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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Increasing crop yield is a significant objective in modern agriculture, with adjusted planting density and rational fertilization strategies standing out as the foremost approaches for attaining such a goal. Through the use of modern artificial intelligence techniques such as genetic algorithms and neural networks, the CPDOS (Crop Planting Density Optimization System), an online intelligent system that can automate the modeling, optimization, and analysis of the two models, was developed in the present study. The goal of the system is to optimize the planting density model and fertilizer application in combination with other computer system development techniques. The CPDOS comprises three main modules: yield density optimization module, optimal planting density range module, and fertilization and planting density optimization module. The three modules are complemented by two modules for data input and result visualization, culminating in the comprehensive process of optimizing planting density and fertilizer allocation through the CPDOS. The CPDOS was tested using potato, corn, and soybean data, and the results show that the optimization effects of planting density and fertilizer application were satisfactory. The CPDOS is an automated crop planting optimization system that integrates algorithms and models and is driven by artificial intelligence technology. The introduction of the CPDOS reduces the barriers to utilizing these algorithms and models, facilitating wider adoption of intelligently optimized planting technology. The platform’s launch will accelerate the swift advancement of this field.

Details

Title
CPDOS: A Web-Based AI Platform to Optimize Crop Planting Density
Author
Zhu, Rongsheng 1 ; Zhang, Zhixin 2 ; Cao, Yangyang 2 ; Hu, Zhenbang 3 ; Yang, Li 3 ; Cao, Haifeng 1 ; Zhao, Zhenqing 4 ; Xin, Dawei 3 ; Chen, Qingshan 3 

 College of Arts and Sciences, Northeast Agricultural University, Harbin 150030, China 
 College of Engineering, Northeast Agricultural University, Harbin 150030, China 
 College of Agriculture, Northeast Agricultural University, Harbin 150030, China 
 College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China 
First page
2465
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
20734395
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2882288262
Copyright
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.