Controlling Agronomic Variables of Saffron Crop Using IoT for Sustainable Agriculture

Author:

Kour Kanwalpreet,Gupta DeepaliORCID,Gupta Kamali,Juneja SapnaORCID,Kaur Manjit,Alharbi Amal H.,Lee Heung-NoORCID

Abstract

Saffron, also known as “the golden spice”, is one of the most expensive crops in the world. The expensiveness of saffron comes from its rarity, the tedious harvesting process, and its nutritional and medicinal value. Different countries of the world are making great economic growth due to saffron export. In India, it is cultivated mostly in regions of Kashmir owing to its climate and soil composition. The economic value generated by saffron export can be increased manyfold by studying the agronomical factors of saffron and developing a model for artificial cultivation of saffron in any season and anywhere by monitoring and controlling the conditions of its growth. This paper presents a detailed study of all the agronomical variables of saffron that have a direct or indirect impact on its growth. It was found that, out of all the agronomical variables, the important ones having an impact on growth include corm size, temperature, water availability, and minerals. It was also observed that the use of IoT for the sustainable cultivation of saffron in smart cities has been discussed only by very few research papers. An IoT-based framework has also been proposed, which can be used for controlling and monitoring all the important growth parameters of saffron for its cultivation.

Funder

MSIT(Ministry of Science and ICT), Korea

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Neural Network Model for Predicting Apple Yield Based on Arrival of Phenological Stage in Conjunction with Leaf disease, Soil and Weather Parameters;SN Computer Science;2024-01-03

2. A novel fine-tuned deep-learning-based multi-class classifier for severity of paddy leaf diseases;Frontiers in Plant Science;2023-09-05

3. Boosting of fruit choices using machine learning-based pomological recommendation system;SN Applied Sciences;2023-08-19

4. Classification of Defective Intensity Levels of Paint in Heritage Buildings using the CNN-SVM Technique;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

5. Ear Biometric: A Deep Learning Approach;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3