Soil suitability analysis and evaluation of pistachio orchard farming, using canonical multivariate analysis

The development of the agricultural sector is considered the backbone of sustainable development in Egypt. While the developing countries of the world face many challenges regarding food security due to rapid population growth and limited agricultural resources, this study aimed to assess the soils of Sidi Barrani and Salloum using multivariate analysis to determine the land capability and crop suitability for potential alternative crop uses, based on using principal component analysis (PCA), agglomerative hierarchical cluster analysis (AHC) and the Almagra model of MicroLEIS. In total, 24 soil profiles were dug, to represent the geomorphic units of the study area, and the soil physicochemical parameters were analyzed in laboratory. The land capability assessment was classified into five significant classes (C1 to C5) based on AHC and PCA analyses. The class C1 represents the highest capable class while C5 is assigned to lowest class. The results indicated that about 7% of the total area was classified as highly capable land (C1), which is area characterized by high concentrations of macronutrients (N, P, K) and low soil salinity value. However, about 52% of the total area was assigned to moderately high class (C2), and 29% was allocated in moderate class (C3), whilst the remaining area (12%) was classified as the low (C4) and not capable (C5) classes, due to soil limitations such as shallow soil depth, high salinity, and increased erosion susceptibility. Moreover, the results of the Almagra soil suitability model for ten crops were described into four suitability classes, while about 37% of the study area was allocated in the highly suitable class (S2) for wheat, olive, alfalfa, sugar beet and fig. Furthermore, 13% of the area was categorized as highly suitable soil (S2) for citrus and peach. On the other hand, about 50% of the total area was assigned to the marginal class (S4) for most of the selected crops. Hence, the use of multivariate analysis, mapping land capability and modeling the soil suitability for diverse crops help the decision makers with regard to potential agricultural development.

Download Full-text

Development of Soil Suitability Ratings Index for Crops in the North – East of Libya Using Geographic Information System

10.36602/jmuas.2020.v02.01.02 ◽

2020 ◽

Vol 2 (1) ◽

pp. 19-29

Author(s):

Bashir A. Nwer ◽

Abdulmeanem M. Whaida ◽

Fatima M. Grab

Keyword(s):

Information System ◽

Geographic Information System ◽

Land Use Planning ◽

Geographic Information ◽

Land Evaluation ◽

Parametric Approach ◽

Suitability Analysis ◽

Local Conditions ◽

Soil Suitability ◽

North East

Agriculture production faces a great challenge for the coming decades which is the food security for the ever-increasing world’s populations. The key role in sustainable agriculture production can be played by sustainable soil uses and management. Land evaluation for specific purpose is an important tool for land use planning. A number of land evaluation techniques have been developed to assess land for different uses. The parametric approach is one that combines various soil and site properties (parameters) that are believed to influence yield using mathematical formula. The Storie Index Rating was an early attempt at quantitative land evaluation and an example of parametric approach. The system has been widely applied around the world, for example, It has been used in California, mainly for irrigated soils (Kudrat and Saha, 1993). In addition, it was adapted in Libya. The Libyan modified index rating takes into account local conditions to determine the properties included. Local experiences were used to classify the soil suitability (Mahmoud, 1995). The rating was taking into account eleven soil properties to produce an overall rating. This paper modified the productivity rating and produce computerized model which uses spreadsheet model for suitability analysis and integrates the results in geographic information system (GIS) environment. The results show that Barley is the most suitable crop with 42 % of the area is very high suitable and about 18 % is not suitable for barley. Whereas maize is about 29 % is high suitable in that soils of the study area, and less than 25 % is not suitable. GIS allow modelling, running a range of soil use scenarios and data manipulate so that the optimal soil use can be identified to achieve sustainable development. In addition, it allows the comparison between different crops to select the most appropriate to local conditions and development goals. This paper is part of series research papers which uses concepts developed and applied in different area of Libya.

Download Full-text

Crop and soil suitability analysis using multi-criteria decision making in drought-prone semi-arid tropics in India

Journal of Soil and Water Conservation ◽

10.5958/2455-7145.2020.00036.3 ◽

2020 ◽

Vol 19 (3) ◽

pp. 271

Author(s):

Rajni Jain ◽

Prem Chand ◽

Sulakshna C. Rao ◽

Priyanka Agarwal

Keyword(s):

Decision Making ◽

Multi Criteria Decision Making ◽

Suitability Analysis ◽

Soil Suitability ◽

Semi Arid

Download Full-text

Statistical analysis of classification

Symposium - International Astronomical Union ◽

10.1017/s0074180900053420 ◽

1966 ◽

Vol 24 ◽

pp. 188-189

Author(s):

T. J. Deeming

Keyword(s):

Multivariate Analysis ◽

Statistical Analysis ◽

Classification Scheme ◽

Analytical Procedure ◽

Narrow Band ◽

Scientific Research ◽

Maximum Amount ◽

Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Download Full-text