Metagenomic evaluation of peanut rhizosphere microbiome from the farms of Saurashtra regions of Gujarat, India.

The narrow zone of soil around the plant roots with maximum microbial activity termed as rhizosphere. Rhizospheric bacteria promote the plant growth directly or indirectly by providing the nutrients and producing antimicrobial compounds. In this study, the rhizospheric microbiota of peanut plants was characterized from different farms using an Illumina-based partial 16S rRNA gene sequencing to evaluate microbial diversity and identify the core microbiome through culture-independent (CI) approach. Further, all rhizospheric bacteria that could grow on various nutrient media were identified, and the diversity of those microbes through culture-dependent method (CD) was then directly compared with their CI counterparts. The microbial population profiles showed a significant correlation with organic carbon and concentration of phosphate, manganese, and potassium in the rhizospheric soil. Genera like Sphingomicrobium, Actinoplanes, Aureimonas _A, Chryseobacterium, members from Sphingomonadaceae, Burkholderiaceae, Pseudomonadaceae, Enterobacteriaceae family, and Bacilli class were found in the core microbiome of peanut plants. As expected, the current study demonstrated more bacterial diversity in the CI method. However, a higher number of sequence variants were exclusively present in the CD approach compared to the number of sequence variants shared between both approaches. These CD-exclusive variants belonged to organisms that are more typically found in soil. Overall, this study portrayed the changes in the rhizospheric microbiota of peanuts in different rhizospheric soil and environmental conditions and gave an idea about core microbiome of peanut plant and comparative bacterial diversity identified through both approaches.

Social capital, government guidance and contract choice in agricultural land transfer.

This study explores the impact of farm households' social capital characteristics and local government policies on the selection of farmland transfer contracts in China's rural industrial revitalization context. Utilizing field research data from 1,979 households in ethnic areas of Hunan Province, this paper constructs an econometric model to assess how farm households' social capital and local governments' involvement in rural industrial revitalization influence farmland transfer contract selections. The findings indicate that, lacking government program support, farmers' social capital significantly affects contract type and duration, but not the rent. Specifically, farmers possessing extensive social capital prefer verbal and short-term contracts (coefficients of 0.525 and 0.643, significant at the 5% level), whereas their influence on rent (coefficient of 2.418, significant at the 5% level) manifests under government program support. These results challenge the conventional theory of farmland transfer contracts and offer substantial empirical support for the development of local government policies in rural industrial revitalization, underlining the critical role of government guidance and social capital in enhancing farmland transfer.

Economic and financial viability of a pig farm in central semi-tropical Mexico: 2022-2026 prospective.

To estimate the economic and financial viability of a pig farm in central sub-tropical Mexico within a 5-year planning horizon, a Monte Carlo simulation model was utilized. Net returns were projected using simulated values for the distribution of input and product processes, establishing 2021 as base scenario. A stochastic modelling approach was employed to determine the economic and financial outlook. The findings reveal a panorama of economic and financial viability. Net income increased by 555%, return on assets rose from 3.36% in 2022 to 11.34% in 2026, and the probability of decapitalization dropped from 58% to 13%, respectively in the aforesaid periods. Similarly, the probability of obtaining negative net income decreased from 40% in 2022 to 18% in 2026. The technological, productive, and economic management of the production unit allowed for a favorable scenario within the planning horizon. There is a growing interest in predicting the economic sectors worth investing in and supporting, considering their economic and development performance. This research offers both methodological and scientific evidence to demonstrate the feasibility of establishing a planning schedule and validating the suitability of the pork sector for public investment and support.

Molecular characteristics and phylogenetic analysis of pigeon paramyxovirus type 1 isolates from pigeon meat farms in Shanghai (2009-2012).

The majority of pigeon paramyxovirus type 1 (PPMV-1) strains are generally non-pathogenic to chickens; however, they can induce severe illness and high mortality rates in pigeons, leading to substantial economic repercussions. The genomes of 11 PPMV-1 isolates from deceased pigeons on meat pigeon farms during passive monitoring from 2009 to 2012 were sequenced and analyzed using polymerase chain reaction and phylogenetic analysis. The complete genome lengths of 11 isolates were approximately 15,192 nucleotides, displaying a consistent gene order of 3'-NP-P-M-F-HN-L-5'. ALL isolates exhibited the characteristic motif of 112RRQKRF117 at the fusion protein cleavage site, which is characteristic of velogenic Newcastle disease virus. Moreover, multiple mutations have been identified within the functional domains of the F and HN proteins, encompassing the fusion peptide, heptad repeat region, transmembrane domains, and neutralizing epitopes. Phylogenetic analysis based on sequences of the F gene unveiled that all isolates clustered within genotype VI in class II. Further classification identified at least two distinct sub-genotypes, with seven isolates classified as sub-genotype VI.2.1.1.2.2, whereas the others were classified as sub-genotype VI.2.1.1.2.1. This study suggests that both sub-genotypes were implicated in severe disease manifestation among meat pigeons, with sub-genotype VI.2.1.1.2.2 displaying an increasing prevalence among Shanghai's meat pigeon population since 2011. These results emphasize the value of developing pigeon-specific vaccines and molecular diagnostic tools for monitoring and proactively managing potential PPMV-1 outbreaks.

On-farm crop diversity, conservation, importance and value: a case study of landraces from Western Ghats of Karnataka, India.

Landraces are important genetic resources that have a significant role in maintaining the long-term sustainability of traditional agro-ecosystems, food, nutrition, and livelihood security. In an effort to document landraces in the on-farm conservation context, Central Western Ghat region in India was surveyed. A total of 671 landraces belonging to 60 crops were recorded from 24 sites. The custodian farmers were found to conserve a variety of crops including vegetables, cereals and pulses, perennial fruits, spices, tuber and plantation crops. The survey indicated a difference in the prevalence of landraces across the sites. A significant difference with respect to the Shannon-diversity index, Gini-Simpson index, evenness, species richness, and abundance was observed among the different survey sites. Computation of a prevalence index indicated the need for immediate intervention in the form of collecting and ex situ conservation of landraces of some crops as a back-up to on-farm conservation. The study also identified the critical determinants of on-farm conservation, including (i) suitability to regional conditions, (ii) relevance in regional cuisine and local medicinal practices, (iii) cultural and traditional significance, and (iv) economic advantage. The information documented in this study is expected to promote the collection and conservation of landraces ex situ. The National Genebank housed at ICAR-NBPGR, New Delhi conserves around 550 accessions of landraces collected from the Central Western Ghats region surveyed in this report. Information collected from custodian farmers on specific uses will be helpful to enhance the utilization of these accessions.

Genetic diversity and phylogenetic relationships of Clostridium perfringens strains isolated from mastitis and enteritis in Egyptian dairy farms.

BACKGROUND: Clostridium perfringens, a common environmental bacterium, is responsible for a variety of serious illnesses including food poisoning, digestive disorders, and soft tissue infections. Mastitis in lactating cattle and sudden death losses in baby calves are major problems for producers raising calves on dairy farms. The pathogenicity of this bacterium is largely mediated by its production of various toxins. RESULTS: The study revealed that Among the examined lactating animals with a history of mastitis, diarrheal baby calves, and acute sudden death cases in calves, C. perfringens was isolated in 23.5% (93/395) of the total tested samples. Eighteen isolates were obtained from mastitic milk, 59 from rectal swabs, and 16 from the intestinal contents of dead calves. Most of the recovered C. perfringens isolates (95.6%) were identified as type A by molecular toxinotyping, except for four isolates from sudden death cases (type C). Notably, C. perfringens was recovered in 100% of sudden death cases compared with 32.9% of rectal swabs and 9% of milk samples. This study analyzed the phylogeny of C. perfringens using the plc region and identified the plc region in five Egyptian bovine isolates (milk and fecal origins). Importantly, this finding expands the known data on C. perfringens phospholipase C beyond reference strains in GenBank from various animal and environmental sources. CONCLUSION: Phylogenetic analyses of nucleotide sequence data differentiated between strains of different origins. The plc sequences of Egyptian C. perfringens strains acquired in the present study differed from those reported globally and constituted a distinct genetic ancestor.

The ecological and biodiversity conservation values of farm dams: A systematic review.

Biodiversity is in rapid decline globally with agriculture being one of the leading causes. Within agricultural landscapes, some features provide a benefit to biodiversity that is disproportionate to their spatial area. An interesting example is artificial ponds-or farm dams-which can support a large variety of taxa. Here, we present a global review of farm dam research related to biodiversity conservation objectives to provide an overview of the topics, key research insights, and the characteristics of current research. We used a three-stage process to screen literature and identified 104 relevant papers across 27 countries encompassing studies of 13 different taxa. Most of the studies were short-term (less than 5 years) with small sample sizes (less than 20 sites). Of the 104 papers, 88 were focussed primarily on ecological outcomes, such as species richness or abundance, and 15 on primary production outcomes, such as crop and livestock yield, despite addressing or measuring ecological metrics. Only one study measured both ecological and primary production outcomes. Studies frequently examined how the features of dams (79 studies) and attributes of the surrounding landscape (47 studies) impact particular species and communities. Terrestrial mammals (1 study) were under-represented in the literature with macrophytes (28 studies), macroinvertebrates (26 studies), and amphibians (19 studies) receiving the most attention. Our results reveal a growing trend towards recognizing farm dams as habitats for various taxa, including amphibians, beetles, dragonflies, and other macroinvertebrates within agricultural environments. Significant knowledge gaps exist in understanding how dam age, invasive species, and effective management practices impact the biodiversity conservation values of farm dams. Future research should emphasize enhancing biodiversity by collaborating with landholders to increase habitat through strategic vegetation planning, minimizing runoff and nutrient inflow, and restricting stock access.

Investigating consumers' experiences with community supported agriculture: Convergent parallel design methods.

Community-supported agriculture (CSA) represents a collaborative model where local farms and community members form partnerships to facilitate the direct delivery of fresh produce from farms to consumers. This study primarily investigates the experiences of current CSA members, focusing on the key factors influencing their retention intentions. Employing a convergent parallel mixed methods approach, this study gathers and analyzes both quantitative data (such as factors affecting members' retention intentions) and qualitative data (derived from interviews reflecting members' perceptions of their CSA experiences). The integration of these datasets provides a comprehensive understanding of the factors that shape CSA membership dynamics. The research findings underscore that Convenience, Product Quality, and Positive Interactions are pivotal factors that contribute to members' Intentions to continue their CSA memberships. These insights are crucial for enhancing the services provided to CSA members and hold significant implications for the broader scope of CSA membership research. This study not only fills a critical gap in understanding the Chinese CSA context but also contributes to the global discourse on sustainable agriculture practices and community engagement.

The low survival rate of European hare leverets in arable farmland: evidence from the predation experiment.

The low survival rate of leverets may significantly contribute to steep population declines and slow recovery of European hares (Lepus europaeus). However, the leveret survival rate in farmlands with different landscape structures is poorly understood, and the existing evidence comes mainly from Western Europe. In this study, we explored the survival of leveret hare dummies along linear semi-natural habitats in homogeneous Central European arable farmland during the main part of the European hare reproduction period (March-April) in 2019 and 2020. The survival rate of hare leverets during the 14-day period was only 22.2%, and all predation events were recorded during the first six days of the experiment. Mammalian predators were responsible for 53.1% of predation events, avian predators for 40.8%, and agricultural operations for 6.1%. The red fox (Vulpes vulpes) was the dominant predator in our study area and was the primary cause of leveret dummy mortality (32.7%), but it also had the highest use-intensity and visit frequency of all of the study plots. Predation by avian predators was associated with patches of lower vegetation height and cover (such as plowed fields) and during daylight hours, whereas the opposite was true for mammalian predators. We propose that improving the habitat quality of arable landscapes by increasing the proportion and quality of extensively used non-farmed habitats (e.g., set-asides, wildflower areas, extensive meadows, fallow land, and semi-natural habitats on arable land) providing cover and shelter for leverets could be an effective management measure for reducing predation risk on leverets.

Crop yields fail to rise in smallholder farming systems in sub-Saharan Africa.

Drawing on a harmonized longitudinal dataset covering more than 55,000 smallholder farms in six African countries, we analyze changes in crop productivity from 2008 to 2019. Because smallholder farmers represent a significant fraction of the world's poorest people, agricultural productivity in this context matters for poverty reduction and for the broader achievement of the UN Sustainable Development Goals. Our analysis measures productivity trends for nationally representative samples of smallholder crop farmers, using detailed data on agricultural inputs and outputs which we integrate with detailed data on local weather and environmental conditions. In spite of government commitments and international efforts to strengthen African agriculture, we find no evidence that smallholder crop productivity improved over this 12-y period. Our preferred statistical specification of total factor productivity (TFP) suggests an overall decline in productivity of -3.5% per year. Various other models we test also find declining productivity in the overall sample, and none of them finds productivity growth. However, the different countries in our sample experienced varying trends, with some instances of growth in some regions. The results suggest that major challenges remain for agricultural development in sub-Saharan Africa. They complement previous analyses that relied primarily on aggregate national statistics to measure agricultural productivity, rather than detailed microdata.

The microplastics distribution characteristics and their impact on soil physicochemical properties and bacterial communities in food legumes farmland in northern China.

Microplastics (MPs) pose a threat to farmland soil quality and crop safety. MPs exist widely in food legumes farmland soil due to the extensive use of agricultural film and organic fertilizer, but their distribution characteristics and their impact on soil environment have not been reported. The abundance and characteristics of MPs, soil physical and chemical properties, and bacterial community composition were investigated in 76 soil samples from five provinces in northern China. The results showed that the abundance of MPs ranged from 1600 to 36,200 items/kg. MPs in soil were mostly fibrous, less than 0.2 mm, and white. Rayon, polyester and polyethylene were the main types of MPs. The influences of MPs on soil physicochemical properties and bacterial communities mainly depended on the type of MPs. Notably, polyethylene significantly decreased the proportion of silt particles, and increased the nitrate nitrogen content as well as the abundance of MPs-degrading bacteria Paenibacillus (p < 0.05). Moreover, bacteria were more sensitive to polyesters in soil with low concentration of organic matter. This study indicated that MPs in food legumes farmland soil presented a higher-level. And, they partially altered soil physicochemical properties, and soil bacteria especially in soil with low organic matter.

Vertical distribution of arsenic and bacterial communities in calcareous farmland amending by organic fertilizer and iron-oxidizing bacteria: Field experiment on concomitant remediation.

The migration and transformation mechanisms of arsenic (As) in soil environments necessitate an understanding of its influencing processes. Here, we investigate the subsurface biogeochemical transformation of As and iron (Fe) through amended in the top 20 cm with iron oxidizing bacteria (FeOB) and organic fertilizer (OF). Our comprehensive 400-day field study, conducted in a calcareous soil profile sectioned into 20 cm increments, involved analysis by sequential extraction and assessment of microbial properties. The results reveal that the introduction of additional OF increased the release ratio of As/Fe from the non-specific adsorption fraction (136.47 %) at the subsoil depth (40-60 cm), underscoring the importance of sampling at various depths and time points to accurately elucidate the form, instability, and migration of As within the profile. Examination of bacterial interaction networks indicated a disrupted initial niche in the bottom layer, resulting in a novel cooperative symbiosis. While the addition of FeOB did not lead to the dominance of specific bacterial species, it did enhance the relative abundance of As-tolerant Acidobacteria and Gemmatimonadetes in both surface (39.2 % and 38.76 %) and deeper soils (44.29 % and 23.73 %) compared to the control. Consequently, the amendment of FeOB in conjunction with OF facilitated the formation of poorly amorphous Fe (hydr)oxides in the soil, achieved through abiotic and biotic sequestration processes. Throughout the long-term remediation process, the migration coefficient of bioavailable As within the soil profile decreased, indicating that these practices did not exacerbate As mobilization. This study carries significant implications for enhancing biogeochemical cycling in As-contaminated Sierozem soils and exploring potential bioremediation strategies. ENVIRONMENTAL IMPLICATION: The long-term exposure of sewage irrigation has potential adverse effects on the local ecosystem, causing serious environmental problems. Microorganisms play a vital role in the migration and transformation of arsenic in calcareous soil in arid areas, which highlights the necessity of understanding its dynamics. The vertical distribution, microbial community and fate of arsenic in calcareous farmland soil profile in northwest China were studied through field experiments. The results of this work have certain significance for the remediation of arsenic-contaminated soil in arid areas, and provide new insights for the migration, transformation and remediation of arsenic in this kind of soil.

The optimisation of Salmonella surveillance programmes for pullet and layer farms using local farm density as a risk factor.

Human salmonellosis cases are often caused by Salmonella serovars Enteritidis and Typhimurium and associated with the consumption of eggs and egg products. Many countries therefore implemented general surveillance programmes on pullet and layer farms. The identification of risk factors for Salmonella infection may be used to improve the performance of these surveillance programmes. The aims of this study were therefore to determine 1) whether local farm density is a risk factor for the infection of pullet and layer farms by Salmonella Enteritidis and Typhimurium and 2) whether the sampling effort of surveillance programmes can be reduced by accounting for this risk factor, while still providing sufficient control of these serovars. We assessed the importance of local farm density as a risk factor by fitting transmission kernels to Israeli surveillance data during the period from June 2017 to April 2019. The analysis shows that the risk of infection by serovars Enteritidis and Typhimurium significantly increased if infected farms were present within a radius of approximately 4 km and 0.3 km, respectively. We subsequently optimized a surveillance programme that subdivided layer farms into low and high risk groups based on the local farm density with and allowed the sampling frequency to vary between these groups. In this design, the pullet farms were always sampled one week prior to pullet distribution. Our analysis shows that the risk-based surveillance programme is able to keep the between-farm R0 of serovars Enteritidis and Typhimurium below 1 for all pullet and layer farms, while reducing the sampling effort by 32% compared to the currently implemented surveillance programme in Israel. The results of our study therefore indicate that local farm density is an important risk factor for infection of pullet and layer farms by Salmonella Enteritidis and Typhimurium and can be used to improve the performance of surveillance programmes.

DairyCoPilot-Automated data compilation and analysis tools for DairyComp data assets.

Modern dairy farm management requires meaningful data and careful analysis to maximize profitability, cow health, and welfare. Current data platforms, such as DairyComp, lack robust integrated data analysis tools. Producers and consultants need dedicated tools to turn collected data sets into assets for informed decision-making processes. The DairyCoPilot app allows users to rapidly extract health and production data from DairyComp, then compile and analyze the data using a menu-driven point-and-click approach. Prospects for training consultants in applied data analysis skills make DairyCoPilot a tool to identify farm management bottlenecks with less time spent for data analysis, improving cow health, and dairy production. The DairyCoPilot Dashboard R Shiny application is published using RStudio Connect: https://connect.doit.wisc.edu/dairy-copilot/.

An On-Farm Workflow for Predictive Management of Paralytic Shellfish Toxin-Producing Harmful Algal Blooms for the Aquaculture Industry.

Paralytic shellfish toxins (PSTs) produced by marine dinoflagellates significantly impact shellfish industries worldwide. Early detection on-farm and with minimal training would allow additional time for management decisions to minimize economic losses. Here, we describe and test a standardized workflow based on the detection of sxtA4, an initial gene in the biosynthesis of PSTs. The workflow is simple and inexpensive and does not require a specialized laboratory. It consists of (1) water collection and filtration using a custom gravity sampler, (2) buffer selection for sample preservation and cell lysis for DNA, and (3) an assay based on a region of sxtA, DinoDtec lyophilized quantitative polymerase chain reaction (qPCR) assay. Water samples spiked with Alexandrium catenella showed a cell recovery of >90% when compared to light microscopy counts. The performance of the lysis method (90.3% efficient), Longmire's buffer, and the DinoDtec qPCR assay (tested across a range of Alexandrium species (90.7-106.9% efficiency; r2 > 0.99)) was found to be specific, sensitive, and efficient. We tested the application of this workflow weekly from May 2016 to 30th October 2017 to compare the relationship between sxtA4 copies L-1 in seawater and PSTs in mussel tissue (Mytilus galloprovincialis) on-farm and spatially (across multiple sites), effectively demonstrating an ∼2 week early warning of two A. catenella HABs (r = 0.95). Our tool provides an early, accurate, and efficient method for the identification of PST risk in shellfish aquaculture.

Survival of highly related ESBL- and pAmpC- producing Escherichia coli in broiler farms identified before and after cleaning and disinfection using cgMLST.

BACKGROUND: Broiler chickens are frequently colonized with Extended-Spectrum Beta-Lactamase- (ESBL-) and plasmid mediated AmpC Beta-Lactamase- (pAmpC-) producing Enterobacterales, and we are confronted with the potential spread of these resistant bacteria in the food chain, in the environment, and to humans. Research focused on identifying of transmission routes and investigating potential intervention measures against ESBL- and pAmpC- producing bacteria in the broiler production chain. However, few data are available on the effects of cleaning and disinfection (C&D) procedures in broiler stables on ESBL- and pAmpC- producing bacteria. RESULTS: We systematically investigated five broiler stables before and after C&D and identified potential ESBL- and pAmpC- colonization sites after C&D in the broiler stables, including the anteroom and the nearby surrounding environment of the broiler stables. Phenotypically resistant E. coli isolates grown on MacConkey agar with cefotaxime were further analyzed for their beta-lactam resistance genes and phylogenetic groups, as well as the relation of isolates from the investigated stables before and after C&D by whole genome sequencing. Survival of ESBL- and pAmpC- producing E. coli is highly likely at sites where C&D was not performed or where insufficient cleaning was performed prior to disinfection. For the first time, we showed highly related ESBL-/pAmpC- producing E. coli isolates detected before and after C&D in four of five broiler stables examined with cgMLST. Survival of resistant isolates in investigated broiler stables as well as transmission of resistant isolates from broiler stables to the anteroom and surrounding environment and between broiler farms was shown. In addition, enterococci (frequently utilized to detect fecal contamination and for C&D control) can be used as an indicator bacterium for the detection of ESBL-/pAmpC- E. coli after C&D. CONCLUSION: We conclude that C&D can reduce ESBL-/pAmpC- producing E. coli in conventional broiler stables, but complete ESBL- and pAmpC- elimination does not seem to be possible in practice as several factors influence the C&D outcome (e.g. broiler stable condition, ESBL-/pAmpC- status prior to C&D, C&D procedures used, and biosecurity measures on the farm). A multifactorial approach, combining various hygiene- and management measures, is needed to reduce ESBL-/pAmpC- E. coli in broiler farms.

Simultaneous Electrochemical Detection of Cu2+ and Zn2+ in Pig Farm Wastewater.

In recent years, the rapid development of pig farming has led to a large quantity of heavy metal-polluted wastewater. Thus, it was desirable to develop a simple heavy metal detection method for fast monitoring of the wastewater from the pig farms. Therefore, there was an urgent need to develop a simple method for rapidly detecting heavy metal ions in pig farm wastewater. Herein, a simple electrochemical method for simultaneous detection of Cu2+ and Zn2+ was developed and applied to pig farm wastewater. With a glassy carbon electrode and anodic stripping voltammetry, simultaneous detection of Cu2+ and Zn2+ in water was achieved without the need for complicated electrode modification. Furthermore, it was found that the addition of Cd2+ can enhance the response current of the electrode to Zn2+, which increased the signal by eight times. After systematic optimization, the limit of detection (LOD) of 9.3 µg/L for Cu2+ and 45.3 µg/L for Zn2+ was obtained. Finally, it was successfully applied for the quantification of Cu2+ and Zn2+ with high accuracy in pig farm wastewater. This work provided a new and simple solution for fast monitoring of the wastewater from pig farms and demonstrated the potential of electrochemical measurement for application in modern animal husbandry.

Dynamics of microbiota and antimicrobial resistance in on-farm dairy processing plants using metagenomic and culture-dependent approaches.

On-farm dairy processing plants, which are situated close to farms and larger dairy processing facilities, face unique challenges in maintaining environmental hygiene. This can impact various stages of dairy processing. These plants operate on smaller scales and use Low-Temperature-Long-Time (LTLT) pasteurization, making them more susceptible to microbial contamination through direct and indirect contact. Antimicrobial-resistant bacteria found on dairy farms pose risks to human health by potentially transferring resistance via dairy products. Our study aimed to investigate microbial distribution and antimicrobial resistance at four key stages: the farm, pre-pasteurization, post-pasteurization, and processing environments. We assessed microbial distribution by quantifying indicator bacteria and conducting metagenomic analysis. Antimicrobial resistance was examined by identifying resistance phenotypes and detecting resistance genes in bacterial isolates and metagenomes. Our results showed that the indicator bacteria were detected at all stages of on-farm dairy processing. We observed a significant reduction in aerobic microbes and coliforms post-pasteurization. However, contamination of the final dairy products increased, suggesting potential cross-contamination during post-pasteurization. Metagenomic analysis revealed that Pseudomonas, a representative psychrotrophic bacterium, was predominant in both the farm (24.1 %) and pre-pasteurization (65.9 %) stages, indicating microbial transfer from the farms to the processing plants. Post-pasteurization, Pseudomonas and other psychrotrophs like Acinetobacter and Enterobacteriaceae remained dominant. Core microbiota analysis identified 74 genera in total, including 13 psychrotrophic bacteria, across all stages. Of the 59 strains isolated from these plants, 49 were psychrotrophic. Antimicrobial resistance analysis showed that 74.6 % (44/59) of isolates were resistant to at least one antibiotic, with cefoxitin-, ampicillin-, amoxicillin-, and ticarcillin-resistant bacteria present at all stages. Identical antimicrobial resistance patterns were observed in isolates from serial stages of the same farm and season, suggesting bacterial transmission across stages. Additionally, 27.1 % (16/59) of isolates carried plasmid-mediated resistance genes, which were also detected in the metagenomes of non-isolated samples, indicating potential antimicrobial resistance gene transmission and their presence in uncultured bacteria. These findings reveal the persistence of antimicrobial-resistant psychrotrophic bacteria in on-farm dairy processing plants, which pose potential health risks via dairy consumption. Our study underscores the importance of both culture-dependent and culture-independent methods to fully understand their distribution and impact.

Joint environmental and social benefits from diversified agriculture.

Agricultural simplification continues to expand at the expense of more diverse forms of agriculture. This simplification, for example, in the form of intensively managed monocultures, poses a risk to keeping the world within safe and just Earth system boundaries. Here, we estimated how agricultural diversification simultaneously affects social and environmental outcomes. Drawing from 24 studies in 11 countries across 2655 farms, we show how five diversification strategies focusing on livestock, crops, soils, noncrop plantings, and water conservation benefit social (e.g., human well-being, yields, and food security) and environmental (e.g., biodiversity, ecosystem services, and reduced environmental externalities) outcomes. We found that applying multiple diversification strategies creates more positive outcomes than individual management strategies alone. To realize these benefits, well-designed policies are needed to incentivize the adoption of multiple diversification strategies in unison.

Pattern Mining-Based Pig Behavior Analysis for Health and Welfare Monitoring.

The increasing popularity of pigs has prompted farmers to increase pig production to meet the growing demand. However, while the number of pigs is increasing, that of farm workers has been declining, making it challenging to perform various farm tasks, the most important among them being managing the pigs' health and welfare. This study proposes a pattern mining-based pig behavior analysis system to provide visualized information and behavioral patterns, assisting farmers in effectively monitoring and assessing pigs' health and welfare. The system consists of four modules: (1) data acquisition module for collecting pigs video; (2) detection and tracking module for localizing and uniquely identifying pigs, using tracking information to crop pig images; (3) pig behavior recognition module for recognizing pig behaviors from sequences of cropped images; and (4) pig behavior analysis module for providing visualized information and behavioral patterns to effectively help farmers understand and manage pigs. In the second module, we utilize ByteTrack, which comprises YOLOx as the detector and the BYTE algorithm as the tracker, while MnasNet and LSTM serve as appearance features and temporal information extractors in the third module. The experimental results show that the system achieved a multi-object tracking accuracy of 0.971 for tracking and an F1 score of 0.931 for behavior recognition, while also highlighting the effectiveness of visualization and pattern mining in helping farmers comprehend and manage pigs' health and welfare.