crop recommendation research paper

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Crop Recommendation System using Machine Learning

2021, International Journal of Scientific Research in Computer Science, Engineering and Information Technology

A vast fraction of the population of India considers agriculture as its primary occupation. The production of crops plays an important role in our country. Bad quality crop production is often due to either excessive use of fertilizer or using not enough fertilizer. The proposed system of IoT and ML is enabled for soil testing using the sensors, is based on measuring and observing soil parameters. This system lowers the probability of soil degradation and helps maintain crop health. Different sensors such as soil temperature, soil moisture, pH, NPK, are used in this system for monitoring temperature, humidity, soil moisture, and soil pH along with NPK nutrients of the soil respectively. The data sensed by these sensors is stored on the microcontroller and analyzed using machine learning algorithms like random forest based on which suggestions for the growth of the suitable crop are made. This project also has a methodology that focuses on using a convolutional neural network as a primary way of identifying if the plant is at risk of a disease or not.

Related Papers

International Journal of Scientific Research in Computer Science, Engineering and Information Technology

International Journal of Scientific Research in Computer Science, Engineering and Information Technology IJSRCSEIT

sunil rathod

Agriculture is the basic source of food supply in all the countries of the world—whether underdeveloped, developing or developed. Besides providing food, this sector has contributions to almost every other sector of a country. According to the report, 2017, about 17 % of the country’s Gross Domestic Product (GDP) is a contribution of the agricultural sector, and it employs more than 45% of the total labor force. In light of the decreasing crop production and shortage of food across the world, one of the crucial criteria of agriculture now-a-days is selecting the right crop for the right piece of land at the right time. Therefore, in our research we have proposed a method which would help suggest the most suitable crop(s) for a specific land based on the analysis of the data on certain affecting parameters like temperature, humidity, air quality and PH of soil using machine learning. In this paper we used geometric progression for predicting best suited crop in field. Keywords—Temper...

IRJET Journal

Murali Krishna Senapaty

Healthy and sufficient crop and food production are very much essential for everyone as the population is increasing globally. The production of crops affects the economy of a country to a great extent. In agriculture, observing the soil, weather, and water availability and, based on these factors, selecting an appropriate crop, finding the availability of seeds, analysing crop demand in the market, and having knowledge of crop cultivation are important. At present, many advancements have been made in recent times, starting from crop selection to crop cutting. Mainly, the roles of the Internet of Things, cloud computing, and machine learning tools help a farmer to analyse and make better decisions in each stage of cultivation. Once suitable crop seeds are chosen, the farmer shall proceed with seeding, monitoring crop growth, disease detection, finding the ripening stage of the crop, and then crop cutting. The main objective is to provide a continuous support system to a farmer so th...

International Journal for Research in Applied Science and Engineering Technology IJRASET

IJRASET Publication

Food production is an important factor in our day to day life. Farming is the method of food production. There are many problems that affect food production .One of the main solutions for the problems of the farmers is good crop selection. We developed a model of 'CROP SELECTION USING IOT AND MACHINE LEARNING' which helps farmers to select the best crop for their farmland. In this study, we use the KNN algorithm to select appropriate crops for the farmland according to the farmer land's climatic conditions. The used dataset consists of parameters like crop name, temperature, humidity and soil ph. In this paper we would like to help farmers to find crops which are more suitable for his land and to increase the yield. The KNN algorithm will output possible 5 crops and the farmer can select his favourable crop from that.

International journal of engineering technology and management sciences

Sunanda Talole

Journal of Nanomaterials

Saravana Selvan

The available nutrient status of the mulberry gardens in the districts of Tamil Nadu is analyzed and evaluated to find the status. In this work, the soil is classified based on the test report to a number of features with fertility indices for boron (B), organic carbon (OC), potassium (K), phosphorus (P), and available boron (B), along with the parameter soil reaction (pH). A total of 10 steps are used for cross-validation purposes wherein in every step, the data involves 10% for validation and the remaining for training data. A fast learning classification methodology known as extreme learning method (ELM) is trained using the data to identify the micronutrients present in the soil. Activation functions such as hard limit, triangular basis, hyperbolic tangent, sine-squared, and Gaussian radial basis are used to optimize the methodology. Based on the analysis performed, the nutrients are classified and the optimal soil conditions are proposed for different regions that are analyzed....

滑铁卢大学毕业证文凭 购买加拿大Waterloo文凭学历

毕业证 学位证 编号☀️出售美国洛约拉马利蒙特大学毕业证书尺寸硕士学位证书【办证微信Q：741003700】LMU毕业证书尺寸出售成绩单修改#一整套留学美国洛约拉马利蒙特大学文凭证件办理【Q微/741003700】#包含美国洛约拉马利蒙特大学毕业证|成绩单|学历认证|使馆认证|归国人员证明|教育部认证|留信网认证永远存档，教育部学历学位认证查询，办理国外文凭国外LMU学历学位认证 #我们提供全套办理服务。 一整套留学美国洛约拉马利蒙特大学文凭证件服务： 一：出售美国洛约拉马利蒙特大学毕业证【办证微信Q：741003700】 #LMU成绩单等全套材料，从防伪到印刷，水印底纹到钢印烫金， 二：真实使馆认证（留学人员回国证明），使馆存档 三：真实教育部认证，教育部存档，教育部留服网站永久可查 四：留信认证，留学生信息网站永久可查 实体公司专业为您服务，如有需要出售美国洛约拉马利蒙特大学毕业证书尺寸LMU文凭证书实拍图请联系我: qq:741003700 微信：741003700 美国洛约拉马利蒙特大学毕业证书制作【Q微/741003700】专业VIP服务《洛约拉马利蒙特大学毕业证办理》《LMU成绩单提高GPA修改》【Q微/741003700】做LMU毕业证文凭洛约拉马利蒙特大学本科毕业证书美国学历认证原版《洛约拉马利蒙特大学成绩单、洛约拉马利蒙特大学学历证明、回国人员证明》【一整套留学文凭证件办理#包含毕业证、成绩单、学历认证、使馆认证、归国人员证明、教育部认证、留信网认证永远存档，教育部学历学位认证查询】办理美国大学毕业证@【Q微/741003700】购买美国洛约拉马利蒙特大学大学文凭学历 【Q微/741003700】洛约拉马利蒙特大学会计专业毕业证√电子工程专业文凭√制作LMU生物工程专业学历证书√洛约拉马利蒙特大学MBA毕业证√洛约拉马利蒙特大学土木工程毕业证√【Q微/741003700】洛约拉马利蒙特大学计算机科学毕业证√LMU商科毕业证【Q微/741003700】√LMU工商管理毕业证√LMU经济学毕业证√洛约拉马利蒙特大学建筑设计毕业证√LMU市场营销毕业证√洛约拉马利蒙特大学机械工程毕业证√洛约拉马利蒙特大学电气工程毕业证√LMU数学毕业证【Q微/741003700】√洛约拉马利蒙特大学物理学毕业证√LMU人工智能毕业证√洛约拉马利蒙特大学会计和金融专业学位证 <a href="成绩单制作修改*美国洛约拉马利蒙特大学毕业证假学历认证仿制" rel="nofollow">LMU学分不够办理洛约拉马利蒙特大学毕业证【Q微/741003700】美国LMU毕业证文凭</a> 天虹大陆武者之间有严格的等级之分，每一境分为下位，中位，上位。每个境界之间实力差别非常大，武徒想要对战武师，除非拥有强大的玄技，或者宝器，否则越级绝对不可能赢。现在……秦天却想越两级挑战武师之境的萧弘，这不是自己找死是什么？萧弘满脸愕然，随后立刻咧嘴笑道：“出售美国洛约拉马利蒙特大学毕业证书尺寸硕士学位证书【办证微信Q：741003700】LMU毕业证书尺寸出售成绩单修改少城主想玩几手？是空手来，还是用兵器吧？如果伤了少城主，秦家不会怪罪吧？”如此好的机会，萧弘如果不懂的抓住，那就是蠢猪了。秦天挑衅在前，这是年轻人之间的纷争，只要萧弘不下重手，秦家不可能出面的。不下重手，不代表不能给秦天留下一些记忆，比如在他胸口留下一道深深的疤痕，让他……永世难忘！秦天耸了耸肩道：“我手上刚好有一把剑，那就随便玩几手把，你不用束手束脚，放手来吧，就算断了我的腿，我保证秦家不会追究。”“好！少城主豪气干云，在下佩服！”萧弘不等萧厉开口，主动应下了挑战，蓝月儿却皱了皱眉，如果真的断了秦天的腿，秦霸肯定不能罢休的。萧厉皱了皱眉，目光投向萧弘说道：“萧弘，随便玩玩就行，别伤了少城主。”“哈哈哈！”秦天听出了萧厉话语中的潜意思，他告诉萧弘，可以凌辱他，却不能断他手脚。

International Journal of Quantum Chemistry

RELATED PAPERS

Communication & Society

José Octavio Islas Carmona

UT毕业证书 托莱多大学学位证

Scientific study of literature

Miruna Doicaru

Seema Mahmood

Mayo Clinic Proceedings

mridula Aggarwal

Aditya Patel

Plant Disease

Carmen barrau

Mathematics of Control, Signals and Systems

Huseyin Akcay

Anales de Pediatría

Miguel Antonio Figueredo Estevez

International Journal of Behavioral Consultation and Therapy

April Nesin

Victor Valeriano

Client – centered Nursing Care Journal

Contradição - Revista Interdisciplinar de Ciências Humanas e Sociais

Lucia Cecilia da Silva

International Journal of Scientific and Technological Research

ahmet alkan

World journal of urology

Ahmed Refat El-Nahas

Clinical Infectious Diseases

Nilmini Chandrasena

Ahmet ÖZTÜRK

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Improving Crop Productivity Through A Crop Recommendation System Using Ensembling Technique

Ieee account.

• Change Username/Password
• Update Address

Purchase Details

• Payment Options
• Order History
• View Purchased Documents

Profile Information

• Communications Preferences
• Profession and Education
• Technical Interests
• US & Canada: +1 800 678 4333
• Worldwide: +1 732 981 0060
• Contact & Support
• About IEEE Xplore
• Accessibility
• Terms of Use
• Nondiscrimination Policy
• Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Farmright – A Crop Recommendation System

• Conference paper
• First Online: 11 January 2023
• Cite this conference paper

• Dviti Arora 8 ,
• Sanjana Drall 8 ,
• Sukriti Singh 8 &
• Monika Choudhary 8  

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1759))

Included in the following conference series:

• International Conference on Advancements in Smart Computing and Information Security

577 Accesses

Agriculture is extremely vital to our economy and boosting the development of this sector always adds up to the economic & political value of our country. Health of all the crops grown is affected by various aspects including technological, biological, and environmental factors. The environmental facet particularly has been drastically changing, posing challenges in front of the peasants. They face a significant difficulty in determining the optimal crop for their farming region to maximize productivity and profit. For Indian farmers, there is no existing reliable recommendation mechanism. Giving an address to this issue, the study proposes a crop recommendation system based on a multi-label classification model which considers the location of peasants, composition of soil, and weather characteristics, and provides a ranked list of suggested crop seed to be produced for greater yield. Researchers compare many algorithms based upon the performance criteria and capabilities to develop the best recommendation model for crops. With a precision of 82.74%, a recall of 80.92%, and an F1 score of 78.67%, the most optimal model was revealed to be an RF Technique. The trained model proved advantageous in catering the farmers with a ranked list of crops deployed along with an interface for better user experience.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Banerjee, G., Sarkar, U., Ghosh, I.: A fuzzy logic-based crop recommendation system. In: Proceedings of International Conference on Frontiers in Computing and Systems, pp. 57–69. Springer (2021)

Google Scholar  

Banjara,T.R., Bohra, J.S., Kumar, S., Ram, A., Pal, V.: Diversification of rice–wheat cropping system improves growth, productivity and energetics of rice in the Indo-Gangetic plains of India. Agric. Res. 11 (1), 48–57 (2021)

Elavarasan, D., Vincent, P.M.D.R.: A reinforced random forest model for enhanced crop yield prediction by integrating agrarian parameters. J. Ambient. Intell. Humaniz. Comput. 12 (11), 10009–10022 (2021). https://doi.org/10.1007/s12652-020-02752-y

Article   Google Scholar  

Indira, D.N.V.S.L.S., Sobhana, M., Swaroop, A.H.L., Phani Kumar, V.: KRISHI RAKSHAN - A Machine Learning based New Recommendation System to the Farmer. In: 6th International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1798–1804. IEEE Xplore (2022)

Jeong, J.: 2016 Random forests for global and regional crop yield predictions PLoS ONE 11 (6), e0156571 (2016)

Krishna Kumar, K., Rupa Kumar, K., Ashrit, R., Deshpande, N., Hansen, J.: Climate impacts on Indian agriculture. Int. J. Climatol.: J. R. Meteorol. Soc. 24 (11), 1375–1393 (2004)

Kumar, R., Singhal, V.: IoT enabled crop prediction and irrigation automation system using machine learning. Recent Advances in Computer Science and Communications (Formerly: Recent Patents on Computer Science) 15 (1), 88–97 (2022)

Kumar, R., Singh, M., Kumar, P., Singh, J.: Crop selection method to maximize crop yield rate using machine learning technique. In: 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), pp. 138–145. IEEE (2015)

Kulkarni, N., Srinivasan, G., Sagar, B., Cauvery, N.: Improving crop productivity through a crop recommendation system using ensembling technique. In: 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS), pp. 114–119. IEEE (2018)

Liu, A., Lu, T., Wang, B., Chen, C.: Crop recommendation via clustering center optimized algorithm for imbalanced soil data. In: 2020 5th International Conference on Control, Robotics and Cybernetics (CRC), pp. 31–35. IEEE (2020)

Malik, A., Kumar, R.: An overview on agriculture in India. Int. J. Mod. Agric. 10 (2), 2087–2095 (2021)

Odutola Oshunsanya, S.: Introductory Chapter: Relevance of Soil pH to Agriculture. Soil pH for Nutrient Availability and Crop Performance, IntechOpen, London (2019). https://doi.org/10.5772/intechopen.82551

Patel, K., Patel, H.: A state-of-the-art survey on recommendation system and prospective extensions. Comput. Electron. Agric. 178 105779 (2020)

Pudumalar, S., Ramanujam, E., Rajashree, R., Kavya, C., Kiruthika, T., Nisha, J.: Crop recommendation system for precision agriculture. In: 2016 Eighth International Conference on Advanced Computing (ICoAC), pp. 32–36. IEEE (2017)

Ramya, M., Balaji, C., Girish, L.: Environment change prediction to adapt climate-smart agriculture using big data analytics. Int. J. Adv. Res. Comput. Eng. & Technol. (IJARCET) 4 (5) (2015)

Sujjaviriyasup, T., Pitiruek, K.: Agricultural product forecasting using machine learning approach. Int. J. Math. Anal. 7 (38), 1869–1875 (2013)

Article   MathSciNet   MATH   Google Scholar  

Teja, M.S., Preetham, T.S., Sujihelen, L., Christy, Jancy, S., Selvan, M.P.: Crop recommendation and yield production using SVM algorithm. In: 6th International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1768–1771 (2022)

Varun Prakash, R., Mohamed Abrith, M., Pandiyarajan, S.: Machine learning based crop suggestion system. In: 6th International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1355–1359. IEEE Xplore (2022)

Vijayabaskar, P., Sreemathi, R., Keertanaa, E.: Crop prediction using predictive analytics. In: 2017 International Conference on Computation of Power, Energy Information and Communication (ICCPEIC), pp. 370–373. IEEE (2017)

India at a Glance, FAO in India. https://www.fao.org/india/fao-in-india/india-at-a-glance/en/ . Accessed 28 Jan 2022

FarmRight, Github. https://github.com/Know-and-Grow/FarmRight-A-Crop-Recommendation-System . Accessed 31 Aug 2022

Open Government Data (OGD) Platform India. https://data.gov.in/ . Accessed 10 Feb 2022

Department of Agricultural Cooperation & Farmers Welfare Homepage. https://agricoop.nic.in/en . Accessed 18 Feb 2022

NASA Prediction Of Worldwide Energy Resources (POWER). https://power.larc.nasa.gov/ . Accessed 01 Mar 2022

Download references

Author information

Authors and affiliations.

Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India

Dviti Arora,  Sakshi, Sanjana Drall, Sukriti Singh & Monika Choudhary

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Dviti Arora .

Editor information

Editors and affiliations.

Marwadi University, Rajkot, India

Sridaran Rajagopal

AVPTI, Rajkot, India

Parvez Faruki

Kalpesh Popat

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Cite this paper.

Arora, D., Sakshi, Drall, S., Singh, S., Choudhary, M. (2022). Farmright – A Crop Recommendation System. In: Rajagopal, S., Faruki, P., Popat, K. (eds) Advancements in Smart Computing and Information Security. ASCIS 2022. Communications in Computer and Information Science, vol 1759. Springer, Cham. https://doi.org/10.1007/978-3-031-23092-9_27

Download citation

DOI : https://doi.org/10.1007/978-3-031-23092-9_27

Published : 11 January 2023

Publisher Name : Springer, Cham

Print ISBN : 978-3-031-23091-2

Online ISBN : 978-3-031-23092-9

eBook Packages : Computer Science Computer Science (R0)

Share this paper

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research