scholarly journals Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation

2012 ◽  
Vol 36 (2) ◽  
pp. 467-474 ◽  
Author(s):  
Samuel de Assis Silva ◽  
Julião Soares de Souza Lima
Keyword(s):  
Principal Component Analysis ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Saturation Index ◽  
Great Influence ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Information Loss ◽  
Coffee Cultivation

The spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 - 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K+, Ca2+, Mg2+, Na+, S, Al3+, pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characteristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.

scholarly journals Magnetic susceptibility to identify landscape segments on a detailed scale in the region of Jaboticabal, São Paulo, Brazil

2012 ◽  
Vol 36 (4) ◽  
pp. 1073-1082 ◽  
Author(s):  
Mariana dos Reis Barrios ◽  
José Marques Junior ◽  
Alan Rodrigo Panosso ◽  
Diego Silva Siqueira ◽  
Newton La Scala Junior
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Magnetic Susceptibility ◽  
Clay Fraction ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Sao Paulo ◽  
São Paulo ◽  
Agricultural Potential

The agricultural potential is generally assessed and managed based on a one-dimensional vision of the soil profile, however, the increased appreciation of sustainable production has stimulated studies on faster and more accurate evaluation techniques and methods of the agricultural potential on detailed scales. The objective of this study was to investigate the possibility of using soil magnetic susceptibility for the identification of landscape segments on a detailed scale in the region of Jaboticabal, São Paulo State. The studied area has two slope curvatures: linear and concave, subdivided into three landscape segments: upper slope (US, concave), middle slope (MS, linear) and lower slope (LS, linear). In each of these segments, 20 points were randomly sampled from a database with 207 samples forming a regular grid installed in each landscape segment. The soil physical and chemical properties, CO2 emissions (FCO2) and magnetic susceptibility (MS) of the samples were evaluated represented by: magnetic susceptibility of air-dried fine earth (MS ADFE), magnetic susceptibility of the total sand fraction (MS TS) and magnetic susceptibility of the clay fraction (MS Cl) in the 0.00 - 0.15 m layer. The principal component analysis showed that MS is an important property that can be used to identify landscape segments, because the correlation of this property within the first principal component was high. The hierarchical cluster analysis method identified two groups based on the variables selected by principal component analysis; of the six selected variables, three were related to magnetic susceptibility. The landscape segments were differentiated similarly by the principal component analysis and by the cluster analysis using only the properties with higher discriminatory power. The cluster analysis of MS ADFE, MS TS and MS Cl allowed the formation of three groups that agree with the segment division established in the field. The grouping by cluster analysis indicated MS as a tool that could facilitate the identification of landscape segments and enable the mapping of more homogeneous areas at similar locations.

scholarly journals The influence of ecological restoration projects on groundwater in Yongding River Basin in Beijing, China

2019 ◽  
Vol 19 (8) ◽  
pp. 2391-2399 ◽  
Author(s):  
Zhuoran Luo ◽  
Shuqi Zhao ◽  
Jin Wu ◽  
Yongxiang Zhang ◽  
Peibin Liu ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Groundwater Quality ◽  
Ecological Restoration ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Spatial And Temporal Variation ◽  
Beijing China ◽  
The Yongding River ◽  
Yongding River

Abstract This study was conducted to investigate the groundwater quality features of the Yongding River in Beijing, China, and its relationship with urban development and ecological restoration projects. The Yongding River has been cut off all year around and the ecological environment has continued to deteriorate. Therefore, a series of river ecological restoration projects of ‘Five Lakes on One Route’ have been implemented. In order to characterize the physico-chemical properties of groundwater and evaluate the effects of these projects on groundwater quality, by using principal component analysis, this study analyzed spatial and temporal variation on the basis of 11 water quality parameters at 10 monitoring sites of ‘Five Lakes on One Route’ for Yongding River during April and September of 2011 and 2016. Principal component analysis demonstrated that relatively poor groundwater is mainly distributed in Fengtai District residential and industrial land, and the groundwater in Mentougou District woods is generally better. The groundwater quality at eight monitoring sites kept the same level or became better, and the construction of the river ecological restoration projects of ‘Five Lakes on One Route’ is important for protecting the groundwater resource.

scholarly journals Diversity of entomopathogenic fungi associated with Mediterranean fruit fly (Ceratitis capitata (Diptera: Tephritidae)) in Moroccan Argan forests and nearby area: impact of soil factors on their distribution

BMC Ecology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ayoub Hallouti ◽  
Mohamed Ait Hamza ◽  
Abdelaziz Zahidi ◽  
Rachid Ait Hammou ◽  
Rachid Bouharroud ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Entomopathogenic Fungi ◽  
Ceratitis Capitata ◽  
Chemical Properties ◽  
Principal Component ◽  
Fruit Fly ◽  
Component Analysis ◽  
Organic Content ◽  
Pathogenicity Test ◽  
Factors Affecting

Abstract Background Studying the ecology of biocontrol-agents is a prerequisite to effectively control medfly (Ceratitis capitata (Diptera: Tephritidae)) with entomopathogenic fungi. In this context, factors affecting the occurrence and distribution of medfly-associated entomopathogenic-fungi were studied. Soil samples (22) were collected from natural and cultivated areas of Souss-region Morocco. Results A total of 260 fungal isolates belonging to 22 species and 10 genera were obtained by using medfly pupae as bait. Medfly-associated fungi were detected in all studied soils and pupae infection percentages ranged from 3.33% to 48%. Two genera, Fusarium and Beauveria were the most frequent with 83 isolates (32%) and 50 isolates (19.23%) respectively. Pathogenicity test of isolated species against medfly pupae showed high mortality rates up to 91% for some strains. Principal component analysis (PCA) demonstrated a strong influence of origin, physical, and chemical properties of soil on the abundance of these fungi. In general, medfly-associated fungi were more abundant in soils with moderate pH (7.5 to 8) having high sand and organic content. High relative humidity negatively influenced the abundance of these fungi. Both factors directly affected the fungal infection percentages in pupae. The response of fungi to these parameters varied among species. According to principal component analysis (PCA), the soils of argan fields and forests were more suitable for the development of medfly-associated fungi than citrus orchards. Conclusions These results guide identifying suitable soils for the effective application of entomopathogenic fungi as biological control agents. In summary, isolated indigenous strains seem to be a promising option to control C. capitata.

scholarly journals Agro-climatic classification in India

MAUSAM ◽  
2021 ◽  
Vol 44 (1) ◽  
pp. 53-60
Author(s):  
A. CHOWDHURY ◽  
H. P. DAS ◽  
S.S. SINGH
Keyword(s):  
Principal Component Analysis ◽  
Soil Moisture ◽  
Spatial Variability ◽  
Principal Component ◽  
Component Analysis ◽  
Climatic Zones ◽  
Climatic Classification ◽  
Agroclimatic Zones ◽  
Rainy Days

In the present study, principal component analysis has been applied to agroclimatic variables for delineating India into homogeneous agroclimatic zones for kharif crops. The vaTiates chosen were soil moisture, water need of the crops, number of rainy days and radiation. Spatial variability of some of these factors has been discussed. Vector 1 and vector 2 were obtained for each of the three separate sets of the variates and plotted to obtain grid maps. Through a process of successive superimposition of these maps, agro-climatic zones have been obtained.  

scholarly journals Characterization of soil chemical properties of strawberry fields using principal component analysis

2013 ◽  
Vol 37 (1) ◽  
pp. 168-176 ◽  
Author(s):  
Gláucia Oliveira Islabão ◽  
Marília Alves Brito Pinto ◽  
Lisiane Priscila Roldão Selau ◽  
Ledemar Carlos Vahl ◽  
Luís Carlos Timm
Keyword(s):  
Principal Component Analysis ◽  
Organic Matter ◽  
Soil Fertility ◽  
Organic Matter Content ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Soil Chemical Properties ◽  
Available Phosphorus ◽  
Very High

One of the largest strawberry-producing municipalities of Rio Grande do Sul (RS) is Turuçu, in the South of the State. The strawberry production system adopted by farmers is similar to that used in other regions in Brazil and in the world. The main difference is related to the soil management, which can change the soil chemical properties during the strawberry cycle. This study had the objective of assessing the spatial and temporal distribution of soil fertility parameters using principal component analysis (PCA). Soil sampling was based on topography, dividing the field in three thirds: upper, middle and lower. From each of these thirds, five soil samples were randomly collected in the 0-0.20 m layer, to form a composite sample for each third. Four samples were taken during the strawberry cycle and the following properties were determined: soil organic matter (OM), soil total nitrogen (N), available phosphorus (P) and potassium (K), exchangeable calcium (Ca) and magnesium (Mg), soil pH (pH), cation exchange capacity (CEC) at pH 7.0, soil base (V%) and soil aluminum saturation(m%). No spatial variation was observed for any of the studied soil fertility parameters in the strawberry fields and temporal variation was only detected for available K. Phosphorus and K contents were always high or very high from the beginning of the strawberry cycle, while pH values ranged from very low to very high. Principal component analysis allowed the clustering of all strawberry fields based on variables related to soil acidity and organic matter content.

Polluted aquifers: identification and characterisation by statistical analysis

2010 ◽  
Vol 61 (2) ◽  
pp. 331-337 ◽  
Author(s):  
Analía Boemo ◽  
Haydée Musso ◽  
Irene Lomniczi
Keyword(s):  
Principal Component Analysis ◽  
Hierarchical Clustering ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Underground Water ◽  
Chemical Components ◽  
Eastern Area ◽  
Western Area ◽  
Physical And Chemical

Hierarchical clustering and principal component analysis applied to chemical components and physicochemical properties of well water proved to be a useful tool for identification and characterisation of aquifers. Underground water of Lerma Valley (Salta, Argentina) was examined for its physical and chemical properties by sampling 46 wells located in two adjacent areas separated by hills, one of them polluted with boron since 1991. Hierarchical clustering splits sampled sites into two main clusters, corresponding to the two areas, establishing the fact that the aquifers should be considered as two different entities in spite of their common recharge area. Values of boron concentration in the eastern area decreased in most of the wells since the pollution sources were eradicated, while four of them experienced a substantial increase, proof of the slow self-recovery of the aquifer. The use of principal component analysis provided evidence of the incipient boron pollution of the aquifer of the western area.

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps, cluster, and Principal Component Analysis

2009 ◽  
Vol 43 (25) ◽  
pp. 3829-3836 ◽  
Author(s):  
Gabriel Ibarra-Berastegi ◽  
Jon Sáenz ◽  
Agustín Ezcurra ◽  
Unai Ganzedo ◽  
Javier Díaz de Argandoña ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Air Quality ◽  
Spatial Variability ◽  
Principal Component ◽  
Component Analysis ◽  
Self Organizing Maps ◽  
Self Organizing

scholarly journals Diversity of entomopathogenic fungi associated with Mediterranean fruit fly (C. capitata) in Moroccan Argan forests and nearby area: impact of soil factors on their distribution

2020 ◽  
Author(s):  
Ayoub HALLOUTI ◽  
Mohamed AIT HAMZA ◽  
Abdelaziz ZAHIDI ◽  
Rachid AIT HAMMOU ◽  
Rachid BOUHARROUD ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Entomopathogenic Fungi ◽  
Chemical Properties ◽  
Principal Component ◽  
Fruit Fly ◽  
Component Analysis ◽  
Organic Content ◽  
Pathogenicity Test ◽  
Factors Affecting ◽  
Physical And Chemical

Abstract Background: Studying the ecology of biocontrol-agents is a prerequisite to effectively control medfly (C. capitata) with entomopathogenic fungi. In this context, factors affecting the occurrence and distribution of medfly-associated entomopathogenic-fungi were studied. Soil samples (22) were collected from natural and cultivated areas of Souss-region Morocco. Results: A total of 260 fungal isolates belonging to 22 species and 10 genera were obtained by using medfly pupae as bait. Medfly-associated fungi were detected in all studied soils and pupae infection percentages ranged from 3.33% to 48%. Two genera, Fusarium and Beauveria were the most frequent with 83 isolates (32%) and 50 isolates (19.23%) respectively. Pathogenicity test of isolated species against medfly pupae showed high mortality rates up to 91% for some strains. Principal component analysis (PCA) demonstrated strong influence of origin, physical and chemical properties of soil on the abundance of these fungi. In general, medfly-associated fungi were more abundant in soils with moderate pH (7.5 to 8) having high sand and organic content. High relative humidity negatively influenced the abundance of these fungi. Both factors directly affected the fungal infection percentages in pupae. The response of fungi to these parameters varied among species. According to principal component analysis (PCA) the soils of argan fields and forests were more suitable for the development of medfly-associated fungi than citrus orchards. Conclusions: These results provide guidance on identifying suitable soils for effective application of entomopathogenic fungi as biological control agents. In summary, isolated indigenous strains seem to be a promising option to control C. capitata.

ETUDE PAR L’ANALYSE EN COMPOSANTES PRINCIPALES DES PROPRIETES CHIMIQUES D’UN SOL FORESTIER 10 ANS APRES ECLAIRCIE

1977 ◽  
Vol 57 (2) ◽  
pp. 147-156 ◽  
Author(s):  
A. GONZALEZ ◽  
M. BOUDOUX ◽  
G. HUBERT
Keyword(s):  
Principal Component Analysis ◽  
Multivariate Analysis ◽  
Sugar Maple ◽  
Chemical Properties ◽  
Basal Area ◽  
Principal Component ◽  
Component Analysis ◽  
Beech Forest ◽  
Analysis Technique

Principal component analysis was used to illustrate the evolution of chemical properties of a soil under sugar maple–beech forest, following two levels of thinning (30 and 50% of basal area). This multivariate analysis technique clearly showed that there were no significant differences between treated and untreated soils 10 yr after thinning.

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