Cotton Verticillium wilt monitoring based on UAV multispectral-visible multi-source feature fusion

R Ma, N Zhang, X Zhang, T Bai, X Yuan, H Bao… - … and Electronics in …, 2024 - Elsevier
Verticillium wilt seriously jeopardizes cotton growth and restricts cotton yields. Therefore, it is
important to accurately, rapidly, and non-destructively estimate the extent of cotton …

[HTML][HTML] Multiple linear regression models with limited data for the prediction of reference evapotranspiration of the Peloponnese, Greece

S Dimitriadou, KG Nikolakopoulos - Hydrology, 2022 - mdpi.com
The aim of this study was to investigate the utility of multiple linear regression (MLR) for the
estimation of reference evapotranspiration (ETo) of the Peloponnese, Greece, for two …

[HTML][HTML] Actual evapotranspiration and energy balance estimation from vineyards using micro-meteorological data and machine learning modeling

S Fuentes, S Ortega-Farías… - Agricultural Water …, 2024 - Elsevier
Actual evapotranspiration (ETa) can be commonly estimated using numerical models based
on i) weather and plant-based parameters, ii) from remotely sensed data and energy …

Grapevine stem water potential estimation based on sensor fusion

N Ohana-Levi, I Zachs, N Hagag, L Shemesh… - … and Electronics in …, 2022 - Elsevier
Estimating vine water status is essential for achieving the desired balance between wine
grape quality and yield in viticulture management and irrigation planning. The growing …

Smart Farming and Precision Agriculture and Its Need in Today's World

S John, PJ Arul Leena Rose - Intelligent Robots and Drones for Precision …, 2024 - Springer
Smart farming and precision agriculture are two intertwined concepts that leverage
technology and data-driven methods to transform conventional farming practices. This …

Paddy yield prediction based on 2D images of rice panicles using regression techniques

Pankaj, B Kumar, PK Bharti, VK Vishnoi, K Kumar… - The Visual …, 2024 - Springer
Crop yield predictions are important for crop monitoring and agronomic management. The
traditional methods for yield predictions are complicated and resource consuming. With the …

Improved demand forecasting of a retail store using a hybrid machine learning model

V Taparia, P Mishra, N Gupta… - Journal of Graphic Era …, 2024 - riverpublishersjournal.com
Accurate demand forecasting is a competitive advantage for all supply chain components,
including retailers. Approaches like naïve, moving average, weighted average, and …

The response of yield, number of clusters, and cluster weight to meteorological factors and irrigation practices in grapevines: A multi-experiment study

N Ohana-Levi, Y Cohen, S Munitz, R Michaelovsky… - Scientia …, 2024 - Elsevier
Abstract Knowledge of the yield components of wine grapevines is essential to achieve
target production and effectively design vineyard management. Therefore, it is necessary to …

An accurate irrigation volume prediction method based on an optimized LSTM model

H Yan, F **e, D Long, Y Long, P Yu, H Chen - PeerJ Computer Science, 2024 - peerj.com
Precise prediction of irrigation volumes is crucial in modern agriculture. This study proposes
an optimized long short-term memory (LSTM) model-based irrigation prediction method that …

[HTML][HTML] Machine-learned actual evapotranspiration for an irrigated pecan orchard in Northwest Mexico

R Stoffer, O Hartogensis, JC Rodríguez… - Agricultural and Forest …, 2024 - Elsevier
Accurate field-scale estimates of the actual evapotranspiration (ET act) based on readily
available input data is indispensable to optimize irrigation in (semi-) arid regions. In this …