Problem In Agricultural Areas Research Articles

Fluoride and nitrogen contamination and potential health risks in the groundwater of a typical agricultural region

ABSTRACT Fluoride and nitrogen contamination is a global concern and has been a serious problem in agricultural areas. This study aims to identify the source of fluoride and nitrogen in the groundwater and assess groundwater quality and human health risks in the Guanzhong Plain, northwest China. The results showed that the concentrations were 0.15–4.74 mg/L for F−, 0.02–89.89 mg/L for NO3−-N, and BDL-2.40 mg/L for NH4+-N in groundwater. Distinct area-dependent distributions of fluoride and nitrogen were observed in the study region. Higher F− and NO3−-N concentrations in groundwater were detected in the northern part, and higher NH4+-N levels were observed in the southern part. Water–rock interaction and agricultural activities were the controlling factors for fluoride and nitrogen distribution in groundwater. About 80% of samples are considered to have good water quality with a Water Quality Index (WQI) < 100. Exposure to fluoride and nitrogen through drinking should require more attention. The total non-carcinogenic risks through oral ingestion of groundwater were 0.22–3.19 for adults and 0.51–7.44 for children, respectively. The order of pollutants in the groundwater in terms of their hazard to residents was F− > NH4+-N > NO3−-N > NO2−-N. The findings of this study could provide more insights into groundwater management.

Penguatan Kapasitas Kader Petani dalam Penanganan Gigitan Ular Berbisa di Wilayah Antirogo

Venomous snakebites represent a significant health problem in agricultural areas, particularly in Antirogo Village, Jember Regency. Insufficient knowledge and skills in preventing and managing venomous snakebites increase the risk for farmers in this area. The Saung Tani Cekatan program aims to enhance the knowledge and preparedness of CEKATAN cadres in handling venomous snakebites. This program involves 30 CEKATAN cadres who receive training through educational methods using mobile applications and PowerPoint presentations, as well as demonstration methods. The activities were conducted in Antirogo Village, Jember Regency. The evaluation was carried out using pretest and posttest questionnaires consisting of closed-ended questions regarding the prevention and management of snakebites. The results showed an increase in the percentage of respondents who answered questions correctly: question 1 (53.3%), question 2 (76.6%), question 3 (86.6%), question 4 (66.6%), question 5 (70%), question 6 (83.3%), question 7 (90%), question 8 (96.6%), question 9 (96.6%), question 10 (100%), question 11 (96.6%), question 12 (100%), question 13 (90%), question 14 (100%), question 15 (56.6%), and question 16 (90%). In conclusion, the Saung Tani Cekatan empowerment program effectively increases cadre knowledge regarding preparedness and management of venomous snakebites in the Antirogo area. This program can be expanded to other agricultural sectors using similar methods.

Impacts of biostimulation and bioaugmentation on woodchip bioreactor microbiomes.

Nitrate pollution is a serious problem in agricultural areas in the U.S. Midwest and other parts of the world. Woodchip bioreactor is a promising technology that uses microbial denitrification to remove nitrate from agricultural subsurface drainage, although the reactor's nitrate removal performance is limited under cold conditions. This study showed that the inoculation of cold-adapted denitrifiers (i.e., bioaugmentation) and the addition of labile carbon (i.e., biostimulation) can influence the microbial populations and enhance the reactor's performance under cold conditions. This finding will help establish a strategy to mitigate nitrate pollution.

Risk Factors for Pesticide Poisoning in Horticultural Farmers in the Agricultural Area of West Seram Regency, Indonesia

Background: In the field of environmental health, pesticide poisoning is still an important health problem in agricultural areas, especially horticultural agriculture, as a result of the risky habit of using pesticides. This study aimed to analyse the risk factors for poisoning in horticultural farmers in West Seram District, Indonesia. Methodology: This study applied a cross-sectional design, involving 298 farmers selected by proportional random sampling technique. The risk factors studied included tenure, the use of personal protective equipment, duration of spraying, frequency of spraying, number of types of pesticides, method of mixing, direction of spraying, and dose of pesticides, smoking while spraying, washing hands when eating, drinking while spraying, spraying time and personal hygiene. Data were collected through interviews, then analyzed using multiple logistic regression test. Results: The results showed that the p-value for each factor was use of personal protective equipment = 0.025, frequency of spraying = 0.023, method of mixing pesticides = 0.004, direction of spraying = 0.017 and personal hygiene = 0.002. Conclusions: It could be concluded that the use of personal protective equipment, personal hygiene, frequency of spraying, method of mixing and spraying direction are risk factors for pesticide poisoning in horticultural farmers.

Increasing the Plant Productivity Using the Automatic Controlled Irrigation System: A Comparative Experimental Study

With the development of technology, today, the use of technology in the field of agriculture has become widespread. In order to meet the increasing demand for agricultural products, automation techniques should be used in agricultural areas in order to make the production of agricultural products simpler and more efficient. In this study, an automation system is designed by making use of technology against problems such as irrigation problem and water shortage, which have become an important problem in agricultural areas. The data coming from the humidity sensor placed in the soil is processed to the controller. According to these processed data, when the soil is dry and the plant needs water, the water-pumping set automatically activates and meets the water needs of the plant. Optimum use of irrigation water to be used in agriculture is prevented unnecessary agricultural irrigation, reducing excessive water waste and providing a very high level of energy savings. At the same time, the negativities caused by excessive irrigation have been prevented. It is observed that the automatic controlled irrigation system used in this study saves a lot of water compared to the conventional irrigation system and increases the productivity of the plants to a great extent.

Critical Limits for Soybean and Black Bean Root Growth, Based on Macroporosity and Penetrability, for Soils with Distinct Texture and Management Systems

Soil compaction is a worldwide problem in agricultural areas, and it is important to define soil properties and reference values that allow knowledge of the compaction level for decision making. The objective of this study was to define the critical values of physical properties associated with the compaction of soils. Three Ultisols and two Oxisols, under different management systems, were collected at different depths for an evaluation of particle size, volumetric moisture, bulk density, and porosity. In the field, soil resistance to penetration and the root length of the soybean and edible black bean crop were measured. The soil profiles presented horizontal layers with similar resistance, but in some cases, there is discontinuity of these layers, which allows the roots to use the zones of lower resistance to deepen in the profile. The values of bulk density and resistance to penetration critical to soybean and edible black bean (only in sandy loam soil) root growth, according to soil textural class, are: sandy loam = 1.66 Mg m−3 and 1.5 to 2 MPa; loam and clay loam = 1.52 Mg m−3 and 1 to 1.5 MPa; silty clay loam and silty clay = 1.32 Mg m−3 and 1.5 to 2 MPa; and clay = 1.33 to 1.36 Mg m−3 and 2 to 3.5 MPa.

Enhancement of nitrate removal under limited organic carbon with hydrogen‐driven autotrophic denitrification in low‐cost electrode bio‐electrochemical reactors

AbstractBACKGROUNDNitrate‐contaminated water is a concerning environmental and health problem in agricultural areas. Due to its low organic carbon content, such water cannot be purified using a conventional bioreactor with heterotrophic denitrification. Low‐cost bio‐electrochemical reactors were established with the aim of enhancing denitrification performance by cooperation of heterotrophic and hydrogenotrophic denitrification.RESULTSAt the lowest C/N ratio of 1.0, the bioreactor reached only 67.4% for NO3‐N removal and 47.5% for total N removal (total N removal rate of ca 1.2 mg L−1 h−1), whereas the Cu reactor (bio‐electrochemical reactor using copper wire as cathode) achieved the best efficiencies of 73.7% and 53.8% for NO3‐N and total N removal (total N removal rate of ca 1.3 mg L−1 h−1), and followed by the SS reactor (bio‐electrochemical reactor using stainless steel wire as cathode). On the other hand, the greatest total organic carbon (TOC) removal efficiency was observed for the bioreactor and followed by the SS reactor and the Cu reactor. The low TOC consumption of 1.2–1.4 mg‐TOC (mg‐N)−1 in the Cu reactor and the SS reactor indicated the enhanced denitrification from coexisting hydrogenotrophic denitrification. In addition, the performance of hydrogenotrophic denitrification was improved by increasing the applied current from 10 to 30 mA.CONCLUSIONSThe abundance of autotrophic denitrifying bacteria (identified as hydrogenotrophs) was higher than that of heterotrophic denitrifying bacteria in both the Cu reactor and the SS reactor. Archromobacter and Flavobacterium were the most dominant genera in the biofilm of the Cu reactor cathode and in the suspended sludge, respectively. Hydrogenophaga were detected in both biomass samples, but were absent from the biomass samples of the conventional bioreactor. © 2021 Society of Chemical Industry (SCI).

Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe

Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that ~75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least one-third of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.

FAKTOR RISIKO KERACUNAN PESTISIDA PADA PETANI HORTIKULTURA DI KABUPATEN LAMPUNG BARAT

Pesticide poisoning is still an important health problem in agricultural areas, especially horticultural agriculture. Various chronic health effects can be caused by long-term exposure to pesticides. This study aims to determine the risk factor of pesticide poisoning in horticultural farmers in West Lampung Regency. The study used a cross sectional design which was conducted in four different areas as the center of horticulture agriculture, West Lampung Regency, Lampung Province. The study involved 289 participants by interviewing, observing and examining blood samples to measure cholinesterase levels as an indicator of pesticide poisoning. In this section, we have applied research ethical procedures. The obtained data were analyzed using Chi squre test, Odds Ratio test and Logistic Regression. The results showed that the risk factors for pesticide poisoning were incomplete use of personal protected equipment (PPE), spraying with the wrong dose and spraying frequency. Unwearing a complete PPE had a 4.54 times (OR = 4.54; 95% CI 2.09-9.83) higher risk of experiencing pesticide poisoning, and statistically suggested, a very significant relationship (p = 0.0001). While the use of excessive dosage has a risk of 4.39 times (OR = 4.39; 95% CI 1.87-10.33; p = 0.001); and the frequency of spraying more than twice a week had a 2.33 times higher risk of experiencing pesticide poisoning (OR = 2.33; 95% CI 1.24-4.40; p = 0.009). Excessive use of pesticide dosage and the frequency of spraying with the cover blanked method are the main factors of pesticide exposure to farmers. On the other hand, the use of PPE is a method of protection from exposure. It needs joint efforts through increasing knowledge about the dangers of pesticides, pesticide management, how to work safely, and the use of PPE.

Spatial Prediction of Nitrate Concentration Using GIS and ANFIS Modelling in Groundwater.

Groundwater contamination by nitrate becomes a major problem in agricultural areas. Nitrate pollution in the groundwater of Coimbatore district of India has been investigated. Seventy-one observation wells within the study area were selected. The samples were collected in three stages with 6months interval during the years 2011 and 2012. The input for creating an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) model is the average of calcium, electrical conductivity, sodium, chlorides, hardness, potassium and the concentration of nitrate was the output from the model. Results of the best ANFIS model were assessed by deterministic, geostatistical and kernel smoothing methods using GIS. Out of the five models developed, ANFIS model V predicts nitrate concentration with 90% accuracy and less root mean square error (0.0934). The results from model V are given as input in GIS to predict spatial nitrate concentration in groundwater. Kriging method is more accurate in estimating nitrate concentration over the study area.

Loss of topsoil and soil erosion by water in agricultural areas: A multi-criteria approach for various land use scenarios in the Western Carpathians using a SWAT model

Erosion by water is a major problem in agricultural areas, especially in mountainous zones. In this context, the mass of detached soil clods is affected by surface run-off. In this paper, the utility of simulated data has been assessed toward various land use scenarios and soil erosion. The aim of the research was to model relevant management options in agriculture areas using spatial data. Long-term monitoring of sediment yield in top-soil loss dynamics models can be applied to evaluate the environmental effects of water pollution. In our study, we used data from 1995 to 2014 to analyze erosive events. The SWAT (Soil and Water Assessment Tool) was selected to assess the rill and inter-rill erosion. The investigations were carried out in an agricultural mountain catchment of the Mątny stream, located in the West Carpathians. Model calibration indices showed satisfactory adjustment of the model to the experimental data. Three scenarios of the catchment land use were distinguished (basic, first and second): the basic involved the actual structure of the land use, including a spring oat crop; in the first, the spring oat crop was replaced with potato crop; and in the second, it was assumed that the entire catchment area was covered by grassland. In the basic scenario, mean annual top-soil loss was 8.01 Mg ha−1, in the first it was 16.99 Mg ha−1, and in the second, 6.02 Mg ha−1. Thus, land management options can provide powerful constraints on predictions of sediment budget (Suspended Sediment Concentration). The management options simulated by SWAT model were important to effectively reduce top-soil loss in agricultural catchments.

Nitrogen contamination in groundwater in an agricultural region along the New Silk Road, northwest China: distribution and factors controlling its fate.

Nitrogen contamination is a global concern and has been a serious problem in agricultural areas. The present study was carried out in an intensively irrigated region of northwest China along the New Silk Road, Yinchuan Plain, where the residents depend on the groundwater as the primary source for drinking. To understand the nitrogen contamination in the aquifer system, the distribution of nitrate and ammonium and its controlling factors were studied based on hydrochemical, hydrogeological, and isotopic analyses. 11.37 and 40% of phreatic water samples are categorized as NO3-N and NH4-N pollution in accordance with the WHO standards. A total of 59.52% of confined water samples has high NH4-N values, exceeding the permissible limit for drinking purpose. The results indicate NO3-N predominates in the shallow water and NH4-N predominates in the deep water for the single phreatic aquifer. For the multilayer structure area, NO3-N predominates in the phreatic aquifer of the western and the southern parts of the plain; NH4-N predominates in the phreatic aquifer of the middle and the northern parts of the plain, and in the confined aquifers where groundwater pumping had been performed. The mixture of synthetic fertilizer and manure/sewage is primarily responsible for the phreatic water based on isotopic analysis. In the confined aquifers, higher NH4-N concentrations are mainly attributed to intensive pumping under higher pumping rates. The results of this study can be used as a scientific basis for the future research on nitrogen in the plain. They can also be used by scholars and decision makers who are interested in groundwater protection and sustainable development.

Selecting spatial scale of covariates in regression models of environmental exposures.

Environmental factors or socioeconomic status variables used in regression models to explain environmental chemical exposures or health outcomes are often in practice modeled at the same buffer distance or spatial scale. In this paper, we present four model selection algorithms that select the best spatial scale for each buffer-based or area-level covariate. Contamination of drinking water by nitrate is a growing problem in agricultural areas of the United States, as ingested nitrate can lead to the endogenous formation of N-nitroso compounds, which are potent carcinogens. We applied our methods to model nitrate levels in private wells in Iowa. We found that environmental variables were selected at different spatial scales and that a model allowing spatial scale to vary across covariates provided the best goodness of fit. Our methods can be applied to investigate the association between environmental risk factors available at multiple spatial scales or buffer distances and measures of disease, including cancers.

IMPACT OF BORON DEFICIENCY ON PLANT GROWTH

Boron (B) is a unique non-metal essential microelement for plants and constantly needed throughout plants life for normal growth and development. Boron deficiency became a world-wide problem in agricultural areas as its management is challenged due to the very minor difference in its deficiency and toxicity. The effects of insufficient B supply on various physical and growth parameters of plant can lead to plant death. The major roles of boron in plant development, the conditions which lead to deficiency, B deficiency symptoms and methods to overcome B deficiency are summarized in the present review work.

Modelling nitrate concentration of groundwater using adaptive neural-based fuzzy inference system

High nitrate concentration in groundwater is a major problem in agricultural areas in Iran. Nitrate pollution in groundwater of the particular regions in Isfahan province of Iran has been investigated. The objective of this study was to evaluate the performance of Adaptive Neural-Based Fuzzy Inference System (ANFIS) for estimating the nitrate concentration. In this research, 175 observation wells were selected and nitrate, potassium, magnesium, sodium, chloride, bicarbonate, sulphate, calcium and hardness were determined in groundwater samples for five consecutive months. Electrical conductivity (EC) and pH were also measured and the sodium absorption ratio (SAR) was calculated. The five-month average of bicarbonate, hardness, EC, calcium and magnesium are taken as the input data and the nitrate concentration as the output data. Based on the obtained structures, four ANFIS models were tested against the measured nitrate concentrations to assess the accuracy of each model. The results showed that ANFIS1 was the most accurate (RMSE = 1.17 and R<sup>2</sup> = 0.93) and ANFIS4 was the worst (RMSE = 2.94 and R<sup>2</sup> = 0.68) for estimating the nitrate concentration. In ranking the models, ANFIS2 and ANFIS3 ranked the second and third, respectively. The results showed that all ANFIS models underestimated the nitrate concentration. In general, the ANFIS1 model is recommendable for prediction of nitrate level in groundwater of the studied region.

Effects of fertilizer placement on solute leaching under ridge tillage and no tillage

Elevated nitrate concentrations in ground water can be a problem in agricultural areas, especially where soils are sandy. Tillage operations, such as ridge tillage (RT) and no tillage (NT) can reduce runoff and erosion but leaching of soluble nutrients could adversely impact groundwater. In a 2-year study, Br was used to trace the effects of fertilizer placement on solute movement under corn ( Zea mays L.) in RT and NT systems on a Monmouth fine sandy loam (Typic Hapludult) in Maryland. Treatments included 120 kg ha −1 of Br − or NO 3 −-N applied in a narrow band near the ridge top (RT-RA) or in the furrow (RT-FA) with ridge tillage, or in the inter-row with NT. Two-dimensional arrays of tensiometers and suction lysimeters were used to follow the movement of water and solutes during and after the corn-growing season. Tillage and fertilizer placement did not significantly affect N uptake when averaged across years. A pronounced argillic horizon beginning at 60 cm depth caused lateral movement of Br. It appears that Br leaching in RT-RA increased slightly due to the crop canopy funneling rain towards the ridge top. Therefore, when fertilizer is applied near the row, rain occurring after full corn canopy may cause greater solute leaching in RT-RA compared to other treatments. Rain during the beginning of the growing season or after harvest caused less leaching in RT-RA. Corn yield could be maximized and N leaching minimized by applying fertilizer to the upper portion of the ridge in RT.