Authors :
Pavan Kumar.Innamuri; Kakumanu Venkata Kasi Viswanath; Katta Harshavardhan Reddy; Jangam Aravind Swamy; Sheelavathy K. V.
Volume/Issue :
Volume 7 - 2022, Issue 5 - May
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/mpwy7yjj
DOI :
https://doi.org/10.5281/zenodo.8374792
Abstract :
Soil classification is a major problem and a
heated topic in many countries. The world's population is
drastically increasing at an alarming rate which in turn
makes the demand for food crops. Farmers are forced to
block soil cultivation since their conventional methods are
insufficient to fulfil escalating needs. To optimize
agricultural output, farmers must understand the best soil
type for a certain crop, which has an impact on growing
food demand. There areseveral methods for categorizing
soil in a scientific way, but each has its own set of
disadvantages, such as time and effort. Computer-based soil
classification approaches are essential since they will aid
farmers in the field and will be quick. Advanced Machine
Learning technique-based soil classification methodologies
can be used to classify soil and extract various featuresfrom
it.
Keywords :
Soil Classification, Crop Prediction, Machine Learning, Convolutional Neural Network.
Soil classification is a major problem and a
heated topic in many countries. The world's population is
drastically increasing at an alarming rate which in turn
makes the demand for food crops. Farmers are forced to
block soil cultivation since their conventional methods are
insufficient to fulfil escalating needs. To optimize
agricultural output, farmers must understand the best soil
type for a certain crop, which has an impact on growing
food demand. There areseveral methods for categorizing
soil in a scientific way, but each has its own set of
disadvantages, such as time and effort. Computer-based soil
classification approaches are essential since they will aid
farmers in the field and will be quick. Advanced Machine
Learning technique-based soil classification methodologies
can be used to classify soil and extract various featuresfrom
it.
Keywords :
Soil Classification, Crop Prediction, Machine Learning, Convolutional Neural Network.
