Vegetable Fields Research Articles

Pollution index and distribution characteristics of soil heavy metals among four distinct land use patterns of Taojia River Basin in China

The accumulation of heavy metals (HMs) in soil has become a pressing global concern due to their persistent and non-degradable nature, resulting in the accumulation of toxic levels in the environment. In recent years, human activities have significantly altered land use patterns, leading to a marked increase in soil HM levels and subsequent land degradation. This research focused on four distinct land use patterns (vegetable fields (VGF), woodland (WDL), cultivated land (CVL), and wasteland (WSL)) commonly found in the Taojia River Basin, Hunan, China, which is facing severe HM pollution. Soil samples were collected from three different depths (0–10 cm, 10–20 cm, and 20–30 cm) to investigate HM distribution and intensity (cadmium (Cd), lead (Pb), copper (Cu), nickel (Ni), and zinc (Zn)), comprehensive soil pollution index, and their relationship with soil microbial and enzymatic activities. The results revealed that the Cd content exceeded the national standard for soil environmental quality, whereas concentrations of other HMs did not exceed the national standard across the four land use patterns. Most soil HMs were concentrated in the surface layer, with Cu, Pb, and Zn concentrations gradually decreasing with increasing soil depth. Conversely, Ni and Cd concentrations tended to increase with greater soil depth. There were significant positive correlations among HMs, indicating homogeneity among them. The pollution index across the HMs ranked as Cd > Ni > Zn > Cu and Pb, with land uses following the order of VGF (2.70) > CVL (2.12) > WSL (1.72) > WDL (1.63). Soil microbial and enzymatic activity was not the primary factor influencing HM concentration. The specific impacts of land use changes on soil HMs depend on management practices, local conditions, and the distribution characteristics of the HMs involved.

Variation of soil pore structure and predication of the related functions following land‐use conversion identified by multi‐scale X‐ray tomography

AbstractLand‐use conversion profoundly influences the soil pore structure, consequently modifying the soil functions. Investigating the variation of multiscale soil pore structure and their associated functions following land‐use change is critical for evaluating land management strategies. However, this topic has not yet been extensively explored in recent studies. In this study, the pore structure of soil following land‐use conversion was quantitatively investigated by multiscale X‐ray tomography. Intact soil aggregates and undisturbed soil cores were collected from paddy fields (PF) and from vegetable fields were converted from paddy fields for 5 years (VF‐5), 13 years (VF‐13), and 20 years (VF‐20), respectively. Results revealed that the connected porosity of both aggregates and soil cores was significantly increased after land‐use conversion. The isolated porosity of soil aggregates increased, while, conversely, it decreased for soil cores. The variance in pore structure was attributed to the development of new pores, including channels created by vegetable roots, fissures, earthworm holes, and packing pores resulting from the decomposition of soil organic matter and the rearrangement of soil particles. The altered pore structure influenced the soil exchangeability and reservation ability. For aggregates, the isolated porosity of PF and VF‐5 accounted for over 70% of the total imaged porosity. These aggregates displayed a larger water and carbon reservation ability, but limited exchangeability of air, water, and nutrients. The isolated porosity of VF‐13 and VF‐20 aggregates accounted for approximately 50% of the total imaged porosity, suggesting they could effectively balance the exchange and storage of air, water, and nutrients. As for soil cores, isolated pores became negligible (<0.2%) following land‐use conversion, leading to the emergence of a drainable pore system suitable for vegetable plantation. These findings offer insights into the development of pore structures and the prediction of soil function variations at multiple scales, both of which are crucial for optimizing soil management protocols.

Social Vulnerabilities Among Hired Migrant and Seasonal Farmworkers During COVID-19: The Need for Employment-Based Indicators

ABSTRACT Objectives This study aimed to explore farmworkers’ experiences of social vulnerability during the peak period of the COVID-19 pandemic. Methods Telephone surveys of 63 migrant and seasonal farmworkers across three major agricultural areas in Florida were conducted. The survey, designed and disseminated with critical support from a statewide farmworker membership and advocacy organization, included items related to social and occupational precarity and a suite of demographic conditions, including specific employment-based indicators and categories. Data were analyzed with SPSS using a series of statistical significance tests including Pearson’s Chi-Square, Fisher’s Exact, T-tests, and Mann-Whitney U. An open-ended question regarding employment precarity was also analyzed for frequencies of responses pertaining to a set of descriptive categories. Results Survey findings demonstrated a high degree of social vulnerability among the farmworker sample, with notable variation in the type and severity of vulnerability and risk exposure across employment-based indicators and occupational categories. For example, a cross-industry comparison between vegetable field workers and greenhouse nursery workers revealed a disparity in COVID-exposure risk through commuting characteristics, as 43% of vegetable field workers used shared, employer-provided transport, while 68% of nursery workers used personal vehicles. Conclusion While previous research has broadly established the extreme precarity of migrant and seasonal farmworkers during the peak COVID-19 period, the variability of experience, exposure to risk, and social vulnerability between farmworkers representing distinct employment-based indicators and occupational categories demonstrated in this study contributes to widening awareness of the importance of assessing farmworker experiences at a more granular level. In addition to delineating social vulnerability across key demographic categories, cross-industry comparisons between farmworkers revealed significant discrepancies in risk and vulnerability to COVID-19. Future research that further explores this variability may reveal opportunities to improve disaster-relief planning and mitigate social vulnerability in future disaster scenarios. The importance of surveying the vulnerability of worker populations, aside from geographic communities, is highlighted.

Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation

Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing’s central urban area. Results indicated that Cd was the primary pollutant, with 28.33 % of soil samples exceeding the screening value. Amaranth was particularly problematic, exceeding thresholds for Cd, Hg, and Cr, and both amaranth and celery showed significantly higher HM accumulation (p < 0.05). The HM pollution level in the soil-vegetable system was moderate or above. The sources of HMs identified via Positive matrix factorization (PMF) model included agricultural activities (18.19 %), natural soil parent material (25.88 %), mixed metal smelting and transportation (30.72 %), and coal combustion (25.21 %). Furthermore, evaluations using the Random Forest (RF) model revealed an intricate interaction of factors influencing the presence of HMs, where enterprise density, population density, and road density played significant roles in HMs accumulation. Monte Carlo assessments revealed higher non-carcinogenic risks for children (Pb, As) and greater carcinogenic risks for adults (Cd). Therefore, the issue of HM pollution in soils and vegetables from fragmented fields in industrial urban areas need attention, given the potential for elevated health risks with long-term vegetable consumption.

Assessing the Fates of Water and Nitrogen on an Open-Field Intensive Vegetable System under an Expert-N System with EU-Rotate_N Model in North China Plain.

Nitrate leaching, greenhouse gas emissions, and water loss are caused by conventional water and fertilizer management in vegetable fields. The Expert-N system is a useful tool for recommending the optimal nitrogen (N) fertilizer for vegetable cultivation. To clarify the fates of water and N in vegetable fields, an open-field vegetable cultivation experiment was conducted in Dongbeiwang, Beijing. This experiment tested two irrigation treatments (W1: conventional and W2: optimal) and three fertilizer treatments (N1: conventional, N2: optimal N rate by Expert-N system, and N3: 80% optimal N rate) on cauliflower (Brassica oleracea L.), amaranth (Amaranthus tricolor L.), and spinach (Spinacia oleracea L.). The EU-Rotate_N model was used to simulate the fates of water and N in the soil. The results indicated that the yields of amaranth and spinach showed no significant differences among all the treatments in 2000 and 2001. However, cauliflower yield under the W1N2 and W1N3 treatments obviously reduced in 2001. Compared with the W1 treatment, W2 reduced irrigation amount by 27.9-29.8%, water drainage by over 76%, increased water use efficiency by 5-17%, and irrigation water use efficiency by 29-45%. Nitrate leaching was one of the main pathways in this study, accounting for 8.4% of the total N input; compared to N1, the input of fertilizer N under the N2 and N3 treatments decreased by over 66.5%, consequently reducing gaseous N by 48-72% and increasing nitrogen use efficiency (NUE) by 17-37%. Additionally, compared with the W1 treatments, gaseous N loss under the W2 treatments was reduced by 18-26% and annual average NUEs increased by 22-29%. The highest annual average NUEs were under W2N3 (169.6 kg kg-1) in 2000 and W2N2 (188.0 kg kg-1) in 2001, respectively. We found that optimizing fertilizer management allowed subsequent crops to utilize residual N in the soil. Therefore, we suggest that the W2N3 management should be recommended to farmers to reduce water and N loss in vegetable production systems.

Assessing the Impact of Clearing and Grazing on Fuel Management in a Mediterranean Oak Forest through Unmanned Aerial Vehicle Multispectral Data

Climate change has intensified the need for robust fire prevention strategies. Sustainable forest fuel management is crucial in mitigating the occurrence and rapid spread of forest fires. This study assessed the impact of vegetation clearing and/or grazing over a three-year period in the herbaceous and shrub parts of a Mediterranean oak forest. Using high-resolution multispectral data from an unmanned aerial vehicle (UAV), four flight surveys were conducted from 2019 (pre- and post-clearing) to 2021. These data were used to evaluate different scenarios: combined vegetation clearing and grazing, the individual application of each method, and a control scenario that was neither cleared nor purposely grazed. The UAV data allowed for the detailed monitoring of vegetation dynamics, enabling the classification into arboreal, shrubs, herbaceous, and soil categories. Grazing pressure was estimated through GPS collars on the sheep flock. Additionally, a good correlation (r = 0.91) was observed between UAV-derived vegetation volume estimates and field measurements. These practices proved to be efficient in fuel management, with cleared and grazed areas showing a lower vegetation regrowth, followed by areas only subjected to vegetation clearing. On the other hand, areas not subjected to any of these treatments presented rapid vegetation growth.

Seasonal Fluctuations in Plant-Parasitic Nematode Vertical Distributions and Their Interactions with Edaphic Factors in Vegetable Fields of South Georgia, U.S.A.

Plant-parasitic nematodes (PPNs) can be found deep in the soil profile, compounding nematode management decisions and detection. This study aimed to understand how seasonal fluctuations in edaphic factors are associated with the vertical distribution of PPNs in south Georgia's vegetable cropping systems. Five-core composite soil samples were taken monthly (March 2020 to February 2022) at three random locations in six vegetable fields. Fields represented three cropping systems (vegetable plasticulture, bare ground cucumber, and plastic bed watermelon rotation) and two regions (north and south) sampled from five 15-cm strata (0 to 15, 15 to 30, 30 to 45, 45 to 60, and 60 to 75 cm). Only soil temperatures and precipitation had seasonal fluctuations; the other edaphic factors were vertically stratified. Latitude and stratum had the strongest associations with nematode composition, showing a clear separation between the north and south regions. Variations in soil texture, porosity, moisture, and PPN vertical distribution suggested that the illuvial zone in the north region was the main factor in the differences observed between regions and strata. Seasonal fluctuations in vertical distribution were found among Meloidogyne incognita and Nanidorus spp. Higher abundances of deep-dwelling PPNs were limited to the south region in the winter for deep-dwelling M. incognita and summer and winter for Nanidorus spp., probably due to the illuvial zone barrier in the north region. Because most root-knot nematodes dwell at ≤30 cm during the summer, fumigant/nematicide applications are recommended during this season to minimize the risk of deep-dwelling escapees.

The role of market in motivating farmers to reduce pesticide use: Evidence from vegetable farms in Shiraz

The overuse of pesticides has harmful impacts on both the environment and human health. Implementing efficient techniques is crucial to manage pesticides and reduce negative impacts effectively. In order to achieve this objective, we evaluated the harm of pesticide application in vegetable fields in Shiraz and identified the factors that impact farmers' behavior in using pesticides. The Environmental Impact Quotient (EIQ) indicator was initially utilized to evaluate the effects of pesticide residues on both human health and the environment. Afterwards, the Logit model was employed to investigate the likelihood of excessive pesticide usage among farmers. Our findings suggest that farmers may not give high importance to environmental and human health considerations when deciding on pesticide usage. Market incentives, such as the quantity and price of vegetables produced without pesticide use, play a significant role in reducing pesticide use in Shiraz vegetable farms. The results of the study can help policy makers in implementing pesticide-free agricultural practices.

Is Ambrosia trifida L. Preparing for a Wider Invasion? Changes in the Plant Morpho-Functional Traits over a Decade

Plastic traits are argued to favor the establishment of invasive alien plants and to evolve during the invasion process, so that invasions may be favored by both plasticity and evolutionary changes in plasticity. Despite this aspect being pivotal to understanding invasion processes, no information is available about the effect of residence time on the evolution of phenotypic plasticity of aliens to produce locally adapted phenotypes. Therefore, we aimed to evaluate changes in the morpho-functional traits of the invasive alien Ambrosia trifida L. over time. Specifically, we grew A. trifida plants under laboratory (at different temperatures: 10 °C, 20 °C and 25 °C) and field conditions by using seeds collected from 2011 to 2020 from an Eastern European population. Data about seedling emergence, vegetative (laboratory and field) and reproductive (field) traits were collected, e.g., maximum plant height (cm), total dry biomass (g), number of flowers (n) and number of new seeds (n). Analysis of variance (ANOVA), linear regressions and a plasticity index were applied to assess differences in plant performances when grown from seeds of different ages. An auto-regressive integrated moving average (ARIMA) model was applied to predict future trends of some key plant traits (maximum height, total dry biomass and number of new seeds). Overall, the time of seedling emergence was not statistically different among seeds of different age, and regression analyses exhibited a positive relationship between residence time (seed age) and vegetative and reproductive parameters of A. trifida. Only male flower production exhibited a negative trend over time. At all temperatures (especially at 25 °C), the vegetative parameters increased with the decrease in residence time. The plasticity index of the measured traits tended to decrease over time for most traits both in the field and in the laboratory trials. The ARIMA model predicted that plant traits will continue to increase in size over time by 2030, suggesting further plastic adaptation of A. trifida. The results highlighted that residence time influences the evolution of phenotypic plasticity of A. trifida, which has strengthened its adaptability to the new conditions over a decade, also demonstrating a great adaptive and invasion potential for the future.

Quantifying vegetation cover on coastal active dunes using nationwide aerial image analysis

AbstractCoastal active dunes provide vital biodiversity, habitat, and ecosystem services, yet they are one of the most endangered and understudied ecosystems worldwide. Therefore, monitoring the status of these systems is essential, but field vegetation surveys are time‐consuming and expensive. Remotely sensed aerial imagery offers spatially continuous, low‐cost, high‐resolution coverage, allowing for vegetation mapping across larger areas than traditional field surveys. Taking Aotearoa New Zealand as a case study, we used a nationally representative sample of coastal active dunes to classify vegetation from red‐green‐blue (RGB) high‐resolution (0.075–0.75 m) aerial imagery with object‐based image analysis. The mean overall accuracy was 0.76 across 21 beaches for aggregated classes, and key cover classes, such as sand, sandbinders, and woody vegetation, were discerned. However, differentiation among woody vegetation species on semi‐stable and stable dunes posed a challenge. We developed a national cover typology from the classification, comprising seven vegetation types. Classification tree models showed that where human activity was higher, it was more important than geomorphic factors in influencing the relative percent cover of the different active dune cover classes. Our methods provide a quantitative approach to characterizing the cover classes on active dunes at a national scale, which are relevant for conservation management, including habitat mapping, determining species occupancy, indigenous dominance, and the representativeness of remaining active dunes.

Intraspecific variation in tomato: Impact on production quality and cadmium phytoremediation efficiency in intercropping systems with hyperaccumulating plant

Intercropping with hyperaccumulators can facilitate the safe utilization of cadmium-contaminated soil. However, the effectiveness of this approach is influenced by plant species and varieties, which necessitates research on optimal plant consortia. In this study, 8 tomato varieties (3 cherry tomatoes and 5 common large-fruit tomatoes) were intercropped with Sedum alfredii in a moderately Cd-contaminated vegetable field. The results showed that the Cd concentration in the fruits of common large-fruit tomato varieties under monoculture was 1.03–1.50 mg/kg, while that in the fruits of cherry tomato varieties was 0.67–0.71 mg/kg. After intercropping with S. alfredii, the fruit Cd concentrations of Hangza 501, Hangza 503, and Hangza 108 decreased by 16.42 %, 19.72 %, and 6.76 %, respectively, while those of the other varieties significantly increased, except for those of Hangza 8. In contrast, the shoot Cd concentration of cherry tomatoes was greater than that of large-fruit tomatoes under monoculture. Furthermore, a significant increase in the shoot Cd concentration was noted in the Hangza 501, Hangza 503 and Hangza 603 plants following intercropping. Additionally, intercropping with S. alfredii increased the concentration of soluble sugars in the fruits of Hangza 8, Hangza 501, Hangza 503 and Hangza 603 by 4.66 %, 17.91 %, 10.60 % and 17.88 %, respectively. Intercropping with tomatoes resulted in a decrease in both the biomass and Cd uptake of S. alfredii. Interestingly, the inhibitory effect on S. alfredii was less pronounced when intercropped with cherry tomatoes than when intercropped with large-fruit tomatoes. Among the intercropping treatments, S. alfredii exhibited the greatest total Cd accumulation (0.06 mg/plant) when intercropped with Hangza 503. In conclusion, the cherry tomato variety Hangza 503 was the most suitable for intercropping with S. alfredii and can be used safely for vegetable production and simultaneous phytoremediation of polluted soil. Our findings suggest that strategic selection of tomato varieties can optimize the effectiveness of “phytoextraction coupled with agro-safe production” technology for managing soil Cd concentrations.

Post-Fire Vegetation (Non-)Recovery across the Edges of a Wildfire: An Unexplored Theme

Wildfires have a significant influence on ecosystems globally, shaping vegetation, biodiversity, landscapes, soil properties, and other ecosystem processes. Despite extensive research on different aspects of wildfires, the edges of burned areas remain understudied, even though they involve complex dynamics. In this study, we analyzed the post-fire vegetation recovery across the edges of a large wildfire in a Mediterranean area. The investigations were focused on patches of woodlands that, in a previous study, showed a normalized burn ratio (NBR) decline one year after the fire. Field vegetation surveys were carried out in areas characterized by different NBR recovery rates and in areas outside the burned area as controls. Five hypotheses were tested, identifying delayed tree mortality as a key factor linked to NBR decline, particularly in low-severity fire zones in proximity to the fire edges. Delayed mortality, observed predominantly near the edges, may also affect unburned or less severely burned patches within the main fire perimeter, highlighting the need for ongoing monitoring. As these areas play a crucial role in the post-fire succession and vegetation dynamics, understanding the second-order effects of a fire is imperative for effective ecosystem management. This study underscores the importance of the long-term assessment of fire impacts, emphasizing the necessity of field surveys alongside remote sensing. Continued observation is essential to elucidate the enduring impacts of wildfires and to facilitate informed restoration strategies.

Spring Abundance, Migration Patterns and Damaging Period of Aleyrodes proletella in the Czech Republic

The cabbage whitefly has become an important pest on brassica vegetables in Central Europe. It does not destroy the affected plants, but the product becomes unmarketable, causing considerable economic losses. The pest is also difficult to control due to its way of life and because it develops resistance to some of the active components of insecticides. In organic farming systems, insecticides are strictly restricted, but neither predators nor whitefly parasitoids are able to keep the pest at a tolerable level. It is, therefore, necessary to become familiar with the whitefly’s life cycle and habits, including mass migration from winter hosts to vegetables. We inspected 44 rapeseed fields across the republic in the period 2014–2021 in order to find the connection between the presence of oilseed rape fields near vegetable growing areas (VGAs) and the abundance of the overwintering cabbage whiteflies. We also conducted regular weekly monitoring of whitefly occurrence in the main cultivation area of the Czech Republic (Polabí) with the aim of specifying critical data important for the successful control of this pest. We found that the cabbage whitefly incidences were many times higher in rapeseed fields close to VGAs compared to areas where the crops are not adjacent. The average number of whiteflies was 0.59 individuals per plant in VGA-1 (oilseed rape grown inside this area or up to 1 km far), 0.052 in VGA-2 (distance 3–10 km from vegetable fields) and 0.014 in VGA-3 (more than 20 km). In the extremely warm year 2016, the difference was up to sixty times. The first CW eggs laid on cruciferous vegetables were usually found around 20 May. The period of mass migration of CW adults to cruciferous vegetables was between 6 June and 2 August. At this time, vegetables are most vulnerable to damage. Successful control of the cabbage whitefly requires the use of fabric netting, combined with an insecticide as needed and trap plants as needed; the latter have to be destroyed before adult whiteflies hatch—typically in early July.

DEVELOPMENTAL CONTROL OF SOME PHYSIOLOGICAL FACTORS ON REPRODUCTIVE BIOLOGY AND RUDIMENTARY EMBRYOS PHENOMENON IN CARROT SEEDS

This study was aimed to investigate delayed germination and immature embryos of carrot seeds; This research was implemented at vegetable field of College of Agricultural Engineering Sciences - University of Baghdad during two sequent seasons (fall and spring). The experiment was conducted using factorial within Randomized Complete Block Design arrangement with three factors and replicates (3X3X2). The aqueous barley sprouts extract (B0, B1) (0, 100 g.L-1) represented the first factor. Trehalose (T0, T1, T2) (0, 50, 75 mmole.L-1) represented the second factor. Calcium (C0, C1, C2) (0, 1, 2 ml.L-1) represented the third factor. Results showed the effectiveness of third order interaction treatment B1T2C1 in increasing germination speed and percent for the seeds of royal umbel (92, 97%); secondary umbel (90.67, 94.67%); and tertiary umbel (75.68, 86.33%). The mentioned treatment increased embryo length for the seeds of primary (royal) umbel (1628.3 µm), secondary umbel (1620.3 µm); and tertiary umbel (874.7 µm ). in compare with the lowest percents that found in B0T0C2 treatment.

Chemical Speciation, Contamination, Human Health Risk Assessment, and Source Identification of Heavy Metals in Soils Composted with Swine Manure

ABSTRACT Heavy metal accumulation in the swine manure composting vegetable soil continues to attract attention for the reason that heavy metals are often added to animal feeds as growth promoters. The seven heavy metals (Cr, Ni, Cu, Zn, As, Cd, and Pb) concentration and chemical speciation in soil samples from 15 swine manure composting vegetable fields of Jiangxi Province were analyzed. The results showed that the average concentration of Cr, Ni Cu, Zn, As, Cd, and Pb was 48.46 ± 5.58 mg/kg, 29.06 ± 1.80 mg/kg, 48.16 ± 9.69 mg/kg, 142.32 ± 38.71 mg/kg, 10.62 ± 2.76 mg/kg, 0.13 ± 0.04 mg/kg, and 15.75 ± 2.36 mg/kg, respectively. The average concentration of Ni, Cu, Zn, and Cd was 1.12, 1.89, 1.77, and 1.17 times greater than their background values, whereas the average concentration of Cr, As, and Pb was lower than their background values. The chemical speciation analysis indicated that these heavy metals were dominated by residual fractions and have low mobility and bioavailability. The Geo-accumulation index (I geo) indicated that the soils were unpolluted with Cr, Ni, As, Cd, and Pb, while unpolluted to moderately polluted with Cu and Zn. The Nemerow comprehensive pollution index suggested that the soils were lightly polluted with heavy metals. They posed a considerable potential ecological risk to the soils. Based on the risk assessment code (RAC), these heavy metals exhibited no to medium risks. There was little non-carcinogenic risk and acceptable carcinogenic risk to humans from the heavy metals. Principal component analysis (PCA) indicated that Ni, Cu, Zn, and Cd originated from the use of a large quantity of swine manure; Pb and As mainly derived from atmospheric deposition; Cr was mainly from natural sources.

Microstructure characterization and corrosion resistance in soil of Mg-2Zn-xCe-yCu alloy for light agricultural machinery

The microstructure, mechanical properties, corrosion behavior, and potential for lightweight applications of Mg-2Zn alloys enhanced with Cu and Ce were investigated. It was observed that the Ce and Cu-containing phases displayed various morphologies in the as-cast and extruded conditions. The extruded alloy, containing 0.8 wt% Ce and 0.5 wt% Cu, exhibited optimal mechanical properties, with the yield strength of 289 MPa, ultimate tensile strength of 336 MPa, and elongation of 15.8 %. Grain boundary and precipitation strengthening significantly contributed to the increase in yield strength. After four months of soil burial, the specimen surface showed localized pits and cracks, likely serving as anodes in the areas including Ce and Cu-containing phases. The corrosion rates in different soil environments paddy, vegetable, orchard, and corn fields were 2.029, 2.293, 2.133, and 1.986 mg·cm−2·d−1, respectively indicating variations due to complex soil conditions. The corrosion products included Mg(OH)2 and Mg5(CO3)4(OH)2·4 H2O, among others, throughout the burial period. Furthermore, model assembly in SolidWorks and static structural simulation with ANSYS confirmed the alloy's reliable load-bearing capacity, safety, and potential as the material for lightweight agricultural machinery.

Improved YOLOv8-Seg Based on Multiscale Feature Fusion and Deformable Convolution for Weed Precision Segmentation

Laser-targeted weeding methods further enhance the sustainable development of green agriculture, with one key technology being the improvement of weed localization accuracy. Here, we propose an improved YOLOv8 instance segmentation based on bidirectional feature fusion and deformable convolution (BFFDC-YOLOv8-seg) to address the challenges of insufficient weed localization accuracy in complex environments with resource-limited laser weeding devices. Initially, by training on extensive datasets of plant images, the most appropriate model scale and training weights are determined, facilitating the development of a lightweight network. Subsequently, the introduction of the Bidirectional Feature Pyramid Network (BiFPN) during feature fusion effectively prevents the omission of weeds. Lastly, the use of Dynamic Snake Convolution (DSConv) to replace some convolutional kernels enhances flexibility, benefiting the segmentation of weeds with elongated stems and irregular edges. Experimental results indicate that the BFFDC-YOLOv8-seg model achieves a 4.9% increase in precision, an 8.1% increase in recall rate, and a 2.8% increase in mAP50 value to 98.8% on a vegetable weed dataset compared to the original model. It also shows improved mAP50 over other typical segmentation models such as Mask R-CNN, YOLOv5-seg, and YOLOv7-seg by 10.8%, 13.4%, and 1.8%, respectively. Furthermore, the model achieves a detection speed of 24.8 FPS on the Jetson Orin nano standalone device, with a model size of 6.8 MB that balances between size and accuracy. The model meets the requirements for real-time precise weed segmentation, and is suitable for complex vegetable field environments and resource-limited laser weeding devices.

Intelligent field monitoring system for cruciferous vegetable pests using yellow sticky trap images and an improved Cascade R-CNN

Cruciferous vegetables are important edible vegetable crops. However, they are susceptible to various pests during their growth process, which requires real-time and accurate monitoring of these pests for pest forecasting and scientific control. Hanging yellow sticky boards are a common way to monitor and trap those pests which are attracted to the yellow color. To achieve real-time, low-cost, intelligent monitoring of these vegetable pests on the boards, we established an intelligent monitoring system consisting of a smart camera, a web platform and a pest detection algorithm deployed on a server. After the operator sets the monitoring preset points and shooting time of the camera on the system platform, the camera in the field can automatically collect images of multiple yellow sticky boards at fixed places and times every day. The pests trapped on the yellow sticky boards in vegetable fields, Plutella xylostella, Phyllotreta striolata and flies, are very small and susceptible to deterioration and breakage, which increases the difficulty of model detection. To solve the problem of poor recognition due to the small size and breaking of the pest bodies, we propose an intelligent pest detection algorithm based on an improved Cascade R-CNN model for three important cruciferous crop pests. The algorithm uses an overlapping sliding window method, an improved Res2Net network as the backbone network, and a recursive feature pyramid network as the neck network. The results of field tests show that the algorithm achieves good detection results for the three target pests on the yellow sticky board images, with precision levels of 96.5, 92.2 and 75.0%, and recall levels of 96.6, 93.1 and 74.7%, respectively, and an F1 value of 0.880. Compared with other algorithms, our algorithm has a significant advantage in its ability to detect small target pests. To accurately obtain the data for the newly added pests each day, a two-stage pest matching algorithm was proposed. The algorithm performed well and achieved results that were highly consistent with manual counting, with a mean error of only 2.2%. This intelligent monitoring system realizes precision, good visualization, and intelligent vegetable pest monitoring, which is of great significance as it provides an effective pest prevention and control option for farmers.

Land-use intensification exerts a greater influence on soil microbial communities than seasonal variations in the Taihu Lake region, China

The Taihu Lake region has undergone intensive land-use conversions from natural wetlands (NW) to conventional rice-wheat rotation fields (RW) and further to greenhouse vegetable fields (GH). Nevertheless, the effects of these conversions on soil microbes, particularly in wetland ecosystem, are not well explicit. To explore the impact of land-use intensification on soil microbial communities, monthly soil samples were obtained from replicate plots representing three land-use types (NW, RW, and GH) in subtropical wetlands and then subjected to amplicon sequencing. Land-use intensification had direct effects on bacterial and fungal community composition, with a more pronounced impact on bacteria than on fungi. These changes in bacterial communities were closely correlated with variations in soil environmental variables, such as NO3−-N, pH, and electrical conductivity. Land-use intensification led to a decrease in bacterial deterministic processes, with an opposing trend observed in the fungal community. In addition, arable lands (RW and GH), which are affected by anthropogenic activities, exhibited more complex networks. Potential metabolic functional groups in GH had higher absolute abundance. Seasonal variations significantly influenced microbial diversity, composition, and potential metabolic functional groups within each land-use type, particularly in summer, although the magnitude of this impact was much smaller than the impact of land-use intensification. Our findings emphasize the importance of comprehending the ecological consequences of land-use intensification in wetlands for sustainable resource management and biodiversity conservation.

First Report of Celery mosaic virus Infecting Celery (Apium graveolens) in Indonesia

Celery mosaic virus (CeMV), member of genus Potyvirus, is reported for the first time in Indonesia, from celery plants (Apium graveolens) in a vegetable field at Berastagi, North Sumatera Province. The plants possessed mosaic and vein clearing symptoms on the leaves as typical of CeMV infection. Virus incidence was confirmed by RT-PCR using degenerate potyvirus primer which amplified partial coat protein and 3’-UTR of the viral genome. Phylogenetic tree analysis placed Indonesian CeMV isolates in one separated clade within CeMV group and shared 96.5%–96.7% nucleotide identity with exemplar isolate of CeMV.