%0 Conference Proceedings
%T Crop Recommendation by Analysing the Soil Nutrients Using Machine Learning Techniques: A Study
%+ B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai
%+ Vels Institute of Science, Technology and Advanced Studies (VISTAS)
%A Jayaraman, Vaishnavi
%A Parthasarathy, Saravanan
%A Lakshminarayanan, Arun, Raj
%A Sridevi, S.
%Z Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 4th International Conference on Computational Intelligence in Data Science (ICCIDS)
%C Chennai, India
%Y Vallidevi Krishnamurthy
%Y Suresh Jaganathan
%Y Kanchana Rajaram
%Y Saraswathi Shunmuganathan
%I Springer International Publishing
%3 Computational Intelligence in Data Science
%V AICT-611
%P 15-26
%8 2021-03-18
%D 2021
%R 10.1007/978-3-030-92600-7_2
%K Soil nutrients
%K Environmental factors
%K Machine learning
%K Prediction
%K Crop recommendation system
%K Yield rate
%Z Computer Science [cs]Conference papers
%X According to India Brand Equity Foundation (IBEF), 32% of the global food market is dependent on Indian agricultural sector. Due to urbanisation, the fertile land have been utilised for non-agricultural purposes. The loss of agricultural lands impacts the productivity and results with diminishing yield. Soil is the most important factor for the thriving agriculture, since it contains the essential nutrients. The food production could be improved through the viable usage of soil nutrients. To identify the soil nutrients, the physical, chemical and biological parameters were examined using many machine learning algorithms. However, the environmental factors such as sunlight, temperature, humidity, and rainfall plays a major role in improving the soil nutrients since it is responsible for the process of photosynthesis, germination, and saturation. The objective is to determine the soil nutrient level by accessing the associative properties including the environmental variables. The proposed system termed as Agrarian application which recommends crops for the particular land using classification algorithms and predicts the yield rate by employing regression techniques. The application will help the farmers in selecting the crops based on the soil nutrient content, environmental factors and predicts the yield rate for the same.
%G English
%Z TC 12
%2 https://inria.hal.science/hal-03772947/document
%2 https://inria.hal.science/hal-03772947/file/512058_1_En_2_Chapter.pdf
%L hal-03772947
%U https://inria.hal.science/hal-03772947
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-ICCIDS
%~ IFIP-AICT-611