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.

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 Factor analysis for soil test data: a methodological approach in environment friendly soil fertility management

2007 ◽  
Vol 8 ◽  
pp. 8-19 ◽  
Author(s):  
Hari Dahal
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Soil Fertility ◽  
Test Data ◽  
Methodological Approach ◽  
Principal Component ◽  
Component Analysis ◽  
Soil Test ◽  
Soil Fertility Management ◽  
Fertility Management

Soil test data were used in factor analysis employing the Principal Component Analysis technique for the reduction and summarization of soil variables. Principal component analysis was found to be highly suggestive in analyzing soil test data on which a rational fertilizer nutrients recommendation can be made for a sustainable soil fertility management reign. The Journal of AGRICULTURE AND ENVIRONMENT Vol. 8, 2007, pp. 8-19

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 Principal Component Analysis on Soil Fertility Parameters of Vegetable Growing Panchayats/ Locations in Ernakulam District of Kerala

2020 ◽  
pp. 58-65
Author(s):  
A. Muhsina ◽  
Brigit Joseph ◽  
Vijayaraghava Kumar
Keyword(s):  
Principal Component Analysis ◽  
Soil Fertility ◽  
Soil Ph ◽  
Principal Component ◽  
Component Analysis ◽  
Organic Carbon Content ◽  
Score Plot ◽  
Five Factors ◽  
Total Variability ◽  
High Level

The present paper used Principal Component Analysis (PCA) on 13 soil fertility parameters including soil pH and electrical conductivity of 17 vegetable growing panchyat/locations in Ernakulam district of Kerala based on 583 soil samples. Soil pH of panchayats varied from 4.2- 5.8 with a coefficient of variation 3.16-12.23 per cent and it was inferred that most of the panchayats in the district had very strongly acidic (pH: 4.2-5) and strongly acidic soils (pH: 5-5.5). High level of organic carbon content was noticed in most of the panchayats except in four panchayats. The results of PCA revealed that five PC’s together explained a total variability of 80 per cent and the remaining PCs accounted for 20 per cent of the variability in the data which has been discarded from further analysis. First principal component accounted for 25 per cent variance followed by PC 2(21%), PC 3(14%), PC 4(10%) and PC 5(10%). Factor analysis generated five factors and they explained 85 per cent of variability. Score plot drawn as part of PCA showed that Chengamanadu, Manjapra and Thirumaradi panchayats had high content of soil available S and B. EC was also found to be higher in these panchayats. Amount of OC, Fe and Mn were more in Kalady, Keerampara and Mudakkuzha of Ernakulam district whereas Thuravur, Piravom and Pothanikkad had highly acidic and Mg rich soils. Amount of Zn was more in Vengoor panchayat. Available K, Ca, P and Cu were found to be higher in Kakkad, Nedumbassery, Vengola and Kadungalloor. Based on the fertility status of each panchayats, they could be classified into different groups.

scholarly journals Effect of Mid-Term Cropping System Adoption on Soil Chemical Properties at Changunarayan Municipality, Bhaktapur, Nepal

2021 ◽  
Vol 8 (2) ◽  
pp. 80-89
Author(s):  
Saroj Koirala ◽  
Santosh Shrestha ◽  
Prashanta Raut ◽  
Bikram Pandey ◽  
Arbindra Timilsina
Keyword(s):  
Organic Matter ◽  
Total Nitrogen ◽  
Soil Ph ◽  
Cropping Systems ◽  
C:N Ratio ◽  
Chemical Properties ◽  
Soil Chemical Properties ◽  
Future Research ◽  
Available Phosphorus ◽  
Wide Range

Soil chemical properties plays a crucial role in crop yield. In this study, we evaluated the chemical properties of soils under three different cropping systems practiced for more than five years in Changunarayan municipality of Bhaktapur district of Nepal. The cropping systems includes- (i) cultivation inside polyhouse (Treatment A: polyhouse), (ii) paddy-wheat rotation (Treatment B: P-W), and (iii) paddy-wheat-vegetable rotation (Treatment C: P-W-V). Thirty-nine composite samples (13 replicates from each site) were taken from the area based on variation in landforms. Soil pH, organic matter (%), total nitrogen (%), available phosphorus (mgkg-1), and available potassium (mgkg-1) were evaluated for each sample. The study revealed that the soil pH was acidic and ranges between 4.71 and 5.39, organic matter (1.6-2.39%), total nitrogen (0.091-0.13%), phosphorus (4.48-29.24mg kg-1) and potassium (88.04-109.52 mg kg-1). A significant lower mean pH (4.71), and higher mean organic matter (2.39%), total nitrogen (0.13%) and available phosphorus (29.24 mgkg-1) were observed in cultivation under polyhouse. Incorporation of vegetable in paddy-wheat system gave significant (p<0.05) higher accumulation of soil phosphorus and consistently raised other nutrient status. Moreover, cultivation under polyhouse raised C:N ratio (10.55) significantly than other system. This finding can be relevant to wide range of readers that focus on soil chemical properties and can be used in developing future research strategy and sustainable soil management system in the area.

scholarly journals PENGARUH APLIKASI KOMPOS KOTORAN SAPI DAN PAITAN TERHADAP SIFAT KIMIA TANAH DAN PERTUMBUHAN TANAMAN KEDELAI

2020 ◽  
Vol 8 (1) ◽  
pp. 123-133
Author(s):  
Putri Alfira Zuraida ◽  
Yulia Nuraini
Keyword(s):  
Organic Matter ◽  
Soil Fertility ◽  
Agricultural Land ◽  
Block Design ◽  
Organic Fertilizer ◽  
Chemical Properties ◽  
Soil Chemical Properties ◽  
Agricultural Product ◽  
Cow Dung ◽  
Randomized Block Design

Fertile agricultural land encourages people to carry out agricultural cultivation activities. But in general, it has decreased soil fertility because its managed intensively without recycling of organic matter and has an impact on decreasing soil fertility chemically such as soil organic carbon and pH then leads to low productivity. Soybean is an agricultural product that necessary to develop because the demand for soybean consumption in East Java Province has always increased. However, Indonesia has not been able to fulfil this demand. One of the technology innovations that can be applied to improve soil fertility that has low organic matter and to increasing soybean production by providing input of quality organic fertilizer in the form of compost (Tithonia and Cow Dung). So this research is important to determine the effect of application cow dung compost and tithonia on soil chemical properties, the growth of soybean crops, and the correlations between soil chemical properties and soybean growth. This study used a randomized block design with 6 treatments and 3 replications. The result showed that the application of tithonia and cow dung compost shows a significant effect on soil chemical properties, plant height, and the number of leaves, but didn’t show a significant effect on the number of branches in every observation. Based on the correlation analysis, the results show a positive correlation between soil chemical properties and soybean growth.

scholarly journals ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA

2012 ◽  
Vol 6 (1) ◽  
pp. 31-40
Author(s):  
Gresyea L. Marcus ◽  
Henry J. Wattimanela ◽  
Yopi A. Lesnussa
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Least Square Method ◽  
Component Analysis ◽  
Least Square ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Analysis Technique ◽  
Independent Variable ◽  
Very High

The climate in Ambon, are influenced by sea climate and season climate, cause of this island arrounded by sea, it is make very high rainfall intensity. A very high collinearity between independent variables, make the estimate can not rely be ordinary least square method so it market with not real regretion coefficient and the collinearity. Collinearity can be detected by linier correlation coefficient between independent variables and also with VIF way. Regretion principal component analysis is used to remove collinearity and all of independent variable into model, this analysis is regretion analysis technique wher eare combinated with principal component analysis technique. The object of this analysis is to simplify the variable by overcast it dimension, we can do it removes the correlation between coefficient by transformation. Regresion can help to solve this case rainfall in Ambon on 2010. So the colinearity to independent variables can be overcome and then we can get the best regretion rutes.

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