期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：12
页码：488-501
出版社：Science and Information Society (SAI)
摘要：Pakistan’s economy is strongly associated with
agriculture sector. For a country having 25 % of GDP
contributed through agriculture, there is a need to modernize the
agriculture by acclimatizing contemporary approaches.
Unfortunately, it has become a common trend among farmers to
cultivate crops, being used in food items or which can easily be
sold out in the market without using knowledge about the
suitability or relevancy of crops to the soil environment.
Consequently, the farmers face financial losses. Many
researchers have proposed soil classification methods for various
soils related researches, but they have very little contribution
towards guidance of the farmers to select most suitable crops for
cultivation at a particular soil type. Without the use of
technology and computer-assisted approaches, the process of
classifying soil environments could not help the farmers in taking
decisions regarding appropriate crop selection in their respective
fields. In this paper, an effective knowledge-oriented approach
for soil classification in Pakistan has been presented using crowd
sourced data obtained from 1557 users regarding 103
agricultural zones. The data were also obtained from AIMS
(Govt. of Punjab) and Ministry of National Food Security &
Research. In this work, random forest classifier has been used for
processing and predicting complex tiered relationship among soil
types belonging to agricultural zones and major suitable crops
for improving yield production. The proposed model helps in
computing the degree of relevancy of crop to agricultural region
that help former selecting suitable crops for their cultivated
lands.
