Influence of Slope Gradient on Coffee Soil Fertility in Goma Woreda of Oromia Region

Abstract BackgroundThe complex nature of the relationship and interaction between LULC and slope gradients resulted in the decline of soil fertility parameters, which aggravate the reduction of sustainable productivity in Ethiopia in general and the study area in particular. This study was aimed to determine the effects of land use land cover and slope gradients on the physicochemical properties of soil in study area A total of 27 composite soil samples were collected from 0-20cm depth under three dominant adjacent LULC across three slope with three replications. The collected soil samples were analyzed for selected soil physicochemical properties. Two-way ANOVA was used to test the mean differences of the soil fertility parameters. ResultThe mean values of soil physicochemical parameters showed that, SOC, TN, AvP, CEC, exchangeable bases (Ca2+ Mg2+, K+, and Na+), PBS, and percentage of clay contents of cultivated land and steep slope gradient (15-30%) were low and significantly different at (P≤0.05) than forest and grad grassland of the same slope gradient.. The gentle slope (3-8%) gradients of the forest lands had the lowest BD and high TP as compared to the others.ConclusionThe overall soil fertility status of the steep slope gradient (15-30%) of cultivated lands is lower than others and cultivating the steep slope is the cause for productivity loss in the study sub-watershed. Therefore, proper land-use planning and the use of integrated soil fertility management strategy give better production and keep the soil fertility status to a better level.

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Influence of Slope Gradient on Coffee Soil Fertility in Goma Woreda of Oromia Region

International Journal of Current Research and Academic Review ◽

10.20546/ijcrar.2021.901.003 ◽

2021 ◽

Vol 9 (1) ◽

pp. 43-49

Author(s):

Mohammed Kedir

Keyword(s):

Soil Fertility ◽

Water Conservation ◽

Soil Samples ◽

Organic Fertilizers ◽

Slope Gradient ◽

Standard Procedures ◽

Wide Range ◽

Study Sites ◽

Future Work ◽

One Way Anova

This study was to evaluate the influence slope gradient on coffee soil fertility. Accordingly, soil samples, and field history was collected from 10 coffee farms during pinhead phase. Soil samples collected from 0-30 cm depth were prepared and analyzed in the laboratory following standard procedures. For data analysis, one-way ANOVA was used. The results revealed that coffee cultivations have practiced under wide range of slope gradients in study sites. Variations in slope gradients significantly influenced the coffee soil fertility. Consequently, OM, clay, CEC, available P, Mg and Na generally showed a decreasing trend with increasing slope gradient, whereas sand was opposite. For sound conclusion, appropriate soil and water conservation measures, N, P, K, organic fertilizers are recommended for future work.

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FACTORS OF THE MANAGEMENT OF THE SOIL FERTILITY IN THE SYSTEM OF IRRIGATED SEVAL TURNOVERS OF THE LOWER VOLGA REGION

PROCEEDINGS of Nizhnevolzhskiy agrouniversity complex science and higher vocational education ◽

10.32786/2071-9485-2018-04-12 ◽

2018 ◽

Keyword(s):

Soil Fertility ◽

Volga Region ◽

Lower Volga Region ◽

Lower Volga

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K-MEANS CLUSTERING ALGORITHM BASED CLASSIFICATION OF SOIL FERTILITY IN NORTH WEST NIGERIA

FUDMA Journal of Sciences ◽

10.33003/fjs-2020-0402-363 ◽

2020 ◽

Vol 4 (2) ◽

pp. 780-787

Author(s):

Ibrahim Hassan Hayatu ◽

Abdullahi Mohammed ◽

Barroon Ahmad Isma’eel ◽

Sahabi Yusuf Ali

Keyword(s):

Soil Fertility ◽

Crop Yield ◽

Clustering Algorithm ◽

Soil Samples ◽

North West ◽

R Programming ◽

Available Information ◽

Northwest Region ◽

The Relationship

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.

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COUNTING TOTAL BACTERIA IN LAND ORGANIC WASTE HOUSEHOLD AND LAND INORGANIC WITH TOTAL PLATE COUNT METHOD (TPC)

Jurnal Penelitian Agrisamudra ◽

10.33059/jpas.v4i2.288 ◽

2017 ◽

Vol 4 (2) ◽

pp. 87-91

Author(s):

Ekamaida Ekamaida

Keyword(s):

Soil Fertility ◽

Bacterial Population ◽

Organic Soil ◽

Biological Properties ◽

Plate Count ◽

Bacterial Populations ◽

Fertility Data ◽

Plate Count Method ◽

The Mean ◽

Total Bacteria

The soil fertility aspect is characterized by the good biological properties of the soil. One important element of the soil biological properties is the bacterial population present in it. This research was conducted in the laboratory of Microbiology University of Malikussaleh in the May until June 2016. This study aims to determine the number of bacterial populations in soil organic and inorganic so that can be used as an indicator to know the level of soil fertility. Data analysis was done by T-Test that is by comparing the mean of observation parameter to each soil sample. The sampling method used is a composite method, which combines 9 of soil samples taken from 9 sample points on the same plot diagonally both on organic soil and inorganic soil. The results showed the highest bacterial population was found in total organic soil cfu 180500000 and total inorganic soil cfu 62.500.000

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