Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
K-MEANS CLUSTERING ALGORITHM BASED CLASSIFICATION OF SOIL FERTILITY IN NORTH WEST NIGERIA
View through CrossRef
Soil fertility determines a plant's development process that guarantees food sufficiency and the security of lives and properties through bumper harvests. The fertility of soil varies according to regions, thereby determining the type of crops to be planted. However, there is no repository or any source of information about the fertility of the soil in any region in Nigeria especially the Northwest of the country. The only available information is soil samples with their attributes which gives little or no information to the average farmer. This has affected crop yield in all the regions, more particularly the Northwest region, thus resulting in lower food production. Therefore, this study is aimed at classifying soil data based on their fertility in the Northwest region of Nigeria using R programming. Data were obtained from the department of soil science from Ahmadu Bello University, Zaria. The data contain 400 soil samples containing 13 attributes. The relationship between soil attributes was observed based on the data. K-means clustering algorithm was employed in analyzing soil fertility clusters. Four clusters were identified with cluster 1 having the highest fertility, followed by 2 and the fertility decreases with an increasing number of clusters. The identification of the most fertile clusters will guide farmers on where best to concentrate on when planting their crops in order to improve productivity and crop yield.
Federal University Dutsin-Ma
Title: K-MEANS CLUSTERING ALGORITHM BASED CLASSIFICATION OF SOIL FERTILITY IN NORTH WEST NIGERIA
Description:
Soil fertility determines a plant's development process that guarantees food sufficiency and the security of lives and properties through bumper harvests.
The fertility of soil varies according to regions, thereby determining the type of crops to be planted.
However, there is no repository or any source of information about the fertility of the soil in any region in Nigeria especially the Northwest of the country.
The only available information is soil samples with their attributes which gives little or no information to the average farmer.
This has affected crop yield in all the regions, more particularly the Northwest region, thus resulting in lower food production.
Therefore, this study is aimed at classifying soil data based on their fertility in the Northwest region of Nigeria using R programming.
Data were obtained from the department of soil science from Ahmadu Bello University, Zaria.
The data contain 400 soil samples containing 13 attributes.
The relationship between soil attributes was observed based on the data.
K-means clustering algorithm was employed in analyzing soil fertility clusters.
Four clusters were identified with cluster 1 having the highest fertility, followed by 2 and the fertility decreases with an increasing number of clusters.
The identification of the most fertile clusters will guide farmers on where best to concentrate on when planting their crops in order to improve productivity and crop yield.
Related Results
The Kernel Rough K-Means Algorithm
The Kernel Rough K-Means Algorithm
Background:
Clustering is one of the most important data mining methods. The k-means
(c-means ) and its derivative methods are the hotspot in the field of clustering research in re...
Classification of soils in Slovenia
Classification of soils in Slovenia
The roots of the modern classification of soils in Slovenia can be traced to the 19<sup>th</sup> century when Croatian Kišpatić produced the first soil classification, ...
Parallel density clustering algorithm based on MapReduce and optimized cuckoo algorithm
Parallel density clustering algorithm based on MapReduce and optimized cuckoo algorithm
In the process of parallel density clustering, the boundary points of clusters with different densities are blurred and there is data noise, which affects the clustering performanc...
FERTILITY TRANSITION IN BANGLADESH: UNDERSTANDING THE ROLE OF THE PROXIMATE DETERMINANTS
FERTILITY TRANSITION IN BANGLADESH: UNDERSTANDING THE ROLE OF THE PROXIMATE DETERMINANTS
Bangladesh has been passing through a crucial phase of fertility transition. The level of fertility declined dramatically during the early 1990s without any remarkable improvement ...
Navigating fertility dilemmas across the lifespan in girls with Turner syndrome—a scoping review
Navigating fertility dilemmas across the lifespan in girls with Turner syndrome—a scoping review
Abstract
BACKGROUND
Girls with Turner syndrome (TS) lack a partial or complete sex chromosome, which causes an accelerated decli...
MR-DBIFOA: a parallel Density-based Clustering Algorithm by Using Improve Fruit Fly Optimization
MR-DBIFOA: a parallel Density-based Clustering Algorithm by Using Improve Fruit Fly Optimization
<p>Clustering is an important technique for data analysis and knowledge discovery. In the context of big data, the density-based clustering algorithm faces three challenging ...
Image clustering using exponential discriminant analysis
Image clustering using exponential discriminant analysis
Local learning based image clustering models are usually employed to deal with images sampled from the non‐linear manifold. Recently, linear discriminant analysis (LDA) based vario...
Local soil classification [soil association/soil slope–soil series], world reference base, and USDA soil taxonomy: roles in soil survey execution
Local soil classification [soil association/soil slope–soil series], world reference base, and USDA soil taxonomy: roles in soil survey execution
The objective was to do a comparative assessment of the best roles of three classification systems, [the “USDA-Soil Taxonomy”; the “World Reference Base (WRB)”; and the presumably ...