Natural and Constructed Cyanobacteria-Based Consortia for Enhancing Crop Growth and Soil Fertility

2021 ◽  
pp. 333-362
Author(s):  
Radha Prasanna ◽  
Nirmal Renuka ◽  
Lata Nain ◽  
B. Ramakrishnan
Keyword(s):  
Soil Fertility ◽  
Crop Growth

Effects of compost and biochar amendments on soil fertility and crop growth in a calcareous soil

2020 ◽  
Vol 43 (20) ◽  
pp. 3002-3019 ◽  
Author(s):  
Noel Manirakiza ◽  
Cevdet Şeker
Keyword(s):  
Soil Fertility ◽  
Calcareous Soil ◽  
Crop Growth

Effects of crop-straw biochar on crop growth and soil fertility over a wheat-millet rotation in soils of China

2014 ◽  
Vol 30 (3) ◽  
pp. 311-319 ◽  
Author(s):  
X. Zhao ◽  
J. W. Wang ◽  
H. J. Xu ◽  
C. J. Zhou ◽  
S. Q. Wang ◽  
...  
Keyword(s):  
Soil Fertility ◽  
Crop Growth ◽  
Crop Straw

Vermicomposting converts fly ash to enrich soil fertility and sustain crop growth in red and lateritic soils

2012 ◽  
Vol 65 ◽  
pp. 100-106 ◽  
Author(s):  
S.S. Bhattacharya ◽  
W. Iftikar ◽  
B. Sahariah ◽  
G.N. Chattopadhyay
Keyword(s):  
Fly Ash ◽  
Soil Fertility ◽  
Crop Growth ◽  
Lateritic Soils

Biochar application to temperate soils: Effects on soil fertility and crop growth under greenhouse conditions

2013 ◽  
Vol 177 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Stefanie Kloss ◽  
Franz Zehetner ◽  
Bernhard Wimmer ◽  
Jannis Buecker ◽  
Franziska Rempt ◽  
...  
Keyword(s):  
Soil Fertility ◽  
Crop Growth ◽  
Temperate Soils

scholarly journals Farmers' knowledge and management of spatial soil and crop growth variability in Niger, West Africa

1995 ◽  
Vol 43 (4) ◽  
pp. 375-389 ◽  
Author(s):  
J.P.A. Lamers ◽  
P.R. Feil
Keyword(s):  
Soil Fertility ◽  
Large Scale ◽  
Management Practices ◽  
Crop Residues ◽  
Agricultural Research ◽  
Crop Growth ◽  
Household Waste ◽  
Extensive Literature ◽  
Growth Variability ◽  
Crop Growth Variability

A household survey conducted in the Sahel, combined with an extensive literature search of baseline studies, complemented on-station research on spatial soil and crop growth variability from a farmers viewpoint. Farmers explained spatial variability in crop growth in terms of differences in soil types, soil fertility and degradation, as well as their cultivation and management practices. Farmers counteract spatial crop growth variability by within-field fallow; kraaling; spot applications of manure, crop residues and household waste; by intentionally moving their settlements; and by exploiting the micro-environmental differences around specific tree and shrub species. However, these strategies also enforce the spatial crop growth variability. The accuracy of farmers' comprehensive knowledge of agriculture, soil, animal husbandry and agro-forestry was confirmed by compartmentalized on-farm and on-station studies conducted in the same region, although explanations of farmers and researchers were not always the same. Farmers are aware of soil fertility management technologies, either coming from outside or developed within the farming community, but are often unable to translate these into action on a large scale. This is due to insufficient resources and socioeconomic, as well as institutional, constraints such as cattle ownership, land tenure, labour requirements and prices of inputs. Implications for agricultural research and technology generation are discussed.

Studies on soil reaction. I. A Résumé

1921 ◽  
Vol 11 (1) ◽  
pp. 19-44 ◽  
Author(s):  
E. A. Fisher
Keyword(s):  
Soil Fertility ◽  
Climatic Factors ◽  
Crop Growth ◽  
The Other ◽  
Soil Conditions ◽  
Soil Reaction ◽  
Absolute Property ◽  
Exact Measurement ◽  
The One ◽  
Biological Nature

Soilfertility is often spoken of as though it were an absolute property of the soil; in reality it is a particular relationship subsisting betweensoil conditionson the one hand andcrop growthon the other. The conditions conducive to soil fertility are the resultant of two main groups of factors, theintrinsicproperties of the soil which are dependent on its chemical, physical and biological nature, and thoseextrinsicproperties impressed on the soil by topographical and climatic factors*. These two groups cannot be sharply distinguished from each other, nor can any hard and fast line be drawn between the various factors comprised in them, because few are at present susceptible of exact measurement. In other words, that particular group of conditions that make up the fertility of a soil is an equilibrium brought about by the interaction of numerous factors some of which however can be varied by the agriculturist by manurial and cultivation operations.

scholarly journals Role of organic food wastes on soil fertility and stevia crop growth and its yield

2020 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
yasser khalifa ◽  
Mohamed Youssef ◽  
Asem Abdel-Gawad
Keyword(s):  
Soil Fertility ◽  
Organic Food ◽  
Crop Growth ◽  
Food Wastes

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.

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