[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127239-en":3,"doc-seo-127239-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},127239,2336475104042,"Skyler","https://ap-avatar.wpscdn.com/avatar/22000c4c32af1715be0?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786537525561427321",8,"Research & Report","Machine Learning Based Agricultural Profitability Recommendation Systems: A Paradigm Shift in Crop Cultivation - Research Article","Growing demand for fruits and vegetables in India has not translated into rapid adoption by farmers who remain tied to traditional food grains. This paper analyzes shifts in food consumption and proposes a machine learning and deep learning approach using historical market price data for fruits and vegetables from 2016 to 2021. The model predicts future monthly and yearly prices to support crop selection and harvest timing. Improved forecasting helps reduce uncertainty and maximize agricultural profitability.","Regular Issue  \nMachine Learning Based Agricultural Profitability Recommendation Systems: A Paradigm Shift in Crop Cultivation  \nNilesh P. Sable1, Rajkumar V. Patil2, Mahendra Deore3, Ratnmala Bhimanpallewar4, Parikshit N. Mahalle5 *  \n1 Department of Computer Science & Engineering (Artificial Intelligence), Bansilal Ramnath Agarwal Charitable Trust's Vishwakarma Institute of Information Technology, Pune (India)  \n2 MIT Art, Design & Technology University, Pune (India)  \n3 Department of Computer Engineering, MKSSS’s Cummins College of Engineering for Women, Pune-411052, Maharashtra,(India)  \n4 Department of Information Technology, Bansilal Ramnath Agarwal Charitable Trust's Vishwakarma Institute of Information Technology, Pune (India)  \n5 Professor and Dean R&D, Bansilal Ramnath Agarwal Charitable Trust's, Vishwakarma Institute of Technology, Pune (India)  \n* Corresponding author: [drsablenilesh@gmail.com](drsablenilesh@gmail.com) (N. P. Sable), [rajkumar.v.patil30@gmail.com](rajkumar.v.patil30@gmail.com) (R. V. Patil), [mdeore83@gmail.com](mdeore83@gmail.com) (M. Deore), [ratnmalab@gmail.com](ratnmalab@gmail.com) (R. Bhimanpallewar), [aalborg.pnm@gmail.com](aalborg.pnm@gmail.com) (P. N. Mahalle)  \nReceived 24 August 2023 | Accepted 16 July 2024 | Published 30 October 2024  \nAbstract   \nIn India, the demand for fruits and vegetables has been consistently increasing alongside the rising population, making crop production a crucial aspect of agriculture. However, despite the growing demand and potential profitability, farmers have been slow to transition from traditional food grain crops to fruits and vegetables. In this paper, we explore the changing demands of food categories in India, highlighting the shift towards increased consumption of fruits and vegetables. Despite the potential benefits, farmers face various challengesand uncertainties associated with cultivating these crops. To address this, we propose the use of Machine Learning (ML) and Deep Learning (DL) techniques to analyze historical market price data for fruits and vegetables from 2016 to 2021 and predict future prices. This accurate prediction system will aid farmers in deciding which crops to grow and when to harvest, ultimately maximizing profits.  \nKeywords   \nAgriculture, Cultivation, Data Analysis, Machine Learning, Regression.  \nDOI: 10. 9781/ijimai.2024.10.005  \nI. Introduction  \nAGRICULTURE, the world's oldest and most important sector,  \nhas always been essential for supplying food, fibers, and fuel to humanity. Archaeological evidence places the origins of farming at about 10,000 years ago, when people began to depend on it for their food [1] . Agriculture plays a crucial role in the development of civilizations by cultivating the soil and raising livestock. Nevertheless, throughout millennia, agricultural growth progressed gradually. Using fire to regulate plant development was a common practice in early agricultural techniques since people had seen how wellestablished vegetation was following wildfires. Farmers gradually started tilling the soil and producing crops on tiny pieces of land by hand using simple equipment. As time went on, productive farming implements were developed, and yield-boosting irrigation methods were mastered [2] .  \nAs per the statistics of Annual crop production in India since 2003- 04 fruit and vegetable production keeps on increasing [3]. With the continuous growth in population and changing food consumption patterns in India, there is an increasing demand for fruits and vegetables. However, farmers have been hesitant to shift from traditional food grain crops to fruits and vegetables due to various reasons. This paper aims to provide a solution by using ML and DL algorithms to analyze historical market price data of Mumbai Agricultural Produce Market Committee (Mumbai APMC) and predict fruit and vegetable prices, assisting farmers in making informed decisions about crop selection and harvesting.  \nChanges in Food Consumpt","cbCaic43nL9HYQTR","https://ap.wps.com/l/cbCaic43nL9HYQTR","pdf",762860,1,16,"English","en",105,"# Introduction\n## Food consumption pattern changes\n## Motivation and research goal\n# Key Highlight of Research\n## Price prediction for fruits and vegetables\n## Literature survey and time series methods","[{\"question\":\"Why do farmers hesitate to switch from food grains to fruits and vegetables?\",\"answer\":\"Fruits and vegetables are riskier because they depend more on environmental conditions, require more labor, and face limited automation challenges. Farmers also need reliable decision support to reduce uncertainty.\"},{\"question\":\"What data range is used for training the prediction system?\",\"answer\":\"The approach analyzes historical market price data for fruits and vegetables from 2016 to 2021.\"},{\"question\":\"How does the proposed ML/DL system help farmers improve profits?\",\"answer\":\"It predicts future monthly and yearly prices, enabling farmers to choose which crops to grow and when to harvest. Better price forecasts support more informed selling and cultivation decisions.\"}]","Machine Learning Based Agricultural Profitability Recommendation Systems: A Paradigm Shift in Crop Cultivation - Research Article | PDF",1785937692,40,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-based-agricultural-profitability-recommendation-systems-a-paradigm-shift-in-crop-cultivation-research-article","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-based-agricultural-profitability-recommendation-systems-a-paradigm-shift-in-crop-cultivation-research-article/127239/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why do farmers hesitate to switch from food grains to fruits and vegetables?","Question",{"text":75,"@type":76},"Fruits and vegetables are riskier because they depend more on environmental conditions, require more labor, and face limited automation challenges. Farmers also need reliable decision support to reduce uncertainty.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What data range is used for training the prediction system?",{"text":80,"@type":76},"The approach analyzes historical market price data for fruits and vegetables from 2016 to 2021.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the proposed ML/DL system help farmers improve profits?",{"text":84,"@type":76},"It predicts future monthly and yearly prices, enabling farmers to choose which crops to grow and when to harvest. 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