scholarly journals Ecological Monitoring of Soils of the Lenkoranchay Basin by Region

2020 ◽  
Vol 6 (2) ◽  
pp. 143-150
Author(s):  
S. Mamedova
Keyword(s):  
Soil Fertility ◽  
Ecological Monitoring ◽  
Fertility Factor ◽  
Ecological Region

Ecological monitoring of soil fertility in the Lenkoranchay basin shows that the fertility factor is decreasing both on watershed and transit soils, and on accumulative soils of the ecological region. However, soil fertility indicators in this ecological region were lower than in previous ones. This is due to the fact that scrubber materials delivered through Lenkoranchay are partially collected on the soils of an accumulative ecological region.

USE OF FACTOR ANALYSIS TO INVESTIGATE RELATIONS BETWEEIS ENVIRONMENTAL VARIABLES AND FORAGE YIELD

1973 ◽  
Vol 53 (2) ◽  
pp. 309-316 ◽  
Author(s):  
J. WADDINGTON
Keyword(s):  
Factor Analysis ◽  
Soil Moisture ◽  
Soil Fertility ◽  
Soil Nutrients ◽  
Wave Energy ◽  
Environmental Variables ◽  
Short Wave ◽  
Forage Yield ◽  
Degree Days ◽  
Fertility Factor

Yields obtained over a 17-yr period from three grasses, one legume, and three grass–legume mixtures, together with six environmental variables, were subjected to factor analysis. Three of the variables (degree-days, hours of bright sunshine, and solar short-wave energy at the top of the earth’s atmosphere) showed a very close interrelation and were interpreted as measures of environmental energy. Age of crop was classed as a soil fertility factor; the available soil nutrients decreased as the age of the forage stand increased. In the factor patterns developed, differences between crops were small in comparison with the overall similarities. Production from the first harvest of the season was equally dependent on energy, soil moisture, and soil fertility. Regrowth was controlled principally by rainfall during and prior to the regrowth period. The ability of factor analysis to extract relatively simple relations from interrelated variables is clearly demonstrated.

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

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.

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

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

Strategies for Soil Fertility Improvement of Arable Land in China

2018 ◽  
Vol 20 (5) ◽  
pp. 84
Author(s):  
Yingjie Hu ◽  
Xiangbin Kong ◽  
Yuzhen Zhang
Keyword(s):  
Soil Fertility ◽  
Arable Land ◽  
Soil Fertility Improvement
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