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A study was conducted with coffee growers from the municipalities of Caldono (Cauca) and Pitalito (Huila) in Colombia. Workshops, participant observation and farm visits were used to identify elements to understand (a) practices to the care of the environment, (b) the perception of the use of plastic materials, and (c) perspective toward biodegradable packages in their practices. Among the main results are an awareness for the care of the water resource and the care of the trees as its main contributions to the protection of its environment. In both communities, the problem is perceived due to the management of plastic waste and its influence on environmental deterioration due to poor management. They also recognize that the development of biodegradable bags can contribute to caring for their environment and make their economic activity more sustainable. [ABSTRACT FROM AUTHOR]

High-repetitive features in unstructured environments and frequent signal loss of the Global Navigation Satellite System (GNSS) severely limits the development of autonomous robot localization in orchard settings. To address this issue, we propose a LiDAR-based odometry pipeline GLIO, inspired by KISS-ICP and DLIO. GLIO is based on a nonlinear observer with strong global convergence, effectively fusing sensor data from GNSS, IMU, and LiDAR. This approach allows for many potentially interfering and inaccessible relative and absolute measurements, ensuring accurate and robust 6-degree-of-freedom motion estimation in orchard environments. In this framework, GNSS measurements are treated as absolute observation constraints. These measurements are tightly coupled in the prior optimization and scan-to-map stage. During the scan-to-map stage, a novel point-to-point ICP registration with no parameter adjustment is introduced to enhance the point cloud alignment accuracy and improve the robustness of the nonlinear observer. Furthermore, a GNSS health check mechanism, based on the robot's moving distance, is employed to filter reliable GNSS measurements to prevent odometry crashed by sensor failure. Extensive experiments using multiple public benchmarks and self-collected datasets demonstrate that our approach is comparable to state-of-the-art algorithms and exhibits superior localization capabilities in unstructured environments, achieving an absolute translation error of 0.068 m and an absolute rotation error of 0.856°. [ABSTRACT FROM AUTHOR]

Abstract Plastic pollution is an increasing global health concern, particularly the ever-increasing amount of tiny plastic particles commonly referred to as micro- and nanoplastics (MNPs). Most research to date on MNP exposure and hazards has focused on environmental species such as aquatic organisms and, more recently, humans, leaving impacts on farm animals largely unstudied. MNPs have been detected in all environmental compartments, including agricultural environments, farm animals and food products originating from them. The health of farm animals can be directly affected by MNPs, while humans can be affected by MNPs present in animal-derived food products. In this perspective article, we argue that MNP research should give more attention to farm animals forming a critical link between the environment and human health. Here, we summarize evidence on sources, exposure routes, levels in farm animals, and potential health effects of MNPs on farm animals, and identify knowledge gaps for future research, such as effects of MNPs on reproduction and development. In particular, the bovine embryo model is a promising model to study effects of MNPs on early development of both farm animals and humans. This perspective article signals the need for follow up studies that will increase our understanding of the transfer of MNPs between environment, farm animals, and humans, and the potential of farm animals to serve as an indicator for other animals, including humans.

Plastic pollution is an increasing global health concern, particularly the ever-increasing amount of tiny plastic particles commonly referred to as micro- and nanoplastics (MNPs). Most research to date on MNP exposure and hazards has focused on environmental species such as aquatic organisms and, more recently, humans, leaving impacts on farm animals largely unstudied. MNPs have been detected in all environmental compartments, including agricultural environments, farm animals and food products originating from them. The health of farm animals can be directly affected by MNPs, while humans can be affected by MNPs present in animal-derived food products. In this perspective article, we argue that MNP research should give more attention to farm animals forming a critical link between the environment and human health. Here, we summarize evidence on sources, exposure routes, levels in farm animals, and potential health effects of MNPs on farm animals, and identify knowledge gaps for future research, such as effects of MNPs on reproduction and development. In particular, the bovine embryo model is a promising model to study effects of MNPs on early development of both farm animals and humans. This perspective article signals the need for follow up studies that will increase our understanding of the transfer of MNPs between environment, farm animals, and humans, and the potential of farm animals to serve as an indicator for other animals, including humans. [ABSTRACT FROM AUTHOR]

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Fruit picking robot requires a powerful vision system that can accurately identify the fruit on the tree. Accurate segmentation of orange fruit in orchards is challenging because of the complex environments due to the overlapping of fruits and occlusions from foliage. In this work, we proposed an image segmentation model called ASE-UNet based on the U-Net architecture, which can achieve accurate segmentation of oranges in complex environments. Firstly, the backbone network structure is improved to reduce the down-sampling rate of orange fruit images, thereby retaining more spatial detail information. Secondly, we introduced the Shape Feature Extraction Module (SFEM), which at enhancing the ability of the model to distinguish between the fruits and backgrounds, such as branches and leaves, by extracting shape and outline information from the orange fruit target. Finally, an attention mechanism was utilized to suppress background channel feature interference in the skip connection and improve the fusion of high-layer and low-layer features. We evaluate the proposed model on the orange fruit images dataset collected in the agricultural environment. The results showed that ASE-UNet achieves IoU, Precision, Recall, and F1-scores of 90.03, 96.10, 93.45, and 94.75%, respectively, which outperform other semantic segmentation methods, such as U-Net, PSPNet, and DeepLabv3+. The proposed method effectively solves the problem of low accuracy fruit segmentation models in the agricultural environment and provides technical support for fruit picking robots. [ABSTRACT FROM AUTHOR]

In bird species, anthropogenic nesting materials have been known to have a negative effect on the survival of birds in general, but in some species, these can be used instead of natural materials, which can have a positive effect on the structural aspects of nests. Our study aims to investigate the type and amount of anthropogenic materials found in the nests of the colonial breeding azure-winged magpie (Cyanopica cyanus) in an agricultural area, as well as the characteristics of these used for each nest structure. We found that plastic litter was used in all of the azure-winged magpie breeding nests observed, and the types and amounts of plastic litter used differed between the cup and the outer. In all nests, soft, elastic, and insulating materials such as polyester fiber were mainly observed in the cup, and strings that weave and anchor branches and soil from nature were mostly found in the outer. The amount of plastic litter used in nests was related to the size of the nest. Plastic litter used in nests is thought to be collected from agricultural materials used in agricultural lands, vinyl greenhouses, and agricultural warehouses in our study site. Consequently, we expect that the phenomenon of azure-winged magpies using plastic litters for nest building may be common situation for the current agricultural environment where plastics are widespread. [ABSTRACT FROM AUTHOR]

The objectives of the present study were (a) to evaluate the importance of climate-related variables in the vaccination patterns applied in sheep and goat farms in Greece and (b) to assess potential interactions between these factors and previously established important health management- and human resources-related factors applied in the farms. Vaccination patterns against chlamydial abortion, clostridial infections, contagious agalactia, contagious ecthyma, foot-rot, paratuberculosis, pneumonia or staphylococcal mastitis were assessed. Climatic variables (2010–2019 and 2018–2019) were obtained for 444 locations with small ruminant farms throughout Greece. Patterns of vaccine administration in the farms were obtained through interviews with farmers. The following nine outcomes were considered: 'vaccination against chlamydial abortion', 'vaccination against clostridial infections', 'vaccination against contagious agalactia', 'vaccination against contagious ecthyma', 'vaccination against foot-rot', 'vaccination against paratuberculosis', 'vaccination against bacterial pneumonia', 'vaccination against staphylococcal mastitis' and 'total number of optional vaccines administered'. Univariable and multivariable analyses were first performed to establish associations of each of the above outcomes with climatic variables. Then, the same approach was employed to assess the importance of climatic variables against health management- and human resources-related factors in the administration of vaccines in the farms of the study. Climatic variables had a higher association with vaccinations against infections in sheep flocks (26 associations) than in goat herds (9 associations) (p = 0.002) and in farms with semi-extensive or extensive management (32 associations) than in farms with intensive or semi-intensive management (8 associations) (p < 0.0001). In 26 cases (38.8% of all analyses evaluated), the climatic variables overshadowed the management- and human resources-related variables assessed as significant predictors for vaccination. In most cases, these referred to sheep flocks (nine cases) and farms with semi-extensive or extensive management (eight cases). For all eight infections, there were changes in the climatic variables found to be significant predictors from the 10-year dataset to the 2-year dataset. The results indicated that, in some cases, climate factors overshadowed factors traditionally considered for the formulation of vaccination programs. This points out the significance of taking into account climate conditions in the health management of small ruminant farms. Future studies can be focused on formulating vaccination programs in accordance with climate factors and also on setting the optimum season(s) for vaccination of animals based on the circulation of the pathogens, the risks for the development of diseases and the stage within the annual production cycle of the animals. [ABSTRACT FROM AUTHOR]

Vision-based localization and mapping for agricultural environment is challenging due to unstructured scene with less distinguishable landmarks and more repetitive textures, scale drift caused by wide and distant view, illumination variations and abrupt movements. To address these challenges, we propose a scale-aware stereo direct odometry with online photometric calibration for agricultural environment. We first propose a scale-aware stereo direct image alignment method to explicitly capture the scale at tracking stage. Then we optimize the scale and affine brightness parameters of stereo frames to keep the scale consistency in the sliding window. Furthermore, we incorporate online photometric calibration to resist illumination changes and exposure differences of image sequence. The proposed system achieves new state-of-the-art results on two public agricultural datasets, demonstrating its effectiveness in challenging agricultural environments. [ABSTRACT FROM AUTHOR]

Automated agricultural machinery has advanced significantly in the previous ten years; however, the ability of such robots to operate safely will be critical to their commercialization. This study provides a holistic evaluation of the work carried out so far in the field of automated agricultural machines' safety, as well as a framework for future research considerations. Previous automated agricultural machines' safety-related studies are analyzed and grouped into three categories: (1) environmental perception, (2) risk assessment as well as risk mitigation, and (3) human factors as well as ergonomics. The key findings are as follows: (1) The usage of single perception, multiple perception sensors, developing datasets of agricultural environments, different algorithms, and external solutions to improve sensor performance were all explored as options to improve automated agricultural machines' safety. (2) Current risk assessment methods cannot be efficient when dealing with new technology, such as automated agricultural machines, due to a lack of pre-existing knowledge. Full compliance with the guidelines provided by the current International Organization for Standardization (ISO 18497) cannot ensure automated agricultural machines' safety. A regulatory framework and being able to test the functionalities of automated agricultural machines within a reliable software environment are efficient ways to mitigate risks. (3) Knowing foreseeable human activity is critical to ensure safe human–robot interaction. [ABSTRACT FROM AUTHOR]

Compared with external environment interferences, the interaction between arthropod natural enemies and pests is the key inherent driver determining the strength of biocontrol services. However, the extent to which this effect can suppress pests is still inconclusive. We combined two complementary experiments to determine how variation in an assemblage of generalist arthropod predators modified the level of biocontrol services for suppression of a key aphid pest in cotton fields. Using generalized linear mixed effect models (GLMM) and path analysis, we clarified the causal relationship between predator/aphid ratios (PAR) and (1) the resulting biocontrol services index (BSI) and (2) the aphid population growth index (APGI) as seen in field predator exclusion trials. We also measured the effect of PAR on APGI in more commercial cotton fields. Our results, at landscape level, indicate that when PAR values increased one unit, BSI values improved 34.1 %, and reduced aphid population growth 28.3 % (the standardized effect coefficient in path analysis) during two weeks in field cage-exclusion trials. The effect of high predator/aphid ratios on reducing the aphid population growth rates was also significant in more commercial cotton fields, which were sampled over a longer time interval (4 weeks). Our study confirmed that there was a causal relationship between the natural enemy/pest ratio and the level of biological pest control services for predators and aphid population growth in crop fields. PAR values (predator/aphid ratios) can, therefore, be used to predict the level of biocontrol services in this context instead of relying on more labor-intensive cage exclusion studies. • The experiments reflect landscape level relationships. • Field-cage exclusion experiments demonstrate that high ratios of predator/aphid abundance enhanced biological pest control services. • The combined effects of a large assemblage of predators significantly suppressed aphid population growth. • The natural enemy/pest ratio can be a robust ecological indicator of the efficacy of biocontrol services. [ABSTRACT FROM AUTHOR]

The activity concentrations of the NORM were measured in thirty samples of plant cultures in agricultural soil irrigated with groundwater from different locations in the Makkah region in Saudi Arabia, using a high purity germanium detector HPGe system. The mean values of the activity concentrations for 226Ra, 232Th, and 40K were found in plants samples 10.41, 1.92, and 4154.92 in Bq. kg−1, for agricultural soil samples were 18.11, 16.12, and 1603.73 Bq. kg−1 respectively, and the irrigation water samples were found 1.57, 0.58, and 118.44 Bq. l−1 respectively. The mean values of Raeq, dose rate, annual effective dose, hazard indices Hex and Hin were 333.09 Bq. kg−1, 179.23 nGy h−1, 1.09 mSv.y−1, 0.89 and 0.92 respectively for plant samples. The gamma doses were higher than world limit values and the Hex and Hin were less unity. The mean values of annual effective doses for ingestion of radionuclides in the plants samples were 2.12 mSv.y−1 for children and 1.86 mSv.y−1 for adults, these results were higher than the world values. These results indicate that, the highest doses refer to the samples location in farm 1, while the lowest values were in farm 3 and farm 6, while the other farms were relatively high than recommended dose values. So, samples of soil, water and plant must be studied in the farm 1 for the highest results of the annual effective doses mSv.y−1 of ingestion of radionuclides in the plants samples for children and adults.

This paper describes the design and implementation of a wireless sensor based on NB-IoT (Narrow Band Internet of Things) for monitoring agricultural environmental information. The sensor is capable of real-time monitoring of four environmental parameters, including ambient temperature, relative humidity, illuminance, and CO2 concentration. In the hardware design, sensor elements are selected based on the measurement ranges and accuracies specified in agricultural environmental monitoring industry standards. The hardware circuit is designed using the BC35-G type NB-IoT module and STM32 MCU (Microcontroller Unit). In the software design, data from the environmental parameters are collected and processed by the STM32 MCU and sent to the OneNET cloud platform through the NB-IoT module. The OneNET cloud platform enables users to view the relevant environmental data collected by the sensors using mobile phones and other mobile terminals. To test the effectiveness of the developed sensors, they were tested in a glass greenhouse at Fuyang Ziqing Agricultural Technology Co., Ltd. in Anhui Province. The results demonstrate that the sensors can accurately collect the data of relevant environmental parameters and can provide stable wireless transmission of data remotely, making them suitable for practical engineering applications. In summary, this wireless remote monitoring sensor based on NB-IoT represents a significant advancement in the field of agricultural automation. The sensor's ability to accurately monitor and wirelessly transmit data in real -time provides farmers with valuable information to optimize crop growth and maximize yields. [ABSTRACT FROM AUTHOR]

Agricultural environment monitoring is to track the residues and accumulation dynamics of pollutants in agricultural products to ensure the safety of agricultural products and human health, and to provide scientific basis for agricultural environment management. The development of network technology has enabled people to share agricultural information resources. However, the openness and sharing of agricultural information resources often brings about data security issues. In addition, the representative method of current monitoring image data is compressed sensing, which lacks effective security technology guarantee in the process of signal acquisition and transmission. Therefore, it is even more necessary to use encryption methods for optimization. Based on the diversity, complexity, and security of the image data, an adaptive algorithm was proposed in this study to realize the reconstruction optimization of compressed sensing technology and the processing of the detected image data. An image fusion algorithm was introduced to realize the differential processing of different frequency subbands. Blockchain technology was introduced into the sensing matrix to realize encryption processing and ensure the security of agricultural environment monitoring image data. The security application analysis of the proposed compressed sensing encryption algorithm showed that the average reconstruction probability of the proposed improved encryption algorithm was 84%, which was less affected by the number of measurements, and the overall fitness changed more smoothly. Moreover, the algorithm had a large signal-tonoise ratio in the reconstruction of agricultural environment images with different scale characteristics, and its scores in the five objective evaluation dimensions of image quality were better than other algorithms. The satisfaction of algorithm process encryption and image data security had reached 80.12% and 89.23%, respectively. This research enhanced and reconstructed the existing agricultural environment monitoring images to help agricultural environment monitoring and make up for the lack of security of agricultural environment monitoring images, which has a very important research value. [ABSTRACT FROM AUTHOR]

Decision‐making for pesticide registration by the US Environmental Protection Agency (USEPA) relies upon crop‐specific scenarios in a tiered framework. These standard modeling scenarios are stated to represent "...sites expected to produce runoff greater than would be expected at 90% of the sites for a given crop/use." This study developed a novel approach to compare the pesticide runoff + erosion (SumRE) mass flux potential of a hydrophobic chemical using 36 of these ecological regulatory scenarios with national‐scale distributions of modeled SumRE from over 750 000 USA‐wide agricultural catchments to provide real‐world context for the simulated transport predictions used for regulatory decision‐making. For the standard scenarios and national scale modeling, "edge of field" SumRE mass flux was estimated using regulatory guidance for a hypothetical pyrethroid. The national‐scale simulations were developed using publicly available soil, hydrography, and crop occurrence /regional timings databases. Relevant soil and crop combinations identified by spatial overlay along with weather data were used in a regulatory model to generate daily SumRE estimates, which were assigned to the catchments. The resulting average annual total SumRE mass fluxes were ranked to produce distributions to compare with the standard regulatory scenario outputs. These comparisons showed that SumRE flux from 25 of the 36 USEPA ecological regulatory crop‐specific scenarios modeled ranked above the 99th percentile of pyrethroid runoff + erosion vulnerability from any catchment growing that crop; SumRE flux from six scenarios was more severe than any catchment. For 12 USEPA regulatory scenarios, the resulting eroded sediment corresponds to highly erodible land (HEL), which the US Department of Agriculture mandates should not be cropped without substantial additional erosion prevention controls for sustainability. Since the pesticide regulatory framework already incorporates many acknowledged assumptions to ensure it conservatively meets protection goals, these HEL observations suggest that the standard scenarios overestimate potential aquatic exposure and that the regulatory process is more protective than intended. Integr Environ Assess Manag 2023;19:175–190. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). KEY POINTS: The US Environmental Protection Agency (USEPA) has developed a set of standard crop scenarios used in modeling for the regulatory risk assessment framework; results from this study show that several of the standard scenarios generate runoff and erosion mass output higher than the USEPA stated 90th percentile protection goal.This study simulated up to 271 340 unique soil and weather combinations per crop with the Pesticide Root Zone Model (PRZM) model covering a range of nine key pyrethroid crops.This study developed a novel approach to compare the pesticide mass flux of a hydrophobic chemical using 36 USEPA standard PRZM crop scenarios with national‐scale distributions of modeled mass flux from over 750 000 USA‐wide agricultural NHD + watershed catchments to put into a real‐world context. [ABSTRACT FROM AUTHOR]

Farmland environmental pollution has put greater pressure on the sustainability of agricultural production systems. Exploring the relationship between farm size and environmental pollution in agriculture can help provide realistic guidance for stakeholders. In this study, the research data from apple farmers in China were used to measure the environmental pollutant emissions caused by apple production using the life-cycle assessment (LCA) approach. The mediating effect model was used to examine the mechanisms and pathways by which farm size affects the environmental effects of apple production and to identify the mediating effects of fertilizer, pesticide, and machinery input intensity. Finally, a heterogeneity analysis was conducted to illustrate the impact of participation in agricultural cooperatives on the environmental performance of apple production for smallholder farmers. The results showed that the apple production system's negative environmental impacts from the agricultural material production phase were more significant compared to the farming phase, with a contribution potential of 56.50%. Farm size directly impacts the environmental effects of apple production, and there is a U-shaped trend between the two, implying that from the perspective of environmental effects, larger farm size is not better. There were some mediating effects in the paths of farm size on the environmental effects, and the largest effect was fertilizer input intensity with a full mediating effect; the second largest effect was machinery input intensity with a partial mediating effect, and the mediating effect accounted for 15.50–15.89% of the total effect; the mediating effect of pesticide input intensity was not significant. In addition, the study also found that joining agricultural cooperatives was beneficial in promoting the improvement of the negative environmental impact caused by apple production. These findings provide insights into optimizing farm inputs for apple production and identifying the appropriate farm size to alleviate multiple environmental impacts, intending to make a marginal contribution to promoting sustainable development of the apple industry in China also providing the research evidence for the comparative study of the environmental burdens of apple production in China and other countries in the world. [ABSTRACT FROM AUTHOR]

In order to improve the environmental protection effect of agricultural body, this paper analyses the development of rural economy based on the concept of sustainable development. Moreover, in order to prevent the development and utilisation of agricultural resources from continuing to fall into the vicious circle of the past, this paper begins to explore new alternative agricultural models. In addition, this paper expounds the concepts of ecological compensation, agricultural versatility, ecological service function and value involved in this paper. From a long-term perspective, the necessary route for the development of modern agriculture is sustainable and emphasises the development of multiple functions of agriculture. Ultimately, this technique applies sustainable development with agricultural ecological protecting the environment research, uses the region as an example to analyses agricultural economic and environmentally sustainable development, analyses the problems of farm ecological environmental protection using real-life case studies, and recommends corresponding defensive measures to serve as a model for future research.

On the basis of the panel data of 31 provinces in China from 2011 to 2020, this paper first constructs an index system through the Pressure-State-Response (PSR) model and conducts a comprehensive evaluation of China's agricultural environment according to the entropy weight TOPSIS model. Second, a coupling coordination degree model is established to calculate the degree of coupling coordination between the agricultural economy and the environment in each province. Finally, a spatial Durbin model is established to analyze the influencing factors of China's agricultural economy. Results show that: ① the overall environment in the eastern region has little change, and the overall level is relatively backward; the agricultural environment in the central region is uneven; the agricultural environment in the western region is quite different from north to south. ② The regions with a high level of coupling coordination are mainly concentrated in the central and southern regions, and the performance is relatively intensive. The agricultural economy and the environment in the western region are extremely uncoordinated, and as is the overall coupling coordination between the agricultural economy and the environment in the eastern region in general. Further improvement is also needed. ③ Fixed asset investment, total power of agricultural machinery, rural electricity consumption, rural population, and rural per capita disposable income all have important influences on China's agricultural economy. ④ The rural population size has a positive and the largest effect on the agricultural economy, whereas rural per capita disposable income has a negative effect on the agricultural economy. Moreover, improving farmers' enthusiasm for farming is one of the key issues to be solved urgently. [ABSTRACT FROM AUTHOR]

This study aimed to uncover related strains of extended-spectrum beta-lactamase Escherichia coli O157:H7 between agricultural matrices (soil, manure and irrigation water) and nearby water sources using multilocus-based phylogenetic analysis. Resistant and nonresistant E. coli O157:H7 were isolated, identified and characterised using standard microbiological methods. The results showed that soil samples had a high prevalence of E. coli O157:H7 (31.73%) and ESBL-producing E. coli O157:H7 (22.11%). Multilocus sequencing typing (MLST) analysis revealed that all ESBL-producing E. coli O157:H7 were identified as ST11. Phylogenetic analysis of E. coli O157:H7 indicated that irrigation water might be a reservoir for E. coli O157:H7. For antibiotic-resistant genes (ARG), the most common was blaTEM in 85% (n = 34), followed by blaOXA in 70% (n = 28), blaNDM and sul1 30% (n = 12) and lastly mcr-1, which was only found in one soil isolate. The results showed that ESBL-producing E. coli O157:H7 isolates were intermixed in three clades, indicating close relatedness between isolated strains from different matrices.

The objectives of the present study were (a) to evaluate the importance of climate-related variables in the vaccination patterns applied in sheep and goat farms in Greece and (b) to assess potential interactions between these factors and previously established important health management- and human resources-related factors applied in the farms. Vaccination patterns against chlamydial abortion, clostridial infections, contagious agalactia, contagious ecthyma, foot-rot, paratuberculosis, pneumonia or staphylococcal mastitis were assessed. Climatic variables (2010–2019 and 2018–2019) were obtained for 444 locations with small ruminant farms throughout Greece. Patterns of vaccine administration in the farms were obtained through interviews with farmers. The following nine outcomes were considered: ‘vaccination against chlamydial abortion’, ‘vaccination against clostridial infections’, ‘vaccination against contagious agalactia’, ‘vaccination against contagious ecthyma’, ‘vaccination against foot-rot’, ‘vaccination against paratuberculosis’, ‘vaccination against bacterial pneumonia’, ‘vaccination against staphylococcal mastitis’ and ‘total number of optional vaccines administered’. Univariable and multivariable analyses were first performed to establish associations of each of the above outcomes with climatic variables. Then, the same approach was employed to assess the importance of climatic variables against health management- and human resources-related factors in the administration of vaccines in the farms of the study. Climatic variables had a higher association with vaccinations against infections in sheep flocks (26 associations) than in goat herds (9 associations) (p = 0.002) and in farms with semi-extensive or extensive management (32 associations) than in farms with intensive or semi-intensive management (8 associations) (p < 0.0001). In 26 cases (38.8% of all analyses evaluated), the climatic variables overshadowed the management- and human resources-related variables assessed as significant predictors for vaccination. In most cases, these referred to sheep flocks (nine cases) and farms with semi-extensive or extensive management (eight cases). For all eight infections, there were changes in the climatic variables found to be significant predictors from the 10-year dataset to the 2-year dataset. The results indicated that, in some cases, climate factors overshadowed factors traditionally considered for the formulation of vaccination programs. This points out the significance of taking into account climate conditions in the health management of small ruminant farms. Future studies can be focused on formulating vaccination programs in accordance with climate factors and also on setting the optimum season(s) for vaccination of animals based on the circulation of the pathogens, the risks for the development of diseases and the stage within the annual production cycle of the animals.

Automated agricultural machinery has advanced significantly in the previous ten years; however, the ability of such robots to operate safely will be critical to their commercialization. This study provides a holistic evaluation of the work carried out so far in the field of automated agricultural machines’ safety, as well as a framework for future research considerations. Previous automated agricultural machines’ safety-related studies are analyzed and grouped into three categories: (1) environmental perception, (2) risk assessment as well as risk mitigation, and (3) human factors as well as ergonomics. The key findings are as follows: (1) The usage of single perception, multiple perception sensors, developing datasets of agricultural environments, different algorithms, and external solutions to improve sensor performance were all explored as options to improve automated agricultural machines’ safety. (2) Current risk assessment methods cannot be efficient when dealing with new technology, such as automated agricultural machines, due to a lack of pre-existing knowledge. Full compliance with the guidelines provided by the current International Organization for Standardization (ISO 18497) cannot ensure automated agricultural machines’ safety. A regulatory framework and being able to test the functionalities of automated agricultural machines within a reliable software environment are efficient ways to mitigate risks. (3) Knowing foreseeable human activity is critical to ensure safe human–robot interaction.

This report outlines the draft genome sequences of six Klebsiella spp. strains from South Korea's agricultural produce and environments. Genome sizes ranged from 5.25 to 6.21 Mbp with 55.64% to 57.55% GC content. Each strain contained multiple plasmid sequences identified by PlasmidFinder, indicating significant antimicrobial resistance., Competing Interests: The authors declare a conflict of interest.

Free-living birds play an important role as bioindicators in natural environments. In this study, we used the micronucleus test and nuclear erythrocyte abnormalities to investigate the difference in the genotoxic damage frequency between animals in agricultural areas (soybean planting) in relation to the conserved area. It was also discussed the bird's eating habits, which are important for ecotoxicological analysis. The results point to a difference between the insectivorous, granivorous, and omnivorous guilds. The omnivore Gnorimopsar chopi was the species that most exhibited micronucleus frequency in the protected area. In the agricultural area, the animals did not differ in the genotoxic damage frequency. In the comparison between common species in both environments, G. chopi from the agricultural area showed a micronuclei frequency almost three times higher in relation to specimens collected in the conserved area. Based on these results, this study adds to the efforts of using the micronucleus test as a simple and accessible tool for biomonitoring the wild fauna. It can be concluded that the passerine, G. chopi, due to its higher genotoxic damage frequency may be a strong candidate to indicate environmental health. [ABSTRACT FROM AUTHOR]

In order to improve the environmental protection effect of agricultural body, this paper analyses the development of rural economy based on the concept of sustainable development. Moreover, in order to prevent the development and utilisation of agricultural resources from continuing to fall into the vicious circle of the past, this paper begins to explore new alternative agricultural models. In addition, this paper expounds the concepts of ecological compensation, agricultural versatility, ecological service function and value involved in this paper. From a long-term perspective, the necessary route for the development of modern agriculture is sustainable and emphasises the development of multiple functions of agriculture. Ultimately, this technique applies sustainable development with agricultural ecological protecting the environment research, uses the region as an example to analyses agricultural economic and environmentally sustainable development, analyses the problems of farm ecological environmental protection using real-life case studies, and recommends corresponding defensive measures to serve as a model for future research. [ABSTRACT FROM AUTHOR]

In agricultural environments, there are a lot of changes invoked by several factors such as season, time of day, weather. Therefore, conventional techniques for autonomous driving are not appropriate because they mainly focus on structured urban environments. In this paper, we propose LiDAR based localization method on agricultural roads, using simplified 2D map which contains boundaries of drivable areas and non-drivable areas. Different from detailed accurate 3D maps, the proposed map can be generated and modified easily. We combined the localization method with nonlinear control law for wheeled mobile robots, and applied to an autonomous small truck. Several experiments are performed using the experimental truck in agricultural environments and resulted successful autonomous drive.

Agricultural intensification negatively affects bird communities, and the response of birds to these changes varies from those that survive and increase their populations (disturb-tolerant species) to those that cannot adapt to new conditions and are regionally extinct (disturb-sensitive species). Thus, the present study sought to investigate the bird community in 39 guava orchards in the semiarid region of the state of Sergipe, northeast Brazil. Field observations were made between July and October 2017, through a one-hour visit to each orchard. Samplings were conducted using the MacKinnon's List method. In addition to bird sampling, walks were carried out in the orchards to observe nesting. Seventy-six species of birds belonging to 30 families were recorded using the guava orchards. The most frequent species were Vanellus chilensis, Columbina talpacoti, Columbina picui, Crotophaga ani, Pitangus sulphuratus and Sporophila albogularis. Of the 186 nests recorded in the orchards, the majority (n = 144 nests; 77.4%) belonged to Columbina picui, Columbina talpacoti and Columbina minuta. The results demonstrate that the bird community in the guava orchards is formed only by disturb- tolerant species, showing that the studied guava orchards are not favorable to the conservation of disturb-sensitive birds of the Caatinga domain. [ABSTRACT FROM AUTHOR]

Farmland environmental pollution has put greater pressure on the sustainability of agricultural production systems. Exploring the relationship between farm size and environmental pollution in agriculture can help provide realistic guidance for stakeholders. In this study, the research data from apple farmers in China were used to measure the environmental pollutant emissions caused by apple production using the life-cycle assessment (LCA) approach. The mediating effect model was used to examine the mechanisms and pathways by which farm size affects the environmental effects of apple production and to identify the mediating effects of fertilizer, pesticide, and machinery input intensity. Finally, a heterogeneity analysis was conducted to illustrate the impact of participation in agricultural cooperatives on the environmental performance of apple production for smallholder farmers. The results showed that the apple production system’s negative environmental impacts from the agricultural material production phase were more significant compared to the farming phase, with a contribution potential of 56.50%. Farm size directly impacts the environmental effects of apple production, and there is a U-shaped trend between the two, implying that from the perspective of environmental effects, larger farm size is not better. There were some mediating effects in the paths of farm size on the environmental effects, and the largest effect was fertilizer input intensity with a full mediating effect; the second largest effect was machinery input intensity with a partial mediating effect, and the mediating effect accounted for 15.50–15.89% of the total effect; the mediating effect of pesticide input intensity was not significant. In addition, the study also found that joining agricultural cooperatives was beneficial in promoting the improvement of the negative environmental impact caused by apple production. These findings provide insights into optimizing farm inputs for apple production and identifying the appropriate farm size to alleviate multiple environmental impacts, intending to make a marginal contribution to promoting sustainable development of the apple industry in China also providing the research evidence for the comparative study of the environmental burdens of apple production in China and other countries in the world.

The dataset presented comprises (raw data) scans of the marked paper contact prints from a dedicated photogrammetric flight and a diagram showing the location of each of these photograms. The flight was commissioned specifically for the soil survey presented herein. The scanned paper prints are those used in the field to characterize the soil salinity of 27,500 ha within the Flumen irrigation district, in the semi-arid Central Ebro Basin, in Spain. On these prints, the soil surveyors marked the locations of the sampling sites. IRYDA, the extinct Spanish Ministry of Agriculture agency, in charge of designing and implementing new irrigation districts, commissioned the flight in 1975. These paper prints enabled us to resample the soils years later, to: (i) determine the soil salinity evolution from 1975 to 1985 [1], and from 1975 to 1999 [2]; (ii) apply electromagnetic induction (EMI) [3] for the same purpose; (iii) use multivariate analysis to discriminate the salinity trends from 1975 to 1999 in the different soil units [4]; and (iv) for land evaluation [5]. The report and two volumes of annexes [6–8], prepared by the contractor INYPSA for IRYDA, contain data on the soluble salts and other soil components sampled in 1975 as well as soil descriptions and agronomical data. The aerial photographs presented herein allow the sites sampled in 1975 to be located. This is the first step in exploiting the legacy data to appraise [9] the effects on the salinity and other soil properties recorded in 1975. The irrigation and the change from basin and border flooding to pressurized techniques, with the merging of many plots, govern these effects.

On the basis of the panel data of 31 provinces in China from 2011 to 2020, this paper first constructs an index system through the Pressure-State-Response (PSR) model and conducts a comprehensive evaluation of China’s agricultural environment according to the entropy weight TOPSIS model. Second, a coupling coordination degree model is established to calculate the degree of coupling coordination between the agricultural economy and the environment in each province. Finally, a spatial Durbin model is established to analyze the influencing factors of China’s agricultural economy. Results show that: ① the overall environment in the eastern region has little change, and the overall level is relatively backward; the agricultural environment in the central region is uneven; the agricultural environment in the western region is quite different from north to south. ② The regions with a high level of coupling coordination are mainly concentrated in the central and southern regions, and the performance is relatively intensive. The agricultural economy and the environment in the western region are extremely uncoordinated, and as is the overall coupling coordination between the agricultural economy and the environment in the eastern region in general. Further improvement is also needed. ③ Fixed asset investment, total power of agricultural machinery, rural electricity consumption, rural population, and rural per capita disposable income all have important influences on China’s agricultural economy. ④ The rural population size has a positive and the largest effect on the agricultural economy, whereas rural per capita disposable income has a negative effect on the agricultural economy. Moreover, improving farmers’ enthusiasm for farming is one of the key issues to be solved urgently.

This research aims to identify sources of information related to practices for preserving the agricultural environment from pollution, to determine the degree and level of knowledge of the researched farmers about the sources of agricultural environment pollution, including (sources of soil pollution - sources of water pollution - sources of air pollution), determining the relationship between the degree of knowledge of the surveyed farmers about the sources of pollution of the agricultural environment and the independent variables studied and identifying the reasons that lead to farmers adopting some unsound practices in disposing of agricultural waste. This research was conducted in Sharkia Governorate on a random sample of (200 farmers), they were selected from four villages in four centers by simple random sampling are: the village of Al-Jalayla in the Ibrahimiya center, the village of AlJaafra in the center of Faqous, the village of Al-Attarin in the center of Derb Negm, and the village of Ahmed Gibran in the center of Zagazig, Using the Published Tables method. They were selected equally by 50 farmers from each of the selected villages. The research data were collected through a personal interview using a questionnaire form during the months of January and February 2021. The use of some statistical methods in analyzing the data are: frequencies, percentages, and arithmetic mean, and the coefficient of correlation "Pearson" was used to test the significance of the relationship between the studied variables. The most important results were:That 33.5% of the total surveyed farmers have a low level of knowledge of the sources of pollution of the agricultural environment. While 31.0% have an average level of knowledge, while only 35.5% of the total sample have a high level of knowledge. This indicates that approximately two-thirds of the sample, 64.5%, have a low and medium knowledge level. It was found that there is a negative significant correlation (0.05) between the degree of knowledge of farmers about the sources of agricultural environmental pollution and both age. It was also found that there is a positive significant correlation relationship at a significant level (0.01) between the degree of farmers ’knowledge of the sources of agricultural environmental pollution and between: Number of years of education, area of agricultural holding, degree of geographical openness, leadership behavior, degree of participation in rural organizations, degree of participation in activities Environment, Degree of exposure to environmental information sources, the attitude towards protecting the environment from pollution. It was also found that the most important reasons that lead to the researched farmers adopting some unsound practices in disposing of agricultural waste were: The lack of places to collect and store agricultural waste, which accounted for 82.5% of the total respondents, The absence of competent responsible authorities for the collection and utilization of waste by 72.5%, The desire to prepare and prepare the land for cultivation and not to delay in planting the next season by 70.5%, and the lack of alternative methods and means to get rid of agricultural waste by 67.0%, and it is the cheapest way to get rid of agricultural waste by 57.5%, Getting used to it as the fastest and easiest way to get rid of agricultural waste 48.5%, and the lack of agricultural machinery necessary for all agricultural waste for free by 46.5%, and the elimination of some agricultural pests and insects in the soil by 44.5%, Familiarity with the methods inherited from parents and grandparents to get rid of farm waste by 44.0%, And not needed and used in the field or home by 42.5%. [ABSTRACT FROM AUTHOR]

Antibiotics are widely used in animal husbandry, planting, and aquaculture in agricultural industries. A large amount of the parent antibiotics used are released into the environment through discharge via feces and urine, posing potential risks to human health and ecosystems. It is thus very important to understand how antibiotics in the agricultural environment threaten the ecological environment and human health. Accordingly, risk assessment of antibiotics in the environment has become the research focus in recent years. The aim of this study was to review the risk assessment methods of antibiotics. The results showed that the ecological environment risk has mainly been assessed by the risk quotient (RQ). Predicted no-impact concentrations (PNECs) are an important indicator for ecological environment risk assessment, but a definite value is still controversial. The hazard quotient (HQ) is generally used to assess health risks. At present, it is necessary to clarify the selection of antibiotic exposure pathways and toxicological thresholds. However, neither of these two methods have currently considered either mixed pollution or the risk of antibiotic metabolites. Further analysis indicated that the ecological risks of antibiotics in the water environment and feces/manure/soil environment were widespread, which had an impact on both the soil and water environment. The types of antibiotics with high risk were different for various cultivated types. The factors including test species, testing conditions, calculation methods, and soil types all affected the detection of PNECs. Human health risk caused by dietary intake of antibiotics was minimal, but it cannot be ignored given the seafood consumption in coastal areas. Moreover, quinolones have both high ecological and human health risks in the agricultural environment. Based on the amount of antibiotics in agriculture and the residual concentration or toxicity of antibiotics in the related environment, this study proposed a priority-control list of antibiotics in the agricultural environment and summarized the main problems in the current antibiotic risk assessment. It will provide helpful support for the scientific optimization of antibiotic risk assessment and the effective control of antibiotics in agricultural environments.

The wide use of mulch by the agricultural system in most parts of the world and with multiple applications, is necessary to improve our knowledge of the effects of mulching on soil physical properties. Thus, this review a critically explains the mechanism of this application. Generally, it affects a field's energy balance by changing the surface radiation budget, by modifying the albedo of the soil surface or shading the soil surface. This has an effect on net radiation. The effect of mulching on evaporation is that it breaks up capillary diffusion and this depends on the type of mulch. Mulching also affects soil water content and soil temperature, the extent to which depends on the type and thickness of the mulch, the soil texture type and climatic conditions. Several studies have reported that the influence of mulching on greenhouse gas emissions is unclear. [ABSTRACT FROM AUTHOR]

This study performed the first environmental and dietary exposure assessment to explore plant uptake of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) from agricultural soil and irrigation water in the Nakdong River delta, South Korea. Annual average concentrations of total PFOA and PFOS ranged from 0.026 to 0.112 µg L−1 (irrigation water), and from 0.818 to 1.364 µg kg−1 (soil), respectively. PFOA and PFOS hotspots were identified downstream of the Nakdong River and were influenced by seasonal climatic variations. The observed average biennial concentration of the sum of PFOA and PFOS decreased in irrigation water, from 0.112 µg L−1 in 2013 to 0.026 µg L−1 in 2015, suggests that the 2013 Persistent Organic Pollutants Control Act may have helped to reduce levels of PFAS at this location. This study calculated some of the highest plant uptake factors reported to date, with values ranging from 0.962 in green onions to < 0.004 in plums. Leafy vegetables and rice are important components of the Korean diet; these groups had the largest contribution to the estimated dietary intake of PFOA and PFOS, which was calculated at 0.449 and 0.140 ng kgbw−1 day−1, respectively. This corresponded to 66.4% for PFOA and 7.9% for PFOS of the EFSA reference dose (RfD). The dietary intake of PFOA and PFOS from crops alone did not exceed the RfD. However, when the estimated daily intake (EDI) from other sources such as tap water, meat, fish, dairy, and beverages was included in the exposure risk assessment, both of the EDIs to PFOA and PFOS exceeded the RfDs, indicating that there may be a risk to human health. This study concludes that consumption of crops might, therefore, be a significant and underappreciated pathway for human exposure to PFAS. [ABSTRACT FROM AUTHOR]

Mercury ion (Hg2+) is one of the most frequently occurring and most toxic heavy metal pollutants, which may seriously damage the growth environment of crops and further threaten the quality and safety of agricultural products and human health. Fluorescence analysis is a simple method of Hg2+ detection with high sensitivity. The analysis performance of fluorescence sensor may be seriously affected by fluorescence probes. Carbon dots (CDs) have the advantages of simple preparation, high fluorescence efficiency, and good biocompatibility. Therefore, fluorescence sensors based on CDs have attracted wide attention. This study introduced the synthesis status of CDs prepared from biomasses such as crops, agricultural products and their wastes, and pointed out that the synthesis of CDs was rich in natural biomass materials, and CDs synthesized by ultrasonic, microwave, and hydrothermal methods have the advantages of low cost, simple preparation process, and environmental protection. In addition, the application research of fluorescence sensor based on CDs for the detection of antibiotics, pesticides, and food additives in the field of agricultural sensing was briefly introduced. Furthermore, the research progress of fluorescence sensor based on CDs in Hg2+ detection was systematically introduced from the perspectives of fluorescence quenching single-signal analysis mode, fluorescence-enhanced single-signal analysis mode and ratio-based signal analysis mode. The fluorescent materials, analytical performance and advantages and disadvantages of each method used in different sensing modes were summarized and compared. Among the single-signal sensors, fluorescence quenching sensors could optimize the detection performance of CDs by doping, surface modification, or "on-off-on" strategies; the fluorescence intensity of fluorescence-enhanced sensors ranged from weak to strong, and fluorescence colors were created from scratch, which could reduce the occurrence of false positive signals, but few fluorescence-enhanced sensors constructed by CDs as probes may occur, which needs to be further developed; The CDs with different properties could be used as reference signals, response signals as well as dual emission matrix in ratio fluorescence sensors. Besides, ratio fluorescence sensor could establish an internal standard to weaken the interference of external factors, the analysis result was more reliable and accurate, and it was easier to realize sensitive visual analysis. Different models of fluorescence sensors were all widely used in the detection of Hg2+ in lake water, soil, and agricultural products. The bottleneck and development trend of the fluorescence sensor based on CDs using biomass as the synthesis source in the field of agricultural sensing were analyzed: 1) the luminescence mechanism of CDs remained unclear due to the complex composition of precursors in the preparation of CDs from crops and agricultural products. Moreover, the fluorescence quantum yield of synthesized CDs was uneven, and it needs to be separated, purified, doped or modified in a targeted manner; 2) most of the CDs based fluorescent sensors could detect only one single target, while the CDs based fluorescent sensors detecting multiple targets at the same time were little reported, and most of the sensing systems were still in the experimental stage, so it was difficult to perform the on-site detection of agricultural environmental quality and crop quality. [ABSTRACT FROM AUTHOR]

This study aimed to uncover related strains of extended-spectrum beta-lactamase Escherichia coli O157:H7 between agricultural matrices (soil, manure and irrigation water) and nearby water sources using multilocus-based phylogenetic analysis. Resistant and nonresistant E. coli O157:H7 were isolated, identified and characterised using standard microbiological methods. The results showed that soil samples had a high prevalence of E. coli O157:H7 (31.73%) and ESBL-producing E. coli O157:H7 (22.11%). Multilocus sequencing typing (MLST) analysis revealed that all ESBL-producing E. coli O157:H7 were identified as ST11. Phylogenetic analysis of E. coli O157:H7 indicated that irrigation water might be a reservoir for E. coli O157:H7. For antibiotic-resistant genes (ARG), the most common was bla TEM in 85% (n = 34), followed by bla OXA in 70% (n = 28), bla NDM and sul1 30% (n = 12) and lastly mcr-1 , which was only found in one soil isolate. The results showed that ESBL-producing E. coli O157:H7 isolates were intermixed in three clades, indicating close relatedness between isolated strains from different matrices. [ABSTRACT FROM AUTHOR]

In this research we are identifying the processes that are key factors for change in the agricultural environment. The PESTLE analysis is used to sort the state of every of the panels and find which one has the most impact. In our case we are identifying macroeconomic factors that have influence on the future development of the sector of agriculture in Bulgaria. In Bulgaria this kind of research has not been done using the PESTLE and will help future researchers to identify strengths and weaknesses in Bulgarian political, economic, sociocultural and technological environments. The legal framework and environmental factors are particularly important for agriculture and have been added in this order because the legal framework carries a higher importance. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China Agricultural University is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Our objectives were to identify genes of the multi-drug efflux system and to evaluate the antimicrobial activities of polypyrrole nanoparticles (PPy-NPs) and aqueous extract of Moringa oleifera against Staphylococcus spp. isolated from dairy farms in Northeast Brazil. Initially, 162 Staphylococcus spp. isolates were subjected to in vitro antimicrobial sensitivity tests. Of these, 35 presented antimicrobial multi-drug resistance phenotypes. These 35 isolates were then referred for the detection of norA, norB, norC, msrA, mgrA, tet-38, and lmrS genes, all of which feature in multi-drug efflux systems. In the isolates carrying the genes, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of PPy-NPs and Moringa oleifera aqueous extract were determined. In the molecular analysis of the 35 isolates norA, norC, tet-38, and msrA genes were detected and for the other genes norB, lmrS and mgrA there was no amplification. Antimicrobial activity was verified of PPy-NPs and aqueous extract of Moringa oleifera in Staphylococcus spp. carrying multi-drug efflux system genes. We concluded that there are multi-drug efflux system genes present in the Staphylococcus spp. from the agricultural environment in Northeast Brazil, and that aqueous extract of Moringa oleifera and PPy-NPs show bactericidal activity against these isolates. [ABSTRACT FROM AUTHOR]

Copyright of Enfances, Familles, Generations is the property of Enfances, Familles, Generations and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Yangtze River Economic Belt is an important production area of grains, oil, livestock, and aquatic products across three regions in China; thus, its agricultural environment is of particular importance. However, the agricultural environment of the Yangtze River Economic Belt has been polluted for a long time by three industrial wastes, agricultural fertilizers, pesticides, and livestock wastes. Although effort to prevent and control pollution has been increased in recent years, the situation remains severe. The assessment of agricultural environmental pollution was explored by using fuzzy comprehensive evaluation and the data from the 11 provinces and cities in the Yangtze River Economic Belt in the period of 2008-2016. The results show that agricultural environmental pollution in the Yangtze River Economic Belt is at a serious level on the basis of research on the current situation of such pollution, the use of relevant environmental pollution index data of the provinces and cities in the region from 2007 to 2016, and the performance of fuzzy comprehensive evaluation. Countermeasures to improve agricultural environmental pollution in the Yangtze River Economic Belt are proposed. They include strengthening the control of pollution caused by the three industrial wastes, pesticides, chemical fertilizers, and livestock) and the environmental education of farmers through various forms. [ABSTRACT FROM AUTHOR]

Abstract: Research on the occurrence of perfluorochemicals (PFCs) such as perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) in the agricultural environment is lacking, in spite of their potential risk via food chain transfer from aquatic and soil-plant systems to animals and/or humans. In the present study, for the first time, soil and water samples collected from 243 different agricultural sites adjacent to waste water treatment plants (WWTPs) belonging to 81 cities and 5 provinces with different levels of industrialization in South Korea were monitored for concentrations of PFOS and PFOA by use of solid phase extraction and liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Significant mean concentrations of PFOA (0.001–0.007 µg L−1 water and

In recent years, intensive and extensive farm managements have resulted in a decline in the quality of cultivated land. Excessive inputs have been leached from farmland to rivers and lakes, especially the leaching of nutrients, heavy metals and pesticide residues, which has aggravated the risk of pollution to agricultural environment. As a critical methodology of agricultural environment monitoring, the lysimeter has been applied to monitor the characteristics of soil leaching components, to simulate the migration of soil water and nutrients, and to assess the effects of farm managements on agricultural ecosystems, eventually to provide technical assistance for scientists to make a better management decision in the farmland ecosystem. In this paper, the methods of construction, layout, soil filling, soil surface isolation and sampling in the main types of lysimeters monitoring system were summarized. Based on that, the merits and shortcomings of different types of lysimeters were analyzed, and the main factors affecting the monitoring results of lysimeter were discussed. In the end, suggestions and prospects were put forward based on the current situation of lysimeter in agricultural environment monitoring. Overall, for the rectangular concrete lysimeter, the biggest advantage is that cost of construction and operation and requirements for technology is relatively low, however, large quantities of soil excavation, concrete construction and soil back filling are always time-consuming and usually cause high soil disturbance and significant artificial effect and need to undergo a transition period. Besides that, the problem of infiltration from inside to outside at the bottom and side of concrete lysimeter also needs to be overcome. Conversely, for barrel or vessel lysimeter, the monolith soil usually undergoes minimal disturbance by extracting and filling the cylindrical blocks, the process is much more simple, which can be achieved just by mechanical equipment including cutting system, crane, trucks and so on. It takes shorter time compared to concrete lysimeter, the whole procedure of obtaining monolith soil just takes one day or more and can be put into use immediately without transition period. Consequently the soil conditions are more comparable to natural field conditions and data could be accurately detected and collected. However, the technological and equipment requirements of monolith soil extraction, filling and transportation are relative high, as well as the cost of construction and operation. Besides that, boundary effect is much more significant compared to the concrete lysimeter due to the minimal soil base area. The artificial effect and boundary effect cannot be eliminated completely at the same time in the semi-closed lysimeter system, the selection and construction of lysimeter system should be depended on specific research needs, local geological and topographic conditions and their own technology level. Therefore, a more practical strategy need to be taken into consideration, that is to build a more suitable lysimeter within the acceptable deviation range and the given budget, being able to implement higher data accuracy with lower costs. Finally, building and running a long-term lysimeter station with continuously improved technologies, joining a platform, sharing methods, data and models, and constructing a network of lysimeter system are also recommended. [ABSTRACT FROM AUTHOR]

Agricultural landscape pattern is the internal driving force of industrial development planning. In order to solve the problem that the traditional landscape pattern evolution model has low fitting degree between the result and the actual situation, a model of agricultural environment ecological landscape pattern evolution based on fuzzy mathematics was proposed. The agricultural ecological landscape is divided into natural ecological landscape, residential landscape, production landscape and public service landscape; Remote sensing data preprocessing of agricultural landscape is realized through five steps: band combination, geometric correction, image registration, image clipping and image enhancement; Based on the index extraction equation of landscape pattern constructed by fuzzy mathematical reasoning, the evolution model of agricultural environmental ecological landscape pattern was constructed by fuzzy mathematical theory. The experimental results show that the model has a high degree of fitting between the results and the actual results, which verifies the practical application effect of the model. [ABSTRACT FROM AUTHOR]

Apple cultivation in Japan typically involves the use of chemical fertilizers and pesticides which can damage the environment. Therefore, in this study we investigated the orchard soil biochemical characteristics as well as the fruit nutrient contents, and pesticide residues of apples grown either organically (organic fertilizers + reduced pesticides) or with conventional chemical fertilizers and pesticide rates. Compared with conventional chemical fertilizer treatment, the organic fertilizer treatment produced fruit with significantly higher contents of sugar, as well as soil with higher total carbon, total nitrogen, and total phosphorus. There were also significantly greater soil bacterial biomass and N circulation in the organically fertilized treatments. Minimal pesticide residues were detected in the organically fertilized fruits, but in the apples cultivated with conventional rates of fertilizers and pesticides there were significantly higher levels of propargite that was used to control spider mites. These residue levels from the conventionally fertilized orchards exceeded European and Codex residue standards. These results indicate that environmentally friendly arboricultural soil management practices, such as organic fertilizer and reduced pesticide cultivation can enhance nutrient cycling in soil, reduce the burden on the environment, and promote food safety and security.