Modelling of Intra-Field Winter Wheat Crop Growth Variability Using in Situ Measurements, Unmanned Aerial Vehicle-Derived Vegetation Indices, Soil Properties, and Machine Learning Algorithms

Modelling of Intra-Field Winter Wheat Crop Growth Variability Using in Situ Measurements, Unmanned Aerial Vehicle-Derived Vegetation Indices, Soil Properties, and Machine Learning Algorithms

Crop growth and yield often vary, not only between farms, but also at the sub-field level. These variations can stem from sub-field heterogeneities of soil and plant biophysical parameters. This means that soil and plant biophysical data can be used to predict intra-field crop growth and yield varia...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Lwandile Nduku, Cilence Munghemezulu, Zinhle Mashaba-Munghemezulu, Wonga Masiza, Phathutshedzo Eugene Ratshiedana, Ahmed Mukalazi Kalumba, Johannes George Chirima
التنسيق: مقال
اللغة:English
منشور في: MDPI AG 2023-11-01
سلاسل:Environmental Sciences Proceedings
الموضوعات:
wheat
UAV
vegetation indices
soil properties
Gaussian process regression
least-squares boosting and bagging regression
الوصول للمادة أونلاين:https://www.mdpi.com/2673-4931/29/1/24

الانترنت

https://www.mdpi.com/2673-4931/29/1/24

مواد مشابهة