Previous Article in Journal
Microbiome Analysis Revealed the Effects of Environmental Factors on the Presence of Toxigenic Fungi and Toxin Production in Rice Grains
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Review

How Can Soil Quality Be Accurately and Quickly Studied? A Review

by
Radwa A. El Behairy
1,
Hasnaa M. El Arwash
2,
Ahmed A. El Baroudy
1,
Mahmoud M. Ibrahim
1,
Elsayed Said Mohamed
3,4,
Dmitry E. Kucher
4 and
Mohamed S. Shokr
1,*
1
Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt
2
Mechatronics Engineering Department, Alexandria Higher Institute of Engineering & Technology (AIET), Alexandria 21311, Egypt
3
National Authority for Remote Sensing and Space Sciences, Cairo 1564, Egypt
4
Department of Environmental Management, Institute of Environmental Engineering, People’s Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Street, 117198 Moscow, Russia
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(8), 1682; https://doi.org/10.3390/agronomy14081682
Submission received: 29 June 2024 / Revised: 22 July 2024 / Accepted: 29 July 2024 / Published: 30 July 2024
(This article belongs to the Special Issue Soil Health and Properties in a Changing Environment)

Abstract

Evaluating soil quality is crucial for ensuring the sustainable use of agricultural lands. This review examines the definition, evaluation methods, indicator selection, and relevant case studies. The concept of soil quality supplements soil science research by deepening our understanding of soils and aiding in the allocation of resources as agriculture intensifies to meet rising global demand. Soil quality provides a framework for educating stakeholders about the essential functions of soils and offers a tool for assessing and comparing different management techniques. Regular evaluation of soil quality is vital for maintaining high crop yields and addressing the gap between production and consumption. Nowadays, many researchers have explored machine learning (ML) and deep learning (DL) techniques and various algorithms to model and predict soil quality with satisfactory results. These chosen indicators can be influenced by chemical, biological, or physical features. This paper compares ML and DL with traditional methods, examining their features, limitations, different categories of machine learning, and their applications in soil quality assessment. Finally, we show that predicting soil quality has the potential to be extremely accurate and efficient with ML and DL. This distinguishes the application of DL and ML from other approaches since they can anticipate the soil quality index without the need for more intricate computations. Our suggestion for future studies is to evaluate soil quality over broader regions and predict it by using more accurate, modern, and faster methods, using a variety of activation functions and algorithms.
Keywords: deep learning; evaluation methods; food security; machine learning; soil quality indicators; sustainable use deep learning; evaluation methods; food security; machine learning; soil quality indicators; sustainable use

Share and Cite

MDPI and ACS Style

Behairy, R.A.E.; El Arwash, H.M.; El Baroudy, A.A.; Ibrahim, M.M.; Mohamed, E.S.; Kucher, D.E.; Shokr, M.S. How Can Soil Quality Be Accurately and Quickly Studied? A Review. Agronomy 2024, 14, 1682. https://doi.org/10.3390/agronomy14081682

AMA Style

Behairy RAE, El Arwash HM, El Baroudy AA, Ibrahim MM, Mohamed ES, Kucher DE, Shokr MS. How Can Soil Quality Be Accurately and Quickly Studied? A Review. Agronomy. 2024; 14(8):1682. https://doi.org/10.3390/agronomy14081682

Chicago/Turabian Style

Behairy, Radwa A. El, Hasnaa M. El Arwash, Ahmed A. El Baroudy, Mahmoud M. Ibrahim, Elsayed Said Mohamed, Dmitry E. Kucher, and Mohamed S. Shokr. 2024. "How Can Soil Quality Be Accurately and Quickly Studied? A Review" Agronomy 14, no. 8: 1682. https://doi.org/10.3390/agronomy14081682

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop