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

Islabão, Gláucia Oliveira; Pinto, Marília Alves Brito; Selau, Lisiane Priscila Roldão; Vahl, Ledemar Carlos; Timm, Luís Carlos

doi:10.1590/s0100-06832013000100017

Cited by 10 publications

(8 citation statements)

References 12 publications

(9 reference statements)

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“…is might be due to the leaching of basic cations, removal of bases by crop harvest, and Al hydrolysis. Various research results showed that basic cations removal through crop harvest [30,43,44], leaching due to excessive precipitation, steepness of the topography, application of inorganic fertilizer [44,45], and mineralization and formation of humic substances [46] were reported as causes for soil acidity formation. Cardelli et al [47] and Alexandra et al [48] also indicated that H + ion released through nitrification of NH 4 + sourced fertilizers on cultivated lands might also encourage the development of lower pH.…”

Section: Soil Ph and Exchangeablementioning

confidence: 99%

Explaining Soil Fertility Heterogeneity in Smallholder Farms of Southern Ethiopia

Laekemariam

Kibret

2020

Applied and Environmental Soil Science

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Soil is spatially heterogeneous and needs site-specific management. However, soil nutrient information at larger scale in most cases is lacking. Consequently, fertilizer advisory services become dependent upon blanket recommendation approach. Subsequently, it affects yield and profitability. This study is aimed at explaining soil fertility heterogeneity in Wolaita zone, Southern Ethiopia. About 789 soil samples were collected to evaluate soil physical (color, particle size, and bulk density) and chemical properties (pH, OC, N, P, K, Ca, Mg, B, Cu, Fe, Mn, Zn, PBS, and CEC). The laser diffraction method for soil particles and mid-infrared diffused reflectance (MIR) spectral analysis for OC, TN, and CEC determination were employed. Mehlich-III extraction and inductively coupled plasma (ICP) spectrometer measurement were used for the remaining elements. The result based on principal component analysis showed that 52% of the total variations were explained by exchangeable bases, CEC, pH, available P, Cu, B, and particle sizes. Clay texture and acidic soil reaction are dominant. Soil parameters with the following ranges were found at low status: soil OC (0.2–6.9%), total N (0.01–0.7%), available P (0.1–238 mg/kg), S (4–30 mg/kg), B (0.01–6.9 mg/kg), and Cu (0.01–5.0 mg/kg). Besides, low levels of exchangeable Ca, Mg, and K (Mg-induced K deficiency) on 22, 34, and 54% soil samples, respectively, were recorded. The soil contained sufficient Fe, Zn, and Mn. In conclusion, the study aids in developing practical decision for optimum soil management interventions and overcomes lower productivity occurring due to fertilizer use that is not tailored to the local conditions. Overall, continuous cropping, low return of crop residues, and low and/or no fertilizer application might have caused the low status of N, P, K, S, B, and Cu. Therefore, application of inorganic fertilizers specific to the site, lime in acidic soils, and organic fertilizers are recommended to restore the soil fertility and improve crop productivity.

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Section: Soil Ph and Exchangeablementioning

confidence: 99%

Explaining Soil Fertility Heterogeneity in Smallholder Farms of Southern Ethiopia

Laekemariam

Kibret

2020

Applied and Environmental Soil Science

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“…PCA is one of the statistical tools that can be used to study the relationship between the chemical properties of the soil/plant or the relationship between them. Several studies investigating the relationship between soil properties and vegetation have been conducted using PCA [23,24,25,26].…”

Section: Introductionmentioning

confidence: 99%

Seasonal Changes of Some Metabolites in Hyoscyamus boveanus (Dunal) Asch. & Schweinf – Saint Katherine, South Sinai, Egypt

El-Absy

2021

AJOB

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This study was conducted to investigate the effects of seasonal fluctuations on some metabolites and to explore the correlation between soil and plant analysis in Hyoscyamus boveanus (H.boveanus) at the Wadi El-Sheikh Awad in Saint Katherine, South Sinai, Egypt. Significant differences (p < 0.05) were observed for physical and chemical properties of the soil associated with H. boveanus during 0-20 and 20-40 cm depths, which increased most of them during the first depth. All chemical composition contents of H. boveanus are influenced significantly (p < 0.05) by seasons studied, except Na+, glycosides, total phenol, crude protein contents. A substantial increase in mineral composition (Na+, K+, P and Fe2+), total alkaloids, glycosides, total phenol, proline, total carbohydrates and all photosynthetic pigments contents were recorded in H. boveanus during the summer season. While, the mineral composition (Ca2+, Mg2+, S, N and Cl-), water content and crude protein contents appeared to be higher in the winter season. The relationships between soil and plant variables were delineated by performing the principal component analysis (PCA). The PC1 and PC2 displayed differences between the soil and plant variables, also, the variables Mg2+, Cl-, pH, EC, Ca2+ and K+ in the soil associated with H. boveanus are variables with better chemical properties of the soil, which affect the plant distribution in Wadi El-Sheikh Awad during the two seasons. The PCA revealed high positive correlations among soil variables as well as among plant variables. Soil magnesium correlated highly and positively with the plant variables i.e., crude protein, water content, Chl b, Chl a+b, carotein and total pigment contents. The pH, EC, and Ca2+ in soil were positively correlated with all chemical composition contents of H. boveanus. Some metabolites in H. boveanus were significantly increased during the summer season compared to the other season, due to the activation of plant physiological stress tolerance mechanisms.

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“…Over the past years, this technique has been used in a variety of domains, including medicine (SILVA et al, 2010), remote sensing (JESUS & EPIPHANIO, 2010), farming (ARRUDA et al, 2012;ARRUDA et al, 2011;YAMAKI et al, 2009), chemistry (BELLOMARINO et al, 2010;FARO JR. et al, 2010), analysis of soil (ISLABÃO et al, 2013), environmental studies (GUEDES et al, 2012;REID & SPENCER, 2009) among others.…”

Section: Introductionmentioning

confidence: 99%

Multivariate statistical analysis to support the minimum streamflow regionalization

Elesbon¹,

Silva²,

Sediyama³

et al. 2015

Eng. Agríc.

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This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q 7,10 , Q 90 and Q 95 ). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall -P a ; total semiannual rainfall of the dry and of the rainy season -P ss and P sc ; watershed drainage area -A d ; length of the main river -L p ; total length of the rivers -L t ; and average watershed slope -S L ). The results of the principal component analysis pointed out that the variable S L was the least representative for the study, and so it was discarded. The most representative independent variables were A d and P sc . The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin. KEYWORDS: principal component analysis, cluster analysis, homogeneous regions. ESTATÍSTICAS MULTIVARIADAS COMO SUPORTE À REGIONALIZAÇÃO DE VAZÕES MÍNIMAS1 RESUMO: Este trabalho teve por objetivo propor uma metodologia baseada em análises estatísticas multivariadas de componentes principais e de agrupamento, com o intuito de identificar as variáveis mais representativas em estudos de regionalização de vazões mínimas e otimizar a obtenção das regiões hidrologicamente homogêneas para a bacia hidrográfica do Rio Doce. Foram utilizadas 10 variáveis referentes às características climáticas e morfométricas da bacia. Essas variáveis foram individualizadas para as 61 estações fluviométricas adotadas, sendo três variáveis dependentes e indicativas das vazões mínimas (Q 7,10 , Q 90 e Q 95 ) e sete independentes (precipitação total anual -P a ; precipitação total do semestre seco -P ss e chuvoso -P sc ; área de drenagem da bacia -A d ; comprimento do rio principal -L p ; comprimento total dos cursos d'água da bacia -L t ; e declividade média da bacia -S L ). O resultado da análise de componentes principais apontou a variável independente S L como a menos representativa e foi excluída do estudo. As variáveis independentes mais representativas foram A d e P sc . As melhores divisões de regiões hidrologicamente homogêneas para as três vazões características estudadas foram obtidas utilizando-se conjuntamente da matriz de similaridade de Mahalanobis e do método de agrupamento do vizinho mais distante. A análise de agrupamento possibilitou a identificação de quatro re...

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

Cited by 10 publications

References 12 publications

Explaining Soil Fertility Heterogeneity in Smallholder Farms of Southern Ethiopia

Explaining Soil Fertility Heterogeneity in Smallholder Farms of Southern Ethiopia

Seasonal Changes of Some Metabolites in Hyoscyamus boveanus (Dunal) Asch. & Schweinf – Saint Katherine, South Sinai, Egypt

Multivariate statistical analysis to support the minimum streamflow regionalization

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