Summary of Roadway Incidents Involving Farm Equipment in Five Midwestern States Using the Fatality Analysis Reporting System (FARS)

Roadway incidents involving farm equipment is a growing area of concern among agricultural safety and health and public health professionals. The aim of this project was to evaluate the usefulness of the Fatality Analysis Reporting System (FARS) and analyze the number of roadway fatal incidents that involve farm equipment. Data collected from the FARS through the National Highway Traffic Safety Administration was used to summarize roadway incidents involving farm equipment. Cases from five midwestern states were analyzed from January to December 2020 using SPSS. Incidents involving farm equipment resulted in 25 cases with Iowa, Michigan, and Wisconsin all reporting six cases each. The most common manner of incidents were single-vehicle crashes and rear-ending incidents. Most of the events occurred during busy agricultural seasons, most often occurring in June and August with five cases each. The FARS dataset is a useful tool to identify cases, but it faces limitations, such as only reporting fatalities and lack of information on specific farm equipment involved in incidents. The results from the study are helpful to better understand roadway incidents and guide future intervention strategies.

Profile and risk factors in farmer injuries: a review based on Haddon matrix and 5 E's risk reduction strategy

Farmers are considered a high-risk group for intentional and unintentional injuries. This review identified significant risk factors for agricultural injuries in farmers and explored injury prevention countermeasures based on the literature. Therefore, CiteSpace software was used to analyze the relevant literature in this field. Additionally, we identified both key risk factors and countermeasures using the Haddon matrix and the 5 E's risk reduction strategies conceptual framework, respectively. The risk factors were identified from four categories (host, agent, physical environment, and social environment) corresponding to three phases (pre-event, event, and post-event). Interventions of 5 E's risk reduction strategies including education, engineering, enforcement, economic, and emergency response have been proven effective in preventing injuries or reducing their severity. Our findings provide a comprehensive foundation and research direction for the study and prevention of injuries among farmers.

Water rights trading planning and its application in water resources management: A water-ecology-food nexus perspective

Nexus approach provides an effective perspective for implementing synergetic management of water resources. In this study, an interval two-stage chance-constrained water rights trading planning model under water-ecology-food nexus perspective (ITCWR-WEF) is proposed to analyze the interaction between water trading and water-ecology-food (WEF) nexus, which fills in the water resources management gaps from a novel nexus perspective. ITCWR-WEF incorporates hydrological simulation with soil and water assessment tool (SWAT), water rights configuration with interval two-stage chance-constrained programming (ITCP), and multi-criterion analysis with Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The developed ITCWR-WEF is applied to a real case of Daguhe watershed, which has characteristics of water scarcity, food producing areas and fragile ecosystem. Initial water rights allocation is addressed before the trading. Mechanisms analysis is designed to reveal mutual effect of water rights trading and WEF nexus. Optimal water management scenario is identified through multi-criterion analysis. Results reveal that the mechanism of water rights trading with WEF nexus under low constraint-violation risk level of water availability and environment capacity is recommended to promote the rational water resources allocation to balance the economic goals, water environment and water supply security, as well as ecological and food water demand guarantees.

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.

Frequent disturbances enhanced the resilience of past human populations

The record of past human adaptations provides crucial lessons for guiding responses to crises in the future1-3. To date, there have been no systematic global comparisons of humans' ability to absorb and recover from disturbances through time4,5. Here we synthesized resilience across a broad sample of prehistoric population time-frequency data, spanning 30,000 years of human history. Cross-sectional and longitudinal analyses of population decline show that frequent disturbances enhance a population's capacity to resist and recover from later downturns. Land-use patterns are important mediators of the strength of this positive association: farming and herding societies are more vulnerable but also more resilient overall. The results show that important trade-offs exist when adopting new or alternative land-use strategies.

Prevalence and risk distribution of schistosomiasis among adults in Madagascar: a cross-sectional study

BACKGROUND

The goal to eliminate the parasitic disease of poverty schistosomiasis as a public health problem is aligned with the 2030 United Nations agenda for sustainable development goals, including universal health coverage (UHC). Current control strategies focus on school-aged children, systematically neglecting adults. We aimed at providing evidence for the need of shifting the paradigm of schistosomiasis control programs from targeted to generalized approaches as key element for both the elimination of schistosomiasis as a public health problem and the promotion of UHC.

METHODS

In a cross-sectional study performed between March 2020 and January 2021 at three primary health care centers in Andina, Tsiroanomandidy and Ankazomborona in Madagascar, we determined prevalence and risk factors for schistosomiasis by a semi-quantitative PCR assay from specimens collected from 1482 adult participants. Univariable and multivariable logistic regression were performed to evaluate odd ratios.

RESULTS

The highest prevalence of S. mansoni, S. haematobium and co-infection of both species was 59.5%, 61.3% and 3.3%, in Andina and Ankazomborona respectively. Higher prevalence was observed among males (52.4%) and main contributors to the family income (68.1%). Not working as a farmer and higher age were found to be protective factors for infection.

CONCLUSIONS

Our findings provide evidence that adults are a high-risk group for schistosomiasis. Our data suggests that, for ensuring basic health as a human right, current public health strategies for schistosomiasis prevention and control need to be re-addressed towards more context specific, holistic and integrated approaches.

The effects of heat exposure on tropical farm workers in Malaysia: six-month physiological health monitoring

Farmers in tropical countries have been impacted by slow-onset heat stress. By comparing the nature of farming activities performed by conventional farmworkers and agroecological farmers, this study examined the changes in physiological health in responses to heat exposure through a six-month longitudinal study. Throughout the six-month follow-up period, the heat stress index (HSI), physiological strain indices (PSI), and physiological health parameters (BMI, blood glucose level, blood cholesterol level, uric acid level) were measured and repeated every two-month. Physiological parameters were recorded twice daily, before and during their first lunch break. This study found that slow-onset heat stress affects farmers differently. The health of agroecological farmers is more resistant to slow-onset extreme temperatures. Pre-existing metabolic health effects from pesticide exposure make conventional farmers more susceptible to extreme temperatures, delaying their bodies' adaptation to rising temperatures.

Modelling the impacts of climate change on cereal crop production in East Africa: evidence from heterogeneous panel cointegration analysis

Climate change has become an issue of concern for sustainable agriculture production. East African nations are heavily reliant on the agriculture sector, which accounts for a substantial amount of their gross domestic product (GDP) and employment. Due to climatic fluctuations, the output of the sector became very unpredictable. Hence, this study investigates the effects of climate change on cereal crop production in nine East African nations between 1990 and 2018. The study implemented pooled mean group (PMG) approach to examine the long-run and short-run dynamic impacts of the varying climatic circumstances on the output of cereal crops. The results reveal that rainfall and carbon emissions have favourable and significant long-run effects on cereal crop output, even though their short-run impacts are negligible. Additionally, cultivated land area and rural population have a constructive role in enhancing agricultural output both in the long-run and short-run. However, average temperatures have negative repercussions on cereal crop production in the long-run and short-run, even though the magnitude of sensitivity is greater in the short-run. Dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) validated the robustness of the long-run findings of the PMG technique. Besides, the Dumitrescu-Hurlin panel causality outcomes indicate that cereal crop output has a bidirectional causality with temperature, carbon emissions, and cropped area. The study further demonstrated unidirectional causation from rural population to cereal crop yield. The study recommends that East African policymakers improve the quality of farm inputs, the adoption of climate-resilient farming practices, the development of water retention facilities and the establishment of crop diversification initiatives.

An Epidemiological Study to Investigate Links between Atmospheric Pollution from Farming and SARS-CoV-2 Mortality

Exposure to atmospheric particulate matter and nitrogen dioxide has been linked to SARS-CoV-2 infection and death. We hypothesized that long-term exposure to farming-related air pollutants might predispose to an increased risk of COVID-19-related death. To test this hypothesis, we performed an ecological study of five Italian Regions (Piedmont, Lombardy, Veneto, Emilia-Romagna and Sicily), linking all-cause mortality by province (administrative entities within regions) to data on atmospheric concentrations of particulate matter (PM_2.5 and PM₁₀) and ammonia (NH₃), which are mainly produced by agricultural activities. The study outcome was change in all-cause mortality during March-April 2020 compared with March-April 2015-2019 (period). We estimated all-cause mortality rate ratios (MRRs) by multivariate negative binomial regression models adjusting for air temperature, humidity, international import-export, gross domestic product and population density. We documented a 6.9% excess in MRR (proxy for COVID-19 mortality) for each tonne/km² increase in NH₃ emissions, explained by the interaction of the period variable with NH₃ exposure, considering all pollutants together. Despite the limitations of the ecological design of the study, following the precautionary principle, we recommend the implementation of public health measures to limit environmental NH₃ exposure, particularly while the COVID-19 pandemic continues. Future studies are needed to investigate any causal link between COVID-19 and farming-related pollution.

More pests but less pesticide applications: Ambivalent effect of landscape complexity on conservation biological control

In agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, therefore supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and natural enemy species, the underlying landscape structure, and their interaction, may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that increased SNH presence boosts predator populations by sustaining high predator density that regulates and keeps pest density below the pesticide application threshold. However, predator presence over all the landscape helps to stabilize the pest population by keeping it under this threshold, which tends to increase pest density at the landscape scale. In addition, the joint effect of SNH presence and predator dispersal ability among hedge and field interface results in a stronger pest regulation, which also limits pest growth. Considering properties of both fields and linear elements, such as local structure and geometric features, provides deeper insights for pest regulation; for example, hedge presence at crop field boundaries clearly strengthens CBC. Our results highlight that the integration of species behaviors and traits with landscape structure at multiple scales is necessary to provide useful insights for CBC.

In the agricultural context, the loss of semi-natural surfaces often results in high pest abundance requiring elevated pesticide loads. Habitat heterogeneity resulting from the agricultural intermixing of arable fields and semi-natural areas is key to allow organism fluxes across agro-ecological interfaces by influencing ecological processes. Semi-natural habitats (SNH) are often restricted to linear structures, such as hedgerows, but they play an important role by hosting a large number of species. However, the effect of hedgerows is controversial, as it could result in a positive, ineffective or negative effect for CBC. Usually, the impacts of landscape structure on pest population dynamics and resulting CBC are assessed through field experiments with a specific focus, which cannot be generalized, lack flexibility and are limited by the need to manipulate relatively large landscapes. Here, we tackle the challenge to investigate the controversial role of semi-natural habitats for CBC by presenting a simulation-based approach, which allows us to characterize the joint influence of landscape structure and species traits on CBC service. Our study corroborates that spatial heterogeneity, species traits and their interactions are fundamental for CBC. We show that hedge presence alone is not sufficient to lead to strong pest reduction, but hedge-based predators help to maintain the pest density under the pesticide threshold. Instead, SNH presence coupled with appropriate predator traits leads to stronger decrease of pest population. Moreover, we highlight an important scaling effect of SNH, which at the local scale has an even more important impact on CBC as local properties are considered.

Preliminary Study on Survey and Population Dynamic of the Terrestrial Snail Monacha obstructa (Pfeiffer) (Hygromiidae, Mollusca) at Crop Fields in Fayoum Governorate, Egypt

<b>Background and Objective:</b> <i>Monacha obstructa</i> has a serious harmful impact as agricultural pest infested field crops, fruits, vegetables and ornamental plants nurseries in multiple Egyptian governorates. The objective of this research was estimating the population dynamic of the terrestrial gastropod species <i>Monacha obstructa</i> (Pfeiffer) (Hygromiidae) on two economic crop fields and its correlation with temperature degree and relative humidity, the level of infestation on other economic crops had been estimated as well. <b>Materials and Methods:</b> This study was conducted in three sites in Fayoum governorate, 1) Forkous village at Tamiya District, 2) Dar Ramadsite including the Experimental farm and research station of the Faculty of Agriculture, Fayoum University, Fayoum District and 3) Feedimeen village at Sannoris District. The distribution and population dynamics of <i>Monacha obstructa</i> were assessed as one of dominant species on two field crops Egyptian clover <i>Trifolium alexandrinum </i>L. and wheat <i>Triticum aestivum</i> L. at Forkous village, Tamiya District and Dar Ramad site, Fayoum District, during two successive seasons 2016/2017 and 2017/2018. <b>Results:</b> Majority of the examined crops in the sites were found with heavy infestation of this species, while the two species <i>Cochlicella acuta</i> (Müller) (Geomitridae) and <i>Massylaea vermiculata </i>(Müller) (Helicidae) recorded in December, 2017 and in January, 2018, respectively, on mango trees in Feedimeen at Sannoris district for only one time. High density of <i>M. obstructa</i> recorded on Egyptian clover more than wheat at Forkous village and Dar Ramad site for the both seasons in this study. <b>Conclusion:</b> Results concluded that <i>Monacha obstructa</i> has a serious harmful impact as agricultural pest infested field crops, fruits, vegetables and ornamental plants nurseries in Forkous village and Dar Ramad site, respectively.

Shift of bacterial communities in heavy metal-contaminated agricultural land during a remediation process

Anthropogenic activities accompanied by heavy metal waste threaten the environment. Heavy metal pollution alters the soil microbial community composition, and the microorganisms that adapt to this stress increase in abundance. The remediation process of contaminated soil not only reduces the concentration of heavy metals but also alters the bacterial communities. High-throughput 16S rDNA sequencing techniques were applied to understand the changes in soil microbial communities. Using the remediation approach of the soil mixing, the concentrations of heavy metals in the contaminated areas were diluted and the soil environment was changed. The change of soil environment as a disturbance contributed to the alteration of microbial diversity of the remediated areas. The pH and heavy metals (Cr, Cu, Ni, and Zn) were the most influential factors driving the changes in community structure. The bacterial community structure was significantly different among sample areas. The decrease of heavy metals in soil may be the important factors that changed the microbial composition. This study provides the better understanding of the changes in composition of microbial communities affected by the remediation process in heavy metal-contaminated soil.

Farm diversification as a potential success factor for small-scale farmers constrained by COVID-related lockdown. Contributions from a survey conducted in four European countries during the first wave of COVID-19

This paper explores to what extent product and marketing channel diversification contributed to the economic success of small-scale agricultural producers involved in short food supply chains after the outbreak of the COVID-19 pandemic. A survey was conducted between April and July 2020 in four countries of the European Union–Estonia, Hungary, Portugal and Romania,–resulting in a relatively large sample of farmers (N = 421). The analysis was built on a semi-nonparametric approach. Approximately 19 percent of small-scale producers were able to increase sales during the first wave of the pandemic, although country-level variation was significant. Fruits and vegetables were by far the most popular products. The importance of specific channels varied across countries, but farm gate sales were among the most important marketing channels both before and during the first wave. The importance of channels that were based on digital resources and home delivery increased. Our evidence indicates that diversification was a strategy that paid off, both in terms of marketing channels and different product categories. However, the impact appears to be nonlinear; the initial advantage generated by diversification rapidly tapered off, either temporarily (in the case of products), or permanently (in the case of marketing channels). Later research may clarify whether these findings are generalizable in other socio-economic contexts, as well as in a non-COVID situation.

Air quality-related health damages of food

Agriculture is a major contributor to air pollution, the largest environmental risk factor for mortality in the United States and worldwide. It is largely unknown, however, how individual foods or entire diets affect human health via poor air quality. We show how food production negatively impacts human health by increasing atmospheric fine particulate matter (PM2.5), and we identify ways to reduce these negative impacts of agriculture. We quantify the air quality-related health damages attributable to 95 agricultural commodities and 67 final food products, which encompass >99% of agricultural production in the United States. Agricultural production in the United States results in 17,900 annual air quality-related deaths, 15,900 of which are from food production. Of those, 80% are attributable to animal-based foods, both directly from animal production and indirectly from growing animal feed. On-farm interventions can reduce PM2.5-related mortality by 50%, including improved livestock waste management and fertilizer application practices that reduce emissions of ammonia, a secondary PM2.5 precursor, and improved crop and animal production practices that reduce primary PM2.5 emissions from tillage, field burning, livestock dust, and machinery. Dietary shifts toward more plant-based foods that maintain protein intake and other nutritional needs could reduce agricultural air quality-related mortality by 68 to 83%. In sum, improved livestock and fertilization practices, and dietary shifts could greatly decrease the health impacts of agriculture caused by its contribution to reduced air quality.

ERA5-based global assessment of irrigation requirement and validation

While only 20% of harvested lands are actually irrigated, 40% of global agricultural production originates from irrigated areas. Therefore, assessing irrigation requirements is essential for the development of effective water-related policies for an efficient management of water resources. Moreover, global-scale analyses are becoming increasingly relevant, motivated by globalized production and international trade of food as well as by the need of common strategies to address climate change.

In this study, a comprehensive model to estimate crop growth and irrigation requirements of 26 main crops at global scale is presented. The model computes a soil water balance using daily precipitation and reference evapotranspiration based on a high-resolution ERA5 reanalysis dataset from the European Copernicus Program. The irrigation requirement, defined as the minimum water volume to avoid water stress, is computed for year 2000 at the resolution of 5 arc-min (or 0.0833°) and aggregated at different spatial and temporal scales for relevant analyses.

The estimated global irrigation requirements for 962 km³ is described in detail, also in relation to the spatial variability and to the monthly variation of the requirements. A focus on different areas of the world (California, Northern Italy and India) highlights the wealth of information provided by the model in different climatic conditions.

National data of irrigation withdrawals have been used for an extensive comparison with model results. A crop-specific validation has also been made for the State of California, comparing model results with local data of irrigation volume and independent estimates of crop water use. In both cases, we found a good agreement between model results and real data.

What empowerment indicators are important for food consumption for women? Evidence from 5 sub-Sahara African countries

This paper draws on data from five sub-Sahara African countries; Uganda, Rwanda, Malawi, Zambia, and Mozambique consisting of 10,041 married women who were cohabitating with a male spouse. The study aim was to investigate the relationship between women's empowerment and women's dietary diversity and consumption of different food items. Women's empowerment was measured using the indicators in the five domains of Women's Empowerment in Agriculture index (WEAI) and women's dietary diversity and food consumption was examined using the women's dietary diversity score (WDDS) measure. OLS and LPM regressions were used and analyses were confirmed using marginal effects from Poisson and logistic regressions. Results suggest that three out of the 10 WEAI indicators of empowerment showed different magnitude and direction in significant associations with improved WDDS and varied associations were found in three out of the five countries examined. In addition, the three significant empowerment indicators were associated with the consumption of different food groups in three out of the five countries examined suggesting that diverse food groups account for the association between the WEAI and WDDS. Improved autonomy, and input in production were associated with improved likelihoods of consumption of dairy products, and fruits and vegetables including vitamin A-rich produce. Empowerment in public speaking was associated with improved consumption of other fruits and vegetables including vitamin A-rich produce. The varied nature of empowerment indicators towards improving women's dietary diversity and food consumption suggests that different empowerment strategies might confer different benefits towards the consumption of different food groups. Further, findings imply that interventions that seek to empower women should tailor their strategies on existing contextual factors that impact on women.

R, D. J. N, Panda AK, Wagh RD, Maske MR, R. V. B. Farming System for Nutrition-a pathway to dietary diversity: Evidence from India

Farming is the main livelihood of a majority of people in India. The country is also home to a large population of undernourished people. This indicates potential for mainstreaming the nutrition dimension in the farming system to impact on nutrition outcomes. A Farming System for Nutrition (FSN) study was conducted in two agro-ecologically different locations from 2013-2018, to explore the feasibility of nutrition-sensitive agricultural interventions. The baseline survey in 2013-2014 revealed that the population in the study area was largely undernourished and that household diets were cereal-dominated. The FSN model was designed in consultation with community members, to increase availability of nutrient-dense cereals and pulses, by enhancing production and crop diversification at the farm level, promoting cultivation of nutrient-rich fruits and vegetables in nutrition gardens and supporting interventions to promote access to animal foods. Nutrition awareness initiatives were undertaken to build capacity at the local level and translate production diversity to consumption diversity. An endline survey was conducted in 2017 (July-October), following three years of intervention. Crop, vegetable and animal food production and food consumption was compared with the baseline data. There was evidence of higher production and consumption of nutrient rich foods, improved household dietary diversity; and understanding and acceptance of nutrition-sensitive agriculture. The number of items consumed under each food group, frequency of consumption of food and average per capita intake of nutrient-rich foods were found to have improved. The results provide evidence regarding feasibility of location-specific FSN models to promote sustainable and healthy diets, using locally available plant and animal food resources, to address nutrition deficiencies in farm families.

Reconstructing dynamics of foodborne disease outbreaks in the US cattle market from monitoring data

Conventional empirical studies of foodborne-disease outbreaks (FDOs) in agricultural markets are linear-stochastic formulations hardwiring a world in which markets self-correct in response to external random shocks including FDOs. These formulations were unequipped to establish whether FDOs cause market reaction, or whether markets endogenously propagate outbreaks. We applied nonlinear time series analysis (NLTS) to reconstruct annual dynamics of FDOs in US cattle markets from CDC outbreak data, live cattle futures market prices, and USDA cattle inventories from 1967–2018, and used reconstructed dynamics to detect causality. Reconstructed deterministic nonlinear market dynamics are endogenously unstable—not self-correcting, and cattle inventories drive futures prices and FDOs attributed to beef in temporal patterns linked to a multi-decadal cattle cycle undetected in daily/weekly price movements investigated previously. Benchmarking real-world dynamics with NLTS offers more informative and credible empirical modeling at the convergence of natural and economic sciences.

The effect of urbanization on agricultural water consumption and production: the extended positive mathematical programming approach

One of the most important factors in the agricultural sector is the supply of water. There are numerous factors affecting the supply of water in the agricultural sector. One of these factors is urban development. After the agricultural and industrial revolution, urban revolution is one of the most important issues in the economic development of countries. Urban development has two implications for agricultural water use; this both increases the demand for agricultural crops and the consumption of water in the household sector, which both lead to a reduction in available water in the agricultural sector. Therefore, determination of the impact of urbanization on water consumption in agriculture is necessary. In this study, we have examined the extended positive mathematical programming method on the agricultural sector of Qazvin Province. The results of the study showed that 1% increase in urbanization would reduce water consumption in agriculture by 0.639 mm³ compared to the base year. Also, household water consumption will reach 92.92-761.9 mm³ in base year. On the other hand, the cultivated area and the production of some irrigated crops (wheat, barley, rapeseed, sunflower, other oilseeds, alfalfa) will decrease to 86.36 hectare and 346.6 tons. In the indirect effect of increasing urbanization, per each percentage urbanization, the household water consumption will decrease by 2.19 mm³, and after a 20-year horizon, the total capacity of the Taleghan Dam will be allocated to Tehran's household water,. So that, 288 mm³ of agricultural water will be reduced, and it will reduce the cultivated area for 28,250 (ha). Also, farmers' gross profits will be 10.5 percent lower than the base year which is a threat for Qazvin plain farming. Solutions were proposed to reduce the negative effects of the urban development phenomenon, including the use of modern irrigation systems in the agricultural sector will significantly increase irrigation efficiency. So that only 1% increase in irrigation efficiency can completely neutralize the direct and indirect negative impacts of urbanization on a 12-year mid-term horizon.

Interactive Web-based Data Visualization and Analysis Tool for Synthetizing on-farm Research Networks Data

The on-farm research network concept enables a group of farmers to test new agricultural management practices under local conditions with support from local researchers or agronomists. Different on-farm trials based on the same experimental design are conducted over several years and sites to test the effectiveness of different innovative management practices aimed at increasing crop productivity and profitability. As a larger amount of historical trial data are being accumulated, data of all the trials require analyses and summarization. Summaries of on-farm trials are usually presented to farmers as individual field reports, which are not optimal for the dissemination of results and decision making. A more practical communication method is needed to enhance result communication and decision making. R Shiny is a new rapidly developing technology for turning R data analyses into interactive web applications. For the first time for on-farm research networks, we developed and launched an interactive web tool called ISOFAST using R Shiny. ISOFAST simultaneously reports all trial results about the same management practice to simplify interpretation of multi-site and multi-year summaries. We used a random-effects model to synthetize treatment differences at both the individual trial and network levels and generate new knowledge for farmers and agronomists. The friendly interface enables users to explore trial summaries, access model outputs, and perform economic analysis at their fingertips. This paper describes a case-study to illustrate how to use the tool and make agronomic management decisions based on the on-farm trial data. We also provided technical details and guidance for developing a similar interactive visualization tool customized for on-farm research network. ISOFAST is currently available at https://analytics.iasoybeans.com/cool-apps/ISOFAST/.

Understanding the relationship between land use and land cover and malaria in Nepal

Malaria is a leading cause of mortality and morbidity globally. Land Use and Land Cover (LULC) change have been found to affect the transmission of malaria in other regions, but no study has examined such relationships in Nepal. Therefore, this study has three aims: first, to analyze the spatial and temporal trend of Malaria Incidence Rate (MIR) between 1999 and 2015, second to assess LULC change between 2000 and 2010, and finally to understand the relationship between LULC and malaria in Nepal. The land cover types examined are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas, and rice paddies. The temporal trend of MIR and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, and built-up area increased in Nepal by 0.8%, 8.2%, and 28.4% respectively, while other LULC variables decreased between 2000 and 2010. MIR decreased significantly in 21 districts; however, four districts, namely Pyuthan, Kaski, Rupandehi, and Siraha, had a significantly increasing MIR trend between 1999 and 2015. MIR was positively related to water bodies and rice paddies during 2001, 2002, and 2003 but negatively related to grassland during 2010. However, there was no relationship between LULC and MIR during 2000, 2011, 2012 and 2013. This information will be helpful for public health officials to increase control efforts in those districts and in areas near water bodies and rice paddies to aid in their effort to eliminate malaria from Nepal.

Spatial-Temporal Characteristics in Grain Production and Its Influencing Factors in the Huang-Huai-Hai Plain from 1995 to 2018

The Huang-Huai-Hai Plain is the major crop-producing region in China. Based on the climate and socio-economic data from 1995 to 2018, we analyzed the spatial-temporal characteristics in grain production and its influencing factors by using exploratory spatial data analysis, a gravity center model, a spatial panel data model, and a geographically weighted regression model. The results indicated the following: (1) The grain production of eastern and southern areas was higher, while that of western and northern areas was lower; (2) The grain production center in the Huang-Huai-Hai Plain shifted from the southeast to northwest in Tai'an, and was distributed stably at the border between Jining and Tai'an; (3) The global spatial autocorrelation experienced a changing process of "decline-growth-decline", and the area of hot and cold spots was gradually reduced and stabilized, which indicated that the polarization of grain production in local areas gradually weakened and the spatial difference gradually decreased in the Huang-Huai-Hai Plain; (4) The impact of socio-economic factors has been continuously enhanced while the role of climate factors in grain production has been gradually weakened. The ratio of the effective irrigated area, the amount of fertilizer applied per unit sown area, and the average per capita annual income of rural residents were conducive to the increase in grain production in the Huang-Huai-Hai Plain; however, the effect of the annual precipitation on grain production has become weaker. More importantly, the association between the three factors and grain production was found to be spatially heterogeneous at the local geographic level.