Crop management using predictive analytics

Title

Crop management using predictive analytics

Creator

Gupta C.

Description

The term "predictive analytics" covers a number of different statistical methods, such as "data mining," "machine learning," and "predictive modelling," which examine past and present data in order to formulate hypotheses and predictions about future events. The use of predictive analytics may provide farmers with the ability to predict future environmental changes more correctly, as well as the demand for their commodities, and improve their ability to make decisions. While predictive analytics may seem like an effective way to forecast future events, it cannot account for unforeseeable changes or external factors that could impact the accuracy of its predictions. Furthermore, relying solely on past and present data can lead to biased outcomes and fail to consider alternative scenarios that may occur. In essence, predictive analytics should not be used as the sole basis for decision-making in any given situation for crop management. 2024, IGI Global. All rights reserved.

Source

Exploring Ethical Dimensions of Environmental Sustainability and Use of AI, pp. 106-125.

Date

2023-01-01

Publisher

IGI Global

Coverage

Gupta C., Christ University, Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 979-836930893-6; 979-836930892-9

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.4018/9798369308929.ch006

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182098873&doi=10.4018%2f9798369308929.ch006&partnerID=40&md5=595ead49cdf24096923daeee8c68042b