Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predictive analysis in smart agriculture Description An account of the resource Analyzing large databases for hidden connections, correlations and insights is known as big data analytics. Although many countries still use outdated farming methods, technological advancements have allowed for specific improvements (especially in developing countries). Big data analytics has the potential to expand the agricultural sector in this regard significantly. The farmers rely heavily on old methods for deciding what to plant and how to cultivate it. Walking through fields, selecting soil samples for moisture analysis, and visually inspecting plant leaves are typical examples of these time-honored practices. Understanding the significance of technology for acquiring crop information in considerable amounts and turning that data into usable knowledge is crucial for agriculturists (mainly farmers). Integration of big data could help agriculture make changes to its current practices. If used correctly, big data analytics can shed light on the most efficient crop cultivation methods. Extensive developments in three areas-crop prediction, precision farming and seed production-are reshaping the agricultural industry. There are four parts to this chapter. The first part of this paper provides an introduction to analytics on big data in agriculture. The second part will then focus on the various big data methods used in the agricultural sector. The third section provides two examples of how big data analysis methods were put to use in the field of agriculture. In the fourth section, the authors examine the several agricultural research avenues open to scholars and scientists. This chapter concludes with a brief overview. 2023 River Publishers. All rights reserved. Creator An entity primarily responsible for making the resource Balaji S.; Ashok J.; Selvaraju P.; Gangwar V.P. Source A related resource from which the described resource is derived Advanced Technologies for Smart Agriculture, pp. 105-127. Publisher An entity responsible for making the resource available River Publishers Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175668892&amp;partnerID=40&amp;md5=1e0f9587cc6c9a4a5997450fde263b3a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175668892&amp;partnerID=40&amp;md5=1e0f9587cc6c9a4a5997450fde263b3a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-877022883-1; 978-877022848-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Balaji S., Department of Electrical and Electronics Engineering, SRM Valliammai Engineering College, India; Ashok J., School of Business and Management, CHRIST (Deemed to be University), India; Selvaraju P., Department of Mathematics, Rajalakshmi Institute of Technology, India; Gangwar V.P., Department of General Marketing, Mittal School of Business, Lovely Professional University, India