Adsorption efficiency of chitosan/clinoptilolite (CS/CZ) composite for effective removal of Cd+2 and Cr+6 ions from wastewater effluents of dairy cattle farms.

The wastewater effluent is responsible for the major ecological impact of the dairy sectors. To avoid the negative consequences of heavy metal pollution on the ecosystem, creative, affordable, and efficient treatment methods are now required before the effluent flows into the surrounding area. This study was aimed at assessing the effectiveness of three different adsorbents for Cd+2 and Cr+6 ions from wastewater effluents of dairy farms, including chitosan (CS), clinoptilolite zeolite (CZ), and chitosan/clinoptilolite zeolite (CS/CZ) composite. The adsorption kinetics of the CS/CZ composite were established using the effects of the key variables (pH, agitation speed, adsorbent concentrations, and contact durations). The removal (%) and adsorption capacities, qe (mg/g), were calculated using the data from the adsorption kinetics. Wastewater samples (n = 60) were collected from the wastewater effluents of five farms. Cd+2 and Cr+6 ion concentrations in all collected samples were determined. Following the CS/CZ composite creation, it was characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (X-RD), and Fourier-transform infrared spectrum (FT-IR). The CS/CZ composite had an adsorption capacity of 92.4 and 96.5 mg/g for both Cd+2 and Cr+6 ions at a concentration of 2.0 g/100 ml, respectively, while the CZ adsorption capacities for the two ions were 87.5 mg/g and 61.0 mg/g, respectively, at 4.0 g/100 ml concentration. The CS was achieved at 55.56 mg/g and 33.3 mg/g, respectively, at the same concentration. The efficiency of heavy metal removal was enhanced by increasing adsorbent concentration, agitation speed, and contact duration. Using CS/CZ composite at 2.0 g/100 ml concentration, 180 min of contact time, and 300 rpm agitation speed, the greatest removal efficiencies for Cd+2 and Cr+6 ions (96.43 and 98.75%, respectively) were demonstrated.

Assessing the impact of biosecurity practices and animal welfare in small-scale mountain dairy farming.

This study estimates the association between the level of biosecurity, animal welfare, milk quality, and economic performance on 2291 mountain dairy farms which largely differs in management and structure from large dairy operations in the lowlands mainly due to climatic and topographic constraints in mountain areas. The dairy industry's increasing emphasis on biosecurity is crucial for ensuring animal health, productivity, and disease mitigation. Therefore, in the present study the biosecurity and animal welfare status of mountain dairy farms were assessed considering the official welfare protocol for dairy cows of the Italian ClassyFarm system. Our findings reveal a suboptimal adoption of biosecurity measures, attributed to structural limitations in mountain farms and farmers' awareness gaps. Despite these challenges, the economic significance of biosecurity adoption is evident, emphasizing potential benefits for farm viability and animal health. Conversely, the study indicates a moderate to good welfare status in assessed farms, reflecting farmers' awareness of the importance of high welfare standards for dairy cows. Improved welfare positively correlates with milk sales and productivity, highlighting the economic advantages of prioritizing animal well-being. Challenges persist, particularly regarding animal housing deficiencies and related consumer concerns about animal welfare in dairy production. Therefore, targeted interventions and educational initiatives are crucial to empower farmers and promote best practices in biosecurity and animal welfare management. However, addressing resultant production cost increases necessitates society's willingness to pay more for animal-based food, emphasizing the importance of aligning economic incentives with sustainable farming practices.

Farmland pest recognition based on Cascade RCNN Combined with Swin-Transformer.

Agricultural pests and diseases pose major losses to agricultural productivity, leading to significant economic losses and food safety risks. However, accurately identifying and controlling these pests is still very challenging due to the scarcity of labeling data for agricultural pests and the wide variety of pest species with different morphologies. To this end, we propose a two-stage target detection method that combines Cascade RCNN and Swin Transformer models. To address the scarcity of labeled data, we employ random cut-and-paste and traditional online enhancement techniques to expand the pest dataset and use Swin Transformer for basic feature extraction. Subsequently, we designed the SCF-FPN module to enhance the basic features to extract richer pest features. Specifically, the SCF component provides a self-attentive mechanism with a flexible sliding window to enable adaptive feature extraction based on different pest features. Meanwhile, the feature pyramid network (FPN) enriches multiple levels of features and enhances the discriminative ability of the whole network. Finally, to further improve our detection results, we incorporated non-maximum suppression (Soft NMS) and Cascade R-CNN's cascade structure into the optimization process to ensure more accurate and reliable prediction results. In a detection task involving 28 pest species, our algorithm achieves 92.5%, 91.8%, and 93.7% precision in terms of accuracy, recall, and mean average precision (mAP), respectively, which is an improvement of 12.1%, 5.4%, and 7.6% compared to the original baseline model. The results demonstrate that our method can accurately identify and localize farmland pests, which can help improve farmland's ecological environment.

Molecular identification of Coxiella burnetii in raw milk samples collected from farm animals in districts Kasur and Lahore of Punjab, Pakistan.

Coxiella burnetii is the worldwide zoonotic infectious agent for Q fever in humans and animals. Farm animals are the main reservoirs of C. burnetii infection, which is mainly transmitted via tick bites. In humans, oral, percutaneous, and respiratory routes are the primary sources of infection transmission. The clinical signs vary from flu-like symptoms to endocarditis for humans' acute and chronic Q fever. While it is usually asymptomatic in livestock, abortion, stillbirth, infertility, mastitis, and endometritis are its clinical consequences. Infected farm animals shed C. burnetii in birth products, milk, feces, vaginal mucus, and urine. Milk is an important source of infection among foods of animal origin. This study aimed to determine the prevalence and molecular characterization of C. burnetii in milk samples of dairy animals from two districts in Punjab, Pakistan, as it has not been reported there so far. Using a convenience sampling approach, the current study included 304 individual milk samples from different herds of cattle, buffalo, goats, and sheep present on 39 farms in 11 villages in the districts of Kasur and Lahore. PCR targeting the IS1111 gene sequence was used for its detection. Coxiella burnetii DNA was present in 19 of the 304 (6.3%) samples. The distribution was 7.2% and 5.2% in districts Kasur and Lahore, respectively. The results showed the distribution in ruminants as 3.4% in buffalo, 5.6% in cattle, 6.7% in goats, and 10.6% in sheep. From the univariable analysis, the clinical signs of infection i.e. mastitis and abortion were analyzed for the prevalence of Coxiella burnetii. The obtained sequences were identical to the previously reported sequence of a local strain in district Lahore, Sahiwal and Attock. These findings demonstrated that the prevalence of C. burnetii in raw milk samples deserves more attention from the health care system and veterinary organizations in Kasur and Lahore of Punjab, Pakistan. Future studies should include different districts and human populations, especially professionals working with animals, to estimate the prevalence of C. burnetii.

Chemical fractionation and mobility of Cd, Mn, Ni, and Pb in farmland soils near a ceramics company.

Soil contamination due to industrial activity in ceramics production is of concern because of the risk of heavy metal pollution. Successive extraction was used to measure and identify the concentrations of Cd, Mn, Ni, and Pb in farming soils near a ceramics company in Nigeria. Furthermore, soil pH and particle size analyses were determined. The concentration of Pb was the highest, followed by that of Ni, Mn, and Cd (lowest), and the mean level of Cd exceeded the regulatory allowed limit of 1.4 mg kg-1. The order of the metals' mobility factors was as follows: Cd > Mn > Ni, Pb. While the Fe-Mn oxide phase had 37% (Mn) and 20 to 83% (Ni), the residual fraction had approximately 30% (Cd) and 19 to 50% (Pb). Soil pollution evaluation was performed using enrichment factor (EF), contamination factor (CF), pollution load index (PLI), and geoaccumulation index (Igeo). Values of EF indicated significant enrichment for all metals, as the EF mean values for Cd, Ni, and Pb in soil were > 1.5. Total EF is of the order Cd > Pb > Ni > Mn. CF results revealed moderate to very high contamination (CF < 1: 3 ≤ CF ≥ 6). Similarly, the PLI indicated moderately to severely polluted soil. The order is 100 m > 200 m > 300 m > 400 m. The Igeo ranged from 1.46 to 2.76 (Cd), 0.07 to 1.62 (Ni), and 0.05 to 2.81 (Pb). The PCA, CA, and EF analyses suggest that the metals are a consequence of anthropogenic activities.

Widespread prevalence of plasmid-mediated blaCTX-M type extended-spectrum beta-lactamase Escherichia coli in backyard broiler production systems in the United States.

Extended-spectrum beta-lactamase (ESBL) Escherichia coli (E. coli) is an emerging pathogen of high concern given its resistance to extended-spectrum cephalosporins. Broiler chicken, which is the number one consumed meat in the United States and worldwide, can be a reservoir of ESBL E. coli. Backyard poultry ownership is on the rise in the United States, yet there is little research investigating prevalence of ESBL E. coli in this setting. This study aims to identify the prevalence and antimicrobial resistance profiles (phenotypically and genotypically) of ESBL E. coli in some backyard and commercial broiler farms in the U.S. For this study ten backyard and ten commercial farms were visited at three time-points across flock production. Fecal (n = 10), litter/compost (n = 5), soil (n = 5), and swabs of feeders and waterers (n = 6) were collected at each visit and processed for E. coli. Assessment of ESBL phenotype was determined through using disk diffusion with 3rd generation cephalosporins, cefotaxime and ceftazidime, and that with clavulanic acid. Broth microdilution and whole genome sequencing were used to investigate both phenotypic and genotypic resistance profiles, respectively. ESBL E. coli was more prevalent in backyard farms with 12.95% of samples testing positive whereas 0.77% of commercial farm samples were positive. All isolates contained a blaCTX-M gene, the dominant variant being blaCTX-M-1, and its presence was entirely due to plasmids. Our study confirms concerns of growing resistance to fourth generation cephalosporin, cefepime, as roughly half (51.4%) of all isolates were found to be susceptible dose-dependent and few were resistant. Resistance to non-beta lactams, gentamicin and ciprofloxacin, was also detected in our samples. Our study identifies prevalence of blaCTX-M type ESBL E. coli in U.S. backyard broiler farms, emphasizing the need for interventions for food and production safety.

Exploring biochar and Moringa oleifera seed proteins for greywater remediation on small farms.

This study investigated the potential of using biochar and Moringa oleifera seed proteins for sustainable greywater treatment in rural Kenya. Greywater samples from washing clothes were collected from households in the Kenyan counties of Kwale and Siaya. Two treatment methods, batch stirring and filtration, were used to assess the effectiveness of using biochar and Moringa oleifera seed protein extract together to treat greywater at a household level. Both methods achieved a significant reduction in contaminants: colour was reduced by up to 43% in Kwale and 67% in Siaya, turbidity decreased by 91-98%, and surfactant levels were lowered by 89-93%. There were increases in total organic carbon and total dissolved solids post-treatment, but both methods effectively reduced levels of phosphates, nitrates and iron. This research highlights the potential of using locally available materials for greywater treatment and provides insights into sustainable water management nature-based solutions in the Global South.

Unlocking sustainable livestock production potential in the Colombian Amazon through paddock division and gender inclusivity.

Low-emissions livestock production can be achieved through scaling production systems integrating trees, forages, and livestock within the same area. Such systems are known as silvopastoral production systems (SPS). However, despite SPS reported benefits, adoption rates globally remain low. This paper, therefore, aims to inform land use policy oriented towards increasing SPS adoption. This study intends to capture this by assessing SPS adoption benefits, identifying determinants of SPS adoption, and thus to contribute to policy for scaling low-emissions livestock production. Data was collected on socioeconomic status, livestock farming technical and economic indicators, and farm and paddock practices through farm-level surveys in four municipalities in the Amazon Piedmont of Colombia. Unlike previous studies that assume homogeneous farm management, when in fact, it is heterogeneous, this study assessed SPS adoption determinants using the paddock (n = 2819) as the unit of analysis. This methodological approach is consistent with paddock-level land use decisions taken by farmers based on socioeconomic and biophysical factors such as soil financial resources, type, and topography. The methodological approach allows us to provide new insights into the determinant of adopting SPS and an understanding of intra-farm level land use decisions. The results show that the adoption of SPS at both paddocks and farm levels in Caquetá is low. The main factors associated with higher SPS adoption levels at the paddock level are framed in gender, resources, and knowledge. We observe that women are more motivated to conserve the environment. Cattle paddocks managed by women, smaller in size, and those with more SPS-related projects show a tendency for medium or high SPS adoption. Furthermore, the positive relationship between access to credit and SPS adoption emphasizes the importance of financial resources tailored to SPS projects. Enhancing gender roles, improving access to finance in land use, and providing training programs on SPS systems can contribute to low-emission livestock production in Colombia. This research paper highlights the significance of implementing diverse management strategies and reaching out to farmers not involved in SPS projects. It emphasizes investments in low-emission livestock production, especially for female heads of households. This approach recognizes the broader benefits of SPS, beyond production and financial gains, promoting the division of paddocks and the adoption of SPS.

Transforming Poultry Farming: A Pyramid Vision Transformer Approach for Accurate Chicken Counting in Smart Farm Environments.

Smart farm environments, equipped with cutting-edge technology, require proficient techniques for managing poultry. This research investigates automated chicken counting, an essential part of optimizing livestock conditions. By integrating artificial intelligence and computer vision, it introduces a transformer-based chicken-counting model to overcome challenges to precise counting, such as lighting changes, occlusions, cluttered backgrounds, continual chicken growth, and camera distortions. The model includes a pyramid vision transformer backbone and a multi-scale regression head to predict precise density maps of the crowded chicken enclosure. The customized loss function incorporates curriculum loss, allowing the model to learn progressively, and adapts to diverse challenges posed by varying densities, scales, and appearances. The proposed annotated dataset includes data on various lighting conditions, chicken sizes, densities, and placements. Augmentation strategies enhanced the dataset with brightness, contrast, shadow, blur, occlusion, cropping, and scaling variations. Evaluating the model on the proposed dataset indicated its robustness, with a validation mean absolute error of 27.8, a root mean squared error of 40.9, and a test average accuracy of 96.9%. A comparison with the few-shot object counting model SAFECount demonstrated the model's superior accuracy and resilience. The transformer-based approach was 7.7% more accurate than SAFECount. It demonstrated robustness in response to different challenges that may affect counting and offered a comprehensive and effective solution for automated chicken counting in smart farm environments.

Maize (Zea mays L.) Plants Alter the Fate and Accumulate Nonextractable Residues of Sulfamethoxazole in Farmland Soil.

The fate of sulfonamide antibiotics in farmlands is crucial for food and ecological safety, yet it remains unclear. We used [phenyl-U-14C]-labeled sulfamethoxazole (14C-SMX) to quantitatively investigate the fate of SMX in a soil-maize system for 60 days, based on a six-pool fate model. Formation of nonextractable residues (NERs) was the predominant fate for SMX in unplanted soil, accompanied by minor mineralization. Notably, maize plants significantly increased SMX dissipation (kinetic constant kd = 0.30 day-1 vs 0.17 day-1), while substantially reducing the NER formation (92% vs 58% of initially applied SMX) and accumulating SMX (40%, mostly bound to roots). Significant NERs (maximal 29-42%) were formed via physicochemical entrapment (determined using silylation), which could partially be released and taken up by maize plants. The NERs consisted of a considerable amount of SMX formed via entrapment (1-8%) and alkali-hydrolyzable covalent bonds (2-12%, possibly amide linkage). Six and 10 transformation products were quantified in soil extracts and NERs, respectively, including products of hydroxyl substitution, deamination, and N-acylation, among which N-lactylated SMX was found for the first time. Our findings reveal the composition and instability of SMX-derived NERs in the soil-plant system and underscore the need to study the long-term impacts of reversible NERs.

Culicoides Midge Abundance across Years: Modeling Inter-Annual Variation for an Avian Feeder and a Candidate Vector of Hemorrhagic Diseases in Farmed Wildlife.

(1) Background: Epizootic hemorrhagic disease virus (EHDV) and bluetongue virus (BTV) are orbiviruses that cause hemorrhagic disease (HD) with significant economic and population health impacts on domestic livestock and wildlife. In the United States, white-tailed deer (Odocoileus virginianus) are particularly susceptible to these viruses and are a frequent blood meal host for various species of Culicoides biting midges (Diptera: Ceratopogonidae) that transmit orbiviruses. The species of Culicoides that transmit EHDV and BTV vary between regions, and larval habitats can differ widely between vector species. Understanding how midges are distributed across landscapes can inform HD virus transmission risk on a local scale, allowing for improved animal management plans to avoid suspected high-risk areas or target these areas for insecticide control. (2) Methods: We used occupancy modeling to estimate the abundance of gravid (egg-laden) and parous (most likely to transmit the virus) females of two putative vector species, C. stellifer and C. venustus, and one species, C. haematopotus, that was not considered a putative vector. We developed a universal model to determine habitat preferences, then mapped a predicted weekly midge abundance during the HD transmission seasons in 2015 (July-October) and 2016 (May-October) in Florida. (3) Results: We found differences in habitat preferences and spatial distribution between the parous and gravid states for C. haematopotus and C. stellifer. Gravid midges preferred areas close to water on the border of well and poorly drained soil. They also preferred mixed bottomland hardwood habitats, whereas parous midges appeared less selective of habitat. (4) Conclusions: If C. stellifer is confirmed as an EHDV vector in this region, the distinct spatial and abundance patterns between species and physiological states suggest that the HD risk is non-random across the study area.

Prevalence, Time of Infection, and Diversity of Porcine Reproductive and Respiratory Syndrome Virus in China.

Porcine reproductive and respiratory syndrome virus (PRRVS) is a major swine viral pathogen that affects the pig industry worldwide. Control of early PRRSV infection is essential, and different types of PRRSV-positive samples can reflect the time point of PRRSV infection. This study aims to investigate the epidemiological characteristics of PRRSV in China from Q4 2021 to Q4 2022, which will be beneficial for porcine reproductive and respiratory syndrome virus (PRRSV)control in the swine production industry in the future. A total of 7518 samples (of processing fluid, weaning serum, and oral fluid) were collected from 100 intensive pig farms in 21 provinces, which covered all five pig production regions in China, on a quarterly basis starting from the fourth quarter of 2021 and ending on the fourth quarter of 2022. Independent of sample type, 32.1% (2416/7518) of the total samples were PCR-positive for PRRSV, including 73.6% (1780/2416) samples that were positive for wild PRRSV, and the remaining were positive for PRRSV vaccine strains. On the basis of the time of infection, 58.9% suckling piglets (processing fluid) and 30.8% weaning piglets (weaning serum) showed PRRSV infection at an early stage (approximately 90% of the farms). The sequencing analysis results indicate a wide range of diverse PRRSV wild strains in China, with lineage 1 as the dominant strain. Our study clearly demonstrates the prevalence, infection stage, and diversity of PRRSV in China. This study provides useful data for the epidemiological understanding of PRRSV, which can contribute to the strategic and systematic prevention and control of PRRSV in China.

Influence of Small-Scale Irrigation on Livelihoods of Rural Farm Households in the Case of Legehida District, Ethiopia.

Irrigation development, particularly small-scale irrigation, is one of the most important projects for improving agricultural productivity in a country's rural communities. The extent to which small-scale irrigation has improved household livelihoods in Ethiopia's rural areas is not widely recognized. As a result, research on the influence of small-scale irrigation on farmers' livelihoods in the Legehida district will be sought. The study took a "with" and "without" strategy, comparing farmers who used irrigation against those who did not. For analysis, both quantitative and qualitative data were employed. The survey's respondents were chosen using a random sample approach from both irrigation users and nonuser households. Quantitative data for the study were collected from randomly selected 241 farm households, of which 113 were users and 128 were nonusers, using a semistructured questionnaire. Accordingly, the propensity score matching model was employed to examine the impacts of small-scale irrigation on farmers' livelihoods. The logit model result indicates that cultivated land size, off-farm income, education level, family size, dependency ratio, total livestock unit, and distance to the nearest agricultural extension office/FTC are determinant factors in determining whether to practice irrigation when other factors remain constant. The impact of irrigation on a household's income and food security (in terms of daily calorie intake) was evaluated using a propensity score matching model. The result shows that a positive and significant impact on farmers who use small-scale irrigation has increased the daily calorie intake and annual income of households by 244.162 kilocalories and 5234.258 ETB, respectively, as compared to nonirrigation users. This shows that households that participate in small-scale irrigation activities have a higher annual income and food security status than comparable groups. In general, the study recommends that to reduce food insecurity and the socioeconomic problems of rural households, irrigation farming is one of the viable solutions; therefore, the government and nongovernmental organizations should extensively focus on the enhancement of small-scale irrigation infrastructure, policies, strategies, and extension services to increase productivity, income, and livelihood improvement in rural households.

The characteristics of the novel bacterial strain Pseudomonas mendocina isolated from freshwater aquaculture farm.

Plastic contamination can cause damage to the water quality of fish farm ponds, and also affect the quality of the final product. Pseudomonas mendocina was found to biodegrade plastics. Our study aimed to investigate the physicochemical properties and drug resistance of P. mendocina isolated from local freshwater aquaculture farms. Firstly, the strain was isolated from aquaculture water and then identified by matrix-assisted flight mass spectrometry and 16S rDNA sequencing. Then, biochemical and antibiotic resistance analyses were performed, and a microbial high-throughput growth detector was used to assess the growth of the strain. Finally, PCR and proteomics analyses were conducted to determine drug-resistance-related genes/proteins. According to the results of the spectrum diagram and sequencing, the isolated bacteria were identified as P. mendocina, and were positive for reactions of ADH, MTE, LAC, MNE, FRU, CIT, MLT, ONPG, and ACE. P. mendocina was sensitive to most of the antibiotics, and its resistance to CHL, MIN, and TIC/CLA was intermediate. Additionally, gyrB was the resistance gene, and mdtA2, mdtA3, mdaB, and emrK1 were closely related to the drug resistance of P. mendocina. Our results show the biochemical properties of P. mendocina in isolated aquaculture water, and provide a new perspective for P. mendocina involved in the biological removal of plastics or microplastics in freshwater aquaculture farms.

Unraveling patterns, causes, and nature-based remediation strategy for non-grain production on farmland in hilly regions.

The surge in non-grain production on farmland (NGPF) poses significant threats to food security and land sustainability, particularly in hilly regions. However, there remains a lack of clarity on how to effectively balance grain and non-grain production in relation to land remediation. Using Wannian County as a case study, we investigate the evolution of this by leveraging high-precision land surveys and satellite imagery. Through the application of bootstrapped partial linear regression models, we identify key influencers behind each type of NGPF. In proposing land remediation solutions, we integrate the results of NGPF and land quality evaluations to identify mismatches between non-grain production and land attributes (i.e., topography, geology, soil, and land use). Our findings reveal a substantial growth in NGPF, expanding from 3838.72 ha to 5659.64 ha (2010-2020), and predominantly occurring on farmland with favorable natural conditions and connected locations such as proximity to roads, town centers, and industrial plants. Surprisingly, the basic farmland protection policy shows limited effectiveness in curbing NGPF, except for garden operations. We identify 1674 NGPF patches suitable for conversion to grain production and provide land remediation suggestions tailored to low-quality farmland with specific natural barriers, thus complementing the demand for regional non-grain production. This study thereby innovatively proposes nature-based land remediation strategies to address the non-grain production dilemma by tailoring NGPF and land quality, offering valuable insights for sustainable farmland management in China and beyond.

Pollution sources and risk assessment of potentially toxic elements in soils of multiple land use types in the arid zone of Northwest China based on Monte Carlo simulation.

The concentration of potentially toxic elements (PTEs) in soils of different land-use types varies depending on climatic conditions and human. Topsoil samples were collected in Northwest China to investigate PTE pollution and risk in different land uses, and thereby estimate the risk of various pollution sources. The results showed that human activity had an impact on PTE concentrations in the study area across all land use types, with farmland, grassland, woodland, and the gobi at moderate pollution levels and the desert at light pollution levels. Different PTE sources pose different risks depending on the land-use type. Apart from deserts, children are exposed to carcinogenic risk from a variety of sources. A mixed natural and agricultural source was the main source of public health risk in the study area, contributing 38.7% and 39.0% of the non-carcinogenic and 40.7% and 35.5% of the carcinogenic risks, respectively. Monte Carlo simulations showed children were at a higher health risk from PTEs than adult s under all land uses, which ranked in severity as farmland > woodland > grassland > gobi > desert. As and Ni has a higher probability of posing both a non-carcinogenic and a carcinogenic risk to children. Sensitivity analysis showed that the contribution of parameters to the assessment model of PTEs exhibited the following contribution pattern: concentration > average body weight > ingestion rate > other parameters. The PTEs affecting the risk assessment model were not common among different land use types, where the importance distribution pattern of each parameter was basically the same in woodland, grassland, and farmland, and Ni contributed the most to carcinogenic risk. However, Cr contributed the most to the carcinogenic risk in the desert and gobi.

A portable, easy-to-use paper-based biosensor for rapid in-field detection of fecal contamination on fresh produce farms.

Laboratory-based nucleic acid amplification tests (NAATs) are highly sensitive and specific, but they require the transportation of samples to centralized testing facilities and have long turnaround times. During the Coronavirus Disease 2019 (COVID-19) pandemic, substantial advancement has been achieved with the development of paper-based point-of-care (POC) NAATs, offering features such as low cost, being easy to use, and providing rapid sample-to-answer times. Although most of the POC NAATs innovations are towards clinical settings, we have developed a portable, paper-based loop-mediated isothermal amplification (LAMP) testing platform for on-farm applications, capable of detecting Bacteroidales as a fecal contamination biomarker. Our integrated platform includes a drop generator, a heating and imaging unit, and paper-based biosensors, providing sensitive results (limit of detection 3 copies of Bacteroidales per cm2) within an hour of sample collection. We evaluated this integrated platform on a commercial lettuce farm with a concordance of 100% when compared to lab-based tests. Our integrated paper-based LAMP testing platform holds great promise as a reliable and convenient tool for on-site NAATs. We expect that this innovation will encourage the fresh produce industry to adopt NAATs as a complementary tool for decision-making in growing and harvesting. We also hope that our work can stimulate further research in the development of on-farm diagnostic tools for other agricultural applications, leading to improved food safety and technology innovation.

Retrospective evaluation of udder recovery of cows with subclinical mastitis following treatment with acoustic pulse technology (APT) on commercial dairy farms and its economic impact.

Retrospective evaluation of udder recovery following treatment of the inflamed quarter with acoustic pulse technology (APT) of cows with subclinical mastitis was done on 4 Israeli commercial dairy farms. Here, we evaluated the APT treatment as a tool to manage subclinical mastitis and its economic consequences in commercial farms. Recovery of the infected glands following APT treatment was compared to the customary no-treatment (NT) for cows with subclinical mastitis. Over 2 years, 467 cows with subclinical mastitis were identified. Subclinical mastitis was defined by elevated somatic cell count (SCC; >1 × 106 cells/mL) in the monthly test-day milk sample; 222 cows were treated with APT and 245 cows were not treated and served as control. Differences between treatment groups in culling, milk quality, milk yield and bacterial elimination were analyzed. After treatment, cure from bacteria was calculated only for cows with pre-isolated bacteria. The percentage of sampled cows determined as cured (no bacterial finding) in the NT group was 32.7% (35/107) (30.9% Gram negative; 32.4% Gram positive) and in the APT-treated group, 83.9% (42/55) (89.4% Gram negative; 80.6% Gram positive). Culling rate due to mastitis was significantly lower (>90%) in the APT-treated vs. NT group. Recovery was 66.0% in the APT group compared to 11.5% in the NT group at 90 d post-treatment. Average milk volume per cow in the APT-treated group was 16.1% higher compared to NT cows. Based on the study, savings incurred by using APT to treat only subclinical cows per 100-cow herd can total $15,106/y, or $309 per treated subclinically infected cow.

Assessing the contribution of nonmarket factors to the market value generated by cow-calf operations in rangelands of the western USA: A true cost accounting approach.

Food system transformation requires a better understanding of the negative and positive externalities involved in food production and consumption. Although negative externalities have received substantial attention, positive externalities have been largely overlooked. True Cost Accounting (TCA) is an economic assessment aimed at accounting for externalities in food systems. The beef industry is an important part of the US food system. In the western USA, beef cattle production is a major land use and economic activity that involves direct links among the cattle, range ecosystems, range management, climate, and ranchers' decisions and welfare. We present a case study based on a TCA assessment to quantify and monetize the contribution of human, social, natural, and produced capitals, as well as farm structure, to the market value generated by cow-calf operations, a key component of the USA beef industry. We estimated an Ordinary Least Square regression model based on indicators of these capitals and of farm structure derived from publicly available data sources at the county level. From model coefficients, we estimated the marginal revenue product of these factors. Results show that nonmarket factors linked with human and social capitals support market performance by contributing to the market value of cow-calf production. These factors operate at scales above the ranch, usually remain hidden, and seldomly are considered in policy decision-making which can lead to policies that inadvertently hamper or eliminate these positive externalities.