A study on the influencing factors of rural land transfer willingness in different terrain areas--Based on the questionnaire survey data of Anhui Province and Qinghai Province, China.

This study delves into the factors influencing the willingness of rural land transfers in different terrain areas, aiming to promote the improvement of land transfer institutions and accelerate the process of scale farming. Based on rural survey data from Anhui and Qinghai provinces in China, this research uses geographical detector and Binary Logistic Model to explore the differential factors affecting the willingness of farmers to participate in land contract transfer in the first and third terrain areas of China. The study examines four dimensions, including individual characteristics, family endowments, social support strategies, and geographical environment. The findings reveal the following: (1) By comparing the mean values, standard deviations, and coefficients of variation of the data from both provinces, it is evident that the indicators of individual characteristics, family endowments, social support strategies, and geographical environment differ significantly between the two provinces. This indicates substantial disparities in the basic attributes of farmers and their living environments. (2) The single-factor explanatory power significantly influencing farmers' willingness to engage in land transfer varies considerably and is statistically significant at the 1% level. The types of interaction between two factors mainly include dual-factor enhancement, nonlinear enhancement, single-factor nonlinear attenuation, and nonlinear attenuation. (3) There are commonalities and differences in the factors that significantly influence farmers' willingness to participate in land transfer in the two provinces. Common factors influencing farmers' land transfer willingness in both provinces include: the educational level of household heads, the health status of household heads, the number of family laborers, the arable land area, the differentiation of agricultural management objectives, the proportion of agricultural operating income, labor service economy, and relocation policies. Factors showing different influences include: the age of household heads, school-age children, the number of family members engaged in different occupations, the proportion of income from off-farm employment, minimum guarantee policies credit support, location distance, and terrain undulation. Therefore, in formulating land transfer policies, the government should prioritize significant driving factors influencing farmers' decision-making behavior in different regions. It is essential to develop and implement land transfer policies tailored to local conditions with the primary goal of safeguarding the rights and interests of the principal stakeholders, thus achieving sustainable land utilization.

How plant composition in margins influences the assemblage of pests and predators and its effect on biocontrol in melon fields.

Many agricultural landscapes offer few resources for maintaining natural enemy populations and floral plantings have frequently been adopted to enhance biological pest control in crops. However, restored margins may harbour both pests and natural enemies. The aim was to compare the abundance of pests and natural enemies in three types of margins (unmanaged, sown herbaceous floral strips and shrubby hedgerows) as well as in adjacent melon fields. Besides, yield was compared among melon fields as way of testing the effect of the type of margin on biocontrol. The research was carried out during 2 years in twelve melon fields from four different locations in southern Spain. Arthropods were sampled periodically in margins and melon fields by visual inspections and Berlese extraction. Hedgerow and floral strips hosted higher numbers of both pests and predators than unmanaged margins. Besides, hedgerows had a similar or higher number of natural enemies than floral strips but lower number of pests. In just a few occasions, the type of margin had a significant effect on the abundance of pests and natural enemies in melon fields, but rarely there was consistency between the two growing seasons. No differences were found in yield. We hypothesised that the lack of association in the abundances of pests and natural enemies between margins and melon fields could be attributed to the overriding effects of the landscape and/or the internal population dynamics of arthropods in melon fields. Overall, shrubby hedgerows are more recommended than herbaceous floral strips.

Soil organic matter and total nitrogen as key driving factors promoting the assessment of acid-base buffering characteristics in a tea (Camellia sinensis) plantation habitat.

The issue of soil acidification in tea plantations has become a critical concern due to its potential impact on tea quality and plant health. Understanding the factors contributing to soil acidification is essential for implementing effective soil management strategies in tea-growing regions. In this study, a field study was conducted to investigate the effects of tea plantations on soil acidification and the associated acid-base buffering capacity (pHBC). We assessed acidification, pHBC, nutrient concentrations, and cation contents in the top 0-20 cm layer of soil across forty tea gardens of varying stand ages (0-5, 5-10, 10-20, and 20-40 years old) in Anji County, Zhejiang Province, China. The results revealed evident soil acidification due to tea plantation activities, with the lowest soil pH observed in tea gardens aged 10-20 and 20-40 years. Higher levels of soil organic matter (SOM), total nitrogen (TN), Olsen phosphorus (Olsen-P), available iron (Fe), and exchangeable hydrogen (H+) were notably recorded in 10-20 and 20-40 years old tea garden soils, suggesting an increased risk of soil acidification with prolonged tea cultivation. Furthermore, prolonged tea cultivation correlated with increased pHBC, which amplified with tea stand ages. The investigation of the relationship between soil pHBC and various parameters highlighted significant influences from soil pH, SOM, cation exchange capacity, TN, available potassium, Olsen-P, exchangeable acids (including H+ and aluminum), available Fe, and available zinc. Consequently, these findings underscore a substantial risk of soil acidification in tea gardens within the monitored region, with SOM and TN content being key driving factors influencing pHBC.

Farming and the risk of developing osteoarthritis in Alberta, Canada.

INTRODUCTION: Because farming is a physically demanding occupation, farmers may be susceptible to developing osteoarthritis (OA). The aim of this study was to determine the risk of developing OA in Canadian farm, non-farm rural and urban residents. METHODS: A retrospective cohort study of five Alberta health administrative databases examined the risk of developing OA among three groups: farm (n=143 431), non-farm rural (n=143 431) and urban (n=143 431) residents over the fiscal years 2000-2001 through 2020-2021. The algorithm for OA ascertainment defined cases based on criteria including one hospital admission, two physician visits within a 2-year interval, or two ambulatory care visits within 2 years. Incidence rates, lifetime risk, and mortality rates were calculated. Cox proportional hazard models compared the incidence of OA for the three groups over the 21 years. RESULTS: A total of 26 957 OA cases were identified among 1 706 256 person-years (PYs) in the farm cohort. The crude incidence rate of OA over a period of 21 years ranged from 19.1 (95% confidence interval (CI) 18.6-19.6) per 1000 PYs in 2001 to 10.0 (95% CI 9.6-10.5) per 1000 PYs in 2021. The overall incidence rate was higher in the farm group (15.8 (95%CI 15.6-16.0) per 1000 PYs) as compared to the non-farm rural (14.7 (95%CI 14.5-14.9) per 1000 PYs) and the urban groups (13.3 (95%CI 13.1-13.4) per 1000 PYs). After adjusting for age and sex, the farm (6%; 95%CI 4-8%), and non-farm rural (9%; 95%CI 7-12%) groups had higher incidence rates than the urban group. The unadjusted non-injury mortality rate for the farm group with OA was lower (13.2 (95%CI 12.9-13.5) per 1000 PYs) than both the urban (14.5; 95%CI 14.1-14.8) and rural (18.0; 95%CI 17.6-18.4) groups. After adjusting for mortality, the lifetime risk of developing OA was 27.7% for farm residents, 25.6% for the non-farm rural cohort, and 24.0% for the urban cohort. CONCLUSION: When accounting for age and sex, farm and non-farm rural residents have a higher risk of developing OA as compared to the urban population. The higher mortality-adjusted lifetime risk of developing OA among farm residents highlights the necessity of specific interventions aimed at reducing the impact of this condition in rural communities. Further research is required to identify specific occupational and lifestyle risk factors associated with OA among farmers and to develop effective strategies for prevention and management.

Public healthcare disparities in Africa: the food production systems and its dichotomy in a South African context.

One of the major concerns of development in Africa is the issue of public health. In Africa, public healthcare has been and still is a problem most African countries are faced with. The problem of public healthcare seems to be unabated even though there are measures that are put in place for its effectiveness. There is hunger, malnutrition, high mortality rate, illnesses and deterioration of life expectancy in most developing countries of Africa. The dramatic unprecedented public health disparity has become a scourge in developing countries where it has purportedly impaired the developmental efforts, economic growth and prosperity. As a result, there is a need to scrutinize possible causes that exacerbates public health issues in developing countries. The paper argues that the current food production system (conventional) contributes to current status of public health as compared to the previous food production system (organic). The purpose of this paper is to conceptualize public healthcare disparities, juxtaposing organic and conventional food production that result as human food consumption. The paper employs literature-based analysis as a methodology to assemble data in respect of public healthcare disparities and food production systems.

Impact of biological manure substitution on grain yield, nitrogen recovery efficiency, and soil biochemical properties.

Fertilization plays a crucial role in ensuring global food security and ecological balance. This study investigated the impact of substituting innovative biological manure for chemical fertilization on rice (Oryza sativa L) productivity and soil biochemical properties based on a three-year experiment. Our results suggested rice yield and straw weight were increased under manure addition treatment. Specifically, 70% of total nitrogen (N) fertilizer substituted by biological manure derived from straw, animal waste and microbiome, led to a substantial 13.6% increase in rice yield and a remarkable 34.2% boost in straw weight. In comparison to the conventional local farmer practice of applying 165 kg N ha-1, adopting 70% of total N plus biological manure demonstrated superior outcomes, particularly in enhancing yield components and spike morphology. Fertilization treatments led to elevated levels of soil microbial biomass carbon and N. However, a nuanced comparison with local practices indicated that applying biological manure alongside urea resulted in a slight reduction in N content in vegetative and economic organs, along with decreases of 10.4%, 11.2%, and 6.1% in N recovery efficiency (NRE), respectively. Prudent N management through the judicious application of partial biological manure fertilizer in rice systems could be imperative for sustaining productivity and soil fertility in southern China.

Influence of maize genotypes and harvest stages on in-silo fermentation quality and nutritional value of corn silage during hot summer condition of the tropics.

The aim of the experiment was to evaluate the potential of promising summer maize genotypes and optimal stage of harvesting these genotypes for ensiling in terms of dry matter (DM), starch, and crude protein (CP) yields, silage fermentation quality, nutrients profile, total digestible nutrients, metabolizable energy (ME) content, Cornell Net Carbohydrate and Protein System (CNCPS) carbohydrate (CHO) subfractions composition, in vitro DM digestibility (DMD) and in situ starch degradation characteristics. Six maize genotypes were chosen for the study: DK9108 from Monsanto, P30Y87, P3939 from Pioneer, QPM-300 (quality protein maize) and W94 from the International Maize and Wheat Improvement Center (CIMMYT), and a local cultivar, Afgoii, from the Cereal Research Institute (Persabaq, KP). A total of 72 plots (8 m × 10 m) were blocked in three replicate fields, and within each field, each genotype was sown in four replicate plots according to a randomized complete block design. For the data analysis, the Proc-Mixed procedure of Statistical Analysis System with repeated measure analysis of variance was used. The DM yield was strongly influenced (P < 0.001) by maize genotypes, varying from 12.6 to 17.0 tons/ha. Except for total CHO and ammonia nitrogen (NH3-N), the contents of all measured chemical components varied (P < 0.001) among the genotypes. Further comparison revealed that, genotype P3939 had a higher (P < 0.05) content of CP (7.27 vs. 6.92%), starch (36.7 vs. 27.9%), DMD (65.4 vs. 60.0%), ME (2.51 vs. 2.30 Mcal/kg) and lactic acid (5.32 vs. 4.83%) and lowest content of NDF (37.3 vs. 43.1%), pH (3.7 vs. 4.10) compared to the local cultivar (Afgoii). Advancement of post-flowering maturity from 25 to 35% DM (23 to 41 days after flowering (DAF)) increased (P < 0.05) the DM yield (10.4 to 17.8 tons/ha), starch content (29.1 to 35.0%), DMD (65.3 to 67.3%) and ME (2.34 to 2.47 Mcal/kg), and decreased (P < 0.001) the contents of CP (7.42-6.73%), NDF (48.8-38.5%), pH (4.10 to 3.60), NH3-N (8.93-7.80%N) and effective degradability of starch (95.4 to 89.4). Results showed that for higher yields and silage nutritional and fermentation quality, maize crops should be harvested at whole crop DM content of 30-35% (34 to 41 DAF). It was further concluded that genotype P3939 is the most suitable summer maize genotype for silage production in terms of yields and silage nutritional and fermentation quality under the hot environmental conditions of the tropics.

Production and optimization of surfactin produced from locally isolated Bacillus halotolerans grown on agro-industrial wastes and its antimicrobial efficiency.

INTRODUCTION: Optimal exploitation of the huge amounts of agro-industrial residuals that are produced annually, which endangers the ecosystem and ultimately contributes to climate change, is one of the solutions available to produce value-added compounds. AIM AND OBJECTIVES: This study aimed at the economic production and optimization of surfactin. Therefore, the production was carried out by the microbial conversion of Potato Peel Waste (PPW) and Frying Oil Waste (FOW) utilizing locally isolated Bacillus halotolerans. Also, investigating its potential application as an antimicrobial agent towards some pathogenic strains. RESULTS: Screening the bacterial isolates for surfactin production revealed that the strain with the highest yield (49 g/100 g substrate) and efficient oil displacement activity was genetically identified as B. halotolerans. The production process was then optimized utilizing Central Composite Design (CCD) resulting in the amelioration of yield by 11.4% (from 49 to 55.3 g/100 g substrate) and surface tension (ST) by 8.3% (from 36 to 33 mN/m) with a constant level of the critical micelle concentration (CMC) at 125 mg/L. Moreover, the physiochemical characterization studies of the produced surfactin by FTIR, 1H NMR, and LC-MS/MS proved the existence of a cyclic lipopeptide (surfactin). The investigations further showed a strong emulsification affinity for soybean and motor oil (E24 = 50%), as well as the ability to maintain the emulsion stable over a wide pH (4-10) and temperature (10-100 °C) range. Interestingly, surfactin had a broad-spectrum range of inhibition activity against Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa, klebsiella pneumonia, and Candida albicans. CONCLUSION: Subsequently, the screening of the isolates and the utilized food-processing wastes along with the extraction technique resulted in a high yield of surfactin characterized by acceptable ST and CMC levels. However, optimization of the cultural conditions to improve the activity and productivity was achieved using Factor-At-A-Time (OFAT) and Central Composite Design (CCD). In contrast, surface activity recorded a maximum level of (33 mN/n) and productivity of 55.3 g/100 g substrate. The optimized surfactin had also the ability to maintain the stability of emulsions over a wide range of pH and temperature. Otherwise, the obtained results proved the promising efficiency of the surfactin against bacterial and fungal pathogens.

AgEvidence: a dataset to explore agro-ecological effects of conservation agriculture.

Conservation agriculture (CA) is a set of principles thought to be able to enhance crop productivity while minimizing impacts on the environment. The evidence base for CA can be challenging to synthesize because it encompasses many different practices and social and agroecological outcomes. To facilitate synthesis of CA evidence we have created a dataset organizing 218 response variables from five common categories of CA: cover crops, tillage management, pest management, nutrient management, and crop diversification. These data cover the Midwestern United States (U.S.) from 1980-2020. The dataset is also summarized and visualized on the AgEvidence website, which enables users to interactively explore, filter, and download data. We hope this dataset will help a wide variety of stakeholders, including researchers, policy makers, advocacy groups, and growers access the evidence needed to make informed and impactful decisions about how to produce food with less negative environmental impact.

Agricultural waste-based modified biochars differentially affected the soil properties, growth, and nutrient accumulation by maize (Zea mays L.) plants.

Biochar (BC) is an organic compound formed by the pyrolysis of organic wastes. Application of BCs as soil amendments has many benefits including carbon sequestration, enhanced soil fertility and sustainable agriculture production. In the present study, we acidified the different BCs prepared from rice straw, rice husk, wheat straw, cotton stalk, poultry manure, sugarcane press mud and vegetable waste; following which, we applied them in a series of pot experiments. Comparisons were made between acidified and non- acidified BCs for their effects on seed germination, soil properties (EC, pH) nutrient contents (P, K, Na) and organic matter. The treatments comprised of a control, and all above-described BCs (acidified as well as non-acidified) applied to soil at the rate of 1% (w/w). The maize crop was selected as a test crop. The results showed that acidified poultry manure BC significantly improved germination percentage, shoot length, and biomass of maize seedlings as compared to other BCs and their respective control plants. However, acidified BCs caused a significant decrease in nutrient contents (P, K, Na) of soil,maize seedlings, and the soil organic matter contents as compared to non- acidified BCs. But when compared with control treatments, all BCs treatments (acidified and non-acidified) delivered higher levels of nutrients and organic matter contents. It was concluded that none of the BCs (acidified and non-acidified) had caused negative effect on soil conditions and growth of maize. In addition, the acidification of BC prior to its application to alkaline soils might had altered soil chemistry and delivered better maize growth. Moving forward, more research is needed to understand the long-term effects of modified BCs on nutrient dynamics in different soils. In addition, the possible effects of BC application timings, application rates, particle size, and crop species have to be evaluated systemtically.

Key factors affecting NH3-N in the Huaihe River Basin due to human activities.

Human activity factors have a significant impact on changes in ammonia nitrogen (NH3-N) content in rivers. Existing research mainly focuses on human activity factors as type factors, and lacks research on the key factors affecting river NH3-N among human activity factors. Therefore, this paper aims to study the key factors affecting human activities on NH3-N in the Huaihe River through various statistical analysis methods. The study found that changes in NH3-N content in the Huaihe River are mainly affected by land use patterns in the basin. There are two different ways in which land use affects NH3-N in rivers: direct effects and indirect effects. We also studied the main pathways through which changes in key factors in human activities affect NH3-N in the Huaihe River by constructing a structural equation model. The results showed that crop sowing area and afforestation area have a significant direct effect on NH3-N in the Huaihe River. In addition, crop sowing area and afforestation area can also affect river NH3-N by regulating the amount of nitrogen fertilizer and human excrement. This study is of great significance for understanding how human activities regulate NH3-N content in rivers.

Estimation of rice yield using multivariate analysis techniques based on meteorological parameters.

This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980-81 to 2020-21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices.

Revealing the spatiotemporal evolution pattern and convergence law of agricultural land transfer in China.

The transfer of land plays a crucial role in revitalizing land resources, acting as a catalyst for promoting the high-quality development of agriculture. The land transfer ratio is a crucial metric for assessing the progress of rural land transfer and the effective allocation of rural land resources. Thus, this study examines the rural land transfer ratio across 30 provinces in China from 2005 to 2020. The study explores the distribution characteristics of the ratio using the rank-size rule and trend surface analysis. The LISA space-time transition method is employed to analyze the spatial and temporal dynamics of the rural land transfer ratio and examine its convergence. The study aims to comprehensively analyze the spatial distribution characteristics and evolutionary patterns of rural land transfer in China, illustrating the convergence and influencing factors during the development process. The results indicate that: (1) The rural land transfer ratio in China is generally increasing, with a spatial pattern showing an upward trend from west to east and from north to south. The main spatial contrast is between the eastern and western regions, with a relatively minor distinction between the southern and northern regions. (2) The LISA space-time transition highlights a significant spatial locking effect in China's rural land transfer ratio, suggesting strong spatial integration in its evolution. (3) Clear indications of σ convergence, absolute ß convergence, and club convergence are evident in China's rural land transfer ratio. This suggests a gradual reduction in internal disparities among provinces and regions, where areas with higher land transfer ratios influence spatial spillover effects on adjacent lower areas. (4) Factors such as transportation infrastructure, irrigation, water conservancy construction, and farmers' per capita income collectively influence the spatial and temporal evolution of China's rural land transfer ratio, with dominant driving factors varying across different periods.

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.

Unveiling the nexus between rural population aging, technical efficiency, and carbon emissions in Chinese agriculture.

INTRODUCTION: According to the seventh national population census in China, the proportion of people aged 65 and above in the population reached 13.5%. The aging trend is more pronounced in rural areas, indicating that China has entered an aging society. This article focuses on agricultural carbon emissions in the context of aging, studying the impact of rural population aging on agricultural carbon emissions. STUDY OBJECTIVES: Under the background of deepening population aging, let us discuss how to maintain the green and sustainable development of agriculture in China. METHODOLOGY: Fixed effects and mediating effects models are used. Technical efficiency is used as a mediating variable to discuss the relationship between rural population ageing, technical efficiency and agricultural carbon emissions. RESULTS: This paper adopts the classical carbon emission calculation theory of IPCC to measure agricultural carbon emissions from 2010 to 2019, and China's plantation carbon emissions show an "inverted U-shaped" trend, reaching a high level in 2015 and then starting to decline. In addition, the fixed-effects benchmark regression found that the aging of the rural population promotes agricultural carbon emissions, and the technical efficiency of agriculture suppresses agricultural carbon emissions. Finally, the mediating effect model is applied to explore the relationship between the three. Using technical efficiency as the mediating variable, it is found that under the masking effect, rural population aging will weaken agricultural carbon emissions through technical efficiency, thus achieving the suppression of agricultural carbon emissions. POLICY RECOMMENDATION: The formulation and modification of agricultural carbon-reducing policy row policies should take full account of the broader context of rural population ageing; increase the interconnectedness and interaction between rural population ageing and agricultural production technology, and actively play a positive role in promoting the efficiency of agricultural technology as a result of rural population ageing; and, in accordance with the actual situation of agricultural research, appropriately increase the strength of financial support for agriculture to improve agricultural technology and promote low-carbon development in agriculture.

Integrating remote sensing classification techniques for land use mapping in semi-arid regions: a case study of the Tamlouka basin, Algeria.

Worldwide, the majority of countries are actively devising strategies to address the challenges associated with unregulated and unmanageable development, the decline in environmental quality and the depletion of valuable agricultural land. This has led to a growing emphasis on understanding land use and land cover. In order to determine a better land use policy, legislators and planners need to know the current distribution of agricultural and urban lands, as well as information about changes in their proportions. Our approach combines data centred on main four themes-geology, slope gradient, hydrographic network and land use-in order to exploit classifier complementarities in our targeted agricultural study area of Tamlouka Basin, Algeria. Landsat 8 OLI-TIRs multispectral imagery and Shuttle Radar Topography Mission (SRTM-1arc v3) were used experimentally for classification and Digital Elevation Model (DEM) analysis. The classification's accuracy is confirmed by comparing the results of the decision tree classification with the validation samples. Results of the combination of several maps of classifications from the different methods show that the Tamlouka alluvial plain, having an area of 19,300 ha and an average slope gradient of less than 2°, drains the elevated reliefs that surround it via hydrographic network. The plain occupies 37% of the total basin area, with over of 60% being used for crop cultivation, regardless of fallow land areas in agricultural rotation at that time. The slope has been identified as a crucial factor determining land use patterns in the study area. This result can be used in prospective watershed management.

Influence of recurrent assessments during data collection on caregivers and young children for an agricultural livelihood intervention in Kenya: a qualitative study.

OBJECTIVES: We sought to understand the influence of recurrent assessments on the behaviour of children and caregivers in a 2-year study of an agricultural livelihood intervention. DESIGN: This study used qualitative exit interviews from caregivers in the control arm of a large, cluster-randomised control trial, Shamba Maisha. SETTING: The study was conducted in Western Kenya and involved 12 health facilities between 2016 and 2019. PARTICIPANTS: Participants were 99 caregivers in the control arm who had a child that was 6-36 months in age at the start of the study. INTERVENTIONS: Intervention participants within Shamba Maisha received an irrigation pump, farming lessons and a microloan. Control participants received no intervention but were offered the intervention after completing the 2-year study. RESULTS: Despite receiving no formal benefits, control caregivers reported improved mental health and enhanced knowledge of their child's health compared with the beginning of the study and reported changes in the child's play and diet that they attributed to participation in study assessments. Caregivers in the control arm attributed their changed behaviour to recurrent questioning, instrumental support, interactions with study staff and increased health knowledge. CONCLUSIONS: Recurrent assessments altered participant behaviour, which may have made inference of the intervention's impact more difficult. In designing future, such studies with intervention and control arms, a trade-off between the gains in statistical power provided by recurrent visits and the avoidance of alterations in participants' behaviour that could affect responses to assessments must be considered when deciding on the number of visits for assessment. TRIAL REGISTRATION NUMBERS: NCT03170986; NCT02815579.

Iron-doped biochar, an agricultural and environmentally beneficial fertilizer.

The utilization of agricultural waste to create value-added goods has benefited waste management while resolving cost-effectiveness and food shortage problems. Returning biochar produced from agricultural waste to the agricultural field is a sustainable method of enhancing crop production while lowering the environmental effect of typical fertilizers. It also enhances soil condition by modulating pH, soil organic carbon, water retention capacity, and soil ion exchange potential. The current work concentrated on the production of iron oxide-loaded biochar from banana peels. Pyrolysis was carried out at temperatures ranging from 400 to 500 °C. The co-precipitation technique was utilized to impregnate Fe3O4 nanoparticles on biochar, and it showed to be an effective and trustworthy method. Loading was done in situ. Characterization techniques such as XRD, FTIR, CHNS, and TGA were employed to characterize synthesized materials. Swelling ratio, water retention, absorbance, and equilibrium water content percentage were used to study the adsorption capabilities of Fe3O4-loaded biochar, soil, and raw biochar. As a consequence, Fe3O4-enriched biochar was shown to have better adsorption capability than raw biochar, which in turn showed better adsorption properties than soil. Iron-loaded biochar was employed as a fertilizer in Abelmoschus esculentus (Okra), and the results showed that it is a cost-effective, environmentally friendly fertilizer.

Simulating the land use change effects on non-point source pollution in the Duliujian River Basin.

The uncertainty in the generation and formation of non-point source pollution makes it challenging to monitor and control this type of pollution. The SWAT model is frequently used to simulate non-point source pollution in watersheds and is mainly applied to natural watersheds that are less affected by human activities. This study focuses on the Duliujian River Basin (Xiqing section), which is characterized by a dense population and rapid urbanization. Based on the calibrated SWAT model, this study analyzed the effects of land use change on non-point source pollution both temporally and spatially. It was found that nitrogen and phosphorus non-point source pollution load losses were closely related to land use type, with agricultural land and high-density urban land (including rural settlements) being the main contributors to riverine nitrogen and phosphorus pollution. This indicates the necessity of analyzing the impact of land use changes on non-point source pollution loads by identifying critical source areas and altering the land use types that contribute heavily to pollution in these areas. The simulation results of land use type changes in these critical source areas showed that the reduction effect on non-point source pollution load is in the order of forest land > grassland > low-density residential area. To effectively curb surface source pollution in the study area, strategies such as modifying urban land use types, increasing vegetation cover and ground infiltration rate, and strictly controlling the discharge of domestic waste and sewage from urban areas can be implemented.