Scopus
🔓 Açık Erişim YÖKSİS Eşleşti
Technological Advances in Soil Penetration Resistance Measurement and Prediction Algorithms
Reviews in Agricultural Science · Ocak 2023
YÖKSİS Kayıtları
Technological Advances in Soil Penetration Resistance Measurement and Prediction Algorithms
Reviews in Agricultural Science · 2023 Google Scholar
ÖĞRETİM GÖREVLİSİ HASAN KIRILMAZ →
Makale Bilgileri
DergiReviews in Agricultural Science
Yayın TarihiOcak 2023
Cilt / Sayfa11 · 93-105
Scopus ID2-s2.0-85150704807
Erişim🔓 Açık Erişim
Özet
Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.
Yazarlar (2)
1
Mustafa Ahmed Jalal Al-Sammarraie
2
Hasan Kırılmaz
Anahtar Kelimeler
digital soil maps
precision agriculture
prediction algorithms
soil penetration resistance
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
University of Baghdad
Baghdad Iraq
Metrikler
3
Atıf
2
Yazar
4
Anahtar Kelime