Spatio-temporal Soil Quality Assessment under Crop Rotation Irrigated with Treated Urban Wastewater using Fuzzy Modelling

Ghaemi, Marjan; Astaraei, Ali Reza; Mahalati, M Nassiri; Emami, Hojat; Sanaeinejad, Hossein

doi:10.2478/intag-2014-0019

Cited by 14 publications

(4 citation statements)

References 26 publications

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“…The spatial and temporal variability of soil attributes and those related to plants have been carried out in several studies considering the fuzzy classification (WANG et al, 2008;KIM et al, 2013, GHAEMI et al, 2014. As regards coffee, there is the application of fuzzy logic in several studies (FONSECA, JESUS, and LIMA, 2016.…”

Section: Methodsmentioning

confidence: 99%

Fuzzy Logic in the Spatial and Temporal Distribution in the Quality of the Beverage in Conilon Coffee

Fonseca¹,

Lima

Silva

et al. 2019

C.Sci.

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<p>The objective in this study was to evaluate the spatial and temporal variability of the beverage quality by applying the fuzzy classification in the final global sensory analysis, for Coffea canephora Pierre ex A. Froehner, in two consecutive harvests. The studied variables were: fragrance (aroma), flavor, bitterness (sweetness), set, balance, cleaning, aftertaste, mouth feel, uniformity, salinity (acidity) and drink (global note). To the average overall scores of the drinks obtained on the cup-tasting at 80.0 points of a sampling, the mesh has applied the function of association of the fuzzy classification linear model to determine the degree of pertinence. The data were analyzed by the descriptive statistics and then by geostatistics to verify the existence and quantify the degree of spatial dependence of the variables. In the interval classified as “very good coffee” is found in the global average grade, in the two harvests. The methodology fuzzy applied in the global beverage note of the coffee conilon seminal made it possible to determine their spatial variability in the same distribution pattern in the two harvests, close ranges, and adjustments to the spherical model, which was confirmed by the spatial correlation of 61.6% among the fuzzy maps for the global score</p>

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Section: Methodsmentioning

confidence: 99%

Fuzzy Logic in the Spatial and Temporal Distribution in the Quality of the Beverage in Conilon Coffee

Fonseca¹,

Lima

Silva

et al. 2019

C.Sci.

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show abstract

“…Step 3: The retrieved literature was counted, and the evaluation indices used in the selected literature were divided into four categories: physics [27,28], chemistry [29,30], biological [31,32] and environment [33,34]. Finally, the frequency of index selection was analysed.…”

Section: Methods Of Indices Selectionmentioning

confidence: 99%

Research on the Evaluation Index System of the Soil Remediation Effect Based on Blockchain

Wang

Liang

2021

Land

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Soil remediation technology has achieved good results at present, but evaluation research on the soil remediation effect is relatively lacking. In the field of soil remediation effect evaluation, there are problems such as unscientific and imperfect indices and the inability to guarantee the authenticity of data. Based on the research results of domestic and foreign scholars and the soil remediation standards of some developed countries, a set of recommended indices for soil remediation evaluation has been formed through the analysis and screening of a large number of documents and the results of expert consultation. However, there are phenomena such as lack of data authenticity, information asymmetry, and low supervision efficiency. Based on the technical characteristics of the blockchain and the current soil remediation effect evaluation requirements, combined with the research results of domestic and foreign scholars and the soil remediation standards of some developed countries, the core technology and corresponding application scenarios were analysed for functional requirements in this paper. The introduction of blockchain technology will improve the authenticity of data and form a decentralized, trustworthy, and traceable supervision model. Finally, an evaluation index system of the soil remediation effect based on blockchain was constructed from the following five aspects: collection of soil remediation indices, the addition of a new blockchain-based soil remediation effect evaluation and supervision model, the determination of index weights, a list of soil remediation effect evaluation indices, and providing feedback and suggestions. Through the application of blockchain technology and the innovative addition of the “regional policy” evaluation index, changes and innovations were made in all aspects of the soil remediation effect evaluation process.

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“…The soil quality index has been determined based on the total data set (TDS) of soil characteristics and minimum data set (MDS) (Ghaemi 2014, Gholoubi 2018, Govaerts et al 2006, Gugino et al 2009, Ranjbar et al 2016. These characteristics should be responsive, flexible, easily measurable and related to management operations and environmental changes (Jarecki andLal 2003, Karlen 1998).…”

Section: Introductionmentioning

confidence: 99%

Effects of Crop Residues and Tillage Operations on Soil Quality Indices

Emami¹,

Riahinia²

2021

pjss

Self Cite

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Tillage and plant residues influence soil attributes and, consequently, soil quality. Therefore, suitable management and maintaining the stability of soil structure is important. This study was performed to evaluate the effects of tillage systems on soil quality during a 4-year crop rotation (wheat, canola, wheat and tomato) at the Agricultural Research Center of Khorasan Razavi province (Iran) from 2011 to 2015. The study was conducted as a randomized complete block design in a factorial arrangement with 3 replications. For this purpose, conventional tillage (CT), minimum tillage (MT) and no-tillage (NT) systems together with three rates of plant residues (0, 1,500, and 3,000 kg ha -1 ) were applied annually after harvesting. Soil quality was determined by using the integrated quality index (IQI) and Nemoro quality index (NQI) based on total data set (TDS) and minimum data set (MDS). In total, 23 physical, chemical, and biological soil characteristics were considered as TDS and 7 out of these were selected as MDS for use in the principal component analysis (PCA). Soil quality in different tillage treatments was determined and the most appropriate indices and effective characteristics for soil quality assessment were selected. Correlation coefficients between IQI TDS and IQI MDS (r = 0.69) and between NQI TDS and NQI MDS (r = 0.76) showed that NQI was a better indicator for assessing soil quality. The NQI TDS provided a more accurate and comprehensive assessment of soil quality. However, using MDS reduced the cost and time with proper precision. Soil quality in MT and NT treatments was more desirable than the CT system, and the addition of plant residues improved the soil quality. According to the results of NQI TDS , IQI TDS , and IQI MDS , soil quality in the NT system with 3,000 kg ha -1 of plant residues and the MT system with 1,500 and 3,000 kg ha -1 of plant residues were more favorable than other soil tillage treatments. Soil characteristics that decreased soil quality in the conven-

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Spatio-temporal Soil Quality Assessment under Crop Rotation Irrigated with Treated Urban Wastewater using Fuzzy Modelling

Cited by 14 publications

References 26 publications

Fuzzy Logic in the Spatial and Temporal Distribution in the Quality of the Beverage in Conilon Coffee

Fuzzy Logic in the Spatial and Temporal Distribution in the Quality of the Beverage in Conilon Coffee

Research on the Evaluation Index System of the Soil Remediation Effect Based on Blockchain

Effects of Crop Residues and Tillage Operations on Soil Quality Indices

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