Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Dual carbon goal and agriculture in China:Exploring key factors influencing farmers’behavior in adopting low carbon technologies

Identifying the factors influencing farmers’adoption of low-carbon technologies(FA)and understanding their impacts are essential for shaping effective agricultural policies amied at emission reduction and carbon sequestration in China.This study employs a meta-analysis of 122 empirical studies,delves into 23 driving factors affecting FA and addresses the inconsistencies present in the existing literature.We systematically examine the effect size,source of heterogeneity,and time-accumulation effect of the driving factors on FA.We find that significant heterogeneity in the factors influencing FA,except for farming experience,sources of heterogeneity from the survey zone,methodology model,technological attributes,report source,financial support,and the sampling year.Additionally,age,farming experience,and adoption cost negatively correlate with FA.In contrast,educational level,health status,technical training,economic and welfare cognition,land contract,soil quality,terrain,information accessibility,demonstration,government promotion,government regulation,government support,agricultural cooperatives member,peer effect,and agricultural income ratio demonstrate a positive correlation.Especially,demonstration and age show a particularly strong correlation.Finally,the effect of demonstration,age,economic and welfare cognition,farming experience,land contract,soil quality,information accessibility,government promotion,and support,as well as agricultural cooperative membership and peer effects on FA,are generally stable but exhibit varying degrees of attenuation over time.The effect of village cadre,family income,farm scale,gender,health status,technical training,and off-farm work on FA show notable temporal shifts and maintain a weak correlation with FA.This study contributes to shaping China’s current low-carbon agriculture policies across various regions.It encourages policymakers to comprehensively consider the stability of key factors,other potential factors,technological attributes,rural socio-economic context,and their interrelations.

Cholinesterase Activity as an Indicator of Health Risks among Kou Valley Farmers

Introduction: Pesticides are currently an essential component of agricultural production techniques for controlling pests and weeds. In Burkina Faso, non-compliance with good practice in the use of pesticides poses a real health problem for the population. This study examines the health risks associated with pesticide management in rice-growing areas. Material and Methods: A field survey was conducted in Bama, involving farmers, focusing on their socio-demographic characteristics, pesticide usage, and health effects. Cholinesterase levels were measured in subsample of farmers using a portable device. Data were analysed using Microsoft Excel, calculating means and percentages for various practices. Health consultations, protection methods, and pesticide management were studied. Erythrocyte acetylcholinesterase activity was compared before and after treatment. Data were categorised into classes based on inhibition levels, and correlation analyses determined relationships between variables such as age, years of experience, and cholinesterase activity. Results: The results indicate that rice cultivation is mainly carried out by a fairly young population, with nearly 63% being under the age of 50. Common poor practices in pesticide use include improper storage and reuse of leftover pesticides. Seven types of pesticides were identified, including organophosphates such as glyphosate, which was used in 26.7% of cases. This organophosphate has resulted in class B poisoning, causing a 30% - 50% reduction in erythrocyte cholinesterase activity. The health effects of pesticide use are felt by agricultural farmers through various symptoms of poisoning. Conclusion: To reduce the occurrence of pesticide poisoning, it is essential to launch information and awareness campaigns among the population and farmers to promote safe practices in pesticide use in Bama, Burkina Faso.

A micro-crosslinked amphoteric hydrophobic association copolymer as high temperature-and salt-resistance fluid loss reducer for water-based drilling fluids

During ultradeep oil and gas drilling,fluid loss reducers are highly important for water-based drilling fluids,while preparing high temperature-and salt-resistance fluid loss reducers with excellent rheology and filtration performance remains a challenge.Herein,a micro-crosslinked amphoteric hydrophobic association copolymer(i.e.,DADC)was synthesized using N,N-dimethyl acrylamide,diallyl dimethyl ammonium chloride,2-acrylamido-2-methylpropane sulfonic acid,hydrophobic monomer,and pentaerythritol triallyl ether crosslinker.Due to the synergistic effects of hydrogen bonds,electrostatic interaction,hydrophobic association,and micro-crosslinking,the DADC copolymer exhibited outstanding temperature-and salt-resistance.The rheological experiments have shown that the DADC copolymer had excellent shear dilution performance and a certain degree of salt-responsive viscosity-increasing performance.The DADC copolymer could effectively adsorb on the surface of bentonite particles through electrostatic interaction and hydrogen bonds,which bring more negative charge to the bentonite,thus improving the hydration and dispersion of bentonite particles as well as the colloidal stability of the drilling fluids.Moreover,the drilling fluids constructed based on the DADC copolymer exhibited satisfactory rheological and filtration properties(FLHTHP=12 m L)after aging at high temperatures(up to200℃)and high salinity(saturated salt)environments.Therefore,this work provided new insights into designing and fabricating high-performance drilling fluid treatment agents,demonstrating good potential applications in deep and ultradeep drilling engineering.

Local Criteria Used by Farmers to Evaluate the Agronomic Performance and the Fertilizing Capacity of Cowpea Varieties: Diversity, Variability and Proximal Relation with Agronomic Measurements in Contrasted Sahelian Locations

When contributing to participatory research, farmers usually appreciate the performance of cowpea varieties using qualitative scores. The score they attribute to each variety are based on local knowledge. The specific criteria they individually use to attribute a score are not well described. The objectives of this work were to: 1) identify and describe exhaustively the local criteria used by farmers to measure the agronomic performance of cowpea;2) assess the variability and statistical structure of these farmer criteria across local contexts;3) and analyze the association between these farmer criteria and the classical agronomic measurement. To achieve these objectives, an augmented block design was implemented across fifteen locations in the regions of Maradi, Dosso and Tillabéri, representing a diversity of local contexts. From a set of 36 cowpea varieties, fifteen varieties were sown per location, including five varieties (controls) common to all locations. In each location, two replicates were sown in randomized Fisher’s blocks. After agronomic measurement and participatory evaluation (scoring of varieties by farmers), a group survey (focus group) was conducted in each location to identify the criteria considered by farmers to found their discretional scoring of varieties during the participatory evaluation. The analysis of the data identified, across locations, thirteen criteria defined by farmers to characterize the agronomic performance of cowpea. Some of these criteria were different according to location. Farmers ranked the three varieties with the best performance for each agronomical trait (Top 3 varieties). A comparison of the farmer ranking with the ranking based on agronomic measurements revealed similarity and complementary between both methods. This study highlighted the importance of considering both local and scientific knowledge in local varietal evaluations.

Distribution and dynamics of niche and interspecific association of dominant phytoplankton species in the Feiyun River basin,Zhejiang,China

To investigate the dominant species and interspecific association in the phytoplankton community of the Feiyun River basin in Zhejiang Province,East China,the main stream and the Shanxi Zhaoshandu Reservoir in the downstream were chosen as the study area,for which 22 sampling sites were designated.Sampling was conducted in September 2021,January,May,and July 2022.Phytoplankton species were identified from both quantitative samples and in-vivo observations.Phytoplankton was quantified by direct counting.Results show that there were 98 species belonging to 6 phyla and 78 genera.In addition,to clarify the niches of the dominant phytoplankton species and their interspecific association,the dominance index was calculated,and a comprehensive analysis was conducted including niche width,niche overlap value,ecological response rate,overall association,chi-square test,and the stability.The phytoplankton community exhibited characteristics of a Cyanobacteria-Chlorophyta-Diatom type community,showing higher diversity in spring and lower diversity in summer.Among 11 dominants phytoplankton species from 3 phyla,both frequency and dominance degree varied seasonally,of which Microcystis sp.was the dominant species in Spring,Autumn,and Winter.The niche widths of the dominant species ranged from 0.234 to 0.933,and were categorized into three groups.The niche overlap values of the 11 dominant species ranged from 0.359 to 0.959,exhibiting significant seasonal differences-highest in winter followed by autumn,spring,and summer in turn.The overall correlation among dominant species in all four seasons revealed a non-significant negative association,resulting in an unstable community structure.A significant portion(84.2%)of species pairs displayed positive associations,suggesting a successional pattern where Diatoms dominated while other dominant species shared resources and space.Despite this pattern,stability measurements indicated that the dominant species community remained unstable.Therefore,careful monitoring is recommended for potential water environment issues arising from abnormal proliferation of dominant species in the watershed during winter.This research built a theoretical foundation with a data support to the early warning of eutrophication and provided a reference for water resources management in similar watersheds along the eastern coast of China.

Strengthening Active Aging through Older People’s Association and Economic Activity of the Older People in Nepal

Aging is a natural lifelong process ending in death. Many older people are living in poverty. Older people are generally considered dependent on others as they grow older. The purpose of this article is to explore the entrepreneurship activities of Nepalese older adults. Data for this study were collected from the project Help Age International (HAI) implemented in Nepal. Qualitative data observations and interviews were used to collect data. The findings of this study show the formation of the Older People’s Association (OPA) has supported many older people to participate outside the home in various social activities. Moreover, regular deposits through OPAs offer little help. OPAs support older people in their need of financial support to implement minor entrepreneurship. Older people who received support were pleased and were actively involved in their activities and also regularly deposited money in them. Subsequently, older people’s participation in social activities has increased and also helped to lower elderly abuse, loneliness, and depression. Local governments should promote such activities which will help with healthy aging.

THAPE: A Tunable Hybrid Associative Predictive Engine Approach for Enhancing Rule Interpretability in Association Rule Learning for the Retail Sector

Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.

Epistasis-aware genome-wide association studies provide insights into the efficient breeding of high-yield and high-quality rice

Marker-assisted selection(MAS)and genomic selection(GS)breeding have greatly improved the efficiency of rice breeding.Due to the influences of epistasis and gene pleiotropy,ensuring the actual breeding effect of MAS and GS is still a difficult challenge to overcome.In this study,113 indica rice varieties(V)and their 565 testcross hybrids(TC)were used as the materials to investigate the genetic basis of 12 quality traits and nine agronomic traits.The original traits and general combining ability of the parents,as well as the original traits and midparent heterosis of TC,were subjected to genome-wide association analysis.In total,381 primary significantly associated loci(SAL)and 1,759 secondary SALs that had epistatic interactions with these primary SALs were detected.Among these loci,322 candidate genes located within or nearby the SALs were screened,204 of which were cloned genes.A total of 39 MAS molecular modules that are beneficial for trait improvement were identified by pyramiding the superior haplotypes of candidate genes and desirable epistatic alleles of the secondary SALs.All the SALs were used to construct genetic networks,in which 91 pleiotropic loci were investigated.Additionally,we estimated the accuracy of genomic prediction in the parent V and TC by incorporating either no SALs,primary SALs,secondary SALs or epistatic effect SALs as covariates.Although the prediction accuracies of the four models were generally not significantly different in the TC dataset,the incorporation of primary SALs,secondary SALs,and epistatic effect SALs significantly improved the prediction accuracies of 5(26%),3(16%),and 11(58%)traits in the V dataset,respectively.These results suggested that SALs and epistatic effect SALs identified based on an additive genotype can provide considerable predictive power for the parental lines.They also provide insights into the genetic basis of complex traits and valuable information for molecular breeding in rice.

Demography and Socio-Economic Aspects on Irrigated Smallholder Agricultural Enterprises and Their Association with the Cultivation of Maize (Zea mays L.) as a Selected Field Crop

The purpose of this study is to correlate demography and socio-economic aspects at Irrigated Smallholder Agricultural Enterprises and their association with the Cultivation of Maize in order to determine its positive impacts at irrigated smallholders’ agricultural entrepreneurs’ household. Chi-square test was used as descriptive analysis method. The Fischer Exact tests were employed to test demography (gender, age, education, and income) in winter and summer production season of irrigated smallholder agricultural enterprises and their association with the cultivation of selected field crop (i.e. maize). The results show that gender results were not being statistically significant, as measured by the Phi measure of effect size, φ = 0.149, p = 0.011, and φ = 0.05, p = 0.392 in summer. As far as age is concern, it appears to be a statistically significant association between cultivating maize and age in winter, φ = 0.046, p = 0.730 in winter and φ = 0.172, p = 0.013. Education winter result not being statistically significant, the effect size showed a weak association, as measured by the Phi measure of effect size, φ = 0.112, p = 0.305 and φ = 0.035, p = 0.948 in summer. Income result not being statistically significant, as measured by the Phi measure of effect size, φ = 0.049, p = 0.399 and φ = 0.081, p = 0.166 in summer. In conclusion, the study shows that the development of best management practices must be based on a comprehensive analysis of the livelihoods and irrigated smallholder agricultural enterprise farming styles of participating irrigated smallholder agricultural entrepreneurs.

Association between Placental Malaria and Severe Pre-Eclampsia in Two University Hospitals of Yaounde City

Context: Pre-eclampsia and placental malaria, are two diseases that share pathophysiological similarities, such as placental ischemia, endothelial dysfunction and production of pro-inflammatory cytokines. Objective: The objective of our study was to investigate the association between placental malaria lesions and severe pre-eclampsia. Methodology: We conducted a prospective analytical cross-sectional study in two University Hospitals in the city of Yaounde (Yaounde Central Hospital and the Gynaecological Obstetrics and Paediatrics Hospital), and in the laboratory of the Centre Pasteur in Yaounde over an eight-month period (1st January 2021 – 1st September 2021). All patients with pre-eclampsia diagnosed according to the criteria of the International Society for the Study of Hypertension (ISSHP) and free of chronic metabolic or infectious pathology were included in this study. The patients were divided into two groups: group 1 (mild pre-eclampsia) and group 2: severe pre-eclampsia. Socio-demographic, clinical and histopathological characteristics specific to pre-eclampsia and placental malaria were investigated. Statistical analysis was performed with SPSS 23.0 software, Chi 2 was used to compare categorical variables, Student t-test was used to compare means, and logistic regression was used to assess the association between placental malaria lesions and PES. Results: The mean age of our study population was 29.93 ± 7.36 years versus 28.28 ± 7.18 years in patients with mild and severe pre-eclampsia respectively. Pre-eclampsia placental lesions (accelerated villous maturation, infarction) were significantly greater in patients with severe pre-eclampsia (p Conclusion: Placental malaria lesions were significantly associated with severe pre-eclampsia and increased the risk of developing severe pre-eclampsia placental lesions by a factor of 10.

Leveraging the potential of big genomic and phenotypic data for genome-wide association mapping in wheat

Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on Central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.Contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.

Navigating Market Choices: Understanding Carrot Market Outlet Selection among Smallholder Farmers in Kenya

This research delves into the hurdles and strategies aimed at augmenting the market involvement of smallholder carrot farmers in Nakuru County, Kenya. Employing a Multinomial Logit (MNL) model, it scrutinizes the factors influencing the selection of marketing outlets among carrot farmers. The findings unveil that a significant majority (81%) of surveyed farmers actively participate in diverse market outlets, encompassing the farm gate, cleaning point, local market, external market, and export market. Notably, pivotal buyers include aggregators, brokers, wholesalers, retailers, and consumers, with transactions predominantly occurring at the farm level. Additionally, the analysis discerns substantial influences of socio-economic characteristics, experiential factors, and geographical proximity on farmers’ choices of market outlets. Specifically, gender, age, land size, farming experience, and distance to markets emerge as critical determinants. Moreover, the study delves into the examination of market margins along the carrot value chain, shedding light on the potential profitability of carrot farming in the region. Remarkably, higher average gross margins are identified in export and external markets, signaling lucrative prospects for farmers targeting these segments. However, disparities in profit distribution between farmers and traders underscore the necessity for interventions to ensure equitable value distribution throughout the value chain. These findings underscore the imperative for tailored interventions to tackle challenges and foster inclusive agricultural development. Strategies such as farmer organizations, contracting, and vertical integration are advocated to enhance market access and profitability for smallholder carrot farmers. Thus, this study enriches our comprehension of the dynamics within carrot value chains and provides valuable insights for policymakers and development practitioners aiming to uplift rural livelihoods and bolster food security.

Climatic and non-climatic factors driving the livelihood vulnerability of smallholder farmers in Ahafo Ano North District,Ghana

Smallholder farmers in Ahafo Ano North District,Ghana,face multiple climatic and non-climatic issues.This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions(FGDs)with 10 respondents.The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022.The relative importance index(RII)value was used to rank the climatic and non-climatic factors perceived by respondents.The socioeconomic characteristics affecting smallholder farmers’perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model.Results showed that mean annual rainfall decreased(P>0.05)but mean annual temperature significantly increased(P<0.05)from 2002 to 2022 in the district.The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature(RII=0.498),erratic rainfall(RII=0.485),and increased windstorms(RII=0.475).The critical non-climatic factors were high cost of farm inputs(RII=0.485),high cost of healthcare(RII=0.435),and poor condition of roads to farms(RII=0.415).Smallholder farmers’perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics(P<0.05).This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors.Therefore,to enhance the resilience of smallholder farmers to climate change,it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.

Tree mycorrhizal associations determine how biodiversity,large trees,and environmental factors drive aboveground carbon stock in temperate forests

Biodiversity,large trees,and environmental conditions such as climate and soil have important effects on forest carbon stocks.However,recent studies in temperate forests suggest that the relative importance of these factors depends on tree mycorrhizal associations,whereby large-tree effects may be driven by ectomycorrhizal(EM)trees,diversity effects may be driven by arbuscular mycorrhizal(AM)trees,and environment effects may depend on differential climate and soil preferences of AM and EM trees.To test this hypothesis,we used forest-inventory data consisting of over 80,000 trees from 631 temperate-forest plots(30 m×30 m)across Northeast China to examine how biodiversity(species diversity and ecological uniqueness),large trees(top 1%of tree diameters),and environmental factors(climate and soil nutrients)differently regulate aboveground carbon stocks of AM trees,EM trees,and AM and EM trees combined(i.e.total aboveground carbon stock).We found that large trees had a positive effect on both AM and EM tree carbon stocks.However,biodiversity and environmental factors had opposite effects on AM vs.EM tree carbon stocks.Specifically,the two components of biodiversity had positive effects on AM tree carbon stocks,but negative effects on EM tree carbon stocks.Environmental heterogeneity(mean annual temperature and soil nutrients)also exhibited contrasting effects on AM and EM tree carbon stocks.Consequently,for the total carbon stock,the positive large-tree effect far surpasses the diversity and environment effect.This is mainly because when integrating AM and EM tree carbon stock into total carbon stock,the opposite diversity-effect(also environment-effect)on AM vs.EM tree carbon stock counteracts each other while the consistent positive large-tree effect on AM and EM tree carbon stock is amplified.In summary,this study emphasized a mycorrhizal viewpoint to better understand the determinants of overarching aboveground carbon profile across regional forests.

Genome-Wide Association Study of Cooked Rice Textural Attributes and Starch Physicochemical Properties in indica Rice

Rice cooking and eating qualities(CEQ)are mainly determined by cooked rice textural parameters and starch physicochemical properties.However,the genetic bases of grain texture and starch properties in rice have not been fully understood.We conducted a genome-wide association study for apparent amylose content(AAC),starch pasting viscosities,and cooked rice textural parameters using 279 indica rice accessions from the 3000 Rice Genome Project.We identified 26 QTLs in the whole population and detected single nucleotide polymorphisms(SNPs)with the lowest P-value at the Waxy(Wx)locus for all traits except pasting temperature and cohesiveness.Additionally,we detected significant SNPs at the SUBSTANDARD STARCH GRAIN6(SSG6)locus for AAC,setback(SB),hardness,adhesiveness,chewiness(CHEW),gumminess(GUM),and resilience.We subsequently divided the population using a SNP adjacent to the Waxy locus,and identified 23 QTLs and 12 QTLs in two sub-panels,WxT and WxA,respectively.In these sub-panels,SSG6 was also identified to be associated with pasting parameters,including peak viscosity,hot paste viscosity,cold paste viscosity,and consistency viscosity.Furthermore,a candidate gene encoding monosaccharide transporter 5(OsMST5)was identified to be associated with AAC,breakdown,SB,CHEW,and GUM.In total,39 QTLs were co-localized with known genes or previously reported QTLs.These identified genes and QTLs provide valuable information for genetic manipulation to improve rice CEQ.

Genome-wide association study of seedling nitrogen-use efficiency-associated traits in common wheat(Triticum aestivum L.)

Nitrogen(N)fertilizer application is essential for crop-plant growth and development.Identifying genetic loci associated with N-use efficiency(NUE)could increase wheat yields and reduce environmental pollution caused by overfertilization.We subjected a panel of 389 wheat accessions to N and chlorate(a nitrate analog)treatments to identify quantitative trait loci(QTL)controlling NUE-associated traits at the wheat seedling stage.Genotyping the panel with a 660K single-nucleotide polymorphism(SNP)array,we identified 397 SNPs associated with N-sensitivity index and chlorate inhibition rate.These SNPs were merged into 49 QTL,of which eight were multi-environment stable QTL and 27 were located near previously reported QTL.A set of 135 candidate genes near the 49 QTL included TaBOX(F-box family protein)and TaERF(ethylene-responsive transcription factor).A Tabox mutant was more sensitive to low-N stress than the wild-type plant.We developed two functional markers for Hap 1,the favorable allele of TaBOX.

Researching the Impact of the Quality of Village Governance on Farmers’Well-Being:From the Perspectives of Income and Occupational Differentiation

The goal of village governance is to improve the well-being of farmers,so this study aims to measure the impact the quality of village governance on the well-being of farmers.It also examines the heterogeneity of this impact across different farmer groups from the perspectives of income levels and occupational differentiation.To this end,this study developed an indicator system based on survey data collected from 1,442 farmers in the Sichuan,Shaanxi,and Gansu provinces,as well as the Ningxia Hui autonomous region.Multiple linear regression models were then used to analyze this data,and the findings revealed that improvements in the quality of village governance significantly increased the well-being of farmers.Specifically,primary-level empowerment and capacity building were shown to contribute the most to the enhancement of the farmers’well-being,followed by social inclusion,and social cohesion was found to have only a minimal effect.In terms of income levels,improving the quality of village governance benefited middle-income farmers the most,followed by low-income farmers,and it had the least effect on high-income farmers.In terms of occupations,full-time farmers gained the most from improvements in the quality of village governance,followed by off-farm farmers,with part-time farmers benefiting the least.Based on these findings,this study suggests that policymakers should improve the quality of village governance to enhance the well-being of farmers,focusing on the impact that level of income and occupational differentiation have on village governance.

Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

Casual associations between blood metabolites and colon cancer

BACKGROUND Limited knowledge exists regarding the casual associations linking blood metabolites and the risk of developing colorectal cancer.AIM To investigate causal associations between blood metabolites and colon cancer.METHODS The study utilized a two-sample Mendelian randomization(MR)analysis to investigate the causal impact of 486 blood metabolites on colorectal cancer.The primary method of analysis used was the inverse variance weighted model.To further validate the results several sensitivity analyses were performed,including Cochran's Q test,MR-Egger intercept test,and MR robust adjusted profile score.These additional analyses were conducted to ensure the reliability and robustness of the findings.RESULTS After rigorous selection for genetic variation,486 blood metabolites were included in the MR analysis.We found Mannose[odds ratio(OR)=2.09(1.10-3.97),P=0.024],N-acetylglycine[OR=3.14(1.78-5.53),P=7.54×10^(-8)],X-11593-O-methylascorbate[OR=1.68(1.04-2.72),P=0.034],1-arachidonoylglycerophosphocholine[OR=4.23(2.51-7.12),P=6.35×10^(-8)]and 1-arachidonoylglycerophosphoethanolamine 4[OR=3.99(1.17-13.54),P=0.027]were positively causally associated with colorectal cancer,and we also found a negative causal relationship between Tyrosine[OR=0.08(0.01-0.63),P=0.014],Urate[OR=0.25(0.10-0.62),P=0.003],N-acetylglycine[0.73(0.54-0.98),P=0.033],X-12092[OR=0.89(0.81-0.99),P=0.028],Succinylcarnitine[OR=0.48(0.27-0.84),P=0.09]with colorectal cancer.A series of sensitivity analyses were performed to confirm the rigidity of the results.CONCLUSION This study showed a causal relationship between 10 blood metabolites and colorectal cancer,of which 5 blood metabolites were found to be causal for the development of colorectal cancer and were confirmed as risk factors.The other five blood metabolites are protective factors.