Assessments of Sweet potato Virus Disease and Influence of Mulching and Organic Insecticide on Sweet Potato Varieties in Kwara State of Nigeria

Aliyu, Taiye Hussein; Popoola, Judoka; Olatinwo, Latifat Kehinde; Eifediyi, E.K.; Arogundade, Olawale

doi:10.4038/jfa.v13i2.5229

Cited by 2 publications

(5 citation statements)

References 15 publications

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“…However, different parameters are used to evaluate and monitor irrigation water quality due to the differences in its context. The parameters most commonly used for irrigation water quality assessment worldwide are electrical conductivity (EC), iron concentration (Fe), pH, and total hardness [26][27][28][29][30][31], as well as the presence and concentration of microorganisms able to cause emitter clogging.…”

Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

“…High values may indicate water's corrosive characteristics. It is considered the most used parameter for evaluating salinity levels and concentrations of soluble salts in water for irrigation use [26,27].…”

Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

“…pH is essential because it influences chemical balances occurring naturally or in unitary water treatment processes. The indirect effect is also significant and can, under certain pH conditions, contribute to the precipitation of chemical elements, exerting effects on nutrient solubilities [27,28].…”

Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

“…Thus, it is typical to use only a few of them in studies on water quality for irrigation, such as pH, EC, iron (Fe), and water hardness. These parameters are more accessible to measure and directly affect the emitters clogging and the formation of microorganisms related to the emitters clogging, especially iron bacteria [27][28][29]31].…”

Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

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A Data-Driven Method for Water Quality Analysis and Prediction for Localized Irrigation

da Silva,

Benso,

Corrêa

et al. 2024

AgriEngineering

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Several factors contribute to the increase in irrigation demand: population growth, demand for higher value-added products, and the impacts of climate change, among others. High-quality water is essential for irrigation, so knowledge of water quality is critical. Additionally, water use in agriculture has been increasing in the last decades. Lack of water quality can cause drip clog, a lack of application uniformity, cross-contamination, and direct and indirect impacts on plants and soil. Currently, there is a need for more automated methods for evaluating and monitoring water quality for irrigation purposes, considering different aspects, from impacts on soil to impacts on irrigation systems. This work proposes a data-driven method to address this gap and implemented it in a case study in the PCJ river basin in Brazil. The methodology contains nine components and considers the main steps of the data lifecycle and the traditional machine learning workflow, allowing for automated knowledge extraction and providing important information for improving decision making. The case study illustrates the use of the methodology, highlighting its main advantages and challenges. Clustering different scenarios in three hydrological years (high, average, and lower streamflows) and considering different inputs (soil-related metrics, irrigation system-related metrics, and all metrics) helped generate new insights into the area that would not be easily obtained using traditional methods.

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Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

Section: Irrigation Water Quality Metricsmentioning

confidence: 99%

See 2 more Smart Citations

A Data-Driven Method for Water Quality Analysis and Prediction for Localized Irrigation

da Silva,

Benso,

Corrêa

et al. 2024

AgriEngineering

View full text Add to dashboard Cite

show abstract

“…Some approaches have been applied for the evaluation of the irrigation water effect on soils and plants. Numerous researchers have used hydro-chemical indices such as SAR, Na%, KI, MR, PI and the Index of Base Change, the chloro-alkaline index (CAI) and the Hydrochemical Facies Evolution Diagram [22][23][24][25][26][27]. Instead of using a single parameter, for better results, the combined use of the chemical analyses of all ions is expected to be a better solution [28].…”

Section: Introductionmentioning

confidence: 99%

Detection of Groundwater Quality Changes in Minia Governorate, West Nile River

et al. 2023

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The need for freshwater supplies is increasingly rising according to the increase in the inhabitants’ expansion and economic growth. Available water resources are reduced by pollution and overpumping. This research’s prime objective is to study changes in the water quality of the Pleistocene aquifer in Minia Governorate. Historical hydro-chemical data of the groundwater in two years 2009 and 2019 were used to study the changes in the groundwater quality of the Pleistocene aquifer under the impact of the recharge and discharge processes. The Nile River, and the Al-Ibrahimia and Bahr Youssef Canals are considered the main sources of aquifer recharge. Collected data from 53 groundwater wells in the Pleistocene aquifer were used to calculate the sodium adsorption ratio (SAR), sodium percentage (Na%), Kelly index (KI), Soluble Sodium Percentage (SSP), magnesium ratio (MR%), permeability index (PI) and chloro-alkaline index (CAI). These data were used to evaluate and detect the quality and changes in groundwater through the years 2009 and 2019 using spatial mapping in the geographic information system (GIS). The values of SAR, KI and Na% varied between 0.06–1.22, 0.02–0.57 meq/L and 3.7–37.63%, respectively, in the year 2009, but these values changed to 0.4–0.75, 0.16–0.28 meq/L and 15.07–23.44% in the year 2019. The calculated MR and PI values indicate that 100% of the groundwater samples were in the “suitable” category. The calculated SSP reflects no changes in groundwater alkalinity between the years 2009 and 2019. The hydro-chemical analysis of the studied groundwater (G.W.) samples shows high pollution levels caused by Pb and Fe in some parts of the study area. Pb was found to be >40 µg/L in the middle parts, whereas Fe was found with high levels in 27% of the studied groundwater samples. The localities of these samples were affected by pollution from the industrial wastewater from the sugar factory of Abou-Qarqas city (e.g., El-Moheet drain), the fertilizer leaching process and pesticides seeping into groundwater from soils and agricultural wastewater.

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Assessments of Sweet potato Virus Disease and Influence of Mulching and Organic Insecticide on Sweet Potato Varieties in Kwara State of Nigeria

Cited by 2 publications

References 15 publications

A Data-Driven Method for Water Quality Analysis and Prediction for Localized Irrigation

A Data-Driven Method for Water Quality Analysis and Prediction for Localized Irrigation

Detection of Groundwater Quality Changes in Minia Governorate, West Nile River

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