more genes in the response to prolonged exposure to the pathogen. Pathogenesis-related (PR) family and mildew resistance locus O (MLO-like) proteins were expressed the most during plum response to the pathogen. The plum initiates complex defense responses by significantly activating 23 pathways according to Kyoto Encyclopedia of Genes and Genomes (KEGG). In this study, expressed genes over the infection were in response to stress, defense, cell death, and disease resistance. The findings of this study could be used as the basis for further research of markers linked to resistance or susceptibility to disease in plum hybrids at an early age, which will improve the plum breeding process. Full article

The prohibition zone policy restricts certain activities in specific areas to protect the environment, while the emission permit policy allows companies to trade emissions permits as a market-based approach to regulation. Can the two policies jointly promote the carbon emission reduction of the pig breeding industry (PBI)? Based on the panel data of 31 provinces and cities in China from 2010 to 2020, this paper adopts propensity score matching and multi-period difference-in-differences (PSM-DID) models to study the impact of the dual policy of the prohibition zone and emission permit on the carbon emissions of the PBI. Our theoretical and empirical findings suggest that the dual policy significantly reduces carbon emissions in the PBI. A mediating analysis reveals that industrial structure and government penalties regulate the impact of the dual policy. Further analysis shows that the prohibition zone policy and the emission permit policy play a synergistic role in the impact on the carbon emissions of the PBI. Regional heterogeneity is also explored, indicating that the carbon emission reduction effect is more significant in western China. Policy implementers should fully consider various policies, regional differences, and regulatory factors, formulating complementary policy combinations to jointly promote the green new quality productivity of the PBI. Full article

The aim of this study was to evaluate the influence of innovative mineral–organic mixtures containing zeolite composites produced from fly ashes and lignite or leonardite on the fractional composition of soil organic matter in sandy loam soil under two-year pot experiments with maize. The fractional composition of soil organic matter (SOM) was analyzed and changes in the functional properties of soil groups were identified using the ATR-FTIR method. Changes in the content of phenolic compounds were assessed, and the potential impact of fertilizer mixtures on soil carbon stocks was investigated. The addition of these mixtures improved the stability of SOM. The application of mineral–organic mixtures significantly increased the total organic carbon (TOC) by 18% after the 2nd year of the experiment. The maximum TOC content in the soil was observed by 33% with the addition of MC3%Leo3% amendment. Nitrogen content in soil was increased by 62% with MV9%Leo6% additive, indicating increased soil fertility. The study highlighted an increase in fulvic acid carbon relative to humic acid carbon, signaling positive changes in organic matter quality. The new mineral–organic mixtures influence changes in specific functional groups (ATR-FTIR) present in the soil matrix, compared to mineral fertilization alone. The additive mixtures also contributed to an increase in soil carbon stocks, highlighting their potential for long-term improvement of soil fertility and carbon sequestration. Full article

Amending saline–alkali soils to improve agricultural productivity is critical for addressing global food security challenges. Biochar is a promising soil amendment, and its modified composites offer significant potential for soil remediation. In this study, we developed a novel phosphoric acid–mineral-comodified biochar composite for saline–alkali soil improvement. SEM and XRD analyses indicate that chemical interactions between phosphoric acid, minerals, and biochar result in the formation of distinct mineral phases on the composite surface. Furthermore, FTIR analysis reveals that these interactions give rise to functional groups such as Si-O-Si, and thermogravimetric analysis demonstrates that the modified biochar composite exhibited enhanced stability. Compared with raw biochar, the modified biochar composites exhibited significant decreases in pH, EC, and base cation content (especially Na⁺), with maximum reductions of 7.26 pH units, 639.5 μS/cm, and 3.69 g/kg, respectively. In contrast, the contents of P, Si, and Ca increased significantly, with maximum increases of 140.04 g/kg, 90.32 g/kg, and 114.27 g/kg, respectively. In addition, the specific surface area and pore volume of the modified biochar composite increased by up to 5.2 and 15 times, respectively. Principal component analysis indicates that mineral type was the primary factor influencing the properties of the composites: hydroxyapatite enhanced porosity and phosphorus levels, whereas kaolinite and montmorillonite increased silicon content. Pot experiments show that the modified biochar composite increased alfalfa plant height by 17.36–20.27% and shoot biomass by 107.32–125.80% in saline–alkali soils. Overall, the newly developed phosphoric acid–mineral–biochar composites were evaluated to have high application potential for saline–alkali soil amendment. Full article

The management of Dollar spot, the fungal disease of turfgrasses, is complicated and, today, tends to include new eco-friendly approaches. The aim of this study is to evaluate the effect of UV-B and UV-C lamps against the infection of Clarireedia species in warm- and cool-season turfgrasses. In vitro tests were performed to evaluate the growth of C. jacksonii mycelium on Potato Dextrose Agar, irradiated with UV-B and UV-C at heights of 5 and 15 cm, 5 s per day for three consecutive days. The same treatments, prolonged for seven days, were applied on naturally infected potted Agrostis stolonifera and Cynodon dactylon × C. transvaalensis, for in vivo tests. Disease severity, antioxidant capacity, and pigment content were assessed at the end of the experiment. Only UV-C reduced the growth of C. jacksonii after 48 h at 5 cm (−36%) and 72 h at both distances (−15 and −27%). Agrostis stolonifera showed symptoms, reduced by UV-C at 5 cm, and fungal structures, except in UV-C exposed samples. Total antioxidant capacity increased after UV-B exposure at 5 cm (+10%). No variations in terms of photosynthetic pigments were observed. These results confirm the potential of UV-C lamps for the containment of Dollar spot. Full article

The aim of the present study was to determine the in vitro starch digestibility kinetics of rehydrated maize grain silages in pigs and to investigate the relationship between the in vitro starch digestibility rate and the physical properties of the mature grain. Grains of seven commercial maize hybrids were harvested at physiological maturity, rehydrated, and ensiled with a commercial inoculant during different ensiling periods (0, 21, and 95 days) in five replicates using a completely randomized design. The starch digestibility rate was determined using first-order kinetics following an in vitro digestibility procedure mimicking the stomach and small intestine of pigs. The tested hybrids differed in their physical properties (test weight, kernel size, and density and hardness), digestion coefficients, and starch digestibility rate (p < 0.05). The starch digestibility rate increased with an increasing ensiling period, with average values of 0.588, 1.013, and 1.179 1/h for 0, 21, and 95 days of ensiling period, respectively. However, the effect of ensiling was more pronounced in hybrids with higher grain hardness, reaching a rate of 1.272 1/h in hybrids with higher grain hardness compared to 1.110 1/h in hybrids with lower grain hardness. In conclusion, ensiling results in higher availability of starch to digestive enzymes, and the duration of ensiling and hardness of the maize hybrid should be considered when formulating the pig diet. Full article

Managing agricultural water pollution (AWP) and agricultural carbon emissions (ACE) together is crucial for addressing the global water resources crisis and climate challenges. Traditional water quality indicators are limited in large-scale evaluations of AWP. The common trends of ACE and AWP, as well as the spatial heterogeneity of their common driving factors also remain unclear. This study introduces a novel framework for analyzing the synergistic reduction of AWP and ACE from the perspective of agricultural grey water footprint (AGWF) and examines disparities in common driving factors across areas with differing levels of economic development and pollution intensities in Zhejiang Province. The results indicate that ACE and AGWF in Zhejiang showed an upward trend from 2010 to 2012, followed by a significant decline from 2013 to 2020. A consistent synergistic reduction trend in grey water footprint and carbon emissions was identified in both the planting and livestock husbandry sectors across Zhejiang. Socio-economic factors jointly influenced the reductions in ACE and AGWF, with technological level and the labor-to-research-and-development (labor-R&D) ratio being the primary drivers, accounting for 79.41% and 78.38% of these reductions, respectively. The impact of agricultural R&D expenditure intensity on AGWF and ACE exhibited spatiotemporal heterogeneity and sectoral disparities. The key to promoting the synergistic reduction of AGWF and ACE lies in advancing the research, development, and application of green agricultural technologies especially in regions where such technologies are not yet fully developed. The results provide a theoretical framework and practical implementation for the integrated management of AWP and ACE, as well as sustainable agricultural policy formulation. Full article

Colletotrichum graminicola can cause leaf spots and stalk rot in maize. The primary function of carbohydrate esterases (CEs) is to eliminate ester modifications from monosaccharides, oligosaccharides, and polysaccharides, thereby facilitating the hydrolysis of sugars. We identified 128 CE genes through whole-genome analysis and functional annotation of C. graminicola TZ–3 here. We further analyzed the physicochemical properties, subcellular localization, conserved motifs, gene structures, promoter regulatory elements of these 128 C. graminicola CE (CgCE) genes. Our results indicated that half of the CgCE proteins were located extracellularly. The CgCE proteins demonstrated diversity in both their structures and motifs. Furthermore, the CgCE gene family contained numerous conserved domains, suggesting potential functional diversity. Regulatory elements associated with various stresses and plant hormones were identified in this study. GO enrichment and expression pattern analysis indicated that the CgCE genes were involved in metabolic processes and might contribute to the establishment of fungal infections and lesion expansion. These results enhance our understanding of the CE family genes in C. graminicola and provide a foundation for further investigations into their roles in fungal pathogenesis. Full article

Soybeans are a crucial crop, and it is therefore necessary to make accurate predictions of their mechanical properties during harvesting to optimize the design of threshing cylinders, minimize the breakage rate during threshing, and enhance the quality of the final product. However, a precise model for the mechanical response of soybean seeds under stress conditions is currently lacking. To establish an accurate finite-element model (FEM) for soybeans that can predict their mechanical behavior under various loading conditions, an ellipsoidal modeling approach tailored for soybeans is proposed. Soybeans harvested in Xinjiang were collected and processed as experimental materials; the average moisture content was 11.77%, there was an average density of 1.229 g/cm³, and the average geometric specifications (height, thickness, and width) were 8.50 mm, 7.92 mm, and 7.10 mm, respectively. Compression tests were conducted on the soybeans in vertical, horizontal, and lateral orientations at the same loading speed to analyze the load and damage stages of these soybeans harvested in Xinjiang. The experimental results indicate that as the contact area decreases, the crushing load increases, with soybeans in the horizontal orientation being able to withstand the highest ultimate pressure. When placed vertically, the soybeans are not crushed; in horizontal and lateral orientations, however, they exhibit varying degrees of breakage. The Hertz formula was simplified based on the geometric characteristics of soybeans, and the elastic moduli in the X, Y, and Z directions of the soybean seeds were calculated as 42.8821 MPa, 40.4342 MPa, and 48.7659 MPa, respectively, using this simplified Hertz formula. A model of the soybeans was created in SolidWorks Ver.2019 and imported into ANSYS WORKBENCH for simulation verification. The simulation results were consistent with the experimental findings. The research findings enhance the understanding of the mechanical behavior of soybean seeds and provide robust scientific support for the optimization of soybean processing technologies and the improvement of storage and transportation efficiency. Full article

This study investigates the presence of mineral oil hydrocarbons (MOHs) in corn silage, aiming to assess contamination levels and identify potential sources, including technological and environmental factors. Given the increasing concern regarding the presence of MOHs all over the food chain, this research provides important data on feed safety. A total of 15 corn silage samples were collected from the feed base of a dairy farm. Sampling was performed systematically across silos (top, middle, bottom layers). The analysis was conducted using LC-GC-FID to quantify mineral oil saturated hydrocarbon (MOSH) and aromatic hydrocarbon (MOAH) fractions. Statistical evaluation was applied to determine contamination patterns and potential influencing factors. The findings confirmed the presence of MOSH and MOAH in the analyzed silage, averaging 23.3 mg/kg MOSH and 1.4 mg/kg MOAH, exceeding European Commission guideline limits. Notably, the MOAH fraction, known for its potential toxicity, was detected at significant levels in several samples. The study highlights that corn silage can act as a source of MOSH/MOAH contamination in livestock feed. Technological processes, especially mechanized harvesting and ensiling, and environmental pollution factors appear to be likely the main contributors, emphasizing the need for improved monitoring and preventive measures to mitigate risks in the feed-to-food chain. Full article

Timely and effective identification and diagnosis of strawberry diseases play essential roles in the prevention of strawberry diseases. Nevertheless, various types of strawberry diseases with high similarity pose a great challenge to the accuracy of strawberry diseases, and the recent module with high parameter counts is not suitable for real-time identification and monitoring. Therefore, in this paper, we propose a lightweight strawberry disease identification method, termed StrawberryNet, to achieve accurate and real-time identification of strawberry diseases. First, to decrease the number of parameters, instead of standard convolution, a partial convolution is selected to construct the backbone for extracting the features of strawberry disease, which can significantly improve efficiency. And then, a discriminative feature extractor, including channel information reconstruction network (CIR-Net) and spatial information reconstruction network (SIR-Net) modules, is designed for abstracting the identifiable features of different types of strawberry disease. A large number of experimental results were conducted on the constructed strawberry disease dataset, containing 2903 images and 10 common strawberry diseases and normal leaves and fruits. Extensive experiments show that the recognition accuracy of the proposed method can reach 99.01% with only 3.6 M parameters, which have good balance between the identification precision and speed compared to other excellent modules. Full article

Microplastic (MP) pollution has raised global concerns, and biodegradable plastics have been recommended to replace conventional ones. The “plastisphere” has been considered a hotspot for the interactions among organisms and environments, but the differences in the properties of soil microbial communities in the plastisphere of conventional and biodegradable MPs remain unclear. This in situ experiment was conducted to compare the diversity and structure of the bacterial community in the plastisphere of conventional MPs (polyethylene [PE]) and biodegradable MPs (polylactic acid [PLA]) in vegetable fields, orchards, paddy fields, and woodlands. It was discovered that the bacterial α-diversity within the plastisphere was significantly lower than that in the soil across all land use. Significant differences between plastic types were only found in the vegetable field. Regarding the community composition, the relative abundances of Actinobacteriota (43.2%) and Proteobacteria (70.9%) in the plastisphere were found to exceed those in the soil, while the relative abundances of Acidobacteriota (45.5%) and Chloroflexi (27.8%) in the soil were significantly higher. The complexity of the microbial network within the plastisphere was lower than that of the soil. Compared with the soil, the proportion of dispersal limitation in the PLA plastisphere significantly decreased, with the greatest reduction observed in the vegetable field treatment, where it dropped from 57.72% to 3.81%. These findings indicate that different land use types have a greater impact on bacterial community diversity and structure than plastics themselves, and that biodegradable MPs may pose a greater challenge to the ecological function and health of soil ecosystems than conventional MPs. Full article

Hemp (Cannabis sativa L.) is one of the oldest annual fiber crops cultivated throughout human history. Addressing the challenges encountered during the harvesting of hemp for seed and fiber purposes requires further investigation. Studies are also needed to determine plant characteristics in terms of both variety and gender. This study aimed to determine the physico-mechanical properties of hemp plants. The stems of male and female hemp plants were divided into three sections along their length: lower, middle, and upper regions. Samples measuring 25.4 mm in length were collected from each section, and measurements of thickness and inner and outer diameter were conducted. The same samples were subjected to axial and lateral compression tests to determine load, elongation, and energy values. According to the results, the thickness of hemp ranged from 2.347 mm to 2.628 mm, the inner diameter varied between 3.986 mm and 4.452 mm, while the outer diameter ranged from 8.861 mm to 9.708 mm. The results showed that male hemp plants have an increase in thickness and inner and outer diameter values from the lower to the upper region compared to female hemp plants. The compressive loads in the axial and lateral directions were found to be higher in male hemp plants compared to female hemp plants. Moreover, elongation and energy requirements during axial and lateral compressions showed trends consistent with the load values across the stem samples. This study determined that the results of axial and lateral compression applied at three different positions (lower, middle, and upper) on male and female hemp stalks varied significantly based on both sex and position. Full article

This study aims to develop a method for predicting walnut (Juglans regia L.) yield based on the walnut orchard point cloud model, addressing issues such as low efficiency, insufficient accuracy, and high costs in traditional methods. The walnut orchard point cloud is reconstructed using unmanned aerial vehicle (UAV) images, and the semantic segmentation technique is applied to extract the individual walnut tree point cloud model. Furthermore, the tree height, canopy projection area, and volume of each walnut tree are calculated. By combining these morphological features with statistical models and machine learning methods, a prediction model between tree morphology and yield is established, achieving prediction accuracy with a mean absolute error (MAE) of 2.04 kg, a mean absolute percentage error (MAPE) of 17.24%, a root mean square error (RMSE) of 2.81 kg, and a coefficient of determination (R²) of 0.83. This method provides an efficient, accurate, and economically feasible solution for walnut yield prediction, overcoming the limitations of existing technologies. Full article